Irebert R. Delgado, Paula J. Dempsey, and Donald L. Simon

Glenn Research Center, Cleveland, Ohio

A Survey of Current Rotorcraft Propulsion

Health Monitoring Technologies

NASA/TM—2012-217420

January 2012
NASA STI Program . . . in Profi le

Since its founding, NASA has been dedicated to the 

advancement of aeronautics and space science. The 

NASA Scientifi c and Technical Information (STI) 

program plays a key part in helping NASA maintain 

this important role.

The NASA STI Program operates under the auspices 

of the Agency Chief Information Offi cer. It collects, 

organizes, provides for archiving, and disseminates 

NASA’s STI. The NASA STI program provides access 

to the NASA Aeronautics and Space Database and 

its public interface, the NASA Technical Reports 

Server, thus providing one of the largest collections 

of aeronautical and space science STI in the world. 

Results are published in both non-NASA channels 

and by NASA in the NASA STI Report Series, which 

includes the following report types:

• TECHNICAL PUBLICATION. Reports of 

completed research or a major signifi cant phase 

of research that present the results of NASA 

programs and include extensive data or theoretical 

analysis. Includes compilations of signifi cant 

scientifi c and technical data and information 

deemed to be of continuing reference value. 

NASA counterpart of peer-reviewed formal 

professional papers but has less stringent 

limitations on manuscript length and extent of 

graphic presentations.

• TECHNICAL MEMORANDUM. Scientifi c 

and technical fi ndings that are preliminary or 

of specialized interest, e.g., quick release 

reports, working papers, and bibliographies that 

contain minimal annotation. Does not contain 

extensive analysis.

• CONTRACTOR REPORT. Scientifi c and 

technical fi ndings by NASA-sponsored 

contractors and grantees.

• CONFERENCE PUBLICATION. Collected 

papers from scientifi c and technical 

conferences, symposia, seminars, or other 

meetings sponsored or cosponsored by NASA.

• SPECIAL PUBLICATION. Scientifi c, 

technical, or historical information from 

NASA programs, projects, and missions, often 

concerned with subjects having substantial 

public interest.

• TECHNICAL TRANSLATION. Englishlanguage translations of foreign scientifi c and 

technical material pertinent to NASA’s mission.

Specialized services also include creating custom 

thesauri, building customized databases, organizing 

and publishing research results.

For more information about the NASA STI 

program, see the following:

• Access the NASA STI program home page at 

http://www.sti.nasa.gov

• E-mail your question via the Internet to help@

sti.nasa.gov

• Fax your question to the NASA STI Help Desk 

at 443–757–5803

• Telephone the NASA STI Help Desk at

 443–757–5802

• Write to:

 NASA Center for AeroSpace Information (CASI)

 7115 Standard Drive

 Hanover, MD 21076–1320
Irebert R. Delgado, Paula J. Dempsey, and Donald L. Simon

Glenn Research Center, Cleveland, Ohio

A Survey of Current Rotorcraft Propulsion

Health Monitoring Technologies

NASA/TM—2012-217420

January 2012

National Aeronautics and

Space Administration

Glenn Research Center

Cleveland, Ohio 44135
Acknowledgments

Thanks to Michael Augustin, Bell Helicopter; Treven Baker, U.S. Army; Keith Calhoun, Rolls-Royce; Gail Cruce, U.S. Army; 

Dave Lewicki, NASA Glenn; Tim Rickmeyer, U.S. Army; Traci Stadtmueller, FAA; and Christopher Wallace, U.S. Army.

Available from

NASA Center for Aerospace Information

7115 Standard Drive

Hanover, MD 21076–1320

National Technical Information Service

5301 Shawnee Road

Alexandria, VA 22312

Available electronically at http://www.sti.nasa.gov

Trade names and trademarks are used in this report for identifi cation 

only. Their usage does not constitute an offi cial endorsement, 

either expressed or implied, by the National Aeronautics and 

Space Administration.

This work was sponsored by the Fundamental Aeronautics Program 

at the NASA Glenn Research Center.

Level of Review: This material has been technically reviewed by technical management. 

This report is a formal draft or working 

paper, intended to solicit comments and 

ideas from a technical peer group.

This report contains preliminary fi ndings, 

subject to revision as analysis proceeds.
NASA/TM—2012-217420 1 

A Survey of Current Rotorcraft Propulsion 

Health Monitoring Technologies 

Irebert R. Delgado, Paula J. Dempsey, and Donald L. Simon 

National Aeronautics and Space Administration 

Glenn Research Center 

Cleveland, Ohio 44135 

Abstract 

A brief review is presented on the state-of-the-art in rotorcraft engine health monitoring technologies 

including summaries on current practices in the area of sensors, data acquisition, monitoring and analysis. 

Also, presented are guidelines for verification and validation of Health Usage Monitoring System 

(HUMS) and specifically for maintenance credits to extend part life. Finally, a number of new efforts in 

HUMS are summarized as well as lessons learned and future challenges. In particular, gaps are identified 

to supporting maintenance credits to extend rotorcraft engine part life. A number of data sources were 

consulted and include results from a survey from the HUMS community, Society of Automotive 

Engineers (SAE) documents, American Helicopter Society (AHS) papers, as well as references from 

Defence Science & Technology Organization (DSTO), Civil Aviation Authority (CAA), and Federal 

Aviation Administration (FAA). 

Nomenclature 

AE Acoustic Emissions 

AI Artificial Intelligence 

AHS American Helicopter Society 

CAA Civil Aviation Authority 

CAP Civil Aviation Publication 

CBM Condition-Based Maintenance 

CI Condition Indicator 

DSTO Defence Science & Technology Organization 

FAA Federal Aviation Administration 

FADEC Full-Authority Digital Electronic Control 

HUMS Health Usage Monitoring System 

ICA Instructions for Continued Airworthiness 

IMDS Integrated Mechanical Diagnostic System 

IVHMS Integrated Vehicle Health Management System 

JTFA Joint Time Frequency Analysis 

LTFC Life-to-First-Crack 

LUI Life Usage Index 

MFOQA Military Flight Operations Quality Assurance 

nRTDA near Real-Time Damage Assessment 

NASA National Aeronautics and Space Administration 

NATO North Atlantic Treaty Organization 

OSST Operations Support & Sustainment Technologies Program (U.S. Army) 
NASA/TM—2012-217420 2 

PDBM Prognostics Diagnostics Based Management 

RFC Retirement-for-Cause 

RUL Remaining Useful Life 

SAE Society of Automotive Engineers 

TBO Time-Between-Overhaul 

TDA Tear-Down Analysis 

VHM Vibration Health Monitoring 

Introduction 

The benefits realized or to be realized from rotorcraft propulsion health management have been well 

documented over the past several decades. This includes maximizing the utilization of the aircraft and/or 

fleet through improved maintenance planning and practices and the optimal use of spare parts. Also, 

aircraft safety is improved through health monitoring of flight critical components such as life-limited 

engine parts as well as gearbox and drive train components for helicopters (Ref. 1). Approaches to health 

usage monitoring of rotorcraft propulsion systems have evolved from monitoring of engine cycles to 

predicting individual part failures. Figure 1 details this progression in fidelity in engine health monitoring 

from the 1970s through the 2000+ time frame (Ref. 2). Figure 2 provides another perspective on the 

health monitoring of components from simple corrective maintenance (e.g., breakdown maintenance) and 

preventative or scheduled maintenance to predictive (e.g., condition-based) and proactive maintenance 

(e.g., prognostics) (Ref. 3). Regardless of the health monitoring approach to rotorcraft engines, improved 

airworthiness or safety, increased readiness or availability, reduced maintenance tasks, and reduced cost 

are the major objectives that govern the choice of a specific HUMS methodology (Refs. 1, 4, 5, and 6). 

