Identification Method for Nonlinear Dynamic Models of Gas Turbine Engines on Acceleration Mode

Lyantsev, O. D.; Kazantsev, A. V.; Abdulnagimov, Ansaf

doi:10.1016/j.proeng.2017.02.339

Cited by 9 publications

(3 citation statements)

References 4 publications

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“…the universal error characteristic in dimensionless coordinates is (22) Similarly, using (20), we get an expression for the estimation error because of the error in the gain setting: the function graph is shown in Fig. 6.…”

Section: Analysis Of the Total Error In The Engine Time Constant Esti...mentioning

confidence: 99%

“…Many works that are previously carried out [13][14][15][16][17][18] investigate such a model and propose algorithms for estimating model coefficients. researches of various authors [6,11,12,[19][20][21][22] propose approaches towards dynamic model corrections. but for their engineering realisation in automatic mode, the accuracy of the adaptive model has to be under control.…”

Section: Introductionmentioning

confidence: 99%

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Development of Turboshaft Engine Adaptive Dynamic Model: Analysis of Estimation Errors

Yepifanov

Bondarenko

2022

Transactions on Aerospace Research

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One of the most perspective directions of aircraft engine development is related to implementing adaptive automatic electronic control systems (ACS). The significant elements of these systems are algorithms of matching of mathematical models to actual performances of the engine. These adaptive models are used directly in control algorithms and are a combination of static and dynamic sub-models. This work considers the dynamic sub-models formation using the Least Square method (LSM) on a base of the engine parameters that are measured in-flight. While implementing this function in the (ACS), the problem of checking the sufficiency of the used information for ensuring the required precision of the model arises. We must do this checking a priori (to determine a set of operation modes, the shape of the engine test impact and volume of recorded information) and a posteriori. Equations of the engine models are considered. Relations are derived that determine the precision of parameters of these models’ estimation depending on the precision of measurement, the composition of the engine power ratings, and durability of observations, at a stepwise change of fuel flow. We present these relations in non-dimensional coordinates that make them universal and ready for application to any turboshaft engine.

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Section: Analysis Of the Total Error In The Engine Time Constant Esti...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Development of Turboshaft Engine Adaptive Dynamic Model: Analysis of Estimation Errors

Yepifanov

Bondarenko

2022

Transactions on Aerospace Research

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show abstract

“…The intended purpose of this research was to observe the effect of VIGV angle modulation on the load change transient, i.e., load increase (acceleration) and load decrease (deceleration), and incorporation of VIGVs resulted in increased surge margin during load increase phase. Lyantsev et al [ 92 ] have studied the acceleration process of a turbojet engine to implicate a new system identification technique for the fast countable automatic control system of dynamic behavior of the gas turbine. The novelty in the work was to determine an acceleration parameter using a numerical optimization method to simulate an accurate acceleration mode using experimental data.…”

Section: Classifications Of Transient Regimes In Igtmentioning

confidence: 99%

Transient Behavior in Variable Geometry Industrial Gas Turbines: A Comprehensive Overview of Pertinent Modeling Techniques

Hashmi

Lemma

Ahsan

et al. 2021

Entropy

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Generally, industrial gas turbines (IGT) face transient behavior during start-up, load change, shutdown and variations in ambient conditions. These transient conditions shift engine thermal equilibrium from one steady state to another steady state. In turn, various aero-thermal and mechanical stresses are developed that are adverse for engine’s reliability, availability, and overall health. The transient behavior needs to be accurately predicted since it is highly related to low cycle fatigue and early failures, especially in the hot regions of the gas turbine. In the present paper, several critical aspects related to transient behavior and its modeling are reviewed and studied from the point of view of identifying potential research gaps within the context of fault detection and diagnostics (FDD) under dynamic conditions. Among the considered topics are, (i) general transient regimes and pertinent model formulation techniques, (ii) control mechanism for part-load operation, (iii) developing a database of variable geometry inlet guide vanes (VIGVs) and variable bleed valves (VBVs) schedules along with selection framework, and (iv) data compilation of shaft’s polar moment of inertia for different types of engine’s configurations. This comprehensive literature document, considering all the aspects of transient behavior and its associated modeling techniques will serve as an anchor point for the future researchers, gas turbine operators and design engineers for effective prognostics, FDD and predictive condition monitoring for variable geometry IGT.

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Nonlinear effects of induced unbalance in the rod fastening rotor-bearing system considering nonlinear contact

Wang

Jin

et al. 2019

Arch Appl Mech

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Identification Method for Nonlinear Dynamic Models of Gas Turbine Engines on Acceleration Mode

Cited by 9 publications

References 4 publications

Development of Turboshaft Engine Adaptive Dynamic Model: Analysis of Estimation Errors

Development of Turboshaft Engine Adaptive Dynamic Model: Analysis of Estimation Errors

Transient Behavior in Variable Geometry Industrial Gas Turbines: A Comprehensive Overview of Pertinent Modeling Techniques

Nonlinear effects of induced unbalance in the rod fastening rotor-bearing system considering nonlinear contact

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