Considerations for the Extension of Gas Path Analysis to Electrified Aircraft Propulsion Systems

2021 ◽  
Author(s):  
Donald L Simon ◽  
Randy Thomas ◽  
Kyle M. Dunlap
Keyword(s):  
Path Analysis ◽  
System Approach ◽  
Engine Performance ◽  
Estimation Accuracy ◽  
Electrical System ◽  
Propulsion Systems ◽  
Turbine Engine ◽  
Analysis Techniques ◽  
Performance Deterioration ◽  
Aircraft Propulsion

Abstract Aircraft operators rely on gas path analysis techniques for monitoring the performance and health of their gas turbine engine assets. This is accomplished by analyzing discernable shifts in measurement parameters acquired from the engine. This paper reviews the founding mathematical principles of gas path analysis, including conventional approaches applied for estimating engine performance deterioration. Considerations for extending the application of gas path analysis techniques to Electrified Aircraft Propulsion (EAP) systems is also discussed, and simulated results from their application to an EAP concept comprised of turbomachinery and electrical system hardware is provided. Results are provided comparing the parameter estimation accuracy offered by taking a whole-system approach towards the problem setup versus that offered by analyzing each subsystem individually. For the latter, the importance of having accurate direct or inferred measurements of external mechanical torque loads placed upon turbomachinery shafts is emphasized.

Considerations for the Extension of Gas Path Analysis To Electrified Aircraft Propulsion Systems

2021 ◽  
Author(s):  
Donald L. Simon ◽  
Randy Thomas ◽  
Kyle M. Dunlap
Keyword(s):  
Path Analysis ◽  
System Approach ◽  
Engine Performance ◽  
Estimation Accuracy ◽  
Electrical System ◽  
Propulsion Systems ◽  
Turbine Engine ◽  
Analysis Techniques ◽  
Performance Deterioration ◽  
Aircraft Propulsion

Abstract Aircraft operators rely on gas path analysis techniques for monitoring the performance and health of their gas turbine engine assets. This is accomplished by analyzing discernable shifts in measurement parameters acquired from the engine. This paper reviews the founding mathematical principles of gas path analysis, including conventional approaches applied for estimating engine performance deterioration. Considerations for extending the application of gas path analysis techniques to Electrified Aircraft Propulsion (EAP) systems is also discussed, and simulated results from their application to an EAP concept comprised of turbomachinery and electrical system hardware is provided. Results are provided comparing the parameter estimation accuracy offered by taking a whole-system approach towards the problem setup versus that offered by analyzing each subsystem individually. For the latter, the importance of having accurate direct or inferred measurements of external mechanical torque loads placed upon turbomachinery shafts is emphasized.

scholarly journals An Integrated Approach for Aircraft Engine Performance Estimation and Fault Diagnostics

2013 ◽  
Vol 135 (7) ◽  
Author(s):  
Donald L. Simon ◽  
Jeffrey B. Armstrong
Keyword(s):  
Kalman Filter ◽  
Engine Performance ◽  
Aircraft Engine ◽  
Fault Isolation ◽  
Performance Estimation ◽  
Estimation Accuracy ◽  
Fault Diagnostics ◽  
Tuning Parameters ◽  
Performance Deterioration ◽  
Health Parameters

A Kalman filter-based approach for integrated on-line aircraft engine performance estimation and gas path fault diagnostics is presented. This technique is specifically designed for underdetermined estimation problems where there are more unknown system parameters representing deterioration and faults than available sensor measurements. A previously developed methodology is applied to optimally design a Kalman filter to estimate a vector of tuning parameters, appropriately sized to enable estimation. The estimated tuning parameters can then be transformed into a larger vector of health parameters representing system performance deterioration and fault effects. The results of this study show that basing fault isolation decisions solely on the estimated health parameter vector does not provide ideal results. Furthermore, expanding the number of the health parameters to address additional gas path faults causes a decrease in the estimation accuracy of those health parameters representative of turbomachinery performance deterioration. However, improved fault isolation performance is demonstrated through direct analysis of the estimated tuning parameters produced by the Kalman filter. This was found to provide equivalent or superior accuracy compared to the conventional fault isolation approach based on the analysis of sensed engine outputs, while simplifying online implementation requirements. Results from the application of these techniques to an aircraft engine simulation are presented and discussed.

Performance Deterioration in Industrial Gas Turbines

1992 ◽  
Vol 114 (2) ◽  
pp. 161-168 ◽  
Author(s):  
I. S. Diakunchak
Keyword(s):  
Gas Turbine ◽  
Service Time ◽  
Gas Turbines ◽  
Engine Performance ◽  
Turbine Engine ◽  
Factors Affecting ◽  
Preventative Measures ◽  
Industrial Gas Turbines ◽  
Performance Deterioration ◽  
Industrial Gas Turbine

This paper describes the most important factors affecting the industrial gas turbine engine performance deterioration with service time and provides some approximate data on the prediction of the rate of deterioration. Recommendations are made on how to detect and monitor the performance deterioration. Preventative measures, which can be taken to avoid or retard the performance deterioration, are described in some detail.

