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2024.07.19
Invited Speech:Research on Method of Gas Turbine Modeling and Fault Diagnosis
Industrial gas turbines, as core equipment for efficient and clean utilization of energy, have been widespread applied in gas-steam combined cycle power plants. To ensure safe, stable, green and efficient operation, it is essential to establish a reliable industrial gas turbine fault diagnosis system. Industrial gas turbines need more flexible operation, due to requirements for power plant frequent frequency regulation and peak regulation in grid-supported mode. It is difficult to filter out quasi-steady-state operation data segment from collected operating data of industrial gas turbine, which makes the applicable boundary of traditional diagnostic methods narrower. For the actual problems to be solved urgently during diagnosis of industrial gas turbines, this topic proposes an improved performance diagnostic method for industrial gas turbines. First, a high-precision thermodynamic modeling method for industrial gas turbines was proposed with consideration of the effect of variable geometry compressor, and the established gas turbine thermodynamic model is validated by actual industrial gas turbine operation data. Next, an improved performance diagnostic method is established, and the health parameters for intake system and exhaust system is proposed in fault diagnosis for the first time and compressor variable geometry is also considered in the diagnostic process. Finally, through actual industrial gas turbine operation test, the effectiveness and reliability of the proposed diagnostic method to diagnose component performance degradation and component abrupt performance damage are verified. The proposed diagnostic method realizes real-time online quantitative diagnosis of all gas-path components under full operating conditions from the minimum IGV opening load to the IGV fully open base load.
日時 |
7月24日(水)16:00~18:00 |
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会場 |
神奈川大学 横浜キャンパス3号館 305号室 |
申込方法 |
聴講無料で、会場は出入自由のため、お気軽にご参加ください。 |
Dr. Yulong Ying received the B.S. degree in power and energy engineering, the M.S. degree in power machinery and engineering, and the Ph.D. degree in marine engine engineering from the Harbin Engineering University, Harbin, China, in 2010, 2013, and 2016, respectively. From 2013 to 2016, he was an Engineer and Researcher with Shanghai Electric Gas Turbine Co., Ltd. He is currently an Associate Professor with the School of Energy and Mechanical Engineering, Shanghai University of Electric Power, Shanghai, China. He is the research leader of Simulation & Mathematics (SimMaths) Lab and an EAI Senior Member. He has published more than 60 research papers and 3 academic books on his research topics. His research interests include the fields of thermodynamics, control system, signal feature extraction and pattern recognition, and power machine fault diagnosis and prognosis.