噪声与振动控制Issue(2)：154-159,6.DOI:10.3969/j.issn.1006-1335.2015.02.035
基于小波包和BP神经网络的风机齿轮箱故障诊断
Fault Diagnosis of Wind Turbine Gearbox Based on Wavelet Packet and Back Propagation Neural Network
摘要
Abstract
Gearbox is the core component of wind turbine, but it can be faulted easily. In order to monitor the gearbox, a fault diagnosis method based on wavelet packet transform and Back Propagation (BP) neural network was put forward. Firstly, the vibration signals of the gearbox were denoised, decomposed and reconstructed according to their characteristics using wavelet packet transform. Then, the fault features of the different frequency band energy were effectively extracted. Fi-nally, the fault energy features extracted were put into BP neural network diagnosis system to recognize the fault types. The system can implement intelligent fault diagnosis. The experiment demonstrated the efficiency of this method.关键词
振动与波/风机齿轮箱/小波包变换/BP神经网络/故障诊断Key words
vibration and wave/wind turbine gearbox/wavelet packet transform/BP neural network/fault diagnosis分类
信息技术与安全科学引用本文复制引用
王皓,周峰..基于小波包和BP神经网络的风机齿轮箱故障诊断[J].噪声与振动控制,2015,(2):154-159,6.基金项目
国家自然科学基金 （）