Engine size and use also influence the implementation of HUMS. Rotorcraft’s smaller turboshaft engines, 

Figures 3 and 4, as compared to fixed-wing turboshaft engines translates to smaller components (e.g., air 

foils) with corresponding lower core air flows (10s of lb/sec compared to 100s of lb/sec). However, 

clearances are proportionally larger thus reducing efficiency and range or payload (Ref. 7). Moreover, 

rotorcraft are used in more hazardous, harsh, and taxing environments such as the current military 

operations in the Middle East (Ref. 8). Resultant rapid engine degradation forces operators to push 

rotorcraft engine limits to obtain the same performance level thus subjecting the engine to higher thermal 

stresses (Ref. 9). Other special considerations for rotorcraft engines include the following (Ref. 4): 

 Torque-matching of engine power outputs to protect helicopter gearboxes; 

 Multiple engine control system adjustment to ensure that one engine does not use excessive life, 

compared to the others; 

 The “automatic” engine throttle movements resulting from Power Turbine Governor system 

operation, to keep the helicopter rotor speed constant despite collective and cyclic pitch inputs from 

the pilot. 

Thus, tools are required that are specific to health and usage monitoring systems of rotorcraft engines. 

This paper’s objectives are the following: 

1. Provide the current state-of-the-art in sensors, algorithms, diagnostics, and prognostic tools installed 

in rotorcraft engines. 

2. Identify gaps to support validation and demonstration of HUMS for rotorcraft engine component 

maintenance credits. 

 
NASA/TM—2012-217420 3 

In support of these objectives, a survey (Appendix A) was sent to a small cross-section of the HUMS 

community to determine the current state-of-the-art in sensors, diagnostics/prognostic tools, and HUMS 

methodology, validation and effectiveness. The group included engine manufacturers, helicopter 

manufacturers, HUMS manufacturers, and HUMS users including the U.S. Army and the U.S. Navy. 

Results of that survey are presented in the appropriate section and are marked as Personal Interview in the 

endnotes. Also included are findings from the Army’s Operations Support & Sustainment Technologies 

(OSST) Program (Refs. 10 to 13). Finally, a literature search was conducted with references from SAE, 

DSTO, NATO, NASA, FAA, Army, and AHS proceedings. The FAA provides general guidelines on 

maintenance credits to extend TBOs for helicopter propulsion systems using HUMS. The SAE documents 

provide more general guidelines and recommended practices on HUMS. In addition, a number of studies 

on the state-of-the-art in HUMS were conducted by DSTO, NATO, and NASA and are referenced 

appropriately below. This paper will cover current standard practices (i.e., philosophies, sensors, data 

acquisition and data transfer, helicopter engine monitoring and analysis, HUMS guidelines, HUMS 

verification and validation), new practices, lessons learned, and future challenges. 

While an effort was made to include references from as wide a range of sources as possible, the 

included bibliography is not exhaustive and therefore the paper should be treated as a work in progress as 

this is a dynamic environment with more rotorcraft being equipped with HUMS every year. The data is 

considered to be current per the publication date of this document. Also, a significant number of 

references are taken from SAE, AHS, DoD, and FAA sources and as such the findings may be geared 

more towards U.S. health usage monitoring systems. Finally, this paper is limited in scope to the 

following dynamic mechanical components for rotorcraft engines. This would include blades/vanes, 

disks, spacers, shafts, bearings, combustors, gears, and rotating seals (Ref. 4). Engine health monitoring 

via gas path analysis or other conventional engine performance parameters is not treated in this paper. For 

additional information in this area, the reader is pointed towards a number of references (e.g., 

NASA/TM—2004-213202, NASA/TM—2005-213622) as a starting point. 

Standard Practices 

Philosophies 

As shown in Figure 2, health monitoring methodologies are evolving from preventative type 

maintenance (i.e., Hard-time, Time-Between-Overhaul (TBO), Retirement-for-Cause (RFC), Damage 

Tolerance) to achieving more Predictive and Prognostic type methods (e.g., on-condition). Preventativetype maintenance or scheduled maintenance is usually based on part history or via elapsed time in use. 

Both predictive and proactive maintenance strategies attempt to extend component time on wing. While 

predictive maintenance seeks to replace components based on part condition through observation or 

through analysis of sensor readings, proactive maintenance seeks to replace parts based on predictive 

analyses. These analyses, in turn, may be based in part on sensor data. Part of the U.S. Army’s ConditionBased Maintenance (CBM) program attempts to extend time on wing through improved life prediction 

methodologies, multi-sensor data fusion, and intelligent reasoning and control (Ref. 3). The U.S. Army’s 

ultimate goal is to have component replacement “on-condition”. Regardless of the health monitoring 

methodology, these maintenance strategies fit within an engine health monitoring framework. SAE ARP 

1587B provides an excellent example via a block diagram of a typical EHM architecture where the 

HUMS information flow path (e.g., sense-acquire-transfer-analyze-act) can be deduced (Ref. 1). 

Sensors 

Existing sensors on helicopter engines provide operational assessments on engine performance (e.g., 

exceedance monitoring, RUL, gas path diagnostics, and maximum power assessments). The gas turbine 

engine’s control system, or Full-Authority Digital Electronic Control (FADEC), contains codes which on 

modern platforms can provide independent checks on the health of the helicopter engines and their 
NASA/TM—2012-217420 4 

subsystems (Ref. 14). A subset of these sensors are used for fault detection including accelerometers 

(vibration monitoring), oil debris monitors (component degradation), and thermocouples (exceedance 

monitoring). Guidelines of actual sensor specifications such as accuracy, resolution, sampling rate, etc. 

are platform/mission specific (Refs. 4, 15, 16, and 17). For example, U.S. Army document ADS-79BHDBK provides typical sensor accuracy and resolution requirements, Table 1 (Ref. 2). Table 2 provides 

additional references on typical specifications for accelerometers, rotational sensors, temperature sensors, 

and oil monitoring devices. Finally, depending upon the type of monitoring function (e.g., 

Limit/Exceedance, Life Usage, mechanical trending, mechanical diagnosis) a number of engine 

measurement parameters may be useful. SAE AIR 4061B provides a matrix of typical engine parameter 

data used with respect to their monitoring function. Parameters include temperature, pressure, thrust, 

vibration, and oil particle count (Ref. 18). 

