NIST Technical Note 1774

FDD CX: A Fault Detection and 

Diagnostic Commissioning Tool for 

Residential Air Conditioners and Heat 

Pumps

Jaehyeok Heo

W. Vance Payne 

Piotr A. Domanski

http://dx.doi.org/10.6028/NIST.TN.1774

NIST Technical Note 1774 
FDD CX: A Fault Detection and 

Diagnostic Commissioning Tool for 

Residential Air Conditions and Heat 

Pumps 

Jaehyeok Heo

W. Vance Payne

Piotr A. Domanski

Energy and Environment Division

Engineering Laboratory

http://dx.doi.org/10.6028/NIST.TN.1774

November 2012

U.S. Department of Commerce 

Rebecca Blank, Acting Secretary

National Institute of Standards and Technology 

Patrick D. Gallagher, Under Secretary of Commerce for Standards and Technology and Director 
Certain commercial entities, equipment, or materials may be identified in this

document in order to describe an experimental procedure or concept adequately.

Such identification is not intended to imply recommendation or endorsement by the

National Institute of Standards and Technology, nor is it intended to imply that the

entities, materials, or equipment are necessarily the best available for the purpose. 

Use of Non-SI Units in a NIST Publication

The policy of the National Institute of Standards and Technology is to use the International System of Units (metric 

units) in all of its publications. However, in North America in the heating, ventilation and air-conditioning industry, 

certain non-SI units are so widely used instead of SI units that it is more practical and less confusing to include some 

measurement values in customary units only. 

Software Disclaimer

This software was developed at the National Institute of Standards and Technology by employees of the Federal 

Government in the course of their official duties. Pursuant to title 17 Section 105 of the United States Code this 

software is not subject to copyright protection and is in the public domain. These programs are experimental 

systems. NIST assumes no responsibility whatsoever for their use by other parties, and makes no guarantees, 

expressed or implied, about its quality, reliability, or any other characteristic. We would appreciate 

acknowledgement if the software is used. This software can be redistributed and/or modified freely provided that 

any derivative works bear some notice that they are derived from it, and any modified versions bear some notice that 

they have been modified.

National Institute of Standards and Technology Technical Note 1774

Natl. Inst. Stand. Technol. Tech. Note 1774, 33 pages (November 2012) 

http://dx.doi.org/10.6028/NIST.TN.1774

CODEN: NTNOEF
Contents

1. Introduction ................................................................................................................................ 1

2. Installation .................................................................................................................................. 2

3. Using FDD CX .............................................................................................................................. 3

3.1. System Information .............................................................................................................. 3

3.2. Fault Detection and Diagnostics........................................................................................... 8

3.3. FDD Results Graphs ............................................................................................................ 10

3.4. About FDD CX ..................................................................................................................... 12

3.5. Guidance on Adjusting Correction Factors ........................................................................ 13

3.6. Guidance on Adjusting Thresholds .................................................................................... 14

4. Application Example ................................................................................................................. 16

4.1. Enter the System Information ........................................................................................... 16

4.2. Run Fault Detection and Diagnostics................................................................................. 17

4.3. Examine FDD Result Graphs.............................................................................................. 20

5. The Fault Detection and Diagnosis Method ............................................................................. 22

References .................................................................................................................................... 25

Acknowledgements....................................................................................................................... 26
1

1. Introduction

In earlier work the National Institute of Standards and Technology (NIST) made detailed 

measurements on the cooling (Payne, Domanski, & Hermes, 2006) and heating [ (Payne, 

Domanski, & Yoon, 2009), (Yoon, Payne, & Domanski, 2011)] performance of a residential, splitsystem, air source, heat pump with faults imposed. The previous research on FDD techniques 

was examined [e.g., (Rossi & Braun, 1997), (Braun, 1999), (Chen & Braun, 2001)] and used to 

refine the rule-based chart technique of fault detection and diagnostics of common faults which 

can occur during operation of an air conditioner (AC) and heat pump (HP) [ (Kim M. , Yoon, 

Payne, & Domanski, 2008). 

While an AC or HP may exhibit a range of faults during its operational life, the list of most 

common faults resulting from improper installation is smaller, with the most prevalent being 

refrigerant undercharge, refrigerant overcharge, and improper indoor air flow. The prevalence 

of these three commissioning faults provided a motivation for developing a standalone 

software tool that incorporated these “commissioning mode” features. The generic nature of 

the FDD method allows this technique to be applied to split systems equipped with

thermostatic expansion valves (TXVs), which represent a majority of residential and light 

commercial systems installed today. 

