NISTIR 6994 

Results from Field Testing of Air Handling 

Unit and Variable Air Volume Box Fault 

Detection Tools 

Jeffrey Schein 

Steven T. Bushby 

Natascha S. Castro 

U.S. DEPARTMENT OF COMMERCE 

National Institute of Standards and Technology 

Building Environment Division 

Building and Fire Research Laboratory 

Gaithersburg, MD 20899-8631 

John M. House 

Iowa Energy Center 

Ames, IA
NISTIR 6994 

Results from Field Testing of Air Handling 

Unit and Variable Air Volume Box Fault 

Detection Tools 

Jeffrey Schein 

Steven T. Bushby 

Natascha S. Castro 

U.S. DEPARTMENT OF COMMERCE 

National Institute of Standards and Technology 

Building Environment Division 

Building and Fire Research Laboratory 

Gaithersburg, MD 20899-8631 

John M. House 

Iowa Energy Center 

Ames, IA 

Prepared for: 

Architectural Energy Corporation 

Boulder, Colorado 

April 2003

 

U.S. Department of Commerce 

Donald L. Evans, Secretary

Technology Administration 

Phillip J. Bond, Under Secretary for Technology 

National Institute of Standards and Technology 

Arden L. Bement, Jr., Director
Abstract 

Building heating, ventilation, and air conditioning (HVAC) equipment routinely fails to satisfy 

performance expectations envisioned at design. Such failures often go unnoticed for extended 

periods of time. Additionally, higher expectations are being placed on a combination of different 

and often conflicting performance measures, such as energy efficiency, indoor air quality, 

comfort, reliability, limiting peak demand on utilities, etc. To meet these expectations, the 

processes, systems, and equipment used in both commercial and residential buildings are 

becoming increasingly sophisticated. This development both necessitates the use of automated 

diagnostics to ensure fault-free operation and enables diagnostic capabilities for the various 

building systems by providing a distributed platform that is powerful and flexible enough to 

perform fault detection and diagnostics (FDD). 

The purpose of the research effort described in this report is to develop, test, and demonstrate 

FDD methods that can detect common mechanical faults and control errors in air-handling units 

(AHUs) and variable-air-volume (VAV) boxes. The tools are intended to be sufficiently simple 

that they can be embedded in commercial building automation and control systems and rely upon 

only sensor data and control signals that are commonly available in these systems. 

AHU Performance Assessment Rules (APAR) is a diagnostic tool that uses a set of expert rules 

derived from mass and energy balances to detect faults in air-handling units. Control signals are 

used to determine the mode of operation for the AHU. A subset of the expert rules corresponding 

to that mode of operation is then evaluated to determine if there is a mechanical fault or a control 

problem. VAV box Performance Assessment Control Charts (VPACC) is a diagnostic tool that 

uses statistical quality control measures to detect faults or control problems in VAV boxes. 

This report describes a research study of the application of APAR and VPACC to HVAC 

systems in real buildings. AHU and VAV box data were collected from several field sites. The 

study examined the effectiveness of the tools in detecting commonly found mechanical faults 

and control problems, the reliability of the tools across different building uses and climate 

regions, and the robustness of the tools in handling data from a variety of HVAC system 

configurations. APAR and VPACC were both found to be successful at finding a wide variety of 

faults. Both tools appear to be suitable for embedding in commercial control products. 

Key words: BACnet, building automation and control, direct digital control, energy management 

systems, fault detection and diagnostics, cybernetic building systems 

Acknowledgments

This work was supported in part by the California Energy Commission Public Interest Energy 

Research (PIER) Program. In addition, this project, like any field study, would not have been 

possible without those individuals who assisted with the data collection aspect of this work. 

Thanks are due to Mark Levi and Stephen May of the U.S. General Services Administration 

Region IX, Louis Coughenour of Enovity, Jim Butler, Olav P. Hegland, and Robert Veelenturf 

of Cimetrics, Xiaohui Zhou of the Iowa Energy Center, Mike Macklin of the Des Moines Area 

Community College, and Joel Bender, H. Michael Newman, and Elaine Stanton-Hicks of Cornell 

University. 
Table of Contents 

Results from Field Testing of Air Handling Unit and Variable Air Volume Box Fault Detection 

Tools ............................................................................................................................................... 1 

1 Introduction............................................................................................................................. 5 

2 Methodology........................................................................................................................... 6 

2.1 FDD for Air Handling Units........................................................................................... 6 

2.1.1 System Description ................................................................................................. 6 

2.1.2 AHU Performance Assessment Rules (APAR)...................................................... 7 

2.1.3 Instrumentation Accuracy Requirements.............................................................. 12 

2.2 FDD for VAV Boxes.................................................................................................... 13 

2.2.1 VAV box Performance Assessment Control Charts - VPACC ............................ 13 

2.2.2 Control Charts....................................................................................................... 13 

2.2.3 System Description ............................................................................................... 15 

2.2.4 CUSUM Applied to VAV Box Diagnostics......................................................... 16 

2.2.5 Point requirements................................................................................................ 18 

2.2.6 Parameters............................................................................................................. 18 

2.2.7 Special Cases ........................................................................................................ 18 

3 Data Sources ......................................................................................................................... 20 

3.1 SITE-1........................................................................................................................... 20 

3.2 SITE-2........................................................................................................................... 20 

3.3 SITE-3........................................................................................................................... 20 

3.4 SITE-4........................................................................................................................... 20 

4 Results................................................................................................................................... 21 

4.1 SITE-1........................................................................................................................... 21 

4.1.1 AHU Supply Air Temperature Fault..................................................................... 21 

4.1.2 AHU Mode Switch Fault ...................................................................................... 22 

4.1.3 AHU Simultaneous Heating and Cooling Fault.................................................... 22 

4.1.4 AHU Temperature Sensor / Damper Fault ........................................................... 23 

4.1.5 VAV Box Zone Temperature Fault .................................................................... 24 

4.2 SITE-2........................................................................................................................... 25 

4.2.1 AHU Saturated Cooling Coil................................................................................ 25 

4.2.2 AHU Mode Switch Fault ...................................................................................... 26 

4.3 SITE-3........................................................................................................................... 27 

4.4 SITE-4........................................................................................................................... 30 

4.4.1 AHU Simultaneous Heating and Cooling Fault.................................................... 30 

4.4.2 VAV Box Airflow Fault ....................................................................................... 31 

5 Summary and Future Work................................................................................................... 32 

6 References............................................................................................................................. 33 
1 Introduction 

Building HVAC equipment routinely fails to satisfy performance expectations envisioned 

at design. Such failures often go unnoticed for extended periods of time. Additionally, 

higher expectations are being placed on a combination of different and often conflicting 

performance measures, such as energy efficiency, indoor air quality, comfort, reliability, 

limiting peak demand on utilities, etc. To meet these expectations, the processes, systems, 

and equipment used in both commercial and residential buildings are becoming 

increasingly sophisticated. This development both necessitates the use of automated 

diagnostics to ensure fault-free operation and enables diagnostic capabilities for the 

various building systems by providing a distributed platform that is powerful and flexible 

enough to perform fault detection and diagnostics (FDD). 

The purpose of the research effort described in this report is to develop, test, and 

demonstrate FDD methods that can detect common mechanical faults and control errors 

in air-handling units (AHUs) and variable-air-volume (VAV) boxes. The tools are 

intended to be sufficiently simple that they can be embedded in commercial building 

control systems and rely upon only sensor data and control signals that are commonly 

available in commercial building automation and control systems. 

AHU Performance Assessment Rules (APAR) is a diagnostic tool that uses a set of expert 

rules derived from mass and energy balances to detect common faults in air-handling 

units. Control signals are used to determine the mode of operation for the AHU. A subset 

of the expert rules corresponding to that mode of operation is then evaluated to determine 

if there is a mechanical fault or a control problem. VAV box Performance Assessment 

Control Charts (VPACC) is a diagnostic tool that uses statistical quality control measures 

to detect faults or control problems in VAV boxes. VPACC can be applied to most VAV 

box control strategies. Fault thresholds are determined by statistical analysis of a database 

of “normal operation” data. The FDD tools for AHUs and VAV boxes are being 

developed with distinct approaches because of the nature of the systems. VAV boxes are 

simple devices with a limited number of operation modes and possible faults. Because the 

building industry is sensitive to first cost, the VAV boxes typically have little 

instrumentation and controllers with limited capability. However, VAV boxes are very 

numerous in a typical HVAC system, resulting in a large amount of data to be monitored 

for faults. AHUs are more complex and thus susceptible to more kinds of faults. They 

also tend to have more instrumentation and more capable controllers. The FDD tools for 

both systems are designed to be robust so that they can adapt to the variety of 

applications typical of their use. 