Data Acquisition and Data Transfer 

The process of acquiring data from the various engine sensors and transferring it to a ground station 

for analysis is accomplished through a variety of methods. The process involves the capture, extraction, 

processing, and analysis of HUMS data through manual methods (e.g., hand-carried, ground-station, 

equipment, physical media), automated methods (e.g., satellite, radio, wireless), or combinations of both. 

The degree of automation is partially driven by the processing and analytical capabilities of the specific 

engine HUMS (Ref. 1). Typically, more detailed or computer intensive analyses are carried out off-board 

due to limited on-board memory and processor capacity (Ref. 19). Data bus standards such as ARINC 

429, ARINC 717, and Mil-Std-1553 are noted here as standard communication protocols for commercial 

and military helicopters, respectively. SAE AS 5395 provides guidelines for HUMS data format 

interchange within an open system architecture. Example HUMS include Honeywell’s 1239 (Ref. 20) 

system and Goodrich’s IVHMS system (Ref. 21). Current challenges include ensuring data accuracy, 

integrity, and reliability through the data acquisition and transfer process (Refs. 16 and 22). Decreasing 

the time from data acquisition to on-board or ground station analysis would increase the effectiveness of 

the HUMS in alerting operators of any engine maintenance issues. Thus, areas for improvement would be 

in increasing the reliability of on-board analyses and increasing on-board data storage and throughput 

while preserving data integrity and quality (Ref. 1). 

Helicopter Engine Monitoring and Analysis 

The objective of helicopter engine health monitoring is to reliably determine the condition of the 

engine and its components and to give an indication of any maintenance required. Traditional 

methodologies such as cycle counting, vibration monitoring, and oil debris monitoring are currently used 

but sometimes require a prohibitive amount of on-board computer resources (e.g., memory, storage, 

processor speed). Thus, one challenge is to balance on-board health and usage monitoring techniques such 

as trending, cycle counts, and condition indicators with available on-board computer resources. Another 

challenge is to reduce the time period from acquisition of the health monitored data and its subsequent 

analysis to resultant maintenance actions, if any, for the helicopter engine. 

The goal of vibration analysis with respect to helicopter engine monitoring is to accurately assess the 

operational condition of rotating parts (e.g., seals, bearings, gears, blades, etc.) and to give sufficient 

warning of impending part failure. Rotating parts exhibit natural frequencies which change as the part 

condition begins to deteriorate. These changes may be observed by the presence and relative amplitude of 

characteristic harmonics and sidebands. The detection of these frequencies of interest is complicated by a 

number of factors including the sensor location relative to the rotating component of interest as well as 

the presence of natural frequencies in the vibration signature of other nearby rotating components. Thus, 

the challenge is to separate the frequencies of interest and accurately determine if maintenance is required 

on the rotating component. Analysis techniques can be broadly grouped into either time domain analyses 

(e.g., Root Mean Square, Crest Factor) or frequency domain analyses (e.g., filtering, FFT, Cepstrum, 
NASA/TM—2012-217420 5 

order tracking) (Ref. 23). Also, because of the large amount of data required for vibration analysis an 

additional challenge, as mentioned previously, is to determine the state of the component with limited onboard snapshot data. 

Similar to vibration analysis, oil debris monitoring seeks to quantify part wear (e.g., oil-wetted 

bearings and gears) due to the detection and identification of debris in the helicopter engine oil system. 

Chip detectors and their corresponding algorithms are used on-board to indicate oil system debris levels 

as well as threshold alarms. Example chip detectors and systems include GasTops MetalSCAN, (Ref. 24) 

Vibro-Meter’s chip detector system, (Ref. 25) or Eaton’s debris monitoring system (Ref. 26). As with 

vibration monitoring, oil debris monitoring alarm levels are worked closely between the manufacturer and 

user. Off-board analyses may include classification, troubleshooting, spectrography, spectrophotometry, 

or scanning electron microscopy (Ref. 27). Regardless of technique, reliability and accuracy of the data 

and timeliness of any maintenance action are key for successful oil debris monitoring. 

The objective of life usage monitoring of life-limited parts (e.g., blades, disks) is to safely and 

reliably predict part remaining useful life (RUL). Two traditional approaches are the safe-life approach 

and damage tolerance approach. The safe-life approach, based primarily on low-cycle fatigue criteria, 

determines part life based on when cracks begin to form on components. Alternatively, the damage 

tolerance approach, based on fracture mechanics, determines the critical crack-length to failure of the 

component. Safe-life methodologies include Rainflow (Ref. 16), and life-to-first crack or LTFC (Ref. 4). 

Damage tolerance methods include RFC and 2/3 dysfunction life (Ref. 4). Also, thermal fatigue and creep 

are considered as well for life-limited components (Ref. 16). Finally, guidelines on the logistics of 

tracking life-limited parts are outlined in SAE AIR 1872 Rev. A (Ref. 16). 

On-board condition indicators (CI) commonly found in HUMS boxes as mentioned in the Sensors 

section, provide alert levels (e.g., hi/lo temperature, vibration, pressure, etc.) and are recorded and 

analyzed using a number of techniques as previously described. The U.S. Army’s ADS-79B-HDBK 

document provides methods on developing and validating CIs (Ref. 2). Again, CI thresholds and alert 

levels are platform specific, and thus are developed closely between the HUMS supplier and user 

(Ref. 28). 

HUMS Guidelines 

A number of organizations have provided guidelines for HUMS relating to overall philosophy, sensor 

specifications, installation, and lessons learned. The Society of Automotive Engineers (SAE) provides a 

number of these documents. A listing is shown in Appendix B. In 1999, the U.K.’s Civil Aviation 

Authority (CAA) published Civil Aviation Publication (CAP) 693 (Ref. 29) that provides operators with 

guidelines for installation and use of health monitoring systems. The CAP described the level of 

monitoring required and provided advice on ensuring that the monitoring was effective and reliable. In 

2006, the CAA published the document CAP 753, (Ref. 30) which provides additional guidance to 

operators using vibration health monitoring (VHM) in helicopter rotor and drive systems. In this 

document they define VHM as, “the monitoring of vibration data and characteristics that can provide 

advance information relating to the development of incipient failures in the engine(s) rotor drive systems 

(Ref. 30)”. 

