Fuzzy Condition Monitoring System for Aviation Gas Turbine Engines

2007 ◽  
Author(s):  
P. S. Abdullayev ◽  
A. M. Pashayev ◽  
R. A. Sadiqov ◽  
A. J. Mirzoyev
Keyword(s):  
Gas Turbine ◽  
Monitoring System ◽  
Condition Monitoring ◽  
Technical Condition ◽  
Regression Equations ◽  
Gas Temperature ◽  
Adequate Model ◽  
Technology Application ◽  
Condition Monitoring System ◽  
Skewness And Kurtosis

In this paper is shown the efficiency of the new Soft Computing technology application at different diagnosing stages of aviation gas turbine engine (GTE) technical condition with using Fuzzy Logic and Neural Networks methods, when the flight information has property of a fuzzy, limitation and uncertainty. On the fuzzy statistical data basis and with high accuracy is made the training of Fuzzy Multiple Linear and Non-Linear models (Fuzzy Regression Equations). Thus for GTE technical condition more adequate model making are analysed dynamics of skewness and kurtosis coefficients’ changes. Researches of skewness and kurtosis coefficients values’ changes show that, distributions of GTE work parameters have fuzzy character. Hence consideration of fuzzy skewness and kurtosis coefficients is expedient. Investigation of the basic characteristics changes’ dynamics of GTE work parameters allows to draw conclusion on necessity of the Fuzzy Statistical Analysis at preliminary identification of the engines’ technical condition. Researches of correlation coefficients values’ changes shows also on their fuzzy character. Therefore for models choice the application of the Fuzzy Correlation Analysis results is offered. For checking of models adequacy is considered the Fuzzy Multiple Correlation Coefficient of Fuzzy Multiple Regression. With a view of completeness of GTE technical condition diagnosing in this paper are considered Fuzzy Thermodynamic Models. As output parameter of these models the outlet gas temperature of gas turbine (turbine exhaust gas temperature -EGT) expediency is considered. In view of limitation of controllable parameters’ structure are used also semiempirical models. The developed GTE condition monitoring system provides stage-by-stage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine temperature condition was made.

scholarly journals IDENTIFICATION SYSTEM FOR THE TECHNICAL CONDITION OF GAS TURBINE ENGINES OF AIRCRAFT

Aviation ◽  
2008 ◽  
Vol 12 (4) ◽  
pp. 101-112 ◽  
Author(s):  
Arif Pashayev ◽  
Djakhangir Askerov ◽  
Ramiz Sadiqov ◽  
Parviz Abdullayev
Keyword(s):  
Gas Turbine ◽  
Soft Computing ◽  
Technical Condition ◽  
Recursive Least Squares ◽  
Turbine Engines ◽  
Identification System ◽  
Regression Equations ◽  
Gas Turbine Engines ◽  
Adequate Model ◽  
Skewness And Kurtosis

In this paper, it is shown that the use of probability‐statistic methods, especially at the early stage of diagnosing the technical condition of aviation gas turbine engines (GTE) when the flight information has fuzzy and limitation and uncertainty properties, is unfounded. Hence the efficiency of the use of Soft Computing methods‐fuzzy logic and neural networks at these diagnostic stages is considered. Training with high accuracy of fuzzy multiple linear and non‐linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. Thus, for to make a more adequate model of the technical condition of GTE, the dynamics changes of skewness and kurtosis coefficients are analysed. Research of skewness and kurtasis coefficients shows, that the statistical distributions of the work parameters of GTE have a fuzzy character. Hence, consideration of fuzzy skewness and kurtosis coefficients is expedient. Investigation of the basic characteristics of the changes in the dynamics of the work parameters of GTE allows to draw the conclusion that it is necessary to use fuzzy statistical analysis during the preliminary identification of the technical condition of engines. Research of changes in the values of correlation coefficients also demonstrates their fuzzy character. Therefore for models choice the application of the Fuzzy Correlation Analysis results is offered. The fuzzy multiple correlation coefficient of fuzzy multiple regression is considered for checking the adequacy of models. At the information sufficiency is offered to use recurrent algorithm of aviation GTE technical condition identification (hard computing technology is used) on measurements of input and output parameters of the multiple linear and nonlinear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The system that is developed to monitor the condition of GTE provides stage‐by‐stage estimation of the technical condition of an engine. As an application of this technique, an estimation of the new operating aviation engine temperature condition was made. Santrauka Straipsnyje atskleidžiamas tikimybinio-statistinio metodo nepagrįstumas diagnozuojant dujų turbininius variklius, kai informacija yra netiksli, ribota ir neapibrėžta. Parodytas technologijos Soft Computing taikymo efektyvumas. Taikant netikslios statistikos, netikslios logikos ir neuroninių tinklų tikslius metodus dujų turbininių variklių diagnozavimui atliekamas daugiamačių tiesinių ir netiesinių modelių (regresijos lygčių), gautų iš netikslių statistinių duomenų, apmokymas. Taikant aprašytą metodą buvo atlikta pradėto eksploatuoti turbininio variklio šiluminės būsenos analizė.

scholarly journals Aircraft Gas Turbine Engines’ Technical Condition Identification System

