Abstract：Aiming at the signal interference problem in fault diagnosis and analysis of submersible pumps, a method of combining local mean decomposition with independent component analysis was proposed. A series of product function components were obtained by decomposing the local mean value of the collected vibration signal, and the cross-correlation coefficient between each component and the vibration signal was calculated. The components with large cross-correlation number were selected to reconstruct and a matrix with the vibration signal was formed. The matrix was processed by fast independent component analysis, and the processed effective data was analyzed by spectrum analysis to get the final spectrum. Through specific experiments, the spectrum diagram of normal operation and fault operation after local mean decomposition and independent component analysis were compared, and the fault analysis and diagnosis were realized. Experimental results showed that the spectrum diagram processed by local mean decomposition and independent component analysis can clearly distinguish the fault characteristic frequency and improve the accuracy of fault diagnosis.
田立勇,张一辙. 基于局部均值分解与快速独立成分分析的潜水泵故障诊断[J]. 计量学报, 2020, 41(5): 585-591.
TIAN Li-yong,ZHANG Yi-zhe. Fault Diagnosis of Submersible Pumps Based on Local Mean Decomposition and Fast Independent Component Analysis. Acta Metrologica Sinica, 2020, 41(5): 585-591.
［1］付云骁, 贾利民, 秦勇, 等. 基于LMD-CM-PCA的滚动轴承 故障诊断方法［J］. 振动、测试与诊断,2017,37(2): 249-401.
Fu Y X, Jia L M, Qin Y, et al. A rolling bearing fault diagnosis method based on lmd-cm-pca［J］. Vibration, testing and diagnosis, 2017, 37(2): 249-401.
［2］马增强, 柳晓云, 张俊甲, 等. VMD和ICA联合降噪方法在轴承故障诊断中的应用［J］. 振动与冲击, 2017, 36(13): 201-207.
Ma Z Q, Liu X Y, Zhang J J, et al. Application of combined noise reduction method of VMD and ICA in bearing fault diagnosis［J］. Vibration and impact, 2017, 36(13): 201-207.
［3］杜冬梅, 张昭, 李红, 等. 基于LMD和增强包络谱的滚动轴承故障分析［J］. 振动、测试与诊断, 2017, 37(1): 92-201.
Du D M, Zhang Z, Li H, et al. Fault analysis of rolling bearings based on LMD and enhanced envelope spectrum［J］. Vibration, testing and diagnosis, 2017, 37(1): 92-201.
［4］郑慧峰, 喻桑桑, 王月兵, 等. 基于经验模态分解和奇异值分解的振动声调制信号分析方法研究［J］. 计量学报, 2016, 37(4): 398-401.
Zheng H F, Yu S S, Wang Y B, et al. Research on the method of vibration tone signal analysis based on empirical mode decomposition and singular value decomposition［J］. Acta Metrologica Sinica, 2016, 37(4): 398-401.
［5］付秀伟, 高兴泉. 基于傅里叶分解与奇异值差分谱的滚动轴承故障诊断方法［J］. 计量学报, 2018, 39(5): 688-692.
Fu X W, Gao X Q. A fault diagnosis method of rolling bearings based on Fourier decomposition and singular value differential spectrum［J］. Acta Metrologica Sinica, 2018, 39(5): 688-692.
［6］刘嘉辉, 董辛旻, 李剑飞. 基于全矢谱时间固有尺度分解和独立分量分析盲源分离降噪的滚动轴承故障特征提取［J］. 中国机械工程, 2018, 29(8): 943-948.
Liu J H, Dong X M, Li J F. The fault features of rolling bearings were extracted based on the proper scale decomposition of the whole vector spectrum and the blind source separation and noise reduction by independent component analysis［J］. China mechanical engineering, 2018, 29(8): 943-948.
［7］张建宇, 孟浩, 胥永刚. 基于信源估计和频域反卷积的滚动轴承故障特征分离与辨识［J］. 中国机械工程, 2017, 28(1): 45-51.
Zhang J Y, Meng H, Xu Y G. Fault feature separation and identification of rolling bearings based on source estimation and frequency deconvolutio［J］. China mechanical engineering, 2017, 28(1): 45-51.
［8］孟宗, 赵东方, 李晶, 等. 基于局部均值分解多尺度模糊熵和灰色相似关联度的滚动轴承故障诊断［J］. 计量学报, 2018, 39(2): 231-236.
Meng Z, Zhang D F, Li J, et al. Fault diagnosis of rolling bearings based on local mean decomposition of multiscale fuzzy entropy and grey similarity correlation［J］. Acta Metrologica Sinica, 2018, 39(2): 231-236.
［9］时培明, 苏晓, 袁丹真, 等. 基于VMD和变尺度多稳随机共振的微弱故障信号提取方法［J］. 计量学报, 2018, 39(4): 515-520.
Shi P M, Su X, Yuan D Z, et al. Weak fault signal extraction method based on VMD and variable-scale multi-stable stochastic resonance［J］. Acta Metrologica Sinica, 2018, 39(4): 515-520.
［10］Han T, Liu X L, Tan A C C. Fault diagnosis of rolling elecment bearings based on Multiscale Dynamic Time Warping［J］. Measurement, 2017, 95: 355-366.
［11］汪朝海,蔡晋辉,曾九孙. 基于经验模态分解和主成分分析的滚动轴承故障诊断研究［J］. 计量学报, 2019, 40(6): 1077-1082.
Wang Z H, Cai J H, Zeng J S. Research on Fault Diagnosis of Rolling Bearing Based on Empirical Mode Decomposition and Principal Component Analysis［J］. Acta Metrologica Sinica, 2019, 40(6): 1077-1082.
［12］Aapo Hyvrinen,等. 独立成分分析［M］. 周宗潭,等译. 北京: 电子工业出版社, 2014: 171-173.
［13］田立勇, 吴境林. 基于Zoom-FFT的排污泵故障诊断与分析［J］. 机械设计与研究, 2018, 34(3): 171-174.
Tian L Y, Wu J L. Fault diagnosis and analysis of blowdown pump based on Zoom-FFT［J］. Mechanical Design and Research, 2018, 34(3): 171-174.
［14］王栋, 丁雪娟. 基于包络解调随机共振和CEEMD的机械早期微弱故障诊断方法研究［J］. 计量学报, 2016, 37(2): 185-190.
Wang D, Ding X J. Study on early mechanical weak fault diagnosis based on envelope demodulation stochastic resonance and CEEMD［J］. Acta Metrologica Sinica, 2016, 37(2):185-190.
2020, Vol. 41 
