Fault diagnosis of wind turbine planetary gearbox based on order analysis and divergence index

作者：Chengbing, He^*; Shunkai, Cai; Dakang, Sun; Lei, Song

来源：Journal of Engineering, 2017, 2017(13): 1394-1398.

DOI：10.1049/joe.2017.0560

• Correlation coefficient
• Empirical mode decomposition method
• Fault diagnosis method
• Information modes
• Planetary gearboxes
• Quasi-stationary
• Resampling method
• Vibration signal

Gearbox is one of the key components of wind turbine, whose fault will directly affect the safety and the operation of the overall wind turbine. This study develops a fault diagnosis method of wind turbine planetary gearbox. Using the order resampling method, the original non-stationary time-domain vibration signal is converted into a signal having a smooth angular domain or quasi-stationary characteristics. The angle domain signal is conducted by empirical mode decomposition method. According to correlation coefficient criteria, the information mode function that contains fault feature is selected for signal reconstruction. The reconstructed signal is carried on by spectrum analysis. According to the classification of planetary gearbox, the fault feature parameters are extracted. J-divergence and KL-divergence (Kullback–Leibler divergence) calculated through the fault feature parameters are used to determine the fault location and describe the severity degree of the fault. Results of the experiments have revealed that the proposed method can be effective and accurate to the fault diagnosis of wind turbine planetary gearbox.

• 出版日期2017
• 单位华北电力大学