摘要
针对时频分析方法在转子油膜失稳诊断方面的不足,提出采用同步压缩小波包变换(synchro-squeezed wave packet transform,简称SSWPT)对汽轮机运行过程中非平稳多分量信号进行连续小波变换,对不同种类信号选取不同主频率小波,得到信号时频图,通过算法可由时频图对原始信号进行重构,并与现有时频方法的精度进行对比。以某电厂1000 MW机组为研究对象,针对调试过程中出现的轴系振动大问题,运用SSWPT方法进行了转子油膜振荡故障诊断分析。利用现场汽轮机诊断管理(turbine diagnosis managment,简称TDM)系统采集数据,进行小波包变换得到小波变换系数,以及故障中非平稳信号的瞬时频率,最后在瞬时频率尺度下对小波包变换系数进行压缩,得到更为准确的频率成分组成。结果表明,该方法对现场非平稳信号的特征提取具有优越性,能够精准判断故障发生的位置和类型,为机组后期故障处理提供可靠依据。
Aiming at the shortcomings of the existing time-frequency analysis methods in the diagnosis of rotor oil film instability faults,synchro-squeezed wave packet transform(SSWPT)is proposed to analyze the nonsmooth multi-component signals during the operation of the steam turbine.By selecting different main frequency wavelets for different kinds of signals,the signal time-frequency graph is obtained,and the original signal can be reconstructed from the time-frequency graph by the algorithm,and the accuracy of the existing time-frequency method is compared.Taking a 1000 MW unit of a power plant as the research object,the rotor oil film oscillation fault diagnosis is carried out by using SSWPT method in view of the major vibration problem of shafting during commissioning.Using the on-site turbine diagnosis managment(TDM)system to collect data and carry out wavelet packet transformation to obtain the wavelet transform coefficient and the instantaneous frequency of non-stationary fault signals.Finally,the wavelet packet transform coefficient is compressed under the instantaneous frequency scale.More accurate frequency components are obtained.The results show that the method is superior to the feature extraction of non-stationary signals,and can accurately judge the location and type of faults,which provides a reliable basis for the unit′s later fault processing.
作者
王涛
张泽
许永伟
张鹏
吕蒙
WANG Tao;ZHANG Ze;XU Yongwei;ZHANG Peng;LÜMeng(North China Electric Power Research Institute Co.,Ltd.Xi′an Branch Xi′an,710000,China;North China Electric Power Research Institute Co.,Ltd.Beijing,100045,China)
出处
《振动．测试与诊断》
EI
CSCD
北大核心
2023年第4期712-716,829,共6页
Journal of Vibration,Measurement & Diagnosis
基金
陕西省重点研发计划资助项目(2023-YBGY-132)。
关键词
轴系振动
故障诊断
非平稳信号
同步压缩小波包变换
频率成分
shaft system vibration
fault diagnosis
non-stationary signal
synchro-squeezed wave packet transform
frequency component