This FDD based commissioning tool software is meant to be applied to residential, unitary, airsource, single-speed, vapor compression air-conditioning (AC) or heat pump (HP) systems with 

nominal cooling capacities less than 19 kW (≈65 000 Btu h-1 or 5.4 tons). Air and refrigerant 

temperatures plus refrigerant saturation temperatures need to be measured throughout the 

system and input into the program to determine proper refrigerant charge and indoor air flow. 
2

2. Installation

2.1. PC System Requirements

Personal computer (PC) with Microsoft® Windows® 7, XP with Service Pack 3, and Vista 

operating systems.

Free space for complete installation: 10.0 MB

The installation module requires .NET Framework 2.0 Service Pack 2 (or later version), which 

can be downloaded from the Microsoft website if not present on the user’s PC.

2.2. Installation Procedure

Click [Start], select [Run], type: D:\NIST FDD CX Ver. 1.0.msi, or use the appropriate letter 

associated with the drive and directory on which the installation module is located, and press 

[Enter]. 

Follow the on screen instructions.

If FDD CX is installed using the default locations, the executable file will be placed in C:\Program 

Files\NIST\FDD CX, and files with example compressor maps and example data will be placed in 

\NIST\FDD CX\data\compressor maps and \NIST\FDD CX\data\examples subdirectories, 

respectively. 
3

3. Using FDD CX

The user selects COOLING or HEATING in the FDD CX opening window of Figure 1, then the 

graphical user interface (GUI) displays the main screen with the System Information tab open. 

The user interacts with FDD CX through the GUI, which consists of three main parts: System 

Information, Fault Detection and Diagnostics, and FDD Result Graphs. The fourth tab, About 

FDD CX, provides general information about the software. 

Figure 1. Opening screen for selecting cooling or heating mode

3.1. System Information

The System information tab is shown in Figure 2 and Figure 3 for the cooling and heating 

modes, respectively. The sequence of steps the user is required to take is listed at the bottom 

on the right hand side of the screen.

Step 1. Select refrigerant

Refrigerant type (R410A, R22,.etc.) is selected to allow calculation of refrigerant properties. 

Step 2. Select compressor model

Compressor mass flow rate coefficients are selected by clicking the Load data button, which 

accesses a spreadsheet file that must be constructed as described in Section 4. A complete 

description of compressor map equations may be found in (AHRI, 2004). A common source of 

the compressor mass flow rate coefficients may be the online resources provided by the 

compressor manufacturer; using the compressor model number, the coefficients may be found. 
4

Figure 2. Cooling system information screen

Figure 3. Heating system information screen
5

If the compressor mass flow rate coefficients cannot be found, use an example compressor 

data file found under \NIST\FDD CX\data\compressor maps\; the mass flow rate map is used to 

predict capacity and efficiency only and will not affect fault detection. 

Figure 4. Compressor map mass flow rate coefficients data file format example

Step 3. Input data

Input of data (temperatures or temperature-based variables) measured on the AC or HP, may 

be performed manually, by entering data using the GUI, or by loading the data from a file 

stored on the PC. If the user wants to manually enter the temperature data, they select the Use

Manual Input button, and then enter the temperatures one-by-one into the data table. If the 

user selects Use File Input, they select the Load Data button and use the File Explorer to select 

the spreadsheet file that contains the data. 

The user must enter 11 cooling or 10 heating temperatures or temperature based variables. 

Table 1 and Table 2 list and describe the inputs and measurement locations for the cooling and 

heating modes, respectively. 
6

Table 1. Cooling temperature input descriptions

Feature 

Name Description

Tid Indoor air dry-bulb temperature. Indoor air handler return (inlet) air dry-bulb 

temperature (°F)

Tidp Indoor air dewpoint temperature. Indoor air handler return (inlet) air dewpoint 

temperature (°F)

Tido Evaporator air exit temperature. Indoor air handler supply (exit) air dry-bulb 

temperature (°F)

Tod Outdoor air dry-bulb temperature. Outdoor unit inlet air dry-bulb temperature (°F)

Todo Condenser air exit temperature. Outdoor unit exit air dry-bulb temperature (°F)

