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Research on Model-Based Fault Diagnosis for a Gas Turbine Based on Transient Performance

Institute of Engineering Thermophysics, Chinese Academy of Science, Beijing 100190, China
University of Chinese Academy of Sciences, Beijing 100049, China
The Key Laboratory of Power Machinery and Engineering of Education Ministry, Shanghai Jiao Tong University, Shanghai 200240, China
Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
Authors to whom correspondence should be addressed.
Appl. Sci. 2018, 8(1), 148;
Received: 7 November 2017 / Revised: 8 December 2017 / Accepted: 26 December 2017 / Published: 22 January 2018
(This article belongs to the Special Issue Gas Turbine Engine - towards the Future of Power)
PDF [4658 KB, uploaded 22 January 2018]


It is essential to monitor and to diagnose faults in rotating machinery with a high thrust–weight ratio and complex structure for a variety of industrial applications, for which reliable signal measurements are required. However, the measured values consist of the true values of the parameters, the inertia of measurements, random errors and systematic errors. Such signals cannot reflect the true performance state and the health state of rotating machinery accurately. High-quality, steady-state measurements are necessary for most current diagnostic methods. Unfortunately, it is hard to obtain these kinds of measurements for most rotating machinery. Diagnosis based on transient performance is a useful tool that can potentially solve this problem. A model-based fault diagnosis method for gas turbines based on transient performance is proposed in this paper. The fault diagnosis consists of a dynamic simulation model, a diagnostic scheme, and an optimization algorithm. A high-accuracy, nonlinear, dynamic gas turbine model using a modular modeling method is presented that involves thermophysical properties, a component characteristic chart, and system inertial. The startup process is simulated using this model. The consistency between the simulation results and the field operation data shows the validity of the model and the advantages of transient accumulated deviation. In addition, a diagnostic scheme is designed to fulfill this process. Finally, cuckoo search is selected to solve the optimization problem in fault diagnosis. Comparative diagnostic results for a gas turbine before and after washing indicate the improved effectiveness and accuracy of the proposed method of using data from transient processes, compared with traditional methods using data from the steady state. View Full-Text
Keywords: fault diagnosis; gas turbine; transient performance; cuckoo search; modeling and simulation; deterioration fault diagnosis; gas turbine; transient performance; cuckoo search; modeling and simulation; deterioration

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Zeng, D.; Zhou, D.; Tan, C.; Jiang, B. Research on Model-Based Fault Diagnosis for a Gas Turbine Based on Transient Performance. Appl. Sci. 2018, 8, 148.

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