Also, in 1999 the FAA published Advisory Circular (AC) 29-2C MG 15, Airworthiness Approval of 

Rotorcraft Health Usage Monitoring Systems (HUMS), which provides guidance to achieve airworthiness 

approval for HUMS installation, credit validation, and Instructions for Continued Airworthiness (ICA) for 

the full range of HUMS applications (Ref. 31). An economic benefit in following AC 29-2C MG 15 is 

that it allows the operator to inspect and remove components based on HUMS indications instead of 

scheduled maintenance intervals for specific components. To receive maintenance credits so as to 

increase the service life of a specific component, the HUMS application for which credits are sought must 

be validated. Evidence must be provided in the form of seeded fault tests and/or fielded data that 

demonstrate the HUMS responds to the specific component fault with appropriate alert limits. Seeded 
NASA/TM—2012-217420 6 

fault testing refers to the process of initiating a defect in a component and monitoring the progression of 

the defect with health monitoring equipment. 

The U.S. Army is also in the process of providing guidelines (ADS-79B) on obtaining maintenance 

credits for its fleet of helicopters. 

Verification and Validation of HUMS 

Verification and validation of HUMS is critical in providing the necessary evidence that justifies the 

use of these systems in making decisions for safety critical maintenance items on not only helicopter 

engine components but the drive, structural, and rotor systems as well. The FAA and U.S. Army define 

Verification and Validation as follows: 

FAA Definition per FAA VVSPAT-A2-PDD-014 (Ref. 32) 

“Verification.—Confirmation that selected work products meets their specified requirements. This 

includes verification of the end product (system, service or operational change) and intermediate 

work products against all applicable requirements. Verification is inherently an incremental process 

since it occurs throughout the development of the end product and work products, beginning with 

initial requirements, progressing through subsequent changes, and culminating in verification of the 

completed end product. 

Validation.—Confirmation that an end product or end product component will fulfill its intended 

purpose when placed in its intended environment. The methods employed to accomplish validation 

are applied to selected work products as well as to the end product and end product components. The 

work products should be selected on the basis of which are the best predictors of how well the end 

product and end product component will satisfy the intended purpose and user needs. Validation may 

address all aspects of an end product in any of its intended environments, such as operation, training, 

manufacturing, maintenance, or support services.” 

U.S. Army Definition per ADS-79X-HDBK-Appendix VV Rev 090110 (Ref. 33) 

“Verification.—Confirms that a system element meets design-to or build-to specifications. 

Throughout the systems life cycle, design solutions at all levels of the physical architecture are 

verified through a cost-effective combination of analysis, examination, demonstration, and testing, all 

of which can be aided by modeling and simulation. 

Validation.—The process of evaluating a system or software component during, or at the end of, the 

development process to determine whether it satisfies specified requirements.” 

Thus verification and validation are complimentary activities that require confirmation that the 

HUMS functions as specified at key points (i.e., component versus system level) during the development 

and test phase of the system. End-to-end testing, verification that the system operates in “all foreseeable 

circumstances”, verification and validation of both software, hardware, and data transfer, an 

understanding of known deficiencies, and use of an appropriate approval authority are also key to these 

two activities (Ref. 4). SAE AIR 5120 provides specific guidance on a tiered verification process 

involving simulation and Rig/Bench testing through Static Aircraft, Engine, and Flight Testing (Ref. 22). 

Finally, SAE AIR 1872 details validation of life usage algorithms at both the algorithm level and system 

level. The importance of a large database for correlation is discussed as well as acceptable deviations 

between computer simulation and system level checks (Ref. 16). The U.S. Army’s CBM program is 

currently validating HUMS through case studies and seeded fault testing (Ref. 28), as well as validation 

of vibration algorithms performance via tear-down analyses (TDAs) of faulted components (Ref. 34). The 

U.S. Army’s V&V process, particularly for maintenance credit, is further detailed by Menon and others 

(Ref. 35). Prior to an end-to-end verification process the document stresses the importance of having a 

HUMS that is controlled with known configurations for all HUMS elements. Validation metrics are 

suggested as well as methods to address data uncertainties, variability, and sample sizes. Examples are 
NASA/TM—2012-217420 7 

given including bearing health monitoring. Also, methodologies to quantify vibration algorithm 

performance are presented in SAE ARP 5783 (Ref. 36). Finally, a method for quantifying engine 

monitoring system performance is given is SAE AIR 4985 (Ref. 37). 

New Practices for Engine Health Monitoring Systems 

In considering new maintenance practices pertaining to HUMS for helicopter engines it is useful to 

consider the following guidelines from Rickmeyer and Dempsey (Ref. 38): 

1. “...any maintenance enhancement, modification, or replacement should be verified and validated as 

good as, or better than, legacy maintenance practices.” 

2. “...any maintenance system proposed to replace legacy inspections and overhaul intervals should 

undergo similar scrutiny to demonstrate sufficient engineering rigor and robust design.” 

3. “The ultimate goal of rotorcraft health management systems for dynamic propulsion components is to 

achieve true “on condition” based maintenance and operational quality while increasing the safety of 

rotorcraft.” 

In addition, cost of implementation would be another factor in considering changes to existing 

maintenance practices for rotorcraft engines. In recent years, a number of promising developments in 

engine health monitoring have begun to address current maintenance practices in an effort to achieve true 

“on condition” based maintenance. A number of these efforts are highlighted below. 

1. Results from the Army’s OSST program show promise in fusing vibration and oil-debris monitoring 

bearing data to provide earlier indications of impending bearing failure as compared to traditional 

condition indicators. Honeywell’s CBM program has demonstrated in seeded bearing tests in both rig 

and engine testing the validity of a two-stage fusion approach. Further, a damage milestone (DM) 

progression methodology is introduced based on bearing geometry and appears to provide a more 

“robust” indication of bearing failure (Ref. 10). Other OSST technologies developed and/or 

demonstrated included erosion detection, continuous power assurance, model-based torque 

prediction, RUL, and power management. The RUL module uses a neural network approach to 

predict disk temperatures and stresses which are then fed into life prediction algorithms in order to 

calculate the remaining useful life (Refs. 11 to 13). 

2. In an effort to reduce operating costs, increase operational availability, and reduce maintenance 

burden, a Regime Recognition system has undergone a initial successful flight test on-board an 

EC135. Determination of the actual mission profile and thus the true load spectrum would enhance 

dynamic component life monitoring (Ref. 39). 

3. The US Navy has begun implementation of automated rotorcraft engine power checks on-board the 

CH/MH-53E which has the GE-64 turboshaft engine. Also part of the Prognostics Diagnostics Based 

Management (PDBM) program, the Navy has also begun demonstration of an engine torque 

performance algorithm as a life assessment module incorporating Life Usage Indices (LUIs) and near 

Real Time Damage Assessments (nRTDAs). Demonstration of these modules was scheduled to begin 

in early 2011 (Ref. 40). 