A previous study [1], describes the theoretical basis of APAR and VPACC and evaluates 

the tools’ performance using data generated by simulation, emulation, and laboratory 

testing. The study examined the breadth of faults that can be detected and the conditions 

under which they can be detected. This report describes the results of a research study to 

extend the previous work by evaluating the application of APAR and VPACC to HVAC 

systems in real buildings. The research, involving the collection of AHU and VAV box 

data from several field sites, examined the effectiveness of these tools in detecting 

5
commonly found mechanical faults and control problems, the reliability of the tools 

across several seasons, and the robustness of the tools in handling data from a variety of 

system types and configurations. The sites include an office building, a restaurant, as 

well as community college and university campuses, featuring constant- and variable-airvolume systems. 

2 Methodology 

2.1 FDD for Air Handling Units 

The fault detection tool described in this section was developed for application to single 

duct variable-volume or constant-volume air handlers with hydronic heating and cooling 

coils and airside economizers. The rules that are used for FDD focus on temperature 

control in an AHU. Hence, the system description will be restricted to components and 

control strategies directly related to temperature control. Figure 2.1 is a schematic 

diagram of a typical single duct air handling unit (AHU). 

C

C

Return

Fan

Recirculation

Air Damper

Normally Open

Exhaust Air Damper

Normally Closed

Cooling

Coil

Heating

Coil

Filter

H

C

Supply

Fan

T & H

T & H

Return Air

Damper

Motor

Air Handling Controller

Outputs

Inputs

Outdoor Air Damper

Normally Closed

From

Zones

To

Zones

T

Outdoor Air Temperature

& Humidity Sensors T

Mixed

Air

Supply

Air

Figure 2.1: Schematic diagram of a single duct air-handling unit 

2.1.1 System Description 

The AHU controller typically controls the supply air temperature to maintain a setpoint 

temperature at a location in the supply duct downstream of the supply fan. Outdoor air 

enters the AHU and is mixed with air returned from the building. The mixed air passes 

over the heating and cooling coils, where if necessary, it is conditioned prior to being 

supplied to the building. The typical operating sequence for AHUs consists of four 

primary modes of operation during occupied periods for maintaining the supply air 

6
temperature and the ventilation at preset levels. The relationship of the four operating 

modes to the control of the heating coil valve, the cooling coil valve and the mixing box 

dampers is shown in Figure 2.2. Sequencing logic determines the mode of operation as 

dictated by various thermal relationships including the internal and external loads on the 

zones served by the AHU. 

In the heating mode (Mode 1 in Figure 2.2), the heating coil valve is controlled to 

maintain the supply air temperature at the heating set point and the cooling coil valve is 

closed. The mixed air dampers are positioned to allow the minimum outdoor air 

necessary to satisfy ventilation requirements. 

Mode 1 Mode 2 Mode 3 Mode 4

Control Signal (%)100

0

Heating

Coil Valve

Cooling

Mixing Box Coil Valve

Dampers

Mode 1 Mode 2 Mode 3 Mode 4

Control Signal (%)100

0

Heating

Coil Valve

Cooling

Mixing Box Coil Valve

Dampers

Figure 2.2: Typical operating modes of an air-handling unit 

As cooling loads increase, the AHU transitions from heating to cooling with outside air 

(Mode 2). In this mode, the heating and cooling coil valves are closed and the mixing box 

dampers are modulated to maintain the supply air temperature at cooling set point. As the 

loads continue to increase, the mixing dampers eventually saturate with the outdoor air 

damper fully open and the AHU changes over to mechanical cooling. When the AHU is 

operating in one of the mechanical cooling modes (Modes 3 and 4), the cooling coil valve 

modulates to maintain the supply air temperature at cooling set point, the heating coil 

valve is closed, and the outdoor air damper is either fully open or at its minimum 

position. There are several different types of economizer controls, generally the 

economizer control logic uses a comparison of the outdoor and return air temperatures or 

enthalpies to determine the proper position of the outdoor air damper such that 

mechanical cooling requirements are minimized. Hence, the third primary mode (Mode 

3) of operation is mechanical cooling with 100 % outdoor air and the fourth primary 

mode (Mode 4) of operation is mechanical cooling with minimum outdoor air. 

2.1.2 AHU Performance Assessment Rules (APAR) 

The basis for the fault detection methodology is a set of expert rules used to assess the 

performance of the AHU. The tool developed from these rules is referred to as APAR 

(AHU Performance Assessment Rules). APAR uses control signals and occupancy 

information to identify the mode of operation of the AHU, thereby identifying a subset of 

the rules that specify temperature relationships that are applicable for that mode. The two 

main mode classifications are occupied and unoccupied. For occupied periods, the mode 

is further categorized as described in the previous paragraph. For convenience, the 

7
operating modes are summarized below: 

• Mode 1: heating 

• Mode 2: cooling with outdoor air 

• Mode 3: mechanical cooling with 100 % outdoor air 

• Mode 4: mechanical cooling with minimum outdoor air 

• Mode 5: unknown 

Because the direct digital control (DDC) output to the actuators of the heating and 

cooling coil valves and the mixing box dampers are known, the mode of operation can be 

ascertained. Although not depicted in Figure 2.2, a fifth mode of operation referred to 

“unknown” operation has been defined and listed above. The unknown mode applies to 

the case in which the AHU is running in an occupied mode, but none of the control 

output relationships defined for Modes 1-4 are satisfied. The unknown mode could be 

associated with mode transitions and/or with faulty operation such as simultaneous 

heating and cooling. 

 

Once the mode of operation has been established, rules based on conservation of mass 

and energy can be used along with the sensor information that is typically available for 

controlling the AHUs. For example, normal operation in the mechanical cooling mode 

with 100 % outdoor air (Mode 3) dictates that the outdoor and mixed air temperatures 

must be approximately equal. Defining Toa and Tma as the outdoor air and mixed air 

temperatures, respectively, the rule (defined as Rule 10) is written as 

 Rule 10: |Toa - Tma| > εt 

where εt is a threshold that depends on the uncertainty (or accuracy) of the 

measurements. The rules are written such that a fault is indicated if a rule is true. In the 

example above, the rule states that if the outdoor and mixed air temperatures are not the 

same (i.e., if true) a fault has occurred. 

As a detailed description of the 28 APAR rules and the reasoning behind them is 

available elsewhere [2], the rules are simply listed in Table 2.1 without detailed 

explanation. Table 2.1 groups the rules according to mode of operation. As indicated in 

the column heading for the rule expression, a true expression indicates a fault. Table 2.2 

presents the rules as related groups and indicates the sensors and control signals used to 

evaluate each rule. The first group of rules treats the relationship of temperatures in the 

coil subsystem of the AHU. For these four rules, only the relational operator in the rules 

change from one mode to another. A typical rule from this subgroup requires the supply 

air temperature to be lower than the sum of the mixed air temperature and the 

temperature rise across the supply fan in the mechanical cooling modes. There are also 

groups of rules treating the mixing box subsystem, the zone subsystem, economizer 

operation, comfort requirements, and controller logic/tuning. Hence, although there are 

28 rules, in reality only a small number of temperature and control signal relationships 

are used to define the rules. 

