scholarly journals Analysis of methods for parametric diagnostics of technical condition of gas turbine units

2019 ◽  
pp. 101-112
Author(s):  
Sergey I. Perevoschikov
Keyword(s):  
Gas Turbine ◽  
Theoretical Basis ◽  
Technical Condition ◽  
Physical Basis ◽  
Methodological Principles

The article is devoted to an analysis of methods, which are proposed for parametric diagnostics of technical condition of gas turbine units. According to the results of the analysis, which consists in checking the error and the physical basis of methods, it is concluded that there are need for the further research in this area by a broader theoretical basis and other methodological principles. The author of the article offers a variant to overcome the disadvantages of the considered methods.

Method of tribodiagnostics of d-30KU engines/KP with the use of a microwave plasma complex: results of metrological examination and analysis of the accuracy

2020 ◽  
pp. 22-29
Author(s):  
A. Bogoyavlenskiy ◽  
A. Bokov
Keyword(s):  
Gas Turbine ◽  
Microwave Plasma ◽  
Technical Condition ◽  
The State ◽  
Turbine Engines ◽  
Metrological Examination ◽  
Gas Turbine Engines ◽  
High Frequency Plasma ◽  
Frequency Plasma ◽  
Primary Standards

The article contains the results of the metrological examination and research of the accuracy indicators of a method for diagnosing aircraft gas turbine engines of the D30KU/KP family using an ultra-high-frequency plasma complex. The results of metrological examination of a complete set of regulatory documents related to the diagnostic methodology, and an analysis of the state of metrological support are provided as well. During the metrological examination, the traceability of a measuring instrument (diagnostics) – an ultrahigh-frequency plasma complex – is evaluated based on the scintillation analyzer SAM-DT-01–2. To achieve that, local verification schemes from the state primary standards of the corresponding types of measurements were built. The implementation of measures to eliminate inconsistencies identified during metrological examination allows to reduce to an acceptable level the metrological risks of adverse situations when carrying out aviation activities in industry and air transportation. In addition, the probability of occurrence of errors of the first and second kind in the technological processes of tribodiagnostics of aviation gas turbine engines is reduced when implementing a method that has passed metrological examination in real practice. At the same time, the error in determining ratings and wear indicators provides acceptable accuracy indicators and sufficient reliability in assessing the technical condition of friction units of the D-30KP/KP2/KU/KU-154 aircraft engines.

Application of neural network expert systems for monitoring, diagnostics and forecasting of technical condition of aircraft engines

2020 ◽  
pp. 51-59
Author(s):  
Д.О. Пушкарёв
Keyword(s):  
Neural Network ◽  
Expert Systems ◽  
Gas Turbine ◽  
Technical Condition ◽  
Turbine Engines ◽  
Gas Turbine Engines ◽  
Fuzzy Interference System ◽  
Interference System ◽  
Monitoring And Diagnostics ◽  
Technical Operation

Рассматривается применение нейросетевых экспертных систем в области контроля, диагностики и прогнозирования технического состояния авиационных ГТД на основе нечеткой логики. Показана методика для решения таких задач в области технической эксплуатации авиационной техники совместно с использованием фаззи-интерференсной системы программы MATLAB. Используя статистические данные о работе двигателя формируется экспертная система на основе нейронной сети позволяющая осуществлять контроль и диагностику ГТД, а также прогнозировать дальнейшее техническое состояния анализируемого двигателя. The application of neural network expert systems in the field of monitoring, diagnostics and forecasting of the technical condition of aviation gas turbine engines based on fuzzy logic is considered. The technique for solving such problems in the field of technical operation of aircraft and using the fuzzy-interference system of the MATLAB program is shown. Using statistical data on the operation of the engine, an expert system is based on the fundamental of a neural network that provide monitoring and diagnostics of gas turbine engines, as well as predicting the further technical condition of the analyzed engine.