2005 ◽  
Author(s):  
P. S. Abdullayev ◽  
A. M. Pashayev ◽  
D. D. Askerov ◽  
R. A. Sadiqov
Keyword(s):  
Gas Turbine ◽  
Least Squares Method ◽  
Technical Condition ◽  
Fuzzy Regression ◽  
Recursive Least Squares ◽  
Identification System ◽  
Regression Equations ◽  
Adequate Model ◽  
Non Linear ◽  
Skewness And Kurtosis

In this paper is shown that the probability-statistic methods application, especially at the early stage of the aviation gas turbine engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence is considered the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods. Training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. Thus for GTE technical condition more adequate model making are analysed dynamics of skewness and kurtosis coefficients’ changes. Researches of skewness and kurtosis coefficients values’ changes show that, distributions of GTE work parameters have fuzzy character. Hence consideration of fuzzy skewness and kurtosis coefficients is expedient. Investigation of the basic characteristics changes’ dynamics of GTE work parameters allows to draw conclusion on necessity of the Fuzzy Statistical Analysis at preliminary identification of the engines’ technical condition. Researches of correlation coefficients values’ changes shows also on their fuzzy character. Therefore for models choice the application of the Fuzzy Correlation Analysis results is offered. At the information sufficiency is offered to use recurrent algorithm of aviation GTE technical condition identification (Hard Computing technology is used) on measurements of input and output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-by-stage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine D-30KU-154 technical condition was made.

Fuzzy Statistics Approach for Aviation GTE Condition Estimation Technique

2006 ◽  
Author(s):  
P. S. Abdullayev
Keyword(s):  
Linear Models ◽  
Least Squares Method ◽  
Early Stage ◽  
Technical Condition ◽  
Multiple Correlation Coefficient ◽  
Fuzzy Regression ◽  
Recursive Least Squares ◽  
Regression Equations ◽  
Adequate Model ◽  
Skewness And Kurtosis

In this paper is shown that the probability-statistic methods application, especially at the early stage of the aviation gas turbine engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence is considered the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods. Training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. Thus for GTE technical condition more adequate model making are analysed dynamics of skewness and kurtosis coefficients’ changes. Researches of skewness and kurtosis coefficients values’ changes show that, distributions of GTE work parameters have fuzzy character. Hence consideration of fuzzy skewness and kurtosis coefficients is expedient. Investigation of the basic characteristics changes’ dynamics of GTE work parameters allows to draw conclusion on necessity of the Fuzzy Statistical Analysis at preliminary identification of the engines’ technical condition. Researches of correlation coefficients values’ changes shows also on their fuzzy character. Therefore for models choice the application of the Fuzzy Correlation Analysis results is offered. For checking of models adequacy is considered the Fuzzy Multiple Correlation Coefficient of Fuzzy Multiple Regression. At the information sufficiency is offered to use recurrent algorithm of aviation GTE technical condition identification (Hard Computing technology is used) on measurements of input and output parameters of the multiple linear and nonlinear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-by-stage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine temperature condition was made.

Trends™: An Automatic Gas Turbine Diagnostic System

1975 ◽  
Author(s):  
J. R. Passalacqua
Keyword(s):  
Gas Turbine ◽  
Monitoring System ◽  
Condition Monitoring ◽  
Diagnostic System ◽  
Data Systems ◽  
Standard Field ◽  
Military Aviation ◽  
Condition Monitoring System ◽  
And Performance ◽  
Engine Condition

This paper describes the development, operation and performance of an automatic engine condition monitoring system by Hamilton Standard Division of United Aircraft. This development is a direct outgrowth of Airborne Integrated Data Systems (AIDS), which have been developed for commercial and military aviation. Application of this technology to an installation at Hartford Electric Light Company’s South Meadow facility led to the development of the system currently being installed at several major utilities and marketed by Hamilton Standard. Field results of the HELCO testing are presented herein. As current installation information becomes available it will be made available to industry.

Marine Gas Turbine Condition Monitoring by Gas Path Electrostatic Detection Techniques

1991 ◽  
Author(s):  
R. A. Cartwright ◽  
C. Fisher
Keyword(s):  
Gas Turbine ◽  
Monitoring System ◽  
Condition Monitoring ◽  
Joint Research ◽  
Detection Techniques ◽  
Debris Particles ◽  
On Line ◽  
Path Condition ◽  
Condition Monitoring System ◽  
And Performance

It was discovered in 1970 that certain gas turbine failures are preceded by an increase in electrostatic activity in the exhaust gases. Joint research by the Royal Aerospace Establishment and Stewart Hughes Limited demonstrated that this characteristic could be used to provide an on-line monitor of the precursors to these failures. An extension of the research applied the theory to the detection of foreign objects ingested into engine inlets. The characteristics and performance of both the Ingested Debris Monitoring System (IDMS) and Engine Distress Monitoring System (EDMS) were examined during a recent 2000 hours endurance trial of a Rolls-Royce Marine Spey gas turbine. The EDMS produced clear evidence of the minor combustor degradation that occurred steadily throughout the trial and also reflected the absence of other engine damage. IDMS data showed that few significant debris particles passed through the engine. Video endoscope and visual inspection confirmed these results. Debris seeding trials further explored the capability of the IDMS to identify the damaging nature of debris and to assess the EDMS signature of consequential engine damage. The paper concludes that electrostatic monitoring at engine inlet and exhaust can identify the ingestion of debris, consequential engine damage and the onset of unexpected distresses caused by blade rubs or combustor degradation. The technique shows potential to provide early warning of certain types of engine damage to Engineer Officers at sea and development into a rugged gas path condition monitoring system continues.