8
Table 2.1: APAR Rule Set 

Mode Rule # Rule Expression (true implies existence of a fault)

1 Tsa < Tma + ΔTsf - εt

2 For |Tra - Toa| ≥ ΔTmin: |Qoa/Qsa - (Qoa/Qsa)min | > εf

 

3 |uhc – 1| ≤ εhc and Tsa,s – Tsa ≥ εt

Heating 

(Mode 1) 

4 |uhc – 1| ≤ εhc

5 Toa > Tsa,s - ΔTsf + εt

6 Tsa > Tra - ΔTrf + εt

Cooling with 

Outdoor Air 

(Mode 2) 7 |Tsa - ΔTsf - Tma| > εt

8 Toa < Tsa,s - ΔTsf - εt

9 Toa > Tco + εt

10 |Toa - Tma| > εt

11 Tsa > Tma + ΔTsf + εt

12 Tsa > Tra - ΔTrf + εt

13 |ucc – 1| ≤ εcc and Tsa – Tsa,s ≥ εt

Mechanical 

Cooling with 

100% Outdoor 

Air 

(Mode 3) 

14 |ucc – 1| ≤ εcc

15 Toa < Tco - εt

16 Tsa > Tma + ΔTsf + εt

17 Tsa > Tra - ΔTrf + εt

18 For |Tra - Toa| ≥ ΔTmin: |Qoa/Qsa - (Qoa/Qsa)min | > εf

19 |ucc – 1| ≤ εcc and Tsa – Tsa,s ≥ εt

Mechanical 

Cooling with 

Minimum 

Outdoor Air 

(Mode 4) 

20 |ucc – 1| ≤ εcc

21 ucc > εcc and uhc > εhc and εd < ud < 1 - εd

22 uhc > εhc and ucc > εcc

23 uhc > εhc and ud > εd

Unknown 

Occupied 

Modes 

(Mode 5) 24 εd < ud < 1 - εd and ucc > εcc

25 | Tsa – Tsa,s | > εt

26 Tma < min(Tra , Toa) - εt

27 Tma > max(Tra , Toa) + εt

All Occupied 

Modes 

(Mode 1, 2, 3, 4, 

or 5) 28 Number of mode transitions per hour > MTmax

9
10

Where 

 MTmax = maximum number of mode changes per hour 

Tsa = supply air temperature 

Tma = mixed air temperature 

Tra = return air temperature 

Toa = outdoor air temperature 

 Tco = changeover air temperature for switching between Modes 3 and 4 

Tsa,s = supply air temperature set point 

 ΔTsf = temperature rise across the supply fan 

ΔTrf = temperature rise across the return fan 

ΔTmin = threshold on the minimum temperature difference between the 

return and outdoor air 

Qoa/Qsa = outdoor air fraction = (Tma - Tra)/(Toa - Tra)

(Qoa/Qsa)min = threshold on the minimum outdoor air fraction 

uhc = normalized heating coil valve control signal [0,1] where uhc = 0 

indicates the valve is closed and uhc = 1 indicates it is 100 % open 

ucc = normalized cooling coil valve control signal [0,1] where ucc = 0 

indicates the valve is closed and ucc = 1 indicates it is 100 % open 

ud = normalized mixing box damper control signal [0,1] where ud = 0 

indicates the outdoor air damper is closed and ud = 1 indicates it is 

100 % open 

εt = threshold for errors in temperature measurements 

 εf = threshold parameter accounting for errors related to airflows 

(function of uncertainties in temperature measurements) 

 εhc = threshold parameter for the heating coil valve control signal 

εcc = threshold parameter for the cooling coil valve control signal 

 εd = threshold parameter for the mixing box damper control signal 

2.1.2.1 Operational and Design Data Requirements 

APAR uses the following occupancy information, setpoint values, sensor measurements, 

and control signals: 

• Occupancy status; 

• Supply air temperature set point; 

• Supply air temperature; 

• Return air temperature; 

• Mixed air temperature; 

• Outdoor air temperature; 

• Cooling coil valve control signal; 

• Heating coil valve control signal; 

• Mixing box damper control 

signal; 

• Return air relative humidity 

(for enthalpy-based economizers 

only) 

• Outdoor air relative humidity 

(for enthalpy-based economizers 

only).
Table 2.2: Summary of Rule Relationships 

Tsa Tra Tma Toa Tsa,s ΔTsf ΔTrf Tco ucc uhc ud

1 1  

7 2  

11 3  

16 4  

2 1 

18 4 

26 1, 2, 3, 4 

27 1, 2, 3, 4 

25 1, 2, 3, 4  

3 1  

13 3 

19 4 

4 1 

14 3 

20 4 

5 2 

8 3 

6 2   

12 3   

17 4   

9 3  

15 4  

10 3  

21 - 

22 -  

23 -  

24 -  

28 - 

Controller Logic/Tuning: Rules are related and 

identify periods of operation associated with 

controller problems, such as simultaneous 

heating and cooling, and excessive mode 

changes. 

Coil Subsystem: The relational sign (<, >, etc.) 

changes based on the mode of operation.

Comfort Requirements: The first four rules 

indicate comfort is sacrificed (with Rules 3, 13, 

and 19 indicating the system is out of control), 

whereas the latter three rules indicate comfort 

could soon be sacrificed (system is out of 

control). 

The relational sign (<, >, etc.) changes based 

on the mode of operation.

Zone Subsystem: Rules are identical.

Economizer: The relational sign (<, >, etc.) 

changes based on the mode of operation.

Mixing Box Subsystem: Rules are related 

through calculation of outdoor air fraction. If 

Rule 26 or 27 is satisfied, the outdoor air 

fraction will be negative or greater than unity.

Sensors and Control Signals Rule Mode * Relationship Between Grouped Rules

* The dash symbol indicates either an unknown mode or multiple modes of operation. 

With the possible exception of the mixed air temperature, this information is generally available 

for most AHUs controlled with a DDC system. If one or more sensors are not available, certain 

rules will no longer be applicable. For instance, in the absence of a mixed air temperature sensor, 

nine rules listed in Table 2.1 (Rules 1, 2, 7, 10, 11, 16, 18, 26, and 27) will be eliminated from 

consideration in APAR. Conversely, the presence of additional sensors would expand the rule set 

and provide an opportunity to either detect more faults, or to detect faults during modes of 

operation in which they would normally be hidden. For instance, if a temperature sensor was 

installed between the heating and cooling coils, leakage through the heating valve could be 

detected during the mechanical cooling modes, whereas normally it would be masked in these 

modes. 

In addition to the operational data listed above, certain design data are needed to implement the 

rules. The required design data are: 

• Minimum and maximum values of control signals for the heating coil valve, cooling coil 

valve and mixing box dampers for normalizing the control signals; 

• Percentage outdoor air necessary to satisfy ventilation requirements; 

• Changeover temperature from mechanical cooling with 100 % outdoor air to mechanical 

cooling with minimum outdoor air (or equivalent condition for enthalpy-based economizer); 

• Description of sequencing/economizer cycle strategy (used to verify that the rules are 

suitable to a particular AHU installation). 

11
2.1.2.2 Detecting and Diagnosing Faults 

APAR does not search for the existence of a specific set of faults. Rather, any fault that causes a 

rule to be satisfied would be detected and additional effort would be necessary to isolate the 

source of the problem. Emulation, simulation, and laboratory experimentation from previous 

work [1] as well as the current study demonstrate that the rule set can identify the following 

faults: 

• Stuck or leaking mixing box dampers, heating coil valves, and cooling coil valves; 

• Temperature sensor faults; 

• Design faults such as undersized coils; 

• Controller programming errors related to tuning, setpoints, and sequencing logic; 

• Inappropriate operator intervention. 

The operating point, severity of a fault, and threshold selection for the rules will obviously 

influence when a particular rule is satisfied. Threshold selection is discussed next. 

2.1.2.3 Threshold Selection 

In addition to the sensor, control signals, and setpoint information, there are other parameters 

that must be specified for APAR. For instance, estimates of the temperature rise across the 

supply fan (and return fan, if one exists) must be provided, a reasonable default is 1.1 oC (2.0 oF). 

A model-based value correlated to the airflow rate or the control signal to the fan could be used 

as the basis for this estimate; however, some amount of training data would likely be necessary 

to establish the correlation. Thresholds used in evaluation of rules such as εt

 in Rule 10 must also 

be specified. Another approach might be to calculate the threshold values based on the 

uncertainty of each sensor or actuator value. As an example, the threshold in Rule 10 would be 

determined from the expression 

εt = εToa + εTma 

where εToa and εTma are the uncertainties associated with the measurement of the outdoor and 

mixed air temperatures. If a threshold is too great, the associated fault(s) must be relatively 

severe to be detected. If, on the other hand, a threshold is too small, normal variation in 

operating conditions may result in false alarms. These threshold values are currently determined 

heuristically for each site. 

2.1.3 Instrumentation Accuracy Requirements 

APAR uses existing sensor points in the control system to perform the fault detection 

calculations. The typical industrial grade sensors that are already installed for control purposes 

have sufficient accuracy. Laboratory grade instruments are not required. Higher quality sensors 

that have been installed and calibrated properly will allow the use of tighter thresholds (less 

severe faults can be detected) than lower quality sensors, or those that have been poorly 

calibrated or installed. 

12
2.2 FDD for VAV Boxes 

2.2.1 VAV box Performance Assessment Control Charts - VPACC 

The primary purpose of heating, ventilating, and air-conditioning (HVAC) equipment in 

commercial buildings is to provide a comfortable and healthy environment for occupants. 

