Research on fault diagnosis and health monitoring of wind power equipment

Jianhua Chen

doi:10.1117/12.2684942

19 October 2023 Research on fault diagnosis and health monitoring of wind power equipment

Jianhua Chen

Proceedings Volume 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023); 127095H (2023) https://doi.org/10.1117/12.2684942
Event: Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 2023, Nanjing, China

Abstract

In recent years, China's wind power has developed rapidly and a large number of wind turbines have been put into operation. Wind turbine collapse tower accidents occur from time to time. In this paper, through a wind turbine collapsing tower accident, the causes of the collapsing tower accident are analyzed from the perspectives of unit design, operation and maintenance management, and quality control by using simulation, performance test, organization analysis and other test methods. The main cause of the inverted tower accident was the overspeed flyer in operation, and the deficiency of the unit design did not eliminate the accident from the source. During operation and maintenance, the irregular operation of personnel is another important cause of the accident. This paper analyzes the possible causes of inverted towers, which helps to reduce the occurrence of such accidents, and makes suggestions to avoid such accidents.

Citation Download Citation

Jianhua Chen "Research on fault diagnosis and health monitoring of wind power equipment", Proc. SPIE 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 127095H (19 October 2023); https://doi.org/10.1117/12.2684942

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