Please wait a minute...
浙江大学学报(工学版)  2018, Vol. 52 Issue (10): 1845-1853    DOI: 10.3785/j.issn.1008-973X.2018.10.002
机械与能源工程     
轴承故障信号的平均组合差值形态滤波分析
余建波, 李传锋, 吕靖香
同济大学 机械与能源工程学院, 上海 201804
Average combination difference morphological filter analysis on fault signals of rolling bearing
YU Jian-bo, LI Chuan-feng, LV Jing-xiang
School of Mechanical Engineering, Tongji University, Shanghai 201804, China
 全文: PDF(1865 KB)   HTML
摘要:

为了提取受谐波和随机噪声干扰的信号中的冲击故障特征,提出基于平均组合差值形态滤波(ACDIF)和Teager能量峭度(TEK)的滚动轴承故障诊断方法.将对冲击成分具有不同抑制方式的4种基本形态算子两两合并加强抑制效果,组合作差反向提取出正、负冲击,构造出一组新的组合差值形态算子(CDIF),通过比较分析选择其中2种CDIF的平均值作为最终滤波输出.针对滤波过程中结构元素(SE)的选择问题,采用TEK作为评价指标筛选最佳结构元素长度,有效提高了滤波处理的效率和精确度.数值仿真和轴承外圈故障振动信号的试验结果表明,利用该方法能够有效地滤除随机噪声和谐波干扰,提取强背景噪声下的冲击故障特征,滤波效果优于传统方法.

Abstract:

A new fault diagnosis method based on average combination difference morphological filter (ACDIF) and Teager energy kurtosis (TEK) was proposed in order to extract the impulse components embedded in vibration signals consisting of much noise and harmonics. The four basic operations with different suppression modes on impact components were combined in pairs for enhancing the effect of pulse suppression. Positive and negative impact was extracted in reverse by combination difference so that several new combination difference (CDIF) operations were constructed. Two CDIFs were selected by comparing the performance of all CDIFs, and the average of two selected CDIFs was regarded as final output. The length of SE was defined by a new criterion named TEK aiming at the selection problem of structure element (SE). Then the effectiveness of ACDIF for fault feature extraction was improved. The experimental results on simulation and bearing vibration signals demonstrate that the method can effectively suppress interference and extract periodic impacts from vibration signals. The comparison results indicate that the method outperforms other methods for bearing fault diagnosis.

收稿日期: 2017-07-17 出版日期: 2018-10-11
CLC:  TH165  
基金资助:

国家自然科学基金资助项目(51375290,71771173);上海航天科技创新基金资助项目(SAST2015054);中央高校基本科研业务费资助项目

作者简介: 余建波(1978-),男,教授,从事机械设备故障诊断的研究.orcid.org/0000-0003-3204-2486.E-mail:jbyu@tongji.edu.cn
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
作者相关文章  

引用本文:

余建波, 李传锋, 吕靖香. 轴承故障信号的平均组合差值形态滤波分析[J]. 浙江大学学报(工学版), 2018, 52(10): 1845-1853.

YU Jian-bo, LI Chuan-feng, LV Jing-xiang. Average combination difference morphological filter analysis on fault signals of rolling bearing. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2018, 52(10): 1845-1853.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2018.10.002        http://www.zjujournals.com/eng/CN/Y2018/V52/I10/1845