Variable-air-volume (VAV) air handling systems are common for conditioning air and delivering 

the air to occupied zones. VAV boxes are an integral part of such systems and are the final piece 

of equipment that air passes through prior to reaching the occupants. As such, it is important to 

ensure that these devices operate correctly. 

The challenges presented in detecting and diagnosing faults in VAV boxes are similar to those 

encountered with other pieces of HVAC equipment. Generally there are very few sensors, 

making it difficult to ascertain what is happening in the device. Limitations associated with 

controller memory and communication capabilities further complicate the task. The number of 

different types of VAV boxes and lack of standardized control sequences add a final level of 

complexity to the challenge. This set of constraints is counterbalanced by the fact that VAV 

boxes are much more numerous than other pieces of HVAC equipment. For instance, buildings 

may have ten to fifteen times more VAV boxes than air-handling units. Hence, maintenance 

staffs would clearly benefit from a tool that assisted them in monitoring VAV box operation. 

The needs and constraints described above have led to the development of VAV Box 

Performance Assessment Control Charts (VPACC), a fault detection tool that uses a small 

number of control charts to assess the performance of VAV boxes. The underlying approach, 

while developed for a specific type of VAV box and control sequence, is general in nature and 

can be adapted to other types of VAV boxes. This section describes the basic concept of control 

charts and their use for determining when control processes have gone “out of control”. The 

specific control charts developed and implemented in VPACC are then presented for a single 

duct pressure-independent throttling VAV box with reheat. 

2.2.2 Control Charts 

Control charts are common tools for monitoring control processes wherein a measured quantity 

is compared to upper and lower limits that define allowable (or fault free) operation. If the 

measured quantity falls outside these limits, the process is said to be “out of control.” The limits 

are typically defined using statistical parameters and, therefore, control charts are often referred 

to as statistical quality control charts. 

There are many different types of control charts. VPACC implements an algorithm known as a 

CUSUM (cumulative sum) chart. The basic concept behind CUSUM charts is to accumulate the 

error between a process output and the expected value of the output. Large values of the 

accumulated error are indicative of an out of control process. With the process output at 

sampling time i denoted xi, the estimate of the expected value denoted x , and the estimate of the 

process standard deviation denoted by 

ˆ

σˆ , the normalized process output is given by: 

13
σˆ

 - x xˆ z i

i = (1) 

The normalized process output is used to compute two cumulative sums defined as follows: 

]S k - z 0, [max S (2a) i = + 1-ii

]T k z 0, [ min T (2b) i = i ++ 1-i

where k is a slack parameter that must be specified. Positive values of z greater than k cause the 

sum S to move away from zero and the sum T to approach or remain at zero. Negative values of z

less than -k cause the sum T to move away from zero and the sum S to approach or remain at 

zero. A process is said to be out of control when either S exceeds a threshold value defined by 

the parameter h, or T falls below -h. Figure 2.3 [3] presents normalized data and the S and T 

cumulative sums for k = 0.5 and h = 5. The first 20 data points come from a random normal 

distribution with a mean value of zero and a standard deviation of unity. The mean value is then 

increased to 0.25, 0.5, 0.75 and 1.0 for subsequent sets of 20 data points. Note that S exceeds the 

threshold value of h after about 68 data points. Because the mean value increases above 0, the 

cumulative sum T remains above its threshold of -5. 

CUSUM charts are generally considered to be effective for detecting gradual shifts in the process 

mean. The most commonly used control charts are Shewhart and Shewhart-type charts. Shewhart 

charts are effective for detecting large, sudden changes in the process mean. Generally Shewhart 

chart limits are set at values of ˆ ± 3 x σˆ . In terms of the normalized parameter z, the chart limits 

are . Shewhart charts were not investigated as part of this study; however, it is interesting 

to note that the basic CUSUM and Shewhart charts are equivalent if the CUSUM parameters k 

and h are selected as k = 3 and h = 0. 

z ±= 3 

Data Point

0 20 40 60 80 100

Data Point

0 20 40 60 80 100

CUSUM

-10

-5

0

5

10

15

20

25

T

S

Upper Chart Limit

Lower Chart Limit

-3

-2

-1

0

1

2

3

z

Figure 2.3: A simple CUSUM control chart indicating an “out of control” process. 

14
2.2.3 System Description 

Figure 2.4 is a schematic diagram of a typical single duct variable-air-volume (VAV) box with 

hydronic reheat. The diagram depicts a damper that is used to modulate airflow to the zone and a 

control valve that modulates hot water flow to the reheat coil. Several sensors are also shown in 

Room

H

C

DP

Hydronic

Reheat Coil

VAV Box Controller

o

Thermostat

T

Damper

Hot Water Supply Hot Water 

Return

M

M

Supply Air

Room

H

C

DP

Hydronic

Reheat Coil

VAV Box Controller

o

Thermostat

T

Damper

Hot Water Supply Hot Water 

Return

M

M

Supply Air

 

Figure 2.4: Schematic diagram of a single duct pressure-independent VAV box with 

hydronic reheat. 

Figure 2.4. The zone thermostat measures the air temperature in the zone. The differential 

pressure transducer is used to measure the flow rate of air into the zone. Finally, the discharge air 

temperature sensor measures the temperature of the air stream entering the zone. This sensor is 

used to provide diagnostic information rather than for control purposes. The VAV box controller 

reads the sensor information, computes control outputs for the damper and reheat valve, and 

transmits these signals to the appropriate actuators. 

Figure 2.5 shows a typical control sequence for a pressure-independent VAV box. A heating set 

point and a cooling set point are specified. As the zone temperature increases above the cooling 

set point, the airflow rate to the zone increases proportionally. This is accomplished by resetting 

the airflow rate setpoint and modulating the damper to achieve this airflow rate. As the zone 

temperature decreases toward the cooling set point, the airflow rate setpoint is decreased and the 

damper gradually closes until it is providing the minimum flow rate necessary for ventilation. If 

the room temperature continues to decrease and reaches the heating set point, the reheat valve 

will begin to open. The airflow rate can also be varied in the heating mode, with the airflow 

increasing as the temperature decreases. Alternatively, a higher fixed airflow rate may be 

specified for heating operation to improve the distribution of the warm air. In Figure 2.5, it is 

15
assumed that a fixed airflow rate associated with the ventilation requirement of the room is 

provided in the heating mode. 

Airflow

Setpoint

Heating

Set

Point

Cooling

Set

Point

Room

Temperature

Valve

Position

Fully Maximum

Open

Fully

Closed

Airflow 

Setpoint

Valve

Heating

Set

Point

Cooling

Set

Point

Room

Temperature

Valve

Position

Minimum 

Fully

Open

Fully

Closed

Valve

Figure 2.5: Damper and valve control sequence as a function of room temperature for a 

single duct pressure-independent VAV box with hydronic reheat.

 

2.2.4 CUSUM Applied to VAV Box Diagnostics 

The previous section described one particular VAV box control strategy. However, a wide 

variety of control strategies are employed by controller manufacturers, most of which use a 

cascaded control loop to maintain the zone temperature and zone airflow rate at setpoint values. 

In order to make VPACC independent of the control strategy used in a particular controller/VAV 

box application, four generic errors were identified: the airflow rate error, the absolute value of 

the airflow rate error, the temperature error, and the reheat coil differential temperature error. As 

long as the VAV box controller has an airflow setpoint, as well as heating and cooling 

temperature setpoints, VPACC will function independently of the control strategy used. 

Common mechanical and control faults will result in a deviation of one or more of these errors 

from its value during normal operation, which can be detected by a CUSUM chart. 

The airflow rate error, Qerror, is defined as 

Qerror = Qactual - Qsetpoint (3) 

where 

Qactual = measured airflow rate 

Qsetpoint = airflow rate set point. 

16
The CUSUMs of this error, SQ and TQ, are effective for detecting damper faults and differential 

pressure sensor faults associated with airflow measurement. 

The absolute value of the airflow rate error, |Qerror|, is defined as 

|Qerror| = |Qactual - Qsetpoint| (4) 

Only one CUSUM value, S|Q|, is defined for this error since the error is never negative. S|Q| is 

effective for detecting unstable damper control faults. 

The temperature error, Terror, is defined as 

Terror = Tzone – CSP : If Tzone > CSP (5a) 

Terror = 0 : If HSP < Tzone < CSP (5b) 

Terror = Tzone – HSP : If Tzone < HSP (5c) 

where 

Tzone = zone temperature 

CSP = cooling set point 

HSP = heating set point. 

