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Diagnostics and Prognostics of Aerospace Engines

Diagnostics and Prognostics of Aerospace Engines
Author: Ravi Rajamani
Publisher: SAE International
Total Pages: 196
Release: 2018-11-28
Genre: Technology & Engineering
ISBN: 0768095395

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The propulsion system is arguably the most critical part of the aircraft; it certainly is the single most expensive component of the vehicle. Ensuring that engines operate reliably without major maintenance issues is an important goal for all operators, military or commercial. Engine health management (EHM) is a critical piece of this puzzle and has been a part of the engine maintenance for more than five decades. In fact, systematic condition monitoring was introduced for engines before it was applied to other systems on the aircraft. Diagnostics and Prognostics of Aerospace Engines is a collection of technical papers from the archives of SAE International, which introduces the reader to a brief history of EHM, presents some examples of EHM functions, and outlines important future trends. The goal of engine health maintenance is ultimately to reduce the cost of operations by catching problems before they become major issues, by helping reduce repair times through diagnostics, and by facilitating logistic optimization through prognostic estimates. Diagnostics and Prognostics of Aerospace Engines shows that the essence of these goals has not changed over time.


Diagnostics and Prognostics of Aerospace Engines

Diagnostics and Prognostics of Aerospace Engines
Author: Ravi Rajamani
Publisher:
Total Pages: 196
Release: 2018
Genre: Airplane
ISBN: 9780768093094

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A collection of technical papers from the archives of SAE International, which introduces the reader to a brief history of EHM, presents some examples of EHM functions, and outlines important future trends.


Diagnostics and Prognostics of Aerospace Engines

Diagnostics and Prognostics of Aerospace Engines
Author: Ravi Rajamani
Publisher: SAE International
Total Pages: 196
Release: 2018-11-28
Genre: Transportation
ISBN: 0768093074

Download Diagnostics and Prognostics of Aerospace Engines Book in PDF, ePub and Kindle

The propulsion system is arguably the most critical part of the aircraft; it certainly is the single most expensive component of the vehicle. Ensuring that engines operate reliably without major maintenance issues is an important goal for all operators, military or commercial. Engine health management (EHM) is a critical piece of this puzzle and has been a part of the engine maintenance for more than five decades. In fact, systematic condition monitoring was introduced for engines before it was applied to other systems on the aircraft. Diagnostics and Prognostics of Aerospace Engines is a collection of technical papers from the archives of SAE International, which introduces the reader to a brief history of EHM, presents some examples of EHM functions, and outlines important future trends. The goal of engine health maintenance is ultimately to reduce the cost of operations by catching problems before they become major issues, by helping reduce repair times through diagnostics, and by facilitating logistic optimization through prognostic estimates. Diagnostics and Prognostics of Aerospace Engines shows that the essence of these goals has not changed over time.


Data Fusion for Enhanced Aircraft Engine Prognostics and Health Management

Data Fusion for Enhanced Aircraft Engine Prognostics and Health Management
Author: National Aeronautics and Space Administration (NASA)
Publisher: Createspace Independent Publishing Platform
Total Pages: 36
Release: 2018-05-29
Genre:
ISBN: 9781720455578

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Aircraft gas-turbine engine data is available from a variety of sources, including on-board sensor measurements, maintenance histories, and component models. An ultimate goal of Propulsion Health Management (PHM) is to maximize the amount of meaningful information that can be extracted from disparate data sources to obtain comprehensive diagnostic and prognostic knowledge regarding the health of the engine. Data fusion is the integration of data or information from multiple sources for the achievement of improved accuracy and more specific inferences than can be obtained from the use of a single sensor alone. The basic tenet underlying the data/ information fusion concept is to leverage all available information to enhance diagnostic visibility, increase diagnostic reliability and reduce the number of diagnostic false alarms. This report describes a basic PHM data fusion architecture being developed in alignment with the NASA C-17 PHM Flight Test program. The challenge of how to maximize the meaningful information extracted from disparate data sources to obtain enhanced diagnostic and prognostic information regarding the health and condition of the engine is the primary goal of this endeavor. To address this challenge, NASA Glenn Research Center, NASA Dryden Flight Research Center, and Pratt & Whitney have formed a team with several small innovative technology companies to plan and conduct a research project in the area of data fusion, as it applies to PHM. Methodologies being developed and evaluated have been drawn from a wide range of areas including artificial intelligence, pattern recognition, statistical estimation, and fuzzy logic. This report will provide a chronology and summary of the work accomplished under this research contract.Volponi, AlGlenn Research CenterARTIFICIAL INTELLIGENCE; INFORMATION SYSTEMS; PROPULSION; RELIABILITY; STATISTICAL ANALYSIS; CHRONOLOGY; FLIGHT TESTS; FUZZY SYSTEMS; GAS TURBINE ENGINES


Data Fusion for Enhanced Aircraft Engine Prognostics and Health Management

Data Fusion for Enhanced Aircraft Engine Prognostics and Health Management
Author: Al Volponi
Publisher: BiblioGov
Total Pages: 40
Release: 2013-06
Genre:
ISBN: 9781289148034

