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| Integrated condition monitoring and fault diagnosis technology for wind turbine drive-train |
| REN Yan1,2*, ZHANG Kai3 |
| 1. School of Electric Power, North China Institute of Water Conservancy and Hydroelectric University, Zhengzhou, Henan 450045, China; 2. Hunan Provincial Key Laboratory of Renewable Energy Electric-Technology, Changsha University of Science & Technology, Changsha, Hunan, 410114, China; 3.Agricultural Science and Technology Exhibition Center of Henan Province, Zhengzhou, Henan 450002, China |
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Abstract To monitor and diagnose structure and operation process of wind turbine drive-train, a single physical simulation or single empirical method is unable to achieve condition monitoring and fault diagnosis of the entire operation. In the paper, these two methods were combined together. A wind turbine drive-train online condition monitoring system was used to conduct data acquiring and pre-process. FFT, FNN and expert system were adopted to carry out diagnosis of various faults, and decision fusion technology was used to optimize the diagnosed results. As a result, an integrated online condition monitoring and fault diagnosis system was built for the wind turbine drive-train. The system was combined with CMS and SCADA to carry out condition monitoring and fault diagnosis for wind turbines. Based on this system, the fault diagnosis of main shaft bearings of a wind turbine in a wind farm was performed, and the vibration amplitude, failure time, fault location and fault degree were analyzed. According to the diagnosed results, the expert advices were provided. The system is very versatile, adaptable, fault-tolerant and easy to implement. Additionally, the system has improved the capabilities of analysis, reasoning, optimization and remote diagnostic, and a higher level of intelligence has been achieved.
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Received: 03 June 2016
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