scholarly journals An Integrated Approach for Aircraft Engine Performance Estimation and Fault Diagnostics

2012 ◽  
Author(s):  
Donald L. Simon ◽  
Jeffrey B. Armstrong
Keyword(s):  
Kalman Filter ◽  
Engine Performance ◽  
Aircraft Engine ◽  
Fault Isolation ◽  
Performance Estimation ◽  
Estimation Accuracy ◽  
Fault Diagnostics ◽  
Tuning Parameters ◽  
Performance Deterioration ◽  
Health Parameters

A Kalman filter-based approach for integrated on-line aircraft engine performance estimation and gas path fault diagnostics is presented. This technique is specifically designed for underdetermined estimation problems where there are more unknown system parameters representing deterioration and faults than available sensor measurements. A previously developed methodology is applied to optimally design a Kalman filter to estimate a vector of tuning parameters, appropriately sized to enable estimation. The estimated tuning parameters can then be transformed into a larger vector of health parameters representing system performance deterioration and fault effects. The results of this study show that basing fault isolation decisions solely on the estimated health parameter vector does not provide ideal results. Furthermore, expanding the number of the health parameters to address additional gas path faults causes a decrease in the estimation accuracy of those health parameters representative of turbomachinery performance deterioration. However, improved fault isolation performance is demonstrated through direct analysis of the estimated tuning parameters produced by the Kalman filter. This was found to provide equivalent or superior accuracy compared to the conventional fault isolation approach based on the analysis of sensed engine outputs, while simplifying online implementation requirements. Results from the application of these techniques to an aircraft engine simulation are presented and discussed.

Performance Deterioration in Industrial Gas Turbines

1991 ◽  
Author(s):  
Ihor S. Diakunchak
Keyword(s):  
Gas Turbine ◽  
Service Time ◽  
Gas Turbines ◽  
Engine Performance ◽  
Turbine Engine ◽  
Factors Affecting ◽  
Preventative Measures ◽  
Industrial Gas Turbines ◽  
Performance Deterioration ◽  
Industrial Gas Turbine

This paper describes the most important factors affecting the industrial gas turbine engine performance deterioration with service time and provides some approximate data on the prediction of the rate of deterioration. Recommendations are made on how to detect and monitor the performance deterioration. Preventative measures, which can be taken to avoid or retard the performance deterioration, are described in some detail.

scholarly journals Aircraft Gas Turbine Engine Health Monitoring System by Real Flight Data

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Mustagime Tülin Yildirim ◽  
Bülent Kurt
Keyword(s):  
Gas Turbine ◽  
Engine Performance ◽  
Aircraft Engine ◽  
Gas Turbine Engine ◽  
Gas Temperature ◽  
Turbine Engine ◽  
Fuel Flow ◽  
The Status ◽  
Performance Deterioration ◽  
Artificial Neural Network Ann

Modern condition monitoring-based methods are used to reduce maintenance costs, increase aircraft safety, and reduce fuel consumption. In the literature, parameters such as engine fan speeds, vibration, oil pressure, oil temperature, exhaust gas temperature (EGT), and fuel flow are used to determine performance deterioration in gas turbine engines. In this study, a new model was developed to get information about the gas turbine engine’s condition. For this model, multiple regression analysis was carried out to determine the effect of the flight parameters on the EGT parameter and the artificial neural network (ANN) method was used in the identification of EGT parameter. At the end of the study, a network that predicts the EGT parameter with the smallest margin of error has been developed. An interface for instant monitoring of the status of the aircraft engine has been designed in MATLAB Simulink. Any performance degradation that may occur in the aircraft’s gas turbine engine can be easily detected graphically or by the engine performance deterioration value. Also, it has been indicated that it could be a new indicator that informs the pilots in the event of a fault in the sensor of the EGT parameter that they monitor while flying.

Electronic Trend Monitoring and Exceedance Recording Systems: A Means to Improved Turbine Engine Reliability

1987 ◽  
Author(s):  
Michael G. Moore
Keyword(s):  
Engine Performance ◽  
Current Sensor ◽  
Time Duration ◽  
Turbine Engine ◽  
Power Cycle ◽  
Current Technology ◽  
Real Time Analysis ◽  
Performance Deterioration ◽  
Computer Keyboard ◽  
Engine Reliability

Current technology has yielded engine mountable, compact microprocessor-based recording systems that can record information that will aid in maintenance planning and, thus, yield improved reliability. Among data available are: 1) Trend Recording - revealing deviations from non indicating engine performance deterioration 2) Exceedance Recording - documenting time, date, duration, and severity of exceedances for parameters such as temperature, torque, N1, N2, etc. 3) Power Ratings - power (“hit”) checks are available instantaneously and through the through the exercise of power cycle, go or no-go determination made through real time analysis of current sensor outputs against defined tolerances adjusted to density altitude. 4) Run Data - total time duration within each scale of the operating range for each engine and airframe parameter 5) Cycle Counts - start, power, life fatigue, creep life, and improper cool down cycles are tracked based upon engine manufacturer formulae These engine recorders primarily utilize the existing engine sensors with no effect on signals to established instrument. Current technology allows these engine recorders to be universal to many different engines, with limit thresholds entered at the factory through a computer keyboard.

