Helicopter gas turbine engine performance analysis: A multivariable approach

Arush, Ilan; Pavel, Marilena D.

doi:10.1177/0954410017741329

Cited by 3 publications

(10 citation statements)

References 5 publications

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“…The main advantages to analyzing data using MPOC models over the single-variable method are: (1) it gives the ability to determine the relative influence of one or more predictor variables to the criterion value; (2) it has the ability to identify outliers, or anomalies; and (3) it gives a superior estimation precision. As demonstrated in Arush and Pavel, 8 MPOC could provide a more accurate engine power estimation (in some cases of more than 300% when compared to the single-variable method). However, the main weakness of the MPOC method is that it struggles with a large number of possible multivariable polynomials (more exactly 512 polynomials) to choose from and there are no guidelines herein.…”

Section: Introductionmentioning

confidence: 95%

“…Such a multivariable approach applied to engine analysis results in a more accurate and realistic available power prediction as it contains the intrinsic couplings between all engine variables. Reference Arush and Pavel 8 demonstrates that the empirical model for the engine output power (equation (4)) should rely on a basic model, superimposed with any possible combination of nine regressors (f 1 –f 9 ) as listed in Table 2. The basic model, referred to as model 1 and denoted hereinafter as CSHP M(1) , is a third-order multivariable polynomial in all engine variables given as equation (5).…”

Section: Helicopter Gas-turbine Engine Flight-testingmentioning

confidence: 99%

“…A practical method to solve for the best-fit coefficient, based on linear concept known as projection onto subspaces, is thoroughly described in Strang 9 and demonstrated in Arush and Pavel. 8 The best-fit solution obtained for any candidate polynomial model can be used to evaluate how precisely this model predicts the actual measured flight-test data. The corrected engine power (CSHP) is estimated by substituting the measured independent variables in the model, i.e.…”

Section: Helicopter Gas-turbine Engine Flight-testingmentioning

confidence: 99%

“…A comprehensive demonstration of the poor estimation using the single-variable method was is presented in Arush and Pavel. 8…”

Section: Introductionmentioning

confidence: 99%

“…A novel method to estimate the maximum output power of a helicopter gas turbine engine more accurately and under a wider range of atmospheric conditions was proposed in Arush and Pavel. 8 This method involves the analysis of the flight test data in terms of referred parameters through a so-called “Multivariable Polynomial Optimization under Constraints” (MPOC). The main advantages to analyzing data using MPOC models over the single-variable method are: (1) it gives the ability to determine the relative influence of one or more predictor variables to the criterion value; (2) it has the ability to identify outliers, or anomalies; and (3) it gives a superior estimation precision.…”

Section: Introductionmentioning

confidence: 99%

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A singular values approach in helicopter gas turbine engines flight testing analysis

Arush

Pavel

Mulder

2020

Proceedings of the Institution of Mechanical Engineers, Part G:

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The process of empirical models evaluation is at the core business of experimental flight-testing data analysis. Accurate and convenient flight-testing of helicopter engine(s) available power is crucial for predicting the total helicopter performance. Common practice in estimation of in-flight helicopter gas turbine engine power consists of a reduction of flight-test data into simplistic single-variable analysis approach. While such an approach is convenient for practical use, it often results in unrealistic predictions of the available engine(s) power. A novel approach for the helicopter available power problem is the so-called Multivariable Polynomial Optimization under Constraints method. In this method, 18 regressors, constructed from the engine non-dimensional parameters, are used to define empirical polynomial models. This paper is intended to complement the Multivariable Polynomial Optimization under Constraints method and answer the question of which multivariable polynomial can be generally used in representing helicopter gas-turbine engine performance? In this sense, a variety of seven gas-turbine engines installed on different helicopters are analyzed, each one giving 512 possible polynomial models to be used for available-power calculations. While conventional statistical methods of hypothesis-testing failed in providing the answer to the question stated above of which the best general empirical model for representing engine performance is, an alternative approach based on the Singular-Value-Decomposition theorem, was proven successful in providing the answer. Moreover, this approach presented in the paper yielded a short list of 10 simple and convenient multivariable polynomials, best representing the performance of all seven engines analyzed as a group.