The CUSUMs of the temperature error, ST and TT, are effective for detecting damper faults, valve 

faults, and temperature sensor faults. The specific definition of temperature error used in this 

report is based on the control sequence described above. Various other commonly used control 

sequences may require changes to the definitions of heating setpoint, cooling setpoint, and 

temperature error. 

The reheat coil differential temperature error, ΔTerror, is defined as 

ΔTerror = Tdischarge – Tentering : If uhc = 0 (6a) 

ΔTerror = 0 : If uhc ≠ 0 (6b) 

where 

Tdischarge = discharge air temperature (the temperature of the air leaving the reheat coil) 

Tentering = entering air temperature (the temperature of the air entering the reheat coil) 

uhc = control signal to the reheat coil valve. 

The positive CUSUM of the reheat coil differential temperature error, SΔT, is effective for 

detecting a leaking reheat coil valve fault. The negative CUSUM, TΔT, is effective for detecting 

temperature sensor faults. The leaking valve fault highlights the advantages of automated FDD. 

Without VPACC, the local controller may be capable of masking this fault by increasing the 

airflow rate into the space. In this scenario there will be no “too hot” or “too cold” complaints, so 

a significant energy penalty may be accrued. 

17
The errors and CUSUMs are only calculated during occupied periods. During unoccupied 

periods, the errors are not computed, and the CUSUMs are reset to zero. The first hour of the 

occupied period is treated the same as the unoccupied period, to allow steady state conditions to 

develop. 

2.2.5 Point requirements 

Most of the points required by VPACC are already available in the local VAV box controller: 

room temperature, cooling setpoint, heating setpoint, airflow rate setpoint, actual airflow rate, 

and occupancy status. Entering air temperature is typically not available, so supply air 

temperature (available over the control network from the AHU controller) could be used. Many 

VAV boxes are equipped with a discharge air temperature sensor, which VPACC needs in order 

to calculate the reheat coil differential temperature error. If a discharge air temperature sensor is 

not available, a simplified version of VPACC could be used, implementing the airflow rate error 

and the temperature error only. 

2.2.6 Parameters 

For each process error to which CUSUM analysis is to be applied, there is a set of parameters 

that must be known and/or specified. These are the expected value of the process error ( ), the 

process error standard deviation (

xˆ

σˆ ), the slack parameter (k), and the alarm limits for the S and T

CUSUMs (hS and hT). For the purposes of this study, the expected value and standard deviation 

of the process error were determined by analysis of a short period of fault-free operation from a 

particular data source. CUSUM analysis was performed for each error using an expected value 

and standard deviation representative of the VAV boxes from each site. These parameters will be 

referred to as the VPACC statistical parameters throughout the remainder of this paper. The 

slack parameter k = 3 and alarm limits hS = hT = 900 are the same for all data sources. To exceed 

the alarm limit value using one min data, an error that is five standard deviations from the mean 

would have to persist for 7.5 h. When a CUSUM does exceed the alarm limit, it is reset to zero 

and the calculations resume. Each CUSUM is also reset to zero during unoccupied periods (and 

during the first hour of occupancy, to allow steady state conditions to develop). Thus, the 

severity of a fault can be established from the number of alarms over a period of time. 

2.2.7 Special Cases 

2.2.7.1 No Discharge Air Temperature Sensor 

Many VAV boxes are equipped with a discharge air temperature sensor, which VPACC needs to 

calculate the reheat coil differential temperature error. If a discharge air temperature sensor is not 

available, a simplified version of VPACC could be used, implementing the airflow rate error, the 

absolute value of the airflow rate error, and the temperature error only. In this case, a leaking 

reheat coil valve (or, in the case of electric reheat, staged reheat enabled “on” in the cooling 

mode) would not be detected unless it was so extreme that the VAV box was unable to maintain 

the zone temperature at the set point, thereby causing alarms due to excessive values of ST. 

18
2.2.7.2 Pressure Dependent 

In some VAV boxes, the damper is controlled directly in response to zone temperature without 

an intermediate determination of an airflow setpoint. Qerror and |Qerror| do not exist for a pressure 

dependent VAV box. In this case, a stuck damper may go undetected. In the case where the zone 

is overcooled, the reheat coil valve will open (or staged reheat will be enabled “on” if electric 

reheat is employed) and compensate for the fault, masking its existence. In the case where the 

zone is undercooled, the rising zone temperature may create alarms due to excessive values of ST. 

2.2.7.3 No Reheat 

Some VAV boxes do not have reheat capabilities. Others do not have reheat available part of the 

year because a two pipe hydronic system is being used for chilled water at that time. Since the 

VAV box cannot take any control action to increase zone temperature, a negative temperature 

error does not necessarily indicate a fault. In this situation, only the ST CUSUM will be 

calculated for Terror. 

2.2.7.4 Dual Duct 

In a dual duct VAV box, there is no reheat coil (and no electric reheat). Instead there are two air 

inlets, namely, a cold deck and a hot deck. Each air inlet has a damper and differential pressure 

sensor. For this arrangement, two airflow errors (Qerror,hot and Qerror,cold) and two absolute value 

airflow errors (|Qerror, hot| and |Qerror, cold|) will be calculated. No ΔTerror will be calculated as there 

is no reheat capability. 

19
3 Data Sources 

3.1 SITE-1 

SITE-1 is a large federal office building in California. Air handling unit data were collected 

from three constant-volume AHUs with enthalpy-based economizers. VAV box data were 

collected from eight single-duct, pressure independent, cooling-only VAV boxes. Stand-alone 

software was configured by facility personnel to automatically collect data from the appropriate 

equipment controllers at 5 min intervals, generate trend data files, and e-mail those files to the 

researchers. 

3.2 SITE-2 

SITE-2 is a restaurant with a pre-existing arrangement for remote monitoring. The monitoring 

firm agreed to provide the researchers with 1 min data collected from one constant-volume AHU 

with a temperature-based economizer. Only those points already being trended were available. 

Mixed air temperature was not one of those points. Although the economizer is controlled to 

maintain the supply air temperature at a setpoint, the heating and cooling coil valves are 

controlled to maintain zone temperature, not supply air temperature, at a setpoint. Therefore, the 

supply air temperature setpoint is not a meaningful quantity in all modes of operation. In 

addition, the zone temperature setpoint, another point not being trended, is varied based on a 

fixed schedule. The zone temperature setpoint is also occupant adjustable. A modified version 

of APAR was developed in which the modes are determined as described earlier, but only a 

subset of the rules, those not involving mixed air temperature or supply air temperature setpoint, 

were evaluated. 

3.3 SITE-3 

SITE-3 is a community college campus. Data were collected from nine single-duct, pressure 

independent VAV boxes with hydronic reheat. The reheat coils are supplied with hot water by a 

two-pipe system (a single piping system is used for chilled water during cooling season and hot 

water during heating season). During the cooling season (the time period during which the data 

was collected) hot water for reheat is not available, so the VAV boxes were treated as if they 

were cooling-only. The building control system was configured by facility personnel to trend 

data from the appropriate equipment controllers at one min intervals. 

3.4 SITE-4 

SITE-4 is a university campus. It was originally intended that the appropriate data would be 

trended using the university’s advanced control system, which would allow the researchers to 

access the equipment controllers via the Internet. Due to time and personnel constraints, it was 

not possible to establish this mode of data collection. However, three weeks of preliminary 1 

min data were trended by facility personnel and made available to the researchers. Data were 

collected from two variable-air-volume AHUs with enthalpy-based economizers, as well as from 

eight pressure independent VAV boxes with hydronic reheat. These systems operate 24 hours 

per day, 7 days per week. There is no occupied/unoccupied scheduling. 

20
4 Results 

Examples of faulty operation are presented from each of the sites. 

4.1 SITE-1 

4.1.1 AHU Supply Air Temperature Fault 

Figure 4.1 shows a plot of temperature and control signal data from one of the AHUs at SITE-1, 

labeled AHU-A. Based on the control signals (cooling coil valve is black, heating coil valve is 

not shown, but remains fully closed, mixing box damper is not shown, but remains aligned for 

minimum ventilation) APAR determines that AHU-A is operating in Mode 4 (mechanical 

cooling with minimum outdoor air), then applies the rules for this mode. One of the rules for 

Mode 4 is Rule 19, which states that if the average cooling coil valve control signal is fully open 

(within 1 %) and the difference between supply air temperature and supply air temperature 

setpoint is greater than 1.7 °C (3.0 °F), the cooling coil valve is saturated and a persistent supply 

air temperature error exists. Figure 4.1 shows the supply air temperature (blue), varies from 9 °C 

to 13 °C (50 °F to 55 °F) and the supply air temperature setpoint (red) is fixed at 7 °C (45 °F) - 

an unreasonably low value for this application. Clearly, the supply air temperature error is 

greater than 1.7 °C (3.0 °F), therefore APAR has detected a fault. Facility personnel confirmed 

that the fault was the result of inappropriate operator intervention. 