Prediction of the Jet Engine Performance Deterioration

2012 ◽  
Author(s):  
Maryam Gholamhossein ◽  
Ameneh Vatani ◽  
Najmeh Daroogheh ◽  
K. Khorasani
Keyword(s):  
Moving Average ◽  
Engine Performance ◽  
Multivariate Methods ◽  
Jet Engine ◽  
Turbine Engine ◽  
Vector Autoregressive ◽  
Autoregressive Integrated Moving Average ◽  
Multivariate Modelling ◽  
Performance Deterioration ◽  
Modelling Methods

This paper deals with performance deterioration modelling of a single spool gas turbine engine based on time-series methods. Towards this end, two univariate and multivariate methods, namely the Autoregressive Integrated Moving Average (ARIMA) and the Vector Autoregressive (VAR) schemes are applied to predict the Turbine Entry Temperature (TET) evolution during the flight cycles for maintenance purposes. In the VAR scheme, two engine process parameters i.e. the Turbine Entry Temperature (TET) and the Compressor Temperature are employed to achieve this prediction goal. The results show that employing multivariate modelling methods lead to better prediction horizons. For each method two scenarios are considered to demonstrate the effectiveness of the models.

Gas Turbine Performance and Health Status Estimation Using Adaptive Gas Path Analysis

2010 ◽  
Vol 132 (4) ◽  
Author(s):  
Y. G. Li
Keyword(s):  
Health Status ◽  
Path Analysis ◽  
Gas Turbine ◽  
Performance Status ◽  
Engine Performance ◽  
Test Cases ◽  
Airflow Rate ◽  
Component Level ◽  
Turbine Engine ◽  
Time Required

In gas turbine operations, engine performance and health status are very important information for engine operators. Such engine performance is normally represented by engine airflow rate, compressor pressure ratios, compressor isentropic efficiencies, turbine entry temperature, turbine isentropic efficiencies, etc., while the engine health status is represented by compressor and turbine efficiency indices and flow capacity indices. However, these crucial performance and health information cannot be directly measured and therefore are not easily available. In this research, a novel Adaptive Gas Path Analysis (Adaptive GPA) approach has been developed to estimate actual engine performance and gas path component health status by using gas path measurements, such as gas path pressures, temperatures, shaft rotational speeds, fuel flow rate, etc. Two steps are included in the Adaptive GPA approach, the first step is the estimation of degraded engine performance status by a novel application of a performance adaptation method, and the second step is the estimation of engine health status at component level by using a new diagnostic method introduced in this paper, based on the information obtained in the first step. The developed Adaptive GPA approach has been tested in four test cases where the performance and degradation of a model gas turbine engine similar to Rolls-Royce aero engine Avon-300 have been analyzed. The case studies have shown that the developed novel linear and nonlinear Adaptive GPA approaches can accurately and quickly estimate the degraded engine performance and predict the degradation of major engine gas path components with the existence of measurement noise. The test cases have also shown that the calculation time required by the approach is short enough for its potential online applications.

Towards Development of a Diagnostic and Prognostic Tool for Civil Aero-Engine Component Degradation

2012 ◽  
Author(s):  
Nqobile Khani ◽  
Clara Segovia ◽  
Rukshan Navaratne ◽  
Vishal Sethi ◽  
Riti Singh ◽  
...  
Keyword(s):  
Life Cycle ◽  
Engine Performance ◽  
Life Cycle Costs ◽  
Turbine Engine ◽  
Prognostic Tool ◽  
Fuel Burn ◽  
Engine Component ◽  
Performance Deterioration ◽  
Maintenance Requirements ◽  
Engine Life

A mechanical device such as an aircraft gas turbine engine will in its lifetime of service show the effects of damage and deterioration. The damage to (and deterioration of) an engine has an adverse effect on the engine’s overall performance. It is therefore vitally important to predict the effects of deterioration on the performance of an engine and on the economic (fuel burn and engine life) implications from an operator’s perspective. Engine component degradation leads to performance deterioration and change, which requires the engine to run hotter and faster so as to meet the required thrust and aircraft performance. Increasing engine operating temperatures and engine speed result in increased creep and fatigue damage to the hot section components and increases the engine life cycle costs. One way of reducing life cycle costs is by better usage of the engine and involves being certain about the life potential of the engine and its components and how this life evolves with use. A sound understanding of how the engine life evolves and to predict remaining life requires understanding the engine’s operating environment and how component damage is sustained and accumulated. Knowledge about the engine condition and the likely stresses to which it will be subjected is required to analyse engine component usage and reduce degradation, raise safe-life limits of components and reduce maintenance requirements. This paper lays the foundation for the development of a prognostic tool that will capture and model the mechanisms of degradation, and predict levels of degradation based on engine deployment. The mechanisms that will cause degradation are assessed and integrated to establish the requirements of the tool. The paper discusses how degradation will affect component and engine performance and also the life of the engine.

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