Te Evaporator exit refrigerant saturation temperature. Refrigerant saturation 

temperature at the vapor line service valve pressure (°F)

Tsh Evaporator exit refrigerant superheat. Refrigerant temperature minus the 

saturation temperature at the vapor line service valve pressure (°F)

Td Compressor discharge refrigerant temperature (°F) [Measured at the discharge port 

of the compressor. ]

Tc Condenser inlet refrigerant saturation temperature. Refrigerant saturation 

temperature at the liquid line service port pressure (°F)

Tsc Condenser exit refrigerant subcooled temperature. Refrigerant saturation 

temperature minus liquid temperature at the liquid line service port (°F)

Tco Condenser exit refrigerant temperature. Refrigerant temperature at the liquid line 

service port (°F)
7

Table 2. Heating temperature input descriptions

Feature 

Name Description

Tid Indoor air dry-bulb temperature. Indoor air handler return (inlet) air dry-bulb 

temperature (°F)

Tido Evaporator air exit temperature. Indoor air handler supply (exit) air dry-bulb 

temperature (°F)

Tod Outdoor air dry-bulb temperature. Outdoor unit inlet air dry-bulb temperature (°F)

Todp Outdoor air dewpoint temperature. Outdoor unit air dewpoint temperature (°F)

Teo,sat Evaporator exit refrigerant saturation temperature. Refrigerant saturation 

temperature at the suction service port pressure (°F)

TshE Evaporator exit refrigerant superheat. Refrigerant temperature minus the 

saturation temperature at the suction service port pressure (°F)

Td Compressor discharge refrigerant temperature (°F) [Measured at the discharge port 

of the compressor.]

Tc Condenser inlet refrigerant saturation temperature. Refrigerant saturation 

temperature at the vapor line service port pressure (°F)

Tsc Liquid line subcooling at the outdoor service valve. Refrigerant saturation 

temperature minus liquid temperature at the liquid line service port (°F)

Tco Condenser exit refrigerant temperature. Refrigerant temperature at the liquid line 

service port (°F)

If the user selects the Manual Input option, the temperatures are entered in the table. Once all 

of the required temperatures are entered, the user clicks on Load Data to update the data 

values used in the calculations. 

If the user selects the Use File Input option, the user must then click the Load Data button and 

navigate to the data file containing the temperature values. Figure 5 and Figure 6 show 

example spreadsheet data files for the cooling and heating modes, respectively.

Figure 5. Cooling example data file
8

Figure 6. Heating example data file

The first line of the data file may contain any kind of text information such as a description of 

the data file, the second line of information may be any kind of text such as the temperature 

labels, and the following lines can be one or more temperature data sets. The first two lines 

are not used by the program and are skipped during the input process. The “END” statement 

must be included in the first column and last row of the data file to indicate the end of the 

temperature data. 

3.2. Fault Detection and Diagnostics

Once the required system information has been provided, the user can move to the Fault 

Detection and Diagnostics screen as shown in Figures 7 and 8 for the cooling and heating 

modes, respectively. The sequence of steps the user should take is listed at the bottom of the 

screen. 

Step 1. Adjust correction factors (optional)

If the user is familiar with the system being tested, correction factors may be input into the 

table. The temperature corrections (positive or negative) allow the predicted, no-fault 

temperatures (features) to be corrected to more closely match system data. The correction 

factors (abbreviated as Corr. fac.) are used when the user has a large set of no-fault data at 

different outdoor and indoor temperatures with which to correct the predicted features. 

Section 3.5 provides additional guidance on using this option. 

Step 2. Adjust thresholds (optional)

If the user has a large set of no-fault data, they may also adjust the Threshold values to 

maximize the No-Fault Probability. Here the user may select appropriate Threshold values for 

the temperature residuals used by the FDD logic to determine system performance. Under the 

Threshold label, the user clicks the drop-down menu and selects Default, Tested, or Manual

values of threshold temperature differences: Default threshold values were selected to 

produce a wide tolerance for measurement uncertainty while maintaining fault detection 

sensitivity; Tested threshold values were determined from laboratory testing; Manual threshold 

values allow the user to input a value. The temperature residual is defined as the measured 

value minus the predicted value. The threshold defines the no-fault temperature difference

value and is the amount of change in a temperature residual that is still considered neither 
9

positive nor negative; meaning that the temperature residual can vary up to the threshold 

amount, above and below zero, before it is considered a non-zero value. Ideally, the residuals 

will all equal zero if the predicted and measured temperature variables are equal. 