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Aircraft gas-turbine engine data is available from a variety of sources, including on-board sensor measurements, maintenance histories, and component models. An ultimate goal of Propulsion Health Management (PHM) is to maximize the amount of meaningful information that can be extracted from disparate data sources to obtain comprehensive diagnostic and prognostic knowledge regarding the health of the engine. Data fusion is the integration of data or information from multiple sources for the achievement of improved accuracy and more specific inferences than can be obtained from the use of a single sensor alone. The basic tenet underlying the data/ information fusion concept is to leverage all available information to enhance diagnostic visibility, increase diagnostic reliability and reduce the number of diagnostic false alarms. This report describes a basic PHM data fusion architecture being developed in alignment with the NASA C-17 PHM Flight Test program. The challenge of how to maximize the meaningful information extracted from disparate data sources to obtain enhanced diagnostic and prognostic information regarding the health and condition of the engine is the primary goal of this endeavor. To address this challenge, NASA Glenn Research Center, NASA Dryden Flight Research Center, and Pratt & Whitney have formed a team with several small innovative technology companies to plan and conduct a research project in the area of data fusion, as it applies to PHM. Methodologies being developed and evaluated have been drawn from a wide range of areas including artificial intelligence, pattern recognition, statistical estimation, and fuzzy logic. This report will provide a chronology and summary of the work accomplished under this research contract.


Prognostic Metrics for Engine Health Management Systems

Prognostic Metrics for Engine Health Management Systems
Author: E-32 Aerospace Propulsion Systems Health Management
Publisher:
Total Pages: 0
Release: 2021
Genre:
ISBN:

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This SAE Aerospace Information Report (AIR) presents metrics for assessing the performance of prognostic algorithms applied for Engine Health Management (EHM) functions. The emphasis is entirely on prognostics and as such is intended to provide an extension and complement to such documents as AIR5871, which offers information and guidance on general prognostic approaches relevant to gas turbines, and AIR4985 which offers general metrics for evaluating diagnostic systems and their impact on engine health management activities.This Aerospace Information Report (AIR) has been superseded by the document AIR7999, "Diagnostic and Prognostic Metrics for Aerospace Propulsion Health Management Systems." AIR7999 consolidates and expands upon the contents of this document (AIR5909) plus AIR4985, "A Methodology for Quantifying the Performance of an Engine Monitoring System." As such, AIR7999 provides a single comprehensive document on diagnostic and prognostic metrics for aerospace propulsion health management systems making the contents of AIR5909 and AIR4985 redundant and unnecessary. This document consolidation strategy was agreed to by the SAE E-32 Aerospace Propulsion Systems Health Management Committee as part of the Committee's Master Plan.


Condition-Based Maintenance in Aviation

Condition-Based Maintenance in Aviation
Author: Ravi Rajamani
Publisher: SAE International
Total Pages: 146
Release: 2018-12-11
Genre: Technology & Engineering
ISBN: 0768095352

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Condition-Based Maintenance in Aviation: The History, The Business and The Technology describes the history and practice of Condition-Based Maintenance (CBM) systems by showcasing ten technical papers from the archives of SAE International, stretching from the dawn of the jet age down to the present times. By scientifically understanding how different components degrade during operations, it is possible to schedule inspections, repairs, and overhauls at appropriate intervals so that any incipient failure can be detected well in advance. Today, this includes more sensors and analytics so that periodic inspections are replaced by automated "continuous" inspections, and analytical methods that detect imminent failures and predict degradation issues more economically and efficiently. Similar concepts are also being developed for delivering prognostics functions, such as tracking of remaining useful life (RUL) of life-limited parts in aircraft engines. The discipline within CBM that deals with this is called prognostics and health management (PHM), which covers all aspects of diagnostics and prognostics, including modeling of systems and subsystems, sensing, data transmission, storage and retrieval, analytical methods, and decision making. Traditionally, nondestructive testing (NDT) methods have been employed during the major airplane checks to assess structural damage. These techniques are enhanced with in- situ sensing techniques that can continuously monitor aircraft structures and report on their health. The move to condition-based assessment of maintenance needs to be balanced by the assurance that safety is not compromised, that initial cost of new equipment is amortized by the savings, and that regulatory authorities are on board with any modifications to the planned maintenance schedule. The trend is clearly to include more CBM functions into Maintenance, Repair and Overhaul (MRO) processes so better cost control can be achieved without ever comprising passenger safety.


Diagnostics and Engine Condition Monitoring

Diagnostics and Engine Condition Monitoring
Author: North Atlantic Treaty Organization. Advisory Group for Aerospace Research and Development. Propulsion and Energetics Panel
Publisher:
Total Pages: 370
Release: 1975
Genre: Aeronautical instruments
ISBN:

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Enhanced Self Tuning On-Board Real-Time Model (Estorm) for Aircraft Engine Performance Health Tracking

Enhanced Self Tuning On-Board Real-Time Model (Estorm) for Aircraft Engine Performance Health Tracking
Author: National Aeronautics and Space Administration (NASA)
Publisher: Createspace Independent Publishing Platform
Total Pages: 56
Release: 2018-05-22
Genre:
ISBN: 9781719488730

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A key technological concept for producing reliable engine diagnostics and prognostics exploits the benefits of fusing sensor data, information, and/or processing algorithms. This report describes the development of a hybrid engine model for a propulsion gas turbine engine, which is the result of fusing two diverse modeling methodologies: a physics-based model approach and an empirical model approach. The report describes the process and methods involved in deriving and implementing a hybrid model configuration for a commercial turbofan engine. Among the intended uses for such a model is to enable real-time, on-board tracking of engine module performance changes and engine parameter synthesis for fault detection and accommodation. Volponi, Al and Simon, Donald L. (Technical Monitor) Glenn Research Center TURBOFAN ENGINES; AIRCRAFT ENGINES; FAULT DETECTION; GAS TURBINE ENGINES; PERFORMANCE PREDICTION; REAL TIME OPERATION; DIAGNOSIS; DATA PROCESSING; PROPULSION