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基于SSD和Teager能量算子的滚动轴承故障诊断方法
供稿: 唐贵基;李楠楠;王晓龙;李琛 时间: 2020-07-10 次数:

唐贵基, 李楠楠, 王晓龙,.基于SSDTeager能量算子的滚动轴承故障诊断方法[J].河南理工大学学报(自然科学版),2020,39(4):82-87.

TANG G J, LI N N, WANG X L, et al.Rolling bearing fault diagnosis method based on SSD and Teager energy operator[J].Journal of Henan Polytechnic University(Natural Science) ,2020,39(4):82-87.

基于SSDTeager能量算子的滚动轴承故障诊断方法

唐贵基1, 李楠楠1, 王晓龙1, 李琛2

1.华北电力大学机械工程系,河北 保定 0710032.西安热工研究院,陕西 西安 710000

摘要:针对滚动轴承早期故障冲击信号较难提取的问题,提出基于奇异谱分解(singular spectrum decompositionSSD)和Teager能量算子的滚动轴承故障诊断方法。首先,利用SSD分解振动信号得到一组不同频带分布的奇异谱分量(singular spectrum componentSSC);其次,根据峭度准则选取最佳SSC分量,利用Teager能量算子计算该分量的瞬时能量信号并对其进行傅里叶分析,从而得到信号的Teager能量谱;最后,根据能量谱图提取故障特征频率。将该方法运用到仿真信号和滚动轴承实测信号中,并和包络谱、EMDEEMD方法进行对比分析,结果表明,该方法能有效解调故障特征信息,准确识别轴承故障类型,诊断效果更佳。

关键词:奇异谱分解;Teager能量算子;故障诊断;动轴承

doi:10.16186/j.cnki.1673-9787.2020.4.11

基金项目:中央高校基本科研业务费专项资金资助项目(2018MS1242017MS190);河北省自然科学基金资助项目(E2019502047

收稿日期:2020/01/04

修回日期:2020/02/12

出版日期:2020/07/15

Rolling bearing fault diagnosis method based on SSD and Teager energy operator

TANG Guiji1, LI Nannan1, WANG Xiaolong1, LI Chen2

1.Department of Mechanical Engineering North China Electric Power University Baoding  071003 Hebei China2.Xi’an Thermal Power Research Institute Xi’an  710000 Shaanxi China

Abstract:Aiming at the problem that the early fault shock signals of rolling bearings are difficult to extracta fault diagnosis method based on singular spectrum decomposition SSD and Teager energy operator was proposed. FirstlySSD was used to decompose the fault signal into a set of singular spectrum components SSCof different frequency bands. Then the optimal SSC component was selected according to the Kurtosis criterionand the Teager energy operator was used to calculate the instantaneous energy signal of the component and Fourier analysis was performed to obtain the Teager energy spectrum of the signal. Finallythe fault characteristic frequency was extracted according to the energy spectrum. The proposed method was applied in simulated signals and rolling bearing measured signals and compared with the envelope spectrumEMD and EEMD methods. The results showed that the proposed method could effectively demodulate the fault feature informationaccurately identify the bearing fault typeand the diagnostic effect was better.

Key words:singular spectrum decomposition;Teager energy operator;fault diagnosis;rolling bearing

  基于SSD和Teager能量算子的滚动轴承故障诊断方法_唐贵基.pdf

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