5

10

15

20

0 100 200 300 400 500 600 700

Time (min) From Beginning of Occupied Period

Temperature (oC)

0

20

40

60

80

100

Control Signal (0 % to 100 %)

Supply Air Temperature

Supply Air Temperature Setpoint

Cooling Coil Valve Control Signal

Figure 4.1 SITE-1 AHU-A Supply Air Temperature Fault 

 

21
4.1.2 AHU Mode Switch Fault 

 Figure 4.2 shows a plot of the control signals, including the cooling coil valve (blue), heating 

coil valve (red), and mixed air damper (green), from another of the AHUs at SITE-1, labeled 

AHU-B. Of interest is the 3 h period from 420 min until 600 min after the beginning of the 

occupied period. During this 3 h time span, APAR observes AHU operation in three different 

modes: Mode 2 (cooling with outdoor air – heating coil valve less than 1 % open, cooling coil 

valve less than 1 % open, mixed air damper greater than 26 % open [25 % is the position for 

minimum outdoor air fraction to meet ventilation requirements plus a 1 % threshold]), Mode 3 

(mechanical cooling with 100 % outdoor air – heating coil valve less than 1 % open, cooling coil 

valve greater than 1 % open, mixed air damper greater than 99 % open), and Mode 4 

(mechanical cooling with minimum outdoor air – heating coil valve less than 1 % open, cooling 

coil valve greater than 1 % open, mixed air damper less than 26 % open). Rule 28 is evaluated 

regardless of mode, stating that if more than seven mode switches are recorded in 1 h, a fault has 

been detected. In this case, the AHU switches between modes 26 times over the 3 h period, 

satisfying Rule 28 for each of the 3 h. The most probable cause of this fault is incorrect tuning 

of the temperature control PID loop in the AHU controller. A follow up with facility personnel 

confirmed the existence of the fault as well as the diagnosis. 

0

20

40

60

80

100

120

400 420 440 460 480 500 520 540 560 580 600 620

Time (min) From Beginning of Occupied Period

Control Signal (0 % to 100 %)

Mixed Air Damper Control Signal

Cooling Coil Valve Control Signal

Heating Coil Valve Control Signal

Figure 4.2 SITE-1 AHU-B Mode Switch Fault 

4.1.3 AHU Simultaneous Heating and Cooling Fault 

Figure 4.3 shows a plot of the control signals from another of the AHUs at SITE-1, labeled 

AHU-C. During a 25 min time span starting 230 min after the beginning of the occupied period, 

22
the heating coil valve (red) is open while the mixing box damper (green) is 100 % open. For a 

10 min period during this time span (from 235 min until 245 min) both the heating coil valve and 

the mixing box damper are 100 % open. This combination of control signals is inconsistent with 

any known mode, so APAR classifies this period of operation as Mode 5 (unknown mode) and 

evaluates the rules associated with this mode. Rule 23, one of the rules associated with Mode 5, 

states that if the average position of the heating coil valve is greater than 1 % and the average 

position of the mixing box damper is more than 26 % (1 % more than the minimum for 

ventilation), then a fault has been detected, since the AHU is simultaneously heating and 

cooling/economizing. The most probable cause of this fault is an AHU controller sequencing 

error. A follow up with facility personnel confirmed this diagnosis. The facility personnel then 

modified the controller sequencing logic. After the modification, the fault was not detected 

again. 

0

20

40

60

80

100

120

200 210 220 230 240 250 260 270 280 290 300

Time (min) From Beginning of Occupied Period

Control Signal (0 % to 100 %)

Mixed Air Damper Control Signal

Heating Coil Valve Control Signal

Cooling Coil Valve Control Signal

4.1.4 AHU Temperature Sensor / Damper Fault 

Figure 4.3 SITE-1 AHU-C Simultaneous Heating and Cooling Fault 

Figure 4.4 shows another plot of temperatures and control signals from AHU-C. From 220 min 

until 700 min after the beginning of the occupied period (approximately an eight hour time span), 

the mixed air damper (green) is positioned for 100 % outdoor air. The cooling coil valve (not 

shown) ranges from fully closed to fully open and the heating coil valve (not shown) remains 

fully closed. Based on this combination of control signals, APAR places AHU-C in Mode 3 

(mechanical cooling with 100 % outdoor air) and evaluates the rules for Mode 3. One of these is 

Rule 10, which states that if the outdoor air and mixed air temperature differ by more than 1.7 °C 

(3.0 °F), a fault has been detected since the outdoor air and mixed air temperature should be the 

same when the mixed air damper is positioned for 100 % outdoor air. During this time, the 

23
mixed air temperature (brown) remains approximately 3 °C (5 °F) greater than the outdoor air 

temperature (blue), satisfying Rule 10. The most probable causes of this fault include a mixed 

air or outside air temperature sensor error or a mixed damper leakage or actuator failure. A 

follow up with facility personnel revealed that the fault was caused by the location of the outdoor 

air temperature sensor on the roof of the building, remote from the AHU outside air intake. 

Although the location of the sensor is less than ideal, it was not possible for the building staff to 

relocate it. 

12

14

16

18

20

22

24

200 250 300 350 400 450 500 550 600 650 700

Time (min) From Beginning of Occupied Period

Temperature (oC)

0

20

40

60

80

100

120

Control Signal (0 % to 100 %)

Mixed Air Damper Control Signal

Mixed Air Temperature

Outdoor Air 

Figure 4.4 SITE-1 AHU-C Temperature Sensor / Damper Fault 

4.1.5 VAV Box Zone Temperature Fault 

Figure 4.5 shows a plot of the zone temperature and the related CUSUM from one of the VAV 

boxes at SITE-1, labeled VAV Box - A. Approximately 500 min after the beginning of the 

occupied period the supply air temperature from the air handling unit (brown) begins to rise, 

reaching a peak of 32 °C (90 °F) at 880 min. The zone temperature (green) closely tracks the 

supply air temperature from the AHU, peaking at approximately the same temperature and at 

approximately the same time. In this operating region the zone temperature error is defined as 

the difference between the zone temperature and the cooling setpoint. This zone temperature 

error is normalized, using sitewide statistical parameters determined from one month of training 

data from SITE-1, by subtracting the average zone temperature error (0.34 °C [0.61 °F]), then 

dividing by the standard deviation (1.0 °C [1.8 °F]). The slack parameter k is set at three, so at 

630 min, when the normalized zone temperature error increases to more than three, the positive 

temperature CUSUM (S_Temp, purple) begins to increase. S_Temp exceeds the alarm limit h 

(set at 180, which, with data at 5 min intervals, corresponds to an error five standard deviations 

greater than average for 7.5 h) at 1000 min after the beginning of the occupied period. Although 

24
building staff were notified of the detection of this fault, they were unable to investigate further. 

Clearly the cause of the problem is the high AHU supply air temperature, however it is unknown 

if there was an AHU fault. It is possible that the AHU supply air temperature setpoint was high 

due to heating demand from other VAV boxes served by the AHU. This may be a system level 

fault, resulting from the hierarchical relationship between different pieces of equipment in the 

HVAC system. 