4. A small business has developed a bearing corrosion detection methodology based on joint timefrequency analysis (JTFA) that shows, from initial seeded fault rig testing and analysis, the potential 

ease and accuracy of quantifying corrosion level severity (Ref. 41). 

5. SAE AIR 1828 RevB notes in the area of oil debris monitoring the trend towards “finer filtration” 

(e.g., 3 to 10 m) and a corresponding increase in sensitivity to spectrometric techniques (e.g., plasma 

spectrometers) (Ref. 27). 

6. The Department of the Navy has begun instituting a knowledge management process known as 

Military Flight Operations Quality Assurance (MFOQA) for its Integrated Mechanical Diagnostic 

Systems (IMDS). The goal of MFOQA is “to provide objective and actionable information that can 
NASA/TM—2012-217420 8 

be used to reduce flight related risks and improve aircrew training, maintenance, and operational 

efficiencies.” The paper referenced here reveals trends and patterns on rotorcraft usage across a fleet 

of helicopters based on IMDS events (e.g., exceedance, flight hours, autorotation) (Ref. 42). 

Lessons Learned 

Given health usage monitoring of rotorcraft engines’ familiar objectives of improved readiness, 

increased airworthiness, reduced maintenance, and reduced costs, a common HUMS philosophy is the 

trend towards true on-condition monitoring—a HUMS research area identified previously by Fraser in 

1994 having potential for substantial cost benefits (Ref. 6). Considering the various R&D efforts working 

towards this goal, a number of lessons learned have been documented in the literature—a number of 

which focus on the areas of data integrity, information management, and communication. Following is a 

brief summary of these three areas. 

Maintaining data integrity (e.g., accuracy, resolution, robustness) through the HUMS data flow 

process (e.g., sense-acquire-transfer-analyze-act) is a continuous challenge through the research, 

development, and validation of HUMS and their subsystems. High false alarm rates have been reported in 

the literature (Refs. 19 and 43). Causes for these alarms stem potentially from faulty sensors or CIs, 

limited field data to validate the CI, or an incomplete understanding of damage progression levels (e.g., 

bearing damage progression) (Ref. 38). With limited on-board data storage capacity it is suggested that 

hybrid models (physics-based and empirical models) may offer a solution that addresses concerns for 

accuracy, ease of development, and maintenance (Ref. 19). 

With increasing quantities of data for analysis from HUMS (vibration, oil debris, etc.), strategies to 

manage the information flow path are vital for success (Ref. 19). This area of needed research was also 

identified by Fraser in 1994 and includes elements that are being instituted or worked on today (Ref. 6): 

 Automatic scheduling of the application of health and usage algorithms. 

 Combining the results of different forms of analysis (e.g., vibration and oil debris analysis). 

 Coordinating and presenting maintenance advice. 

 Screening and taking account of bad data, and flagging monitoring system faults. 

 Parts life tracking and interfacing with logistics management schemes. 

 Automatic processing of other data. 

 Archiving of selected data. 

 Coordinating and maintaining fleet status records. 

Modularity, efficiency, and timeliness in the information management process would also support 

increased rotorcraft airworthiness and availability. Alternatively, a “sluggish” process could potentially 

lead to maintenance “shortcuts” or “neglect” (Ref. 19). Also, differences in rotorcraft usage (e.g., desert, 

city, training) require a finer knowledge management process as given by example in the previous section 

by the Department of the Navy’s MFOQA program. 

Finally, the need for continuous and clear communication is essential for both users and suppliers of 

HUMS, engines, and airframe manufacturers throughout the design, development, and implementation of 

the HUMS (Refs. 4 and 15). From developing specifications and tailoring existing systems or developing 

new subsystems to fit within user parameters to finally validating the system as a whole requires constant 

lines of communication, preferably early in the process (Ref. 19). SAE AIR 1871C provides a number of 

lessons learned on HUMS for both propulsion as well as drive train systems. 
NASA/TM—2012-217420 9 

Future Challenges 

Improvements for HUMS for rotorcraft engines are identified and grouped in terms of management, 

sensors, and analysis. Management of HUMS programs and information will be necessary in working 

towards true on-condition monitoring. Effecting worthwhile change in current engine monitoring methods 

will require insight and understanding of the level of robustness and engineering rigor required to 

maintain safety and airworthiness standards (Ref. 38). For users (individual and small market) without the 

resources to pull data off the aircraft and transfer it for analysis, the ability to download data without 

intervention would make it possible to monitor engines post-flight and track operation (Ref. 44). In terms 

of extending TBOs for rotorcraft engines, Rickmeyer and Dempsey, suggest a number of methods 

(Ref. 38): 

 TBO extension based on field experience but limited to current calculated part lives. 

 Instituting a reliability-based approach to validating a HUMS with statistical rigor. 

 Redesign and requalify legacy TBO components to extend TBO. 

Simon and others point out a number of needed engine sensor improvements in vibration (50 kHz 

bandwidth), oil debris (non-magnetic debris detection in the 125 to 700 μm range), oil quality (real-time 

measurement), blade health (300 g vib, 100 to 500 kHz bandwidth), prognostics (2000 F metal 

temperature measurement), and NDE (wireless eddy-current). Also, “for production engine applications, 

these sensors need to be affordable, reliable, light-weight, and be readily installable and accessible.” The 

report also alludes to virtual sensors via “indirect measurement techniques” (Ref. 45). Also, embedded 

sensors (Ref. 28) in combination with wireless technology in engine components could potentially 

streamline the acquisition of HUMS data as well as eliminate issues involved with cabling and optimizing 

sensor location. 

There is a continuous challenge to improve the reliability and confidence levels of an algorithm, 

condition indicator, analytical method, or the HUMS as a whole especially for obtaining maintenance 

credits. Statistical methods are currently being investigated for HUMS for rotorcraft engines. Sapsard 

provides some initial statistical guidance on the number of engines (or engine components) to monitor in 

a fleet (Ref. 4). Rickmeyer and Dempsey include hypothesis testing as well as sample size determination 

for reliability, demonstration and testing of a CI to detect a component fault (Ref. 38). Also, ASTM E 

122-09 provides general guidance on calculating sample size (Ref. 46). Finally, MIL-HDBK-781A gives 

guidance on test plans, test methods, and environmental profiles for reliability testing of systems and 

equipment (Ref. 47). These sources also implicitly state a requirement of technical or expert background 

regarding the potential sources of faults in the system (e.g., rotorcraft engine) such that the statistical 

techniques are used in a judicious manner. 