Figure 7. Cooling fault detection and diagnosis screen
10

Figure 8. Heating fault detection and diagnosis screen

Step 3. Adjust value of EER/COP alarm control

The EER or COP Alarm Control (%) is adjusted here to provide the user with a visual indication of 

a predicted efficiency degradation that is equal to or greater than the Alarm Control (%). If the 

EER or COP degradation is greater than the set value, the EER/COP Warning button will light-up, 

and the fault with the greatest probability is most likely occurring. 

Step 4. Run

If the user entered temperature data manually, they should click the Run single data set button 

to obtain FDD results. If the user entered temperature data from a spreadsheet file with more 

than one data set of temperatures (more than one row of temperature data), then they may 

use the Run single data set button, Run all data sets button, or Run all with timer button. By 

clicking the Run single data set button, each line of data is evaluated in a single-step fashion; a 

single click evaluates one line of data at a time. The Run all data sets button processes all of 

the data within the data file. The Run all with timer button processes the entire data set with a 

small pause between evaluations. Run all with timer produces the same result as Run single 

data set, but does so without stopping as each new set of temperature data is evaluated. 

The Rule Based Chart indicates the positive or negative sign of a particular temperature residual 

for a particular fault. For example, in the first row, first column of the cooling mode table, the 

value of -1 indicates that a negative temperature residual exists for the evaporator refrigerant 

saturation temperature during an undercharged refrigerant fault (UC). The value of 0 for an 

overcharge fault (OC) indicates a neutral change in evaporator refrigerant saturation 
11

temperature. A neutral change means that the temperature residual does not vary more than 

plus or minus the threshold value. A positive one (1) indicates a positive temperature 

difference for refrigerant superheat with an undercharge fault. 

The cells within the Individual Probability table, shown in Figure 7 and Figure 8, correspond 

directly with the cells in the Rule Based Chart table. For example, Row 1, Column 1 of the 

Individual Probability table in Figure 7 is the probability, P between 0 and 1, that Te has a 

negative temperature residual based upon the threshold value used. 

The Probability table indicates the total probability of an Undercharge fault (UC), overcharge 

fault (OC), indoor air flow fault (EF in cooling, CF in heating), or No-Fault (NF). The numeric 

values shown in this table are also plotted in the Fault Classifier chart. 

The Fault Classifier chart shows different height bars with the tallest bar indicating the most 

likely fault condition including no-fault probability. 

Performance Information shows the abbreviation of the most likely fault condition, the 

estimated change in system efficiency (EER/COP), and the EER/COP Warning light. The warning 

light will change color if the estimated change in system efficiency is greater than or equal to 

the Alarm Control (%) value. 

3.3. FDD Result Graphs

Once the user has selected Run data on the Fault Detection and Diagnostics tab, they may 

examine the averaged fault detection and diagnostic statistics on the FDD Result Graphs screen

shown in Figure 9 and Figure 10 for the cooling and heating modes, respectively. If the user 

were processing the data in single steps or using the Run all with timer from the Fault Detection 

and Diagnostics screen, the averaged parameters are updated for those temperature data sets 

processed thus far; the averaged parameters would not be indicative of the averages for the 

entire data set. If the user has selected Run all data sets, then the averages presented would 

be averages for the entire data set. 
12

Figure 9. Cooling FDD results graphs screen for a no-fault condition

Figure 10. Heating FDD results graphs screen for a no-fault condition
13

The average probability of a fault is shown graphically on the far left of the screen. Four fault 

conditions, including the NF (No-Fault) condition, are shown as red bars. The condition with 

the highest probability of occurrence will have the tallest bar in this graph. The numeric values 

of the individual probability percentages are shown in the table below the graph. In the 

example shown in Figure 9, NF or No-Fault, has the highest probability. 

The center graph in Figure 9 shows the average values of the temperature residuals. If the 

measured (input) values were identical to the predicted values (no-fault values), the residuals 

would be exactly zero. Since the data that was processed to generate Figure 9 was No-Fault 

data, the residuals are very small and are much less than the temperature threshold values 

entered on the Fault Detection and Diagnostics screen. 

The graph on the right side of Figure 9 shows the predicted percentage degradation in system 

performance due to the most likely fault. Since this graph was generated with no-fault data, 

the residuals are close to zero indicating a no-fault system. 