20

22

24

26

28

30

32

34

0 100 200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400 1500

Time (min) From Beginning of Occupied Period

Temperature (oC)

0

50

100

150

200

250

CUSUM Accumulated Sum

4.2 SITE-2 

4.2.1 AHU Saturated Cooling Coil 

Figure 4.6 shows a plot from an AHU at SITE-2, labeled AHU-A. For the first 450 min of 

occupancy, the heating coil (red) remains closed, the mixed air damper (green) is aligned for the 

minimum outside air fraction, and the cooling coil valve (blue) is saturated at 100 %. Based on 

these control signals, APAR determines that AHU-A is operating in Mode 4 (mechanical cooling 

with minimum outdoor air). This AHU is a single zone unit in which the cooling coil valve is 

controlled to maintain zone temperature at the zone temperature setpoint rather than supply air 

temperature at the supply air temperature setpoint. One of the rules associated with Mode 4 is 

Rule 20, which, as modified for SITE-2, states that if the average cooling coil valve position is 

greater than 99 % open, the valve is saturated and any additional cooling load will cause the zone 

temperature to drift. When this rule is satisfied, APAR declares a warning rather than a fault, 

since the supply air temperature error cannot be evaluated (see the description of SITE-2 in 3.2, 

Figure 4.5 SITE-1 VAV Box-A Zone Temperature Fault 

AHU Supply Air 

Zone Temperature

Stemp (positive zone temperature error CUSUM)

Cooling Setpoint

Heating Setpoint

25
for further explanation). The zone temperature (brown) is maintained between 20 °C (68 °F) and 

22 °C (72 °F), a reasonable range for the application. There are many possible diagnoses 

including: temperature sensor error, cooling coil valve actuator failure, inappropriate 

operator/occupant intervention, temperature control PID loop tuning error, or sequencing logic 

error. On the other hand, it is entirely possible that this warning was caused by some unusual 

activity in the zone which generated a large cooling load. A follow up with facility personnel 

was not possible. 

Figure 4.6 Site-2 AHU-A Saturated Cooling Coil Fault 

0

20

40

60

80

100

120

0 50 100 150 200 250 300 350 400 450 500

Time (min) From Beginning of Occupied Period

Control Signal (0 % to 100 %)

15

17

19

21

23

25

27

29

Temperature (oC)

Cooling Coil Valve Control Signal

Mixed Air Damper Control Signal

Heating Coil Valve Control Signal

Zone Temperature

 

4.2.2 AHU Mode Switch Fault 

Figure 4.7 shows a plot of the control signals from AHU-A, including the cooling coil valve 

(blue), heating coil valve (red), and mixed air damper (green). During the first three hours of the 

occupied period APAR observes AHU-A cycle between two different modes: Mode 2 (cooling 

with outdoor air – heating coil valve less than 1% open, cooling coil valve less than 1% open, 

mixed air damper open more than 21% [20% is the minimum for ventilation]) and Mode 3 

(mechanical cooling with 100 % outdoor air – heating coil valve less than 1% open). Rule 28 is 

evaluated regardless of mode, stating that if more than seven mode switches are recorded in an 

hour, a fault has been detected. In this case, the AHU switches between the two modes 72 times 

during the three hour period, satisfying Rule 28 for each of the three hours. The most probable 

cause of this fault is either a sequencing error or incorrect tuning of the temperature control PID 

loop in the AHU controller. The existence of the fault was confirmed by the monitoring firm and 

reported to the facility personnel, who were unable to investigate further. 

26
0

20

40

60

80

100

120

0 20 40 60 80 100 120 140 160 180 200

Time (min) From Beginning of Occupied Period

Control Signal (0 % to 100 %)

Cooling Coil Valve Control Signal

Mixed Air Damper Control Signal

Heating Coil Valve Control Signal

 

AV box E reveals that 

the zone temperature routinely exceeds the cooling set point of 22.2 oC (72 oF) by 2.2 oC (4 oF) to 

3.3 oC (6 oF). This produces 70 alarms of ST per week on average and nine weeks with 100 to 115 

alarms of ST. It is common for the discharge air temperature to this zone to be 15.6 oC (60 oF) to 

21.1 oC (70 oF), indicating that the capacity problems are due at least in part to the manner in 

which the AHU is being controlled and/or to the design of the system. Another VAV box (C) on 

the same AHU routinely operates in the heating mode 1.1 oC (2 oF) to 1.7 oC (3 oF) below the 

heating set point of 22.2 oC (72 oF). The lack of reheat makes it impossible for the AHU to 

satisfy the two zones when one requires cooling and the other heating. Operational changes to 

Figure 4.7 Site-2 AHU-A Mode Switch Fault 

4.3 SITE-3 

Results from 20 weeks of field testing for each of the nine VAV boxes are summarized in Table 

4.1. The number reported in a cell represents the total number of alarms over the 20 week period 

of a particular CUSUM and a particular VAV box. The total number of alarms for each box are 

also reported in the last column of Table 4.1. Note that the total excludes SQ and TQ because they 

are in essence a subset of S|Q|. That is, an alarm of SQ or TQ will always produce an alarm of S|Q|, 

although S|Q| may alarm first if, for instance, the airflow errors are predominantly positive but 

include some large negative errors as well. Because reheat was not available, VPACC did not 

monitor the zone temperature error in the heating mode. 

The VPACC results in Table 4.1 indicate that VAV boxes E and I are performing poorly and 

VAV boxes F, G, and H are performing well. The other VAV boxes are performing somewhere 

between these two extremes. Closer inspection of the trended data for V

27
reduce the minimum airflow rates for the heating mode may help alleviate the problem of 

overcooling certain zones. 

Table 4.1 

VPACC results for the field data sets. 

Number of Alarms 

VAV Box 

SQ TQ ST TT S|Q| Total 1

A 0 29 36 0 29 65 

B 0 125 62 0 125 187 

C 0 38 42 0 38 80 

D 0 104 52 0 105 157 

E 0 70 1406 0 72 1478 

F 0 1 0 0 1 1 

G 0 0 1 0 0 1 

H 0 10 3 0 10 13 

I 0 674 3 0 674 677 

1

 Total = ST + TT + S|Q| because SQ and TQ are subsets of S|Q|. 

The VPACC results in Table 4.1 indicate that box I has severe airflow control problems. The 

minimum number of alarms of TQ in a week is seven, while the average is close to 34. This 

indicates that the flow rate to the zone is consistently less than the set point airflow rate. This is 

true whether the VAV b s to indicate that 

the static pressure is not sufficient to deliver the amount of air needed in the zone. Due to the 

re of the flow error, S|Q| alarms at the same times as TQ. 

ox operates in the heating or cooling mode. This seem

natu

VAV boxes F and G alarm only one time each over the twenty weeks of testing. Inspection of 

the process data supported the findings of VPACC, namely, that the control was quite good. 

VAV box H also performed well, with 11 of the 13 alarms occurring during the week of June 10-

16, 2002. For much of the first part of that week, the AHU supply air temperature ranged from 

18.3 oC (65 oF) to 21.1 oC (70 oF), causing the zone temperature to exceed its cooling set point of 

22.2 oC (72 oF) by nearly 1.1 oC (2 oF). Hence the problem does not appear to be with the control 

of the VAV box. The controller operated in the heating mode during most of the testing and this 

contributed to the low number of alarms because only flow control was monitored in the heating 

mode. 

The performance of the remaining four VAV boxes (A,B,C, and D) is a little more difficult to 

assess. A significant number of the alarms for each occur during five weeks of the testing, 

namely, May 20-26, 2002, May 27 to June 2, 2002, June 10-16, 2002, July 8-14, 2002, and July 

22-28, 2002. Specifically, 55 of 65 alarms for A, 111 of 187 alarms for B, 75 of 80 alarms for C, 

and 101 of 156 alarms for D occur during those five weeks. 

The problem in the weeks of May 20-26, 2002 and May 27 to June 2, 2002 is associated with the 

AHU temperature control. All four boxes (as well as E, which is served by the same AHU) have 

a significant number of ST alarms during these two weeks. Closer inspection of the trended data 

indicates the discharge air temperatures to the zones exceeded 23.9 oC (75 oF) for nearly 20 h 

28
over the latter part of the first week and the beginning of the second week. Since this time period 

encompasses the Memorial Day holiday, it is likely that there was a scheduling inconsistency 

that had the AHU and VAV boxes operating in an occupied mode while the chiller was not 

running. 

he problem in the other three weeks is a sudden drop in the airflow through the four boxes. 

Figure 4.8 shows the ture error (Terr error (Qerror) for box D during a 

portion of the week of July 8-14, 2002. The sudden drop in the airflow rate produces large 

negative airflow errors and positive temp rs. A sho in F re 4.9, this results in 

numerous airflow ala s (TQ) and o tem atur arm ( ) . This particular problem occurs at 

six distinct times in the three weeks. The problem occurs at the same t in each of the boxes 

and also occurs in box E. The fact that the alarm ccur the same in each of the boxes 

points to the AHU as the likely source of the problem. 

