提出一种基于匹配追踪预处理的轴承故障诊断算法，避免了传统共振解调方法对带通滤波的经验依赖，消除了传统方法在处理环节产生的互调干扰频率成分，能够精确提取损伤轴承的故障频率。通过在轮对跑合实验台上进行试验验证，结果显示比传统共振解调方法有一定优势，可以更有效提取轮对轴承的损伤故障。
Abstract
A bearing fault diagnosis algorithm is proposed based on matching Pursuit pretreatment. This method can avoid the experience dependence on bandpass filtering of traditional envelope spectrum methods. This method also can remove the additional interference frequency component from processing chain of the traditional methods, and it can precisely extract the failure frequency of damage bearings. By testing on real collecting signals on running-wheel bench, this method has some advantages over the traditional method of envelope spectrum, and it can effectively extract the wheel failure of the bearing damage.
关键词
匹配追踪 /
故障诊断 /
互调 /
轮对轴承
{{custom_keyword}} /
Key words
matching pursuit /
fault diagnosis /
intermodulation /
wheel bearing
{{custom_keyword}} /
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1] 梅宏斌. 滚动轴承振动监测与诊断 理论•方法•系统[M]. 北京：机械工业出版社，1995.
[2] 刘金朝，丁夏完，王成国. 自适应共振解调法及其在滚动轴承故障诊断中的应用[J]. 振动与冲击，2007, 26(1): 38-41,158.
Liu Jin-zhao, Ding Xia-wan, Wang Cheng-guo. Adaptive resonance demolation method and its application to fault diagnosis of freight carrolling bearings[J]. Journal of vibration and shock, 2007, 26(1): 38-41,158.
[3] 张 进，冯志鹏，褚福磊. 滚动轴承故障特征的时间—小波能量谱提取方法[J]. 机械工程学报，2011，47(17): 44-49. Zhang Jin, Feng Zhi-peng, Chu Fu-lei. Extraction of rolling bearing fault feature based on time-wavelet energy spectrum[J]. Journal of mechanical engineering, 2011, 47(17): 44-49.
[4] 王诗彬，许佳，朱忠奎. 瞬态成分参数的最小二乘法辨识及其轴承故障特征提取应用[J]. 机械工程学报，2012, 48(7):68-76.
Wang Shi-bin, Xu Jia, Zhu Zhong-kui. LSM-based transient parameter identification and its application in feature extraction of bearing fault[J]. Journal of mechanical engineering,2012,48(7):68-76.
[5] MALLAT S G, ZHANG Z. Matching pursuits with time-frequency dictionaries[J]. IEEE Transactions on Signal Processing, 1993, 41(12): 3377-3415.
[6] 范 虹，孟庆丰，张优云,等. 基于改进匹配追踪算法的特征提取及其应用[J]. 机械工程学报，2007,43(7):115-119.
Fan Hong, Meng Qing-feng, Zhang You-yun,et al. Feature extraction based on modified matching pursuit and its application[J]. Journal of mechanical engineering, 2007, 43(7): 115-119.
[7] 崔玲丽，王婧，邬娜，等. 基于轴承故障信号特征的自适应冲击字典匹配追踪方法及应用[J].振动与冲击，2014，33(11):54-60.
Cui Ling-li, Wang Jing, Wu Na, etc. Bearing fault diagnosis based on self-adaptive impulse dictionary matching pursuit[J]. Journal of vibration and shock, 2014, 33(11):54-60.
[8] 余发军，周凤星，严保康. 基于字典学习的轴承早期故障稀疏特征提取[J].振动与冲击，2016,35(6):181-186.
Yu Fa-jun, Zhou Feng-xing, Yan Bao-kang. Bearing initial fault feature extraction via sparse representation based on dictionary learning[J]. Journal of vibration and shock, 2016,35(6):181-186.
[9] DiMaggio S J, Sako, B H. Basic system identification for condition monitoring of turbopumps[C]. 2001 IEEE Aerospace Conference, 73189-73200.
[10] QIAN S,CHEN D. Signal representation using adaptive normalized Gaussian functions[J]. Signal Processing, 1994, 36(1): 329-355.
[11] FAROOK S, GORAN S. Nonparametric waveform estimation using filter bank[J]. IEEE Transactions on Signal Processing, 1996,44(2): 240-247.
[12] 费晓琪，孟庆丰，何正嘉. 基于冲击时频原子的匹配追踪信号分解及机械故障特征提取技术[J].振动与冲击，2003, 22(2): 26-29,22.
Fei Xiao-qi, Meng Qing-feng, He Zheng-jia.Signal decomposition with matching pursuits and technology of extraction machinery fault feature based on impulse time-frequency atom[J]. Journal of vibration and shock, 2003, 22(2): 26-29.
[13] 王江萍. 机械设备故障诊断技术及应用[M]. 西安:西北工业大学出版社，2004.
[14] 梁瑜，贾利民，蔡国强，等. 滚动轴承的非线性动力学故障模型研究[J]. 中国铁道科学，2014,35(1):98-104.
Liang Yu, Jia Li-min, Cai Guo-qiang,et al. Research on nonlinear dynamics fault model of rolling bearing[J]. China railway science, 2014, 35(1): 98-104.
{{custom_fnGroup.title_cn}}
脚注
{{custom_fn.content}}
PDF(999 KB)
