Fuzzy-neural Approach for Aircraft Gas Turbine Engines Diagnosing

Pashayev, A. M.; Askerov, D.; Sadiqov, R.; Abdullayev, P. S.

doi:10.2514/6.2004-6222

Cited by 10 publications

(11 citation statements)

References 0 publications

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“…This allowance affects the GTE technical condition monitoring reliability and causes of the error decision in the GTE diagnostic and operating process [1][2][3] (Fig.1).Experimental investigation conducted by manual records shows that at the beginning of monitoring during 40÷60 measurements accumulated values of recorded parameters of good working order GTE aren't normal distribution.…”

Section: Abstract-gasmentioning

confidence: 99%

“…If for all training pairs, deviation value Е is less than given then training (correction) parameters of the network comes to end [1][2][3]. In opposite case it continues until value Е reach minimum.…”

Section: Abstract-gasmentioning

confidence: 99%

“…Correction of network parameters for left and right part is carried out as follows: The structure of NN for identification of the equation (1) parameters is given in [1][2][3].…”

Section: Abstract-gasmentioning

confidence: 99%

“…Therefore, it is necessary to note that correct application of fuzzy correlation-regression approach demands the analysis of fuzzy characteristics of GTE work parameters distributions. With this purpose should be carried out fuzzy analysis of distribution character of GTE work parameters on the basis of fuzzy values of skewness and kurtosis coefficients under the following formulas [1][2][3] ( ) ( ) …”

Section: Gte Condition Monitoring By Fuzzy Statistical Analysis mentioning

confidence: 99%

“…In such case on the basis analysis of regression coefficient's values (coefficients of influence) of all engine's multiple regression models with the help of mathematical statistics are formed base and admissible range of coefficients [3,9]. GTE Condition Monitoring using Regression Analysis and Kalman type Filter (Second Stage) is present in [1].…”

Section: Gte Condition Monitoring Using Statistical Analysis and mentioning

confidence: 99%

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Aircraft Gas Turbine Engines’ Technical Condition Identification System

Abdullayev

Pashayev

Askerov

et al. 2005

Volume 1: Turbo Expo 2005

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Abstract-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 non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-bystage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine temperature condition was made.

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Section: Abstract-gasmentioning

confidence: 99%

Section: Abstract-gasmentioning

confidence: 99%

“…Correction of network parameters for left and right part is carried out as follows: The structure of NN for identification of the equation (1) parameters is given in [1][2][3].…”

Section: Abstract-gasmentioning

confidence: 99%

Section: Gte Condition Monitoring By Fuzzy Statistical Analysis mentioning

confidence: 99%

Section: Gte Condition Monitoring Using Statistical Analysis and mentioning

confidence: 99%

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Aircraft Gas Turbine Engines’ Technical Condition Identification System

Abdullayev

Pashayev

Askerov

et al. 2005

Volume 1: Turbo Expo 2005

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Identification and standardization of maneuvers based upon operational flight data

Wang¹,

Jiang²,

Liu³

et al. 2015

Chinese Journal of Aeronautics

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To find a way of loads analysis from operational flight data for advanced aircraft, maneuver identification and standardization jobs are conducted in this paper. For thousands of sorties from one aircraft, after studying the flight attitude when performing actions, the start and end time of the maneuvers can be determined. According to those time points, various types of maneuvers during the flight are extracted in the form of multi-parameters time histories. By analyzing the numerical range and curve shape of those parameters, a characteristic data library is established to model all types of maneuvers. Based on this library, a computer procedure using pattern-recognition theory is programmed to conduct automatic maneuver identification with high accuracy. In that way, operational loads are classified according to maneuver type. For a group of identified maneuvers of the same type, after the processes of time normalization, trace shifting, as well as averaging and smoothing, the idealization standard time history of each maneuver type is established. Finally, the typical load statuses are determined successfully based on standard maneuvers. The proposed method of maneuver identification and standardization is able to derive operational loads effectively, and might be applied to monitoring loads in Individual Aircraft Tracking Program (IATP).

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