3.4. About FDD CX

The user may select the About FDD CX tab to read background information on the software as 

shown in Figure 11. Contact information for any software questions or comments is also 

provided on this screen. 

Figure 11. Background information screen for FDD CX
14

3.5 Guidance on Adjusting Correction Factors

If the user has no-fault data (such as Cooling NF example.xlsx and Heating NF examples.xlsx files 

in the \NIST\FDD CX\data\examples subdirectory), they may run FDD CX and compare the 

measured and predicted features to determine appropriate correction factors. These 

correction factors should ideally include a range of outdoor and indoor temperature conditions, 

and at the least, should include several data sets. Correction factors are just additive offsets 

that may be used to help the generic no-fault model predictions more closely match no-fault 

measured data. 

The FDD methodology depends on evaluating differences between the temperature values 

(features) measured during system operation and the values considered to be “correct” values 

for a fault-free system. These “correct” or “no-fault” values are calculated by FDD CX as a 

function of indoor and outdoor conditions based on measurements taken in environmental 

chambers on a fault-free residential heat pump. While the general trends of the calculated 

features are expected to be very similar for all vapor compression systems, absolute values of 

these features may differ due to differences in components used in different systems. For this 

reason, the Fault Detection and Diagnostics screen provides an option to input correction 

parameters for the FDD features to provide an offset, thus accounting for these differences. 

Since refrigerant subcooling is the most influential feature for determining the proper 

refrigerant charge in the system, we have included Figures 12 and 13 to show the generic nofault model’s predictions for Tsc as a function of outdoor temperature for the cooling and 

heating modes, respectively. . If the installer has knowledge of the proper system subcooling 

for a given set of ambient conditions, they may input a correction factor for the Tsc parameter 

on the Fault Detection and Diagnostics screen. The user should use the appropriate outdoor 

temperature, determine the predicted subcooling, and input an offset value that is the 

difference between the generic no-fault model and the manufacturer’s value. 
15

Figure 12. Cooling generic no-fault model refrigerant subcooling temperature

Figure 13. Heating generic no-fault model refrigerant subcooling temperature
16

3.6. Guidance on Adjusting Thresholds

Do not decrease the values of thresholds unless you have reliable no-fault temperature data for 

your particular system, and it is a system similar to the 13 SEER, 8.5 HSPF heat pump used to 

develop the current version of FDD CX. Temperature thresholds may be adjusted if the user has 

knowledge of the variation in temperature measurements of the no-fault system. Reducing 

thresholds increases the sensitivity of the diagnostics but potentially increases the probability 

of false alarms; thus, the user must carefully combine the adjustment of correction factors and 

thresholds with knowledge of the no-fault system to produce reliable fault detection and 

diagnosis. The magnitudes of temperature changes will vary from system to system based 

upon many factors such as refrigerant line set lengths, indoor air flow restrictions (duct work, 

filters, etc.), and system rated efficiency. 

Thresholds are a measure of how well a particular temperature variable can be predicted by the 

generic no-fault model. Temperature variations will be much higher for field assembled system 

measurements than laboratory tested system measurements. Thresholds attempt to capture 

the effects of measurement uncertainty in variables that are predicted by the generic no-fault 

model. The default temperature thresholds used by FDD CX attempt to provide fault detection 

while maintaining sensitivity to faults in varied, yet similar, systems. 
17

4. Application Example

The following example illustrates how FDD CX diagnoses a cooling mode undercharged 

refrigerant fault. Example files for this illustration include Cooling UC 4 examples.xlsx, Cooling 

UC Add1 examples.xlsx, and Cooling UC Add2 examples.xlsx. 

Example files for no-fault, refrigerant undercharge, refrigerant overcharge, and indoor coil air 

flow restrictions are also given in the \NIST\FDD CX\data\examples subdirectory for the cooling 

and heating modes. Table 3 lists and describes the example data files included with FDD CX.

