基于形态非抽样融合与DCT高阶奇异熵的液压泵退化特征提取

PDF(2557 KB)

振动与冲击 ›› 2015, Vol. 34 ›› Issue (22) : 54-61.

论文

孙健，李洪儒，王卫国，许葆华

作者信息 +

Degradation Fault Feature Extraction of Hydraulic Pump Based on Morphological Undecimated Decomposition

Sun Jian Li Hongru WANG Weiguo Xu Baohua

Author information +

文章历史 +

摘要

针对轴向柱塞式液压泵性能退化过程中振动信号非线性强、退化特征提取困难等问题，提出一种基于形态非抽样融合与DCT高阶奇异熵的退化特征提取方法。首先，在形态非抽样的一般框架下，提出了形态非抽样小波融合方法，通过构建特征能量因子对各分解层近似信号进行筛选，并依据融合规则实现双通道振动信号的融合重构，以改善重构信号中的特征信息；在此基础上，利用DCT高阶谱分析法对融合信号作进一步处理，并通过奇异值分解分别计算Shannon奇异熵和Tsallis奇异熵，以此作为液压泵性能退化特征向量；最后，利用仿真信号以及液压泵的实测振动信号，验证了该方法的有效性。

Abstract

To solve the problem that the vibration signals are strongly nonlinear and the degradation feature is difficult to extract, the degradation feature extraction method based upon morphological undecimated wavelet decomposition fusion (MUWDF) and DCT high order singular entropy is proposed. First of all, the MUWDF algorithm is presented under the framework of morphological undecimated decomposition. The approximate signals of all decomposition layers are selected by feature energy factor and dual-channel vibration signals are fused according to the presented fusion rules so as to increase feature information proportion. On this basement, the high order spectrum analysis algorithm modified by DCT is proposed for further dealing with the fused signal. Singular entropies of Shannon and Tsallis, which are considered as fault degradation feature of hydraulic pump, are respectively achieved by singular value decomposition. Finally, the proposed method is verified by simulation signals and pump vibration signals in various loose slipper degrees.

导出引用

孙健，李洪儒，王卫国，许葆华. 基于形态非抽样融合与DCT高阶奇异熵的液压泵退化特征提取[J]. 振动与冲击, 2015, 34(22): 54-61

Sun Jian Li Hongru WANG Weiguo Xu Baohua . Degradation Fault Feature Extraction of Hydraulic Pump Based on Morphological Undecimated Decomposition[J]. Journal of Vibration and Shock, 2015, 34(22): 54-61

