基于SSWPT的转子油膜失稳故障分析  

Fault Analysis of Rotor Oil Film Instability Based on Synchrosqueezed Wave Packet Transform

作　　者：唐贵基[1] 徐振丽 TANG Guiji;XU Zhenli(Hebei Key Laboratory of Electric Machinery Health Maintenance&Failure Prevention,North China Electric Power University,Baoding 071003,Hebei Province,China)

机构地区：[1]华北电力大学河北省电力机械装备健康维护与失效预防重点实验室,河北保定071003

出　　处：《动力工程学报》2021年第5期387-393,共7页Journal of Chinese Society of Power Engineering

基　　金：河北省自然科学基金资助项目(E2020502031)。

摘　　要：针对已有的时频分析方法在转子非平稳特征提取方面的不足,提出采用同步压缩小波包变换(SSWPT)方法进行转子油膜失稳故障分析。首先将采集的振动信号进行小波包变换得到小波包变换系数,然后求取信号的瞬时频率,最后对小波包变换系数沿信号瞬时频率方向进行压缩,从而将各频率成分清晰呈现于时频图中。分别利用仿真、实验信号及油膜涡动现场故障数据对该方法进行了验证,并与希尔伯特黄变换(Hilbert-Huang Transform, HHT)时频分析方法进行了对比。结果表明:该方法能够成功提取转子油膜失稳故障特征频率,体现了其在转子油膜失稳故障诊断中的优越性。Aiming at the shortcomings of the existing time-frequency analysis methods in rotor non-stationary feature extraction, synchrosqueezed wave packet transform(SSWPT) was introduced to analyse the fault of rotor oil film instability. Firstly, the signal of vibration was transformed into wavelet packet transform coefficients and then the instantaneous frequency of signal was obtained. Finally, the coefficients of wavelet packet transform were compressed along the instantaneous frequency direction so that the frequency components were clearly presented in time-frequency diagram. Simulated signals, experimental signals and field fault data of oil film whirl were used to verify the method, which was compared with Hilbert-Huang transform(HHT). Results show that the proposed method can successfully extract the characteristic frequency of rotor oil film instability fault, reflecting its superiority in rotor oil film instability fault diagnosis.

关 键 词：转子 油膜失稳 故障诊断 同步压缩小波包变换 现场数据 

分 类 号：TH133[机械工程—机械制造及自动化]