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Section: Introductionmentioning

confidence: 95%

Section: Helicopter Gas-turbine Engine Flight-testingmentioning

confidence: 99%

Section: Helicopter Gas-turbine Engine Flight-testingmentioning

confidence: 99%

“…A comprehensive demonstration of the poor estimation using the single-variable method was is presented in Arush and Pavel. 8…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A singular values approach in helicopter gas turbine engines flight testing analysis

Arush

Pavel

Mulder

2020

Proceedings of the Institution of Mechanical Engineers, Part G:

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A dimensionality reduction approach in helicopter level flight performance testing

2023

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Evaluation of the power required in level flight is essential to any new or modified helicopter performance flight-testing effort. The conventional flight-test method is based on an overly simplification of the induced and profile power components required for a helicopter in level flight. This simplistic approach incorporates several drawbacks that not only make execution of flight sorties inefficient and time consuming, but also compromise the level of accuracy achieved. This paper proposes an alternative flight-test method for evaluating the level-flight performance of a conventional helicopter while addressing and rectifying all identified deficiencies of the conventional method. The proposed method, referred to as the corrected-variables screening using dimensionality reduction (CVSDR), uses an original list of 36 corrected variables derived from basic dimensional analysis principles. This list of 36 corrected variables is reduced using tools of dimensionality reduction to keep only the most effective level-flight predictors. The CVSDR method is demonstrated and tested in this paper using flight-test data from a MBB BO-105 helicopter. It is shown that the CVSDR method predicts the power required for level flight about 21% more accurately than the conventional method while reducing the required flight time by an estimate of at least 60%. Unlike the conventional method, the CVSDR is not bounded by the high-speed approximation associated with the induced power estimation, therefore it is also relevant to the low airspeed regime. This low-airspeed relevancy allows the CVSDR method to bridge between the level-flight regime and the hover. Although demonstrated in this paper for a specific type of helicopter, the CVSDR method is applicable for level-flight performance flight testing of any type of conventional helicopter.

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Control Programs of the Aviation Gas Turbine Engine in the Modes of Acceleration, Gas Reset, Start-up. Optimization and Estimation of the Quality of Control Programs

Tovkach

2022

ECS

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The article is devoted to the formation of requirements for the accuracy of regulation of an aviation gas turbine engine, one of which is the maintenance of engine thrust at a given operating mode, regardless of the engine condition, within the gas temperature margin. Its value should not be significantly affected by turning on or off additional power and air consumers, as well as various regulatory influences on the part of the automatic control system (turning on or turning off the bypass in the compressor and blowing the housings, partial restriction of the supply of cooled air, changing the position of the guiding devices). Fulfilling the requirements for the accuracy of regulation is important for ensuring the reliability and safety of the operation of the power plant and the convenience of controlling the aircraft. In order to reduce operating costs, it is necessary that during operation, a minimum number of additional settings of the ACS in the acceleration mode, gas reset and start-up mode are required. The control program is implemented in the form of a automatic control system (ACS), which is a closed circuit of the main feedback. There is also a flexible local feedback loop in the circuit, which is designed to stabilize the ACS, which contributes to the fact that the ACS is quite stable. The presence of feedback in the ACS indicates that the system may be unstable, so the analysis of the ACS should include an assessment of its stability and, if necessary, the selection of measures and means for its stabilization. Changing the input signal at the first moment of time leads to a corresponding increase in deviation, since the links in front of the object and the object itself have inertia and therefore the rotation frequency cannot change instantly. The change in deviation, being an amplified amplifier, thyristor converter and generator, taking into account their inertia, leads to a gradual change in the control value, the voltage on the anchor, which smoothly changes the frequency of rotation of the shaft so that the tracking error, that is, the deviation, is directed to zero. Voltage feedback stabilizes the ACS and increases its speed. This is how tracking is done. The implementation of wireless technologies in the ACS of the gas station has been studied, which will allow to reduce the mass and dimensions of the nodes due to the reduction of the number of connectors and cables, increase the reliability and accuracy of the adjustment of the ACS, reduce maintenance costs and increase fire safety.

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Helicopter gas turbine engine performance analysis: A multivariable approach

Cited by 3 publications

References 5 publications

A singular values approach in helicopter gas turbine engines flight testing analysis

A singular values approach in helicopter gas turbine engines flight testing analysis

A dimensionality reduction approach in helicopter level flight performance testing

Control Programs of the Aviation Gas Turbine Engine in the Modes of Acceleration, Gas Reset, Start-up. Optimization and Estimation of the Quality of Control Programs

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