参考文献

[1] 唐宏宾, 吴运新, 滑广军, 马昌训. 基于EMD包络谱分析的液压泵故障诊断方法[J]. 振动与冲击, 2012, 31(9):44-48.
Tang Hongbin, Wu Yunxin, Hua Guangjun, Ma Changxun. Fault diagnosis of pump using EMD and envelope spectrum analysis [J]. Journal of Vibration and Shock, 2012, 31(9):44-48.
[2] D. Ciuonzo, G. Papa, G. Romano, et al..One-bit decentralized detection with a rao test for multi-sensor fusion [J].IEEE Signal Processing Letters, 2013, 20(9):861-864
[3] M. S. Safizadeh, S. K. Latifi..Using multi-sensor data fusion for vibration fault diagnosis of rolling element bearings by accelerometer and load cell [J].Information Fusion, 2014, 18(1):1-8
[4] M. Higger, M. Akcakaya, D. Erdogmus.A robust fusion algorithm for sensor failure [J].IEEE Signal Processing Letters, 2013, 20(8):755-758
[5] P. Angelov, R. Yager. Density-based averaging- A new operator for data fusion [J]. Information Science, 2013, 222(10):164-174
[6] C. M. Wei, R. S. Blum.Theoretical analysis of correlation-based quality measures for weighted averaging image fusion [J].Information Fusion, 2010, 11(1):301-309
[7] J. A. Rodger.Toward reducing failure risk in an integrated vehicle health maintenance system: A fuzzy multi-sensor data fusion kalman filter approach for IVHMS [J].Expert Systems with Applications, 2012, 39(6):9821-9835
[8] W. B. Yang, S. Y. Li.A switch-mode information fusion filter based on ISRUKF for autonomous navigation of spacecraft [J].Information Fusion, 2014, 18(3):33-42
[9] 任亚飞, 柯熙政.多小波基多尺度多传感器数据融合[J]. 传感器与微系统. 2010, 29(9):77-79
Ren Yafei, Ke Xizheng. Multi-wavelet-basis multi-scale multi-sensor data fusion [J].Transducer and Microsystem Technologies, 2010, 29(9):77-79
[10] 吕新艳, 顾晓辉.多传声器小波多尺度信息融合滤波算法[J].仪器仪表学报, 2013, 33(4):787-793
Lv Xinyan, Gu Xiaohui. Filtering algorithm for multi-microphones based on wavelet multi-scale information fusion [J].Chinese Journal of Science Instrument, 2012, 33(4):787-793
[11] Zhang J F, Smith J S, Wu Q H. Morphological Un-Decimated Wavelet Decomposition for Fault Location on Power Transmission Lines[J].IEEE Transactions on Circuits and Systems, 2006, 53(6):1395-1402
[12] 林勇, 杨友东, 刘健. 形态非抽样小波在主减速器振动特征提取中的应用[J].农业机械学报, 2010, 41(2):209-214
Lin Yong, Yang Youdong, Liu Jian. Feature Extraction Methods of Vibration Signal in Automabile Main Reducer Based on Morphological Un-decimated Wavelet [J].Journal of Agricultural Engineering, 2010, 41(2):209-214
[13] 黄兵峰, 沈路, 周晓军, 刘莉. 基于形态非抽样小波分解的滚动轴承故障特征提取[J].农业机械学报, 2010, 41(2):204-207
Huang Bingfeng, Shen Lu, Zhou Xiaojun, et al. Fault Feature Extraction of Rolling Element Bearing based on Morphological Undecimated Wavelet Decompostion[J].Journal of Agricultural Engineering, 2010, 41(2):209-214
[14] 孙志辉, 吕文泉. 基于形态非抽样小波和S变换的轧机振动信号分析[J].北京科技大学学报, 2013, 35(3):366-370
Sun Zhihui, Lv Wenquan. Signal Analysis of Rolling Mill Vibration Based on Morphological Un-decimated Wavelets and S-transform[J].Journal of University of Sceince and Technology Beijing, 2013, 35(3):366-370
[15] 李富强, 刘国华, 吴志根. 基于双谱和奇异值分解的结构损伤试验[J].浙江大学学报, 2012, 46(10):1872-1879
Li Fuqiang, Liu Guohua, Wu Zhigen. Experimental study of structural damage based on bispectral analysis and singular value decomposition [J].Journal of Zhejiang University, 2012, 46(10):1872-1879
[16] 陈彦龙, 张培林, 伍晓亮. DCT和相关分析在轴承故障诊断中的应用[J].机械强度, 2013, 35(2):138-141
Chen Yanlong, Zhang Peilin, Wu Xiaoliang. Research on DCT based correlation analysis and its use in the bearing fault diagnosis[J].Journal of Mechanical Strength, 2013, 35(2):138-141
[17] 范新桥, 朱永利. 基于高阶多分辨率奇异熵的高压输电线路故障选相[J].电力自动化设备, 2011, 31(4):50-54
Fan Xinqiao, Zhu Yongli. Faulty phase selection based on high-order multi-resolution singular entropy for high-voltage transmission lines[J].Electric Power Automation Equipment, 2011, 31(4):50-54
[18] 章立军, 阳建宏, 徐金梧, 等. 形态非抽样小波及其在冲击信号特征提取中的应用[J].振动与冲击, 2007, 26(10):56-59
Zhang Lijun, Yang Jianhong, Xu Jinwu, et al. Morphological Undecimated Wavelet and Its Application to Feature Extraction of Impulsive Signal[J].Journal of Vibration and Shock, 2007, 26(10):56-59
[19] A. J. Morenilla, R. M. Carmona, J. L.S. Romero. Mathematical morphology for design and manufacturing[J].Mathematical and Computer Modeling, 2011, 54(7):1753-1759
[20] J. Cousty, L. Najman, F. Dias, J.Serra. Morphological filtering on graphs[J].Computer Vision and Image Understanding, 2013, 117(4):370-385
[21] Bing Li, Peilin Zhang, Zhengjun Wang. Gear Fault Detection using Multi-scale Morphological filters [J].Measurement, 2011, 44(10):2078-2089
[22] Wei He, Zhinong Jiang, Qiang Qin. A Joint Adaptive Wavelet Filter and Morphological Signal Processing Method for Weak Mechanical Impulse Extraction[J].Journal of Mechanical Science and Technology, 2011, 24(8):1709-1716
[23] Hao R J, Chu F L. Morphological Un-decimated Wavelet Decomposition for Fault Diagnostics of Rolling Element Bearings[J].Journal of Sound and Vibration, 2009, 4(1):1164-1177
[24] 王冰, 李洪儒, 许葆华. 一种多元素多尺度形态非抽样小波分解方法[J].轴承, 2013, 11(5):43-48
Wang Bing, Li Hongru, Xu Baohua. A Kind of Mult-element and Multi-scale Morphological Undecimated Wavelet Decomposition Method[J].Bearing, 2013, 11(5):43-48.
[25] 钱祖平, 许渊, 邵尉, 陈金. 基于高阶谱和时域分析的电台稳态特征提取算法[J].电子与信息学报, 2013, 35(7):1599-1606
Qian Zuping, Xu Yuan, Shao Wei, Chen Jin. Extraction Algorithm of Radio Steady State Characteristics Based on High Order Spectrum and Time-domain[J].Journal of Electronics & Information Technology, 2013, 35(7):1599-1606.
[26] E.Rufei Fiori, A. Plastino. A Shannon-Tsallis transformation [J]. Physica A : Statistical Mechanics and its Applications, 2013, 392(8): 1742-1749.