Data fusion shows promising results as given by the OSST example discussed above (e.g., fusion of 

vibration and oil debris monitoring data). Acoustic emissions (AE) sensing is another potential research 

area for HUMS for rotorcraft engines. Case studies in the drive train area (e.g., gears) are currently being 

investigated by He and others. AE has been used extensively for non-destructive evaluation of materials 

for cracks and has shown an insensitivity to background noise in rotating machinery as well as sensitivity 

to faults and their locations (Ref. 48). Other areas of potential research include artificial intelligence (AI) 

monitoring techniques such as neural networks and fuzzy logic with the potential advantage of learned 

automated fault detection in rotorcraft engines. 

Other needed advancements for rotorcraft engine HUMS include diagnostic tools for isolating faulted 

hardware and trending conditions. Also, needed would be real time life usage recognition and 

performance tracking of engine health and mission planning capabilities to reduce maintenance test 

flights to determine the same (Ref. 34). 

Beyond post flight and real-time analysis, prognostic methods would be needed to advance HUMS 

for engines towards true on-condition monitoring. The inherent nature of these predictive methodologies 

would necessitate a solid statistical and technical basis to ensure accuracy. Benefits would include 
NASA/TM—2012-217420 10 

reduced reliance on manual checks and inspections as well as improved flight safety, improved 

operational availability, reduced life cycle costs, optimized maintenance/inspection intervals (Refs. 1 and 

49). Prognostic approaches may include experienced-based, evolutionary, feature progression, AI-based, 

state estimator, and physics-based (Ref. 49). 

Identified Gaps 

A number of gaps have been identified that may complicate the implementation of maintenance 

credits to extend part life for rotorcraft engines. While not an exhaustive list, the gaps identified in this 

research are centered from the viewpoint that HUMS technology have been developed for specific 

engines, platforms, missions, etc. This would include sensor and their locations on engines, the CIs 

developed and their associated alert levels, the means of acquiring the data and transferring it to ground 

station in a timely manner, and finally, acquiring a sufficient data set for accurate analysis. Certainly, the 

development of HUMS technology in terms of accuracy and robustness is of primary concern for 

accurately assessing the condition of rotorcraft engine health. However, to extend part life through the use 

of maintenance credits would require greater consistency in the use of HUMS technology, possibly at the 

fleet/mission level if not higher. Also, CI maturity in terms of accuracy and robustness will need to be 

improved to reduce false alarm rates to acceptable levels. Finally, the need for efficient management of 

HUMS data as well as continued consistent and clear communication between HUMS users/suppliers 

from Depot to management level will be necessary to successfully implement the maintenance credit 

process in both the civil and military rotorcraft engine environment. 

Conclusions 

A brief review on the state-of-the-art in HUMS technology was conducted for rotorcraft engines. 

Survey feedback from the HUMS community, a review of the literature, and a review of HUMS 

guidelines (SAE, DoD, etc.) have resulted in a number of observations. A number of collaborative efforts 

between HUMS users and suppliers appear to have shown promise in furthering HUMS technology. One 

example is fusing bearing and vibration data to determine impending part failure (e.g., OSST program). 

Another example is increasing the fidelity of determining part life by an automated regime recognition 

program (e.g., EC135). In general, the application of any HUMS technology to existing rotorcraft engines 

is highly specific to platform and mission. Close collaboration between users and suppliers is critical to 

the successful implementation of the technology, particularly in the case where Maintenance Credits are 

being sought by users from the various governing bodies (e.g., FAA, CAA). As always, airworthiness, 

readiness, and availability will remain uncompromised. Also, statistical rigor, accuracy of data, reduction 

of false alarms, and data integrity are key to further development of analytical tools, CIs, HIs, etc. 

Research efforts and developments in the area of prognostics will be increasingly important in realizing 

true on-condition monitoring. Finally, timeliness of maintenance actions will also be a factor to the 

success of any HUMS program. 

 
NASA/TM—2012-217420 11 
NASA/TM—2012-217420 12 
NASA/TM—2012-217420 13 

TABLE 1.—U.S. ARMY SENSOR ACCURACY AND 

RESOLUTION REQUIREMENTS (REF. 2) 

Signal Accuracy Resolution 

Spool speed 0.1 percent 0.05 percent 

Temperature 1.8 F 0.9 F 

Engine intake 7.2 F 3.6 F 

Compressor exit 7.2 F 3.6 F 

Stator outlet 7.2 F 3.6 F 

Exhaust gas 3.6 F 1.8 F 

Turbine blade 7.2 F 3.6 F 

Engine intake pressure 0.290 psi 0.145 psi 

Compressor exit pressure 1.45 psi 0.435 psi 

Indicated airspeed 2 kts 1 kts 

Pressure altitude 100 ft 50 ft 

G-load 0.01 g 0.005 g 

TABLE 2.—GENERAL SOURCES FOR HELICOPTER ENGINE SENSOR SPECIFICATIONS 

Sensor Source 

General SAE ARP 1217 RevA 

Accelerometer ADS-79B-HDBK, SAE AIR 1839C, SAE AS5391, SAE AS8054 

Rotational sensor SAE AS5392 

Temperature SAE AIR 46B, SAE AIR 1900 RevA, SAE AS8005 RevA 

Oil monitoring SAE AIR 1828 RevB 
 
NASA/TM—2012-217420 15 

Appendix A—HUMS Questionnaire 

1. What HUMS regulations, recommended practices, or industry standards do you follow? (e.g., FAA, 

SAE, DoD, internal). 

2. Please state any objectives or goals for your engine HUMS program and describe your approach 

within your maintenance procedures. (e.g., Time-based, conditioned-based monitoring, other) 

3. What helicopter platforms do you operate or apply your technology to? (Please provide both 

helicopter and engine make/model.) 

4. Describe your HUMS equipment. If possible, please provide manufacturer, system, sensor, engine 

measurement parameter, etc. (References, attachments are welcome.) 

5. Describe your HUMS information flow path (i.e., sense-acquire-transfer-analyze-act). 

6. Describe your HUMS algorithms or condition indicators (CIs) used to determine the health of an 

engine component. 

7. How is your HUMS validated/benchmarked? 

8. How effective is your HUMS program? Quantify in terms of reduced operating costs, improved 

vehicle readiness, or improved safety if possible. 

9. What is needed for further advancement of HUMS for helicopter engines? (i.e., Where in your 

opinion should the next HUMS advancements be in? Diagnostic Tools? Instrumentation? Prognostic 

Tools?) 

10. Open comment. Do you have any other concerns, questions, comments not addressed in the previous 

questions? 