Table 3. List of FDD CX example data files

Filename Description

Cooling EF 2 examples.xlsx Cooling mode indoor (evaporator) air flow restriction

Cooling NF example.xlsx Cooling mode no-fault

Cooling OC 3 examples.xlsx Cooling mode refrigerant overcharge

Cooling UC 4 examples.xlsx Cooling mode refrigerant undercharge

Cooling UC Add1 examples.xlsx Cooling mode refrigerant undercharge after adding 

refrigerant for the first time

Cooling UC Add2 examples.xlsx Cooling mode refrigerant undercharge after adding 

refrigerant for the second time

Heating CF examples.xlsx Heating mode indoor (condenser) air flow restriction

Heating NF examples.xlsx Heating mode no-fault

Heating OC examples.xlsx Heating mode refrigerant overcharge

Heating UC examples.xlsx Heating mode refrigerant undercharge

4.1. Enter the System Information

Step 1. Select the Refrigerant Type

Start the FDD CX program and go to the System Information screen. On the right side of the 

screen, select your refrigerant type. In this case select R410A. 

Step 2. Input Compressor Map Coefficients

Input the compressor mass flow rate coefficients from a file saved on your device as shown in 

Figure 14. In this case select R410A_Scroll_2.5t.xlsx under the data\compressor maps\

subdirectory. 
18

Figure 14. Compressor map coefficients input from data file

Step 3. Input Temperature Data

The system should be operated for at least 15 minutes to allow system temperatures to 

stabilize. Refrigerant temperatures should be recorded along with service port pressures. 

Saturated refrigerant temperatures can be read directly from the appropriate scale on the 

refrigerant gauge-set attached to the service ports. These temperature and pressure readings 

may be taken one time or multiple times at intervals to generate a data set for input into the 

FDD CX program. 

Select the Cooling UC 4 examples.xlsx file located in the data\examples\ subdirectory. Selecting 

this file will load the temperature values. Move to the next tab. 

4.2. Run Fault Detection and Diagnostics

Now select the Fault Detection & Diagnostics tab to get to the screen shown in Figure 15. User 

input may be performed in the areas highlighted by the rectangles.
19

Step 1. Adjust correction factors (optional)

Adjust the correction factors if you have knowledge of any offset in predicted temperature 

values caused by your particular setup. We do not adjust the offsets for this example. 

Step 2. Adjust thresholds (optional)

Feature thresholds may be increased or decreased; lowering the threshold values makes the 

FDD algorithm more sensitive, but increases the probability of a false alarm. We do not adjust 

the thresholds for this example. 

Step 3. Adjust value of EER alarm control (optional)

The Alarm Control (%) value is adjustable and the EER Warning light (or COP Warning light if in 

the heating mode) will change to a red color if the efficiency degrades by the indicated 

percentage or more. In this example case, we leave the Alarm Control (%) value at the default 

5 %. 

Step 4. Run (single data set, all data sets, all with timer)

Click one of the Run buttons highlighted in Figure 15 within the red rectangle. Run single data 

set will execute one line of data at a time by single-stepping through the input data file. 

Current results for the current line of data are displayed on the left of the screen and within the 

Fault Classifier graph. Continued clicking of the Run single data set button executes more lines 

of data, one line of data per click of the button. 

Clicking the Run all data sets button will process all of the data in the input file. The results for 

the last data line processed will be shown on the Fault Detection & Diagnostics page; the results 

for the most recently processed temperature data set are always displayed on this page. 

Clicking the Run all with timer button will process each line of temperature data in the input file 

with a pause between evaluations. This pause allows the user to more easily view results for 

each temperature data line of the file without having to continuously press the Run single data 

set button. The results for the most recently evaluated data set line of the data file are 

displayed on this screen. 
20

Figure 15. Fault Detection & Diagnostics screen before running data

The green rectangle in Figure 15 highlights the # of Data Sets and # of Current Data Set. The # 

of Data Sets indicates the total number of lines of temperature data contained in the input file. 

The # of Current Data Set indicates which line of temperature data are currently being 

processed from the input data file. 

Figure 16 shows the results after the Run all data sets button is clicked with the Cooling UC 4 

examples.xlsx file. All of the data sets have been processed, and an undercharge fault is 

indicated by the Fault Classifier graph on the right of the screen. The EER percent change 

shows slightly more than -10 % which tripped the EER Warning button to turn red. The 

refrigerant subcooling is a critical parameter for proper refrigerant charge, and it is lower than 

the predicted value with a residual of -6.8 °F (low subcooling). The low value of EER coupled 

with the UC fault indication and low subcooling shows that more refrigerant charge should be 

slowly added to the system. Add refrigerant to the system and wait 15 minutes before 

checking system temperatures again. Re-enter the temperature data on the System 

Information screen using File or Manual input. Make sure you click the Load Data button to 

