Open-circuit fault diagnosis method of inverter in wind turbine yaw system based on GADF image coding

• Published in: Computers & electrical engineering 2024-07, Vol.117, p.109252, Article 109252
• Main Authors: Hu, Yaogang, Luo, Pengwen, Liu, Huaisheng, Shi, Pingping, Jiang, Neng, Deng, Qinhan, Liu, Shunqiang, Zhou, Jingsen, Han, Huali
• Format: Article
• Language: English
• Subjects: Convolution neural network; Gram angle field; Inverter; Open-circuit fault; Wind turbine; Yaw system
• ISSN: 0045-7906; 1879-0755
• DOI: 10.1016/j.compeleceng.2024.109252

Considering the concealment of inverter open-circuit faults in yaw system of wind turbines, a method for diagnosing open-circuit fault of yaw system inverter is proposed based on Gramian Angular Difference Field (GADF) image coding in this article. Firstly, the current vector phase in the vicinity of relatively high yaw speed is collected as monitoring data. Secondly, considering the insufficient fault feature extraction ability of Convolutional Neural Network (CNN) structures with single dimensional data input during model training, the one-dimensional current vector phase is encoded into two-dimensional image by GADF image coding and an effective CNN fault diagnosis model is obtained with fewer fault samples. Finally, by comparing with actual monitoring data of wind turbine, the effectiveness of yaw system simulation model is verified. The proposed method can achieve identification and localization of open-circuit fault for single and two power devices, which is found to have better anti-noise interference effect and the results are not affected by yaw angle and mechanical torque. It is approved that the proposed method is effective with a simulation on the RT-LAB platform.