CTV: A New Method for Mapping a Full Scale Prototype of an Axial Compressor

1996 ◽  
Author(s):  
Vasco Mezzedimi ◽  
Pierluigi Nava ◽  
Dave Hamilla
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Theoretical Basis ◽  
Axial Compressor ◽  
Heavy Duty ◽  
Test Vehicle ◽  
Testing Method ◽  
Area Reduction ◽  
Speed Range ◽  
Compressor Inlet

The full mapping of a new gas turbine axial compressor at different speeds, IGV settings and pressure ratios (from choking to surge) has been performed utilizing a complete gas turbine with a suitable set of modifications. The main additions and modifications, necessary to transform the turbine into the Compressor Test Vehicle (CTV), are: - Compressor inlet throttling valve addition - Compressor discharge bleed valve addition - Turbine 1st stage nozzle area reduction - Starting engine change (increase in output and speed range). This method has been successfully employed on two different single shaft heavy-duty gas turbines (with a power rating of 11MW and 170 MW respectively). The paper describes the theoretical basis of this testing method and a specific application with the above mentioned 170 MW machine.

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 Flow simulation in air intake system of gas turbine

2021 ◽  
Vol 23 (4) ◽  
pp. 66-83
Author(s):  
V. L. Blinov ◽  
I. S. Zubkov ◽  
Yu. M. Brodov ◽  
B. E. Murmanskij
Keyword(s):  
Numerical Simulation ◽  
Gas Turbine ◽  
Gas Turbines ◽  
Numerical Models ◽  
Flow Simulation ◽  
Technical Condition ◽  
Model Parameters ◽  
Intake System ◽  
Performance Factors ◽  
Air Intake

THE PURPOSE. To study the issues of air intake system’s performance as the part of the gas turbines. To estimate the possibility of modeling different performance factors of air intake systems with numerical simulation methods. To develop the recommendations of setting up the grid and the numerical models for researches in air intake system’s performance and assessing the technical condition of elements of it. METHODS. The main method, which was used during the whole study, is computational fluid dynamics with usage of CAE-systems.RESULTS. During the study the recommendations for setting up the numerical model were developed. Such factors as grid model parameters, roughness scale, pressure drop in elements of air intake system and some more were investigated. The method for heat exchanger’s performance simulation were created for modeling the air temperature raising. CONCLUSION. The air intake system’s performance analysis becomes one of the actual topics for research because of the high demands of gas turbines to air, which is used in its annulus. The main part of these researches is in analysis of dangerous regimes of work (e.g. the icing process of annulus elements) or in assessing technical condition of air intake systems and its influence to the gas turbine as a whole. The developed method of numerical simulation allows to get the adequate results with low requirements for computational resources. Also this method allows to model the heat exchanger performance and study its defects’ influence to the performance of air intake system as a whole. 

Identification Technique of Aircraft Gas Turbine Engine’s Health

Volume 3 ◽  
2004 ◽  
Author(s):  
A. M. Pashayev ◽  
D. D. Askerov ◽  
R. A. Sadiqov ◽  
P. S. Abdullayev
Keyword(s):  
Gas Turbine ◽  
Least Squares Method ◽  
Early Stage ◽  
Nonlinear Models ◽  
New Technology ◽  
Correlation Coefficients ◽  
Technical Condition ◽  
Recursive Least Squares ◽  
Regression Equations ◽  
Linear And Nonlinear

Groundlessness of probability-statistic methods application is shown, especially at an early stage of the aviation gas turbine engine (GTE) technical condition diagnosing, when the volume of the information has property of the fuzzy, limitation and uncertainty. Hence efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the fuzzy logic and neural networks methods is considered. Training with high accuracy of multiple linear and nonlinear models (the regression equations) received on the statistical fuzzy data basis is made. For models choice is offered the application of the fuzzy correlation analysis results. Dynamics of correlation coefficients changes is considered. At the information sufficiency it 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). As application of the given technique the estimation of the new operating aviation engine D-30KU-154 (aircraft Tu-154M) technical condition was made.

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