process the input data each time. 
21

Figure 16. Undercharge fault data file output using Run all data sets button

Figure 17 shows the results of adding charge to the system for a second time and taking 

temperature data as shown in the file, Cooling UC Add1 examples.xlsx. The addition of 

refrigerant produced a temperature residual pattern that indicates a no-fault status for the 

given threshold limits. Refrigerant subcooling is lower than predicted by the no-fault 

correlation. Even though no-fault is indicated, the -3.1 °F Tsc residual indicates that subcooling 

is still slightly low. A third addition of refrigerant could be performed to increase refrigerant 

subcooling and produce a near zero Tsc residual. 
22

Figure 17. Fault Detection & Diagnostics screen after refrigerant is added

Figure 18 shows the results after adding refrigerant to the system for a third time and taking 

temperature data as shown in the file, Cooling UC Add2 examples.xlsx. No-Fault is still 

indicated at a higher probability. Refrigerant subcooling increased to almost the no-fault value, 

thus the probability of a no-fault system increased greatly. No other faults are indicated thus 

the system is properly charged and no more adjustments to charge should be made. 

4.3. Examine FDD Result Graphs

Click on the FDD Result Graphs tab and review the results shown in Figure 19. The left graph 

shows that the no-fault average probability is greater than 68 %. The center bar chart shows 

that the temperature residuals are less than 1.5 °F and are much less than their respective 

threshold values. Since the system is fault free, the EER Change is zero as shown in the bar 

chart on the right. 
23

Figure 18. Fault Detection & Diagnostics screen after third addition of refrigerant

Figure 19. FDD Result Graphs after third addition of refrigerant charge
24

5. The Fault Detection and Diagnosis Method 

The methods used by the FDD CX program are based upon steady-state values of important 

system temperatures. These system temperatures change in response to changes in the 

system’s operational environment and refrigerant charge. By examining the pattern of change 

that occurs in these temperatures due to an imposed fault, the software tool detects the fault 

and diagnoses the most likely cause. The experimental basis of the generic no-fault model was 

developed and explained in (Payne, Domanski, & Hermes, 2006), (Kim, Payne, & Domanski, 

2008) and (Kim M. , Yoon, Payne, & Domanski, 2010). The basis for this technique is the rule 

based chart statistical analysis developed by Rossi and Braun (1997). 

Rossi and Braun (1997) developed a statistical FDD method for a roof-top air conditioner. The 

FDD system operated with seven representative temperature measurements. The residual 

values were used as performance indices for both fault detection and diagnosis. The residuals 

of seven FDD features were assumed to obey a Gaussian distribution. Statistical properties of 

the residuals for current and normal operation were used to classify the current operation as 

faulty or normal. 

The rule based chart method used by the FDD CX software is limited to residential systems 

equipped with a thermostatic expansion valve (TXV), similar to that described in Payne, 

Domanski, & Hermes (2006). Rooftop systems or systems utilizing short tube/capillary tube 

expansion devices will not follow the generic no-fault system model; thus, the FDD CX tool 

cannot be used to commission these systems or check for faults. For systems that have 

characteristics tracked by the generic no-fault model, the FDD CX software will predict the 

general trends of the system temperatures and allow the user to adjust temperatures predicted 

by the no-fault model to match those of the system that he knows is fault free. 

Once the important system temperatures (FDD features) are steady, the differences in the 

mean values and the generic no-fault reference model values (the feature residuals) are 

calculated for each temperature (feature). A temperature difference (feature residual) may 

have one of three values; the temperature difference or temperature residual may be positive

(up-arrow ), negative (down-arrow ), or neutral (no change, NC (−)). The neutral or no-fault 

temperature residual is defined by a positive and negative threshold (±ε) about the measured

temperature value. The neutral case defines a fault free system by allowing the measured 

temperature and the predicted temperature to be different without necessarily indicating a 

faulty system. No two systems are installed exactly the same, no temperatures are measured 

at exactly the same location, and no person can repeat temperature measurements exactly the 

same way each time; thus, the neutral case, with its ±ε threshold, allows a generic temperature 

prediction correlation to function for a wide variety of similar systems. The positive, neutral, 

and negative values of temperature residuals have an associated probability of occurrence, P(C 

| X), as shown in Figure 20. The sum of all of the probabilities equals 1 or 100 %. 
25

Figure 20. Threshold for a predicted temperature (Kim et al. 2008)

The selection of the neutral threshold value, ε, involves setting a confidence level (for example 

99 %) to avoid a false alarms. With ε defined, the probability for each of the three temperature 

residual cases (positive, negative, or neutral) may be calculated from the three areas under the 

Gaussian distribution as shown in Figure 20. 