A Gas Turbine Condition-Monitoring System

1995 ◽  
Vol 107 (6) ◽  
pp. 23-33 ◽  
Author(s):  
James R. Hardin ◽  
Ivan L. Howell ◽  
J. Richard Mirilovich ◽  
John J. Hartranft ◽  
David L. Schreder
Keyword(s):  
Gas Turbine ◽  
Monitoring System ◽  
Condition Monitoring ◽  
Condition Monitoring System

Parametric Modeling of Exhaust Gas Emission From Natural Gas Fired Gas Turbines

1996 ◽  
Vol 118 (3) ◽  
pp. 553-560 ◽  
Author(s):  
L. E. Bakken ◽  
L. Skogly
Keyword(s):  
Air Pollution ◽  
Gas Turbine ◽  
Monitoring System ◽  
Condition Monitoring ◽  
Gas Turbines ◽  
Nox Emissions ◽  
Exhaust Gas ◽  
On Line ◽  
Condition Monitoring System ◽  
Line Condition

Increased focus on air pollution from gas turbines in the Norwegian sector of the North Sea has resulted in taxes on CO2. Statements made by the Norwegian authorities imply regulations and/or taxes on NOx emissions in the near future. The existing CO2 tax of NOK 0.82/Sm3 (US Dollars 0.12/Sm3) and possible future tax on NOx are analyzed mainly with respect to operating and maintenance costs for the gas turbine. Depending on actual tax levels, the machine should be operated on full load/optimum thermal efficiency or part load to reduce specific exhaust emissions. Based on field measurements, exhaust emissions (CO2, CO, NOx, N20, UHC, etc.) are established with respect to load and gas turbine performance, including performance degradation. Different NOx emission correlations are analyzed based on test results, and a proposed prediction model presented. The impact of machinery performance degradation on emission levels is particularly analyzed. Good agreement is achieved between measured and predicted NOx emissions from the proposed correlation. To achieve continuous exhaust emission control, the proposed NOx model is implemented to the on-line condition monitoring system on the Sleipner A platform, rather than introducing sensitive emission sensors in the exhaust gas stack. The on-line condition monitoring system forms an important tool in detecting machinery condition/degradation and air pollution, and achieving optimum energy conservation.

Design and Implementation of a Condition Monitoring System for Process Plants, Off-Shore Platforms, and Pipeline Compressor Stations

1995 ◽  
Author(s):  
Meherwan P. Boyce ◽  
Arkalgud N. Lakshminarasimha ◽  
Timothy S. Mullin
Keyword(s):  
Monitoring System ◽  
Condition Monitoring ◽  
Distribution Analysis ◽  
Gas Temperature ◽  
Network Systems ◽  
Industrial Complexes ◽  
Process Plants ◽  
Condition Monitoring System ◽  
Real Gas Equations ◽  
Shore Platforms

This paper presents the design and features of a Condition Monitoring System (CMS) suitable for process plants, off-shore platforms, pipeline compressor stations and other facilities. The system uses advanced computer technologies such as client/server computer networks and satellite data transmission to achieve its objectives. Diagnostic windows can display condition monitoring data from any process component and on any PC connected to the network. Systems with these features are currently installed on off-shore platforms, chemical plants, and other industrial complexes. The design and features of the CMS are explained by using an off-shore oil platform that consists of sixteen machine trains. To show the system’s analysis capability, the performance analysis of a natural gas compressor which uses real-gas equations is detailed. Useful CMS design features such as exhaust gas temperature distribution analysis, turbine load distribution charts, trending and “what-if” calculation procedures are also explained.

U.S. Navy, LM2500 Gas Turbine Condition Monitoring Development Experience

1980 ◽  
Author(s):  
M. G. Kandl ◽  
D. A. Groghan
Keyword(s):  
Gas Turbine ◽  
Monitoring System ◽  
Condition Monitoring ◽  
Development Program ◽  
Turbine Engines ◽  
Gas Turbine Engines ◽  
Marine Application ◽  
Development Experience ◽  
Condition Monitoring System ◽  
The Impact

A review of U.S. Navy experience in the development of a shipboard gas turbine condition monitoring system (CMS) is presented. The system considered was developed for use with the 20,000 HP General Electric, LM2500 main propulsion gas turbine engines used on the Navy’s DD-963 class destroyers and FFG-7 patrol frigate class ships. The initial CMS development program started with a broad range of measured gas turbine parameters and was successively reduced to a simpler system using only selected parameters useful for the marine application. A land-based test as well as an at-sea test is presented, together with a discussion of the impact such a system would have on DD 963 class engine removals.

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