[1] YU J. Local and nonlocal preserving projection for bearing defect classification and performance assessment[J]. IEEE Transactions on Industrial Electronics, 2012, 59(5):2363-2376.
[2] MARAGOS P, SCHAFER R. Morphological filters-Part I:their set-theoretic analysis and relations to linear shift-invariant filters[J]. IEEE Transactions on Acoustics Speech and Signal Processing, 1987, 35(8):1153-1169.
[3] 李豫川, 伍星, 迟毅林, 等. 基于形态滤波和稀疏分量分析的滚动轴承故障盲分离[J]. 振动与冲击, 2011, 30(12):170-174 LI Yu-chuan, WU Xing, CHI Yi-lin, et al. Blind separation for bearing faults based on morphological filtering and sparse component analysis[J]. Journal of Vibration and Shock, 2011, 30(12):170-174
[4] MENG L, XIANG J, WANG Y, et al. A hybrid fault diagnosis method using morphological filter-translation invariant wavelet and improved ensemble empirical mode decomposition[J]. Mechanical Systems and Signal Processing, 2015, 50:101-115.
[5] HU Z, WANG C, ZHU J, et al. Bearing fault diagnosis based on improved morphological filter[J]. Measurement, 2016, 80:163-178.
[6] DONG Y, LIAO M, ZHANG X, et al. Fault diagnosis of rolling element bearing based on modified morphological method[J]. Mechanical Systems and Signal Processing, 2011, 25:1276-1286.
[7] 鄢小安, 贾民平. 参数优化的组合形态-hat变换及其在风力发电机组故障诊断中的应用[J]. 机械工程学报, 2016, 52(13):103-110 YAN Xiao-an, JIA Min-ping. Parameter optimized morphological filter-hat transform and its application in fault diagnosis of wind turbine[J]. Journal of Mechanical Engineering, 2016, 52(13):103-110
[8] DENG L, ZHAO R. Fault feature extraction of a rotor system based on local mean decomposition and Teager energy kurtosis[J]. Journal of Mechanical Science and Technology, 2014, 28(4):1161-1169.
[9] 张文斌, 杨辰龙, 周晓军. 形态滤波方法在振动信号降噪中的应用[J]. 浙江大学学报:工学版, 2009, 43(11):2096-2099 ZHANG Wen-bin, YANG Chen-long, ZHOU Xiao-jun. Application of morphology filtering method in vibration signal de-noising[J]. Journal of Zhejiang University:Engineering Science, 2009, 43(11):2096-2099
[10] 王书涛, 张金敏, 李圆圆, 等. 基于数学形态学和模糊聚类的旋转机械故障诊断[J]. 仪器仪表学报, 2012, 33(5):1055-1061 WANG Shu-tao, ZHANG Jin-min, LI Yuan-yuan, et al. Rotating machinery fault diagnosis based on mathematical morphology and fuzzy clustering[J]. Chinese Journal of Scientific Instrument, 2012, 33(5):1055-1061
[11] HARALICK R M, STERNBERG S R, ZHUANG X. Image analysis using mathematical morphology[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1987(4):532-550.
[12] 章立军, 杨德斌, 徐金梧, 等. 基于数学形态滤波的齿轮故障特征提取方法[J]. 机械工程学报, 2007, 43(2):71-75 ZHANG Li-jun, YANG De-bin, XU Jin-wu, et al. Approach to extracting gear fault feature based on mathematical morphological filtering[J]. Journal of Mechanical Engineering, 2007, 43(2):71-75
[13] 王天金, 冯志鹏, 郝如江, 等. 基于Teager能量算子的滚动轴承故障诊断研究[J]. 振动与冲击, 2012, 31(2):1-6 WANG Tian-jin, FENG Zhi-peng, HAO Ru-jiang, et al. Fault diagnosis of rolling element bearings based on Teager energy operator[J]. Journal of Vibration and Shock, 2012, 31(2):1-6
[14] RAJ A S, MURALI N. Early classification of bearing faults using morphological operators and fuzzy inference[J]. IEEE Transactions on Industrial Electronics, 2013, 60(2):567-574.
[15] Case western reserve university bearing data center website[EB/OL]. 2011-05-11. http//csegroups.case.edu/bearingdatacenter/pages/download-data-file.
[16] 张小龙, 张氢, 秦仙蓉, 等. 基于ITD-形态滤波和Teager能量谱的轴承故障诊断[J]. 仪器仪表学报, 2016, 37(4):788-795 ZHANG Xiao-long, ZHANG Qing, QIN Xian-rong, et al. Fault diagnosis method for rolling bearing based on ITD-morphological filter and Teager energy spectrum[J]. Chinese Journal of Scientific Instrument, 2016, 37(4):788-795

[1] 祝文颖, 冯志鹏. 基于迭代Hilbert变换的行星齿轮箱振动信号分析[J]. 浙江大学学报(工学版), 2017, 51(8): 1587-1595.