Examples of a rule based charts (RBC) are shown in Tables 4 and 5 for the cooling and heating 

modes, respectively. Each fault, listed by rows in the table, is characterized by positive, 

negative, or neutral temperature differences (cells in the corresponding fault row) for the 

important features (columns of the table). Each cell can be positive, negative or neutral and 

has an associated probability (0< P(C | X)<1). The probability of no-fault must also be included 

and determined in the same way as other faults. Obviously, a no-fault case occurs when the 

temperature differences are all neutral. The probability of a given fault is the product of all 

probabilities in a given row. When the probability of a given fault is higher than the no-fault 

probability, the system most likely has this fault occurring. 

Table 4. Example cooling rule based chart

Fault Type Te Tsh Tc Td Tsc dTea dTca

Cooling, refrigerant undercharge       

Cooling, refrigerant overcharge – –    – –

Cooling, reduced indoor coil air flow  –  – –  

No-fault – – – – – – –

( | ) PC X ↑ i PC X ( − | i) ( | ) PC X ↓ i

μ ε i i − μi μ ε i i + xi

PDF , (μ σi i)

( ) 2

,NF ,NF , N μ σ i i

μi,NF

Moving Window Mean Value

No-Fault Reference Model Prediction
26

Table 5. Example heating rule based chart

Fault Type Tc Td Tsc TshE TshC dTca

Heating, refrigerant undercharge     – 

Heating, refrigerant overcharge    –  –

Heating, reduced indoor coil air flow    –  

No-fault – – – – – –
27

References 

AHRI. (2004). Standard for performance rating of positive displacement refrigerant compressors 

and compressor units. Arlington, VA: Air-Conditioning, Heating, and Refrigeration 

Institute.

Braun, J. (1999). Automated fault detection and diagnostics for vapor compression cooling 

equipment. International Journal of Heating, Ventilating, Air-Conditioning and 

Refrigerating Research, 5(2), 85-86.

Chen, B., & Braun, J. E. (2001). Simple rule-based methods for fault detection and diagnostics 

applied to packaged air conditioners. ASHRAE Transactions, 107(1), 847-857.

Kim, M., Payne, W., & Domanski, P. (2008). Cooling Mode Fault Detection and Diagnosis 

Method for a Residential Heat Pump. Gaithersburg, MD: NIST Special Publication 1087, 

National Inst. of Standards and Technology.

Kim, M., Yoon, S. H., Payne, W. V., & Domanski, P. A. (2008). Cooling mode fault detection and 

diagnosis method for a residential heat pump. Gaithersburg, MD: Special Publication 

1087, National Inst. of Standards and Techn.

Kim, M., Yoon, S. H., Payne, W. V., & Domanski, P. A. (2010). Development of the reference 

model for a residential heat pump system for cooling mode fault detection and 

diagnosis. Journal of Mechanical Science and Technology, 24(7), 1481-89.

Payne, W., Domanski, P. A., & Hermes, C. (2006). Performance of a residential heat pump 

operating in the cooling mode with single faults imposed. NISTIR 7350, National Institute 

of Standards and Technology. Gaitherburg, MD: U.S. Dept. of Commerce.

Payne, W., Domanski, P. A., & Yoon, S. H. (2009). Heating mode performance measurements for 

a residential heat pump with single-faults imposed. Gaithersburg, MD: Technical Note 

1648, National Inst. of Standards and Techn.

Rossi, T., & Braun, J. E. (1997). A statistical rule-based fault detection and diagnostic method for 

vapor compression air conditioners. HVAC&R Research, 3(1), 19-37.

Yoon, S. H., Payne, W. V., & Domanski, P. A. (2011). Residential heat pump heating performance 

with single faults imposed. Applied Thermal Engineering, 31, 765-771.
28

Acknowledgements

The authors would like to acknowledge Min Sung Kim, Seok Ho Yoon, and Jin Min Cho for their 

work in developing the background material used in this user’s manual. Also, John Wamsley, 

Glen Glaeser, and Art Ellison provided technician support for the data used to develop the 

generic, no-fault reference temperature correlations.