Development of a Real-Time Turbine Engine Diagnostic System

Bickford, R. L.; Malloy, Donald J.; Sverdrup, Jacobs

doi:10.2514/6.2002-4306

Cited by 12 publications

(7 citation statements)

References 1 publication

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“…Since the 1970s, the United States has developed various LRE fault detection and diagnosis systems, which are widely used in the Space Shuttle Main Engine (SSME) [3,18], mainly including the red line parameter system (Redline), Anomaly and Failure Detection System (System for Anomaly and Failure Detection, SAFD) [19], Rocket Engine Health Management System [20], Health Management System for Rocket Engine (HMSRE), Integrated Vehicle Health Management System (IVHMS), Real-Time Turbine Engine Diagnostic System (RTTEDS) [21], Real-Time Vibration Monitoring System(RTVMS) [22], Post-Test Diagnostic System (PTDS), Health Monitoring System (HMS) [23], Intelligent Integrated Vehicle Management System (IIVMS), etc. [2,24,25].…”

Section: Development History Of Liquid Rocket Engine Diagnostic Systemmentioning

confidence: 99%

Research and Development of Fault Diagnosis Methods for Liquid Rocket Engines

Wang

Ding

2022

Aerospace

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Currently, considerable efforts are being focused on the development of reusable rockets and smart rockets due to the heavy requirements of future next-generation aerospace transportation. Safety, low-launching cost, and repeatability are expected from liquid rocket for fulfilling the big dreams of space transportation, exploration, and travelling. Therefore, research on fault detection of the liquid rocket engines (LRE) is critical for satisfying the above claims. Therefore, a comprehensive survey on the research and development of fault diagnosis systems and methods for the liquid rocket engines is presented. First, development history of liquid rocket engine diagnostic systems is reviewed thoroughly. Then three broad headings of the fault detection approaches of liquid rocket engines are divided through the summary and analysis of the existing methods, including approaches using signal processing, model-driven approach, and approach using artificial intelligence (AI). Then the paper discusses the concrete algorithms according to the classification features of the algorithms. In the end, the future developments of the fault detection approaches are presented, which will mainly pay attention to the reusability and intelligence of the rockets.

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Section: Development History Of Liquid Rocket Engine Diagnostic Systemmentioning

confidence: 99%

Research and Development of Fault Diagnosis Methods for Liquid Rocket Engines

Wang

Ding

2022

Aerospace

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“…The elements of U are assumed to be mutually exclusive. 2 U denotes the power set of U, then U=(a 1 ,a 2 ,a 3 ,…,a n ); 2 U ={{Φ}，{a 1 }，…，{a n }，{a 1 ，a 2 }，{a 1 ，a 3 }…，{a 1 ，a n }，…，{a n-1 ，a n }，{a 1…”

Section: D-s Evidence Theorymentioning

confidence: 99%

“…Aero-engine, as the power device for the aircraft, its stability and reliability will directly affect the safety of flight. Therefore, in order to find the aero-engine fault quickly and accurately, several sensors were installed in multiple parts of engine for signal acquisition [1]. However, when multiple sensors support the same functions, data fusion for these sensors is needed to find out fault feature, improve the certainty and reliability of information and realize the engine fault diagnosis.…”

Section: Introductionmentioning

confidence: 99%

Research on Diagnosis Data Fusion of Aero-engine based on Improved K-means Cluster and D-S Evidence Theory

Zhang¹,

Liu²

2015

Proceedings of the 2015 International Industrial Informatics and Computer Engineering Conference

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The data fusion method combined improved K-means clustering algorithm with D-S evidence theory was used for vibration fault data fusion of aero-engine in this paper. The later calculated amount was reduced by the improved K-means clustering algorithm. On the basis of the improved K-means clustering algorithm, the basic belief function of vibration data was determined. D-S evidence theory was used for fusion of fault vibration data of aero-engine which had been processed through the improved K-means clustering analysis. The results of diagnostic instance show that the method can improve the diagnosis rates of aero-engine fault effectively.

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“…Propulsion performance diagnostics and optimization (PPDO) is a key technology of vehicle management systems, which plays a crucial role in increasing thrust, improving fuel efficiency, and prolonging engine life. Over the last several decades, extensive researches have been carried out for the development of PPDO [1][2][3][4][5][6][7][8][9][10][11]. Current researches usually focus on two aspects.…”

Section: Introductionmentioning

confidence: 99%

Propulsion performance diagnostics and optimization based on the estimation of measurement biases and hybrid optimization

Zhang

Tang

Shen

et al. 2011

Proceedings of the Institution of Mechanical Engineers, Part G:

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This article deals with performance diagnostics and optimization of aircraft propulsion systems. To eliminate the adverse effects of unknown measurement biases on performance diagnostics, a new design approach based on measurement biases estimation is proposed. In this approach, measurement biases and the component deviation parameters (CDPs) are treated as a part of the augmented state vector, and multiple Kalman filters are designed based on different biases hypotheses to estimate the augmented states. Through the estimated measurement biases, the effects of actual biases are eliminated and accurate performance diagnostics is achieved. Moreover, considering the synthesis influence of linearization errors and initial values on the conventional linear programming (LP) method, a hybrid optimization algorithm based on LP and sequential quadratic programming (SQP) is investigated to improve the optimization accuracy and convergence speed. This algorithm uses a parallel subregion LP method to obtain the global feasible initial value, and then utilizes the SQP algorithm to search for the optimal solution. Simulations are carried out at cruise-operating conditions. The results demonstrate that the CDPs are estimated accurately, and the propulsion performance and online optimization ability are also improved.

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Development of a Real-Time Turbine Engine Diagnostic System

Cited by 12 publications

References 1 publication

Research and Development of Fault Diagnosis Methods for Liquid Rocket Engines

Research and Development of Fault Diagnosis Methods for Liquid Rocket Engines

Research on Diagnosis Data Fusion of Aero-engine based on Improved K-means Cluster and D-S Evidence Theory

Propulsion performance diagnostics and optimization based on the estimation of measurement biases and hybrid optimization

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