 

NASA/TM—2012-217420 17 

Appendix B—SAE HUMS Related Documents 

SAE AIR46 The Preparation and Use of Chromel-Alumel Thermocouples for Aircraft Gas Turbine 

Engines 

SAE AIR1828 (R) Guide to Engine Lubrication System Monitoring 

SAE AIR1839C (R) A Guide to Aircraft Turbine Engine Vibration Monitoring Systems 

SAE AIR 1872 Guide to Life Usage Monitoring and Parts Management for Aircraft Gas Turbine 

Engines 

SAE AIR 1873 Guide to Limited Engine Monitoring Systems for Aircraft Gas Turbine Engines 

SAE AIR 1900 (R) Guide to Temperature Monitoring in Aircraft Gas Turbine Engines 

SAE AIR 4061B (R) Guidelines for Integrating Typical Engine Health Management Functions 

 Within Aircraft Systems 

SAE AIR 4175 (R) A Guide to the Development of a Ground Station for Engine Condition Monitoring 

SAE AIR 4176 Cost Versus Benefits of Engine Monitoring Systems 

SAE AIR 4985 A Methodology for Quantifying the Performance of an Engine Monitoring System 

SAE AIR 4986 Engine Electrostatic Gas Path Monitoring 

SAE AIR 5120 Engine Monitoring System Reliability and Validity 

SAE AIR 5317 A Guide to APU Health Management 

SAE AIR 5871 Prognostics for Gas Turbine Engines 

SAE AIR 1871C (R) Lessons Learned from Developing, Implementing, and Operating a Health 

Management System for Propulsion and Drive Train Systems 

SAE AIR 4174 A Guide to Aircraft Power Train Monitoring 

SAE ARP 1217 Instrumentation Requirements for Turboshaft Engine Performance Measurements 

SAE ARP 1587B Aircraft Gas Turbine Engine Health Management System Guide 

SAE ARP 5783 Health and Usage Monitoring Metrics Monitoring the Monitor 

SAE AS4831 Software Interfaces for Ground-Based Monitoring Systems 

SAE AS5391 Health and Usage Monitoring System Accelerometer Interface Specification 

SAE AS5392 Health and Usage Monitoring System, Rotational System Indexing Sensor 

Specification 
NASA/TM—2012-217420 18 

SAE AS5393 Health and Usage Monitoring System, Blade Tracker Interface Specification 

SAE AS5394 Health and Usage Monitoring System, Advanced Multipoint Interface Specification 

SAE AS5395 Health and Usage Monitoring System Data Interchange Specification 

SAE AS8005 Minimum Performance Standard Temperature Instruments 

SAE AS8054 Airborne Engine Vibration Monitoring (EVM) System, Guidelines for Performance 

Standard for 
NASA/TM—2012-217420 19 

References 

1. SAE ARP 1587 Rev B. Aircraft Gas Turbine Engine Health Management System Guide. 

May 2007. 

2. US Army ADS-79B-HDBK. Condition Based Maintenance Systems for US Army Aircraft 

Systems. Aug. 2010. 

3. Condition Based Maintenance Plus DoD Guidebook. May 2008. 

4. NATO RTO TR-028. Recommended Practices for Monitoring Gas Turbine Engine Life 

Consumption. April 2000. 

5. SAE AIR 4176. Cost Versus Benefits of Engine Monitoring Systems. Oct. 2005. 

6. Fraser, K.F. “An Overview of Health and Usage Monitoring Systems (HUMS) for Military 

Helicopters.” DSTO-TR-0061. Sept. 1994. 

7. Young, G.K., et al. “A Status of NASA Rotorcraft Research.” NASA/TP—2009-215369, 

September 2009. 

8. Delgado, I.R., et al. “A Review of Engine Seal Performance and Requirements for Current and 

Future Army Engine Platforms.” NASA/TM—2008-215161. Mar. 2008. 

9. http://www.aviation-database.com/aviation_database_pages1/Robinson-Helicoptermaintenance.html. 

10. Uluyol, O, et al. “A Systematic Approach to Bearing Health Monitoring.” American Helicopter 

Society 66th Annual Forum, Phoenix, Arizona, May 11-13, 2010. 

11. Goericke, J., et al. “An Embedded, Physics-Based Approach for Turboshaft Engine Continuous 

Power Assurance and Performance Monitoring.” American Helicopter Society 65th Annual Forum, 

Grapevine, Texas, May 27-29, 2009. 

12. Gordon, G., et al. “Development of a Multi-Faceted Integrated Health Management System for 

Rotorcraft Engines.” American Helicopter Society 66th Annual Forum, Phoenix, Arizona, 

May 11-13, 2010. 

13. Goericke, J., et al. “Validation, Verification, and Hardware Implementation of Physics-Based PHM 

Systems for Continuous Power Assurance, Erosion Detection, and Model-Based Torque for 

Helicopter Turboshaft Engines.” American Helicopter Society 66th Annual Forum, Phoenix, 

Arizona, May 11-13, 2010. 

14. Volponi, A.J., et al., “Development of an Information Fusion system for Engine Diagnostics and 

Health Management.” NASA/TM—2004-212924. Feb. 2004. 

15. SAE AIR 1873. Guide to Limited Engine Monitoring Systems for Aircraft Gas Turbine Engines. 

Oct. 2005. 

16. SAE AIR 1872 Rev A. Guide to Life Usage Monitoring and Parts Management for Aircraft Gas 

Turbine Engines. May 1998. 

17. Fraser, K.F. “Effectiveness of Helicopter Health and Usage Monitoring Systems (HUMS) in the 

Military Environment.” DSTO-TN-0028. March 1996. 

18. SAE AIR 4061B. Guidelines for Integrating Typical Engine Health management Functions Within 

Aircraft Systems. February 2008. 

19. SAE AIR 1871C. Lessons Learned from Developing, Implementing, and Operating a Health 

Management System for Propulsion and Drive Train Systems. Jan. 2011. 

20. http://www51.honeywell.com/aero/common/documents/myaerospacecatalogdocuments/Helicopters-documents/Zing_HUMS_1100-1200-1400_Series.pdf. 

21. http://www.goodrich.com/Goodrich/Businesses/Sensors-and-Integrated-Systems/Products/VehicleHealth-Management-Systems/Integrated-Vehicle-Health-Management-Systems-%28IVHMS%29. 

22. SAE AIR 5120. Engine Monitoring System Reliability and Validity. Nov. 2006. 

23. SAE AIR 1839C. A Guide to Aircraft Turbine Engine Vibration Monitoring Systems. Feb. 2008. 

24. http://www.gastops.com/metalscan.php. 

25. http://www.vibro-meter.com/aerospace/debris.html. 

26. http://www.eaton.com/ecm/groups/public/@pub/@eaton/@aero/documents/content/ct_194536.pdf. 
NASA/TM—2012-217420 20 

27. SAE AIR 1828 Rev. B. Guide to Engine Lubrication System Monitoring. Jun. 2005. 

28. Augustin, M. Personal Interview. 8 Mar. 2011. 

29. CAA CAP 693. Acceptable Means of Compliance Helicopter Health Monitoring. May 1, 1999. 

30. CAA CAP 753. Helicopter Vibration Health Monitoring (VHM) Guidance Material for Operators 

Utilising VHM in Rotor and Rotor Drive Systems of Helicopters. June 2006. 