T

 tempera or) and airflow

erature erro s wn igu

rm ne per e al ST

ime

s o at time

-1

2

3

Data Point (1-min. Intervals)

2000 2250 2500 2750 3000 3250 3500 3750 4000

T

error (oC)

0

1

Qerror (%)

-50

50

100

0

-2 -100

Figure 4.8 Field data for VAV box 101W during the week of July 8, 2002 

Considering the remaining 16 weeks of data, the results from VPACC indicate that boxes A and 

nificant problem. 

C are performing fairly well (averaging about 1 alarm per week), while boxes B and D are not 

doing as well. In general boxes B and D lack capacity in the cooling mode, as indicated by actual 

airflow rates that are considerably less than the set point values. In the case of box B, the 

resultant temperature errors can be significant, sometimes exceeding 1.1 oC (2 oF). Despite the 

capacity problems, temperature control in zone D is not a sig

29
Data Point (1-min. Intervals)

2000 2250 2500 2750 3000 3250 3500 3750 4000

800

1000

-1000

-800

600

-600

-400

-200

0

200

400

CUSUM

ST

Figure 4.9 VPACC output corresponding to the conditions in Figure 7a 

4.4 SITE-4 

4.4.1 AHU Simultaneous Heating and Cooling Fault 

Figure 4.10 shows a plot of the control signals from one of the AHUs at SITE-4, labeled AHUA. During the first 1140 min (19 h) of the day, the heating coil valve (red) varies between 5 % 

and 35 % open. Over the same time period, the mixing box damper (green) varies between 25 % 

and 35 % open. This AHU has two separate mixing box dampers: one allows the minimum 

amount of outdoor air for ventilation, while the other is for cooling with outside air. The mixing 

box damper position shown in Figure 4.10 refers to the arrangement for cooling with outside air. 

The cooling coil is closed throughout the 19 h time period. This combination of control signals 

is inconsistent with any known mode of operation, so this period of operation is classified as 

Mode 5 (unknown mode) and evaluates the rules associated with Mode 5. Rule 23, one of the 

rules associated arrangement of 

HU-A, states that if the average position of the heating coil valve is greater than 1 % and the 

urther. 

TQ

 with Mode 5 and modified to reflect the mixing box damper 

A

average position of the mixing box damper is greater than 1 %, then a fault has been detected, 

since the AHU is simultaneously heating and cooling/economizing. The most probable cause of 

this fault is either a sequencing error or a temperature sensor error related to the specific control 

strategy implemented in this AHU, in which the cooling coil valve, heating coil valve, and 

mixing box damper are each controlled by independent PID loops, along with independent 

temperature sensors and setpoints. Facility personnel were not able to investigate f

30
0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

0 200 400 600 800 1000 1200 1400

100.0

Control Signal (0 % to 100 %)

Cooling Coil Valve Control Signal

Heating Coil Valve Control Signal

Mixing Box Damper Control Signal

Time (min)

31

tential 

site. 

 

4.4.2 VAV Box Airflow Fault 

A sufficient quantity of data to generate statistical parameters for the SITE-4 VAV boxes was 

not available, so parameters from SITE-1 were used instead. SITE-1 parameters were chosen 

because SITE-1 and SITE-4 both have single-duct, pressure-independent VAV boxes. Figure 

4.11 shows a plot of zone airflow data and the damper control signal from a VAV box at SITE-4, 

labeled VAV Box - A. For this entire day, the airflow setpoint (blue) is 0.27 m3

/s (580 cfm). 

The actual measured airflow rate (red) is in the region of (0.46 ±0.02) m3

/s [(965 ±50) cfm]. The 

damper control signal (not shown) is 0 %. The positive airflow CUSUM (purple) steadily 

increases, exceeding the alarm limit (set at 900, which, with data at 1 min intervals, corresponds 

to an error five standard deviations greater than average for 7.5 h) at 1415 min. A follow up with 

facility personnel confirmed the existence of the fault. Possible diagnoses include: airflow 

sensor failure, damper/actuator failure, improper airflow control PID loop tuning, control logic 

sequencing error, or inappropriate operator intervention. A study to determine robust sets of 

statistical parameters for a variety of systems is needed; however, this example illustrates the 

possiblity of using the CUSUM approach without collecting training data from each po

Figure 4.10 SITE-4 AHU Simultaneous Heating and Cooling Fault 
0.00

0.10

0.20

0.30

0.40

0.50

0.60

0 200 400 600 800 1000 1200 1400

Time (min)

Airflow (m^3 / s)

0

100

200

300

400

500

600

700

800

900

1000

CUSUM Accumulated Sum

Measured Airflow

Airflow Setpoint

SQ (positive airflow error CUSUM)

Figure 4.11 SITE-4 VAV Box Airflow Fault 

5 Summary and Future Work 

ence that the FDD tools will perform in an even greater variety of applications. Several 

faults have been successfully detected and confirmed by building operations staff. Every site has 

been found to have at least one fault. Even though the sample size is small, these results appear 

to confirm the hypothesis that faults of the type that can be detected by these tools are common. 

This report presents the results of a field study to evaluate APAR, a rule based FDD tool for 

AHUs, and VPACC, a statistical quality control based FDD tool for VAV boxes. APAR consists 

of a set of expert rules, derived from mass and energy balances. Control signals are used to 

determine the AHU’s mode of operation, which identifies the subset of the rules to be evaluated. 

VPACC uses a small set of process errors, valid for most VAV box control strategies, to measure 

VAV box performance. CUSUM charts, a statistical quality control tool, are used to evaluate the 

process errors. Thresholds are determined by statistical analysis of a database of “normal 

operation” data. 

APAR and VPACC were evaluated using data from several different sources – an office 

building, a restaurant, and community college and university campuses, featuring constant- and 

variable-air-volume systems. Any evaluation using field data must contend with some inherent 

difficulties: reliance on sensor data to discern the true state of the system, the inability to report 

a “false positive” (an undetected fault), and ambiguity regarding what constitutes a fault. 

However, in this case consistent results across diverse testing environments gives a high level of 

confid

32
33

 a parallel study beyond the scope of this report, the FDD tools were embedded in AHU and 

VAV box controllers and evaluated in a laboratory setting. Follow-on work will require 

partnering with control system manufacturers to conduct field tests of APAR and VPACC, 

embedded in their own controller products. 

NIST’s vision of full commercialization of automated fault detection and diagnostics is one in 

which APAR and VPACC, along with appropriate parameters and thresholds, are packaged 

within HVAC control products. In order for this vision to become reality, more work is needed 

in three main areas. First, it is impractical to expect trend data to be evaluated to determine the 

necessary parameters and thresholds for each site, as was done in this study. Ideally, sets of 

robust parameters and thresholds that are effective across specified ranges of applications would 

be available. Additional field data from a wide variety of systems must be collected in order to 

determine these robust parameters and thresholds. Also, the current embedded FDD tools are 

written using generic mathematical functions available in the languages in which the controllers 

are programmed. Although this approach is suitable for a technology demonstration, built-in 

APAR and VPACC functions would greatly simplify the task of embedding FDD in a control 

program. Finally, more work is needed to develop alternative ways to interpret FDD results and 

deliver this information to the building operator. The most direct approach is to generate an 

alarm that the operator must acknowledge whenever a rule is satisified (APAR) or a cumulative 

sum exceeds the alarm limit (VPACC). Refinements to the basic scheme are possible. For 

example, rather than automatically sending the alarm to the operator, the building control system 

could highlight, on demand, those devices having experienced the greatest number of alarms in a 

given period of time. Or, ent system is used, an alarm 

could automatically generate an appropriate work order. However, many faults are the result of 

design or commissioning issues that are beyond the scope of the building maintenance staff. 

uipment, such as an air handling unit, boiler, or chiller, 

ools”, NISTIR 6964. 

In

if an automated maintenance managem

Furthermore, a fault in another piece of eq

could result in this approach generating a large number of alarms, perhaps overwhelming the 

operator. A mechanism is needed to resolve multiple conflicting fault reports before reporting 

them to the operator. 

6 References 

[1] Castro, N.S., Schein, J., Park, C., Galler, M.A., Bushby, S.T., and House, J.M., 2002, 

“Results from Simulation and Laboratory Testing of Air Handling Unit and Variable Air Volume 

Box Diagnostic T

[2] House, J.M., Vaezi-Nejad, H., and Whitcomb, J.M., 2001, “An Expert Rule Set for Fault 

Detection in Air-Handling Units,” ASHRAE Transactions, Vol. 107, Pt. 1: pp. 858-871. 

[3] Ryan, Thomas P., 2000, Statistical Methods for Quality Improvement, 2nd Edition, Wiley and 

Sons, New York.