31. FAA Advisory Circular (AC) 29-2C. Certification of Transport Category Rotorcraft. Chapter 3. 

Airworthiness Standards Transport Category Rotorcraft. Miscellaneous Guidance (MG). AC 29 

MG 15. Airworthiness Approval of Rotorcraft Health Usage Monitoring Systems (HUMS). 

32. FAA. Air Traffic Organization NextGen and Operations Planning Services. Verification and 

Validation Operations Guide. VVSPAT-A2-PDD-014. Version 2.0. Aug. 31, 2010. 

33. Vertical Lift Consortium. CBM Maintenance Credit Verification and Validation Process – Initial 

Draft. ADS-79X-HDBK-Appendix VV Rev 090110. Sept. 1, 2010. 

34. Rickmeyer, T. Personal Interview. 14 Mar. 2011. 

35. Menon, P., et al., “Verification and Validation Process for CBM Maintenance Credits.” American 

Helicopter Society 67th Annual Forum, Virginia Beach, Virginia, May 3-5, 2011. 

36. SAE ARP 5783. Health and Usage Monitoring Metrics – Monitoring the Monitor. Feb. 2008. 

37. SAE AIR 4985. A Methodology for Quantifying the Performance of an Engine Monitoring System. 

Jan. 2005. 

38. Rickmeyer, T., et al. “Processes & Considerations in Extensions to Time Between Overhauls and 

Paths to On-Condition for US Army Rotorcraft Propulsion Systems.” American Helicopter Society 

67th Annual Forum, Virginia Beach, Virginia, May 3-5, 2011. 

39. Hoffmann, F., “Usage Based Maintenance for Dynamic Components of Rotorcrafts.” American 

Helicopter Society 67th Annual Forum, Virginia Beach, Virginia, May 3-5, 2011. 

40. Neubert, C., et al., “U.S. Marine Corps Condition Based Maintenance Approach for the CH-53E 

Helicopter: Five Year Progress Report,” American Helicopter Society 67th Annual Forum, 

Virginia Beach, Virginia, May 3-5, 2011. 

41. Lee, H., et al., “Diagnosing Bearing Corrosion using Joint Time Frequency Vibration Analysis.” 

American Helicopter Society 67th Annual Forum, Virginia Beach, Virginia, May 3-5, 2011. 

42. Fuller, B., et al., “Aggregate Analysis of Health and Usage Monitoring System Data on Naval 

Rotorcraft.” American Helicopter Society 67th Annual Forum, Virginia Beach, Virginia, May 3-5, 

2011. 

43. Tumer, I., et al., “A Survey of Aircraft Engine Health Monitoring Systems.” AIAA-99-2528. 

44. Calhoun, K., Personal Interview. 9 Mar. 2011. 

45. Simon, D., et al., “Sensor Needs for Control and Health Management of Intelligent Aircraft 

Engines.” NASA/TM—2004-213202. Aug. 2004. 

46. ASTM E 122-09. Standard Practice for Calculating Sample Size to Estimate, With Specified 

Precision, the Average for a Characteristic of a Lot or Process. 

47. MIL-HDBK-781A. Department of Defense Handbook for Reliability Test Methods, Plans, and 

Environments for Engineering, Development, Qualification, and Production. Apr. 1, 1996. 

48. He, D., et al., “Using HHT Based Acoustic Emission Feature Quantification for Rotating Machine 

Fault Detection,” American Helicopter Society 67th Annual Forum, Virginia Beach, Virginia, 

May 3-5, 2011. 

49. SAE AIR 5871. Prognostics for Gas Turbine Engines. Jun 2008. 
REPORT DOCUMENTATION PAGE Form Approved 

OMB No. 0704-0188 

The public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the 

data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this 

burden, to Department of Defense, Washington Headquarters Services, Directorate for Information Operations and Reports (0704-0188), 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302. 

Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB 

control number. 

PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. 

1. REPORT DATE (DD-MM-YYYY)

01-01-2012 

2. REPORT TYPE

Technical Memorandum 

3. DATES COVERED (From - To)

4. TITLE AND SUBTITLE

A Survey of Current Rotorcraft Propulsion Health Monitoring Technologies 

5a. CONTRACT NUMBER

5b. GRANT NUMBER

5c. PROGRAM ELEMENT NUMBER

6. AUTHOR(S)

Delgado, Irebert, R.; Dempsey, Paula, J.; Simon, Donald, L. 

5d. PROJECT NUMBER

5e. TASK NUMBER

5f. WORK UNIT NUMBER

WBS 877868.02.07.03.01.01.01 

7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES)

National Aeronautics and Space Administration 

John H. Glenn Research Center at Lewis Field 

Cleveland, Ohio 44135-3191 

8. PERFORMING ORGANIZATION

 REPORT NUMBER

E-18092 

9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES)

National Aeronautics and Space Administration 

Washington, DC 20546-0001 

10. SPONSORING/MONITOR'S

 ACRONYM(S)

NASA 

11. SPONSORING/MONITORING

 REPORT NUMBER

NASA/TM-2012-217420 

12. DISTRIBUTION/AVAILABILITY STATEMENT

Unclassified-Unlimited 

Subject Category: 07 

Available electronically at http://www.sti.nasa.gov 

This publication is available from the NASA Center for AeroSpace Information, 443-757-5802

13. SUPPLEMENTARY NOTES

14. ABSTRACT

A brief review is presented on the state-of-the-art in rotorcraft engine health monitoring technologies including summaries on current 

practices in the area of sensors, data acquisition, monitoring and analysis. Also, presented are guidelines for verification and validation of 

Health Usage Monitoring System (HUMS) and specifically for maintenance credits to extend part life. Finally, a number of new efforts in 

HUMS are summarized as well as lessons learned and future challenges. In particular, gaps are identified to supporting maintenance credits 

to extend rotorcraft engine part life. A number of data sources were consulted and include results from a survey from the HUMS 

community, Society of Automotive Engineers (SAE) documents, American Helicopter Society (AHS) papers, as well as references from 

Defence Science & Technology Organization (DSTO), Civil Aviation Authority (CAA), and Federal Aviation Administration (FAA).

15. SUBJECT TERMS

Helicopter engines; Performance; Health 

16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF

 ABSTRACT

UU 

18. NUMBER

 OF 

 PAGES

24 

19a. NAME OF RESPONSIBLE PERSON

STI Help Desk (email:help@sti.nasa.gov) 

a. REPORT

U 

b. ABSTRACT

U 

c. THIS 

PAGE

U 

19b. TELEPHONE NUMBER (include area code)

443-757-5802 

Standard Form 298 (Rev. 8-98)

Prescribed by ANSI Std. Z39-18