Compound fault feature extraction of rolling bearing based on parameters adaptive CYCBD
-
摘要:
针对滚动轴承早期故障信号特征难以准确提取与分离问题,提出参数自适应最大2阶循环平稳盲解卷积(CYCBD)的滚动轴承复合故障特征提取方法。基于不同的故障类型,以谐波能量比指标为适应度函数,采用麻雀搜索算法自适应获取解卷积的最佳滤波器长度和循环频率,利用得到的最佳参数组合对原信号中的故障成分逐一提取,并对解卷积后的信号开展包络谱分析,实现轴承复合故障的诊断。分析结果表明:所提出方法能够在强噪声背景下,清晰准确地分离出轴承故障实测信号中的内圈故障频率的1~4倍频及外圈故障的1~6次谐波分量,而其他常用方法只能提取到少数故障频率且分辨能力较低,所提出方法的诊断效果明显,具有更高的应用价值和推广性能。
-
关键词:
- 麻雀搜索算法 /
- 最大2阶循环平稳盲解卷积 /
- 滚动轴承 /
- 复合故障 /
- 特征提取
Abstract:In view of the difficulty to accurately extract and separate the features of the early fault signals of rolling bearings, a compound fault feature extraction method of rolling bearing based on parameters adaptive maximum second-order cyclostationarity blind deconvolution (CYCBD) was proposed. Based on different fault types, the harmonics energy ratio index was used as the fitness function, and the sparrow search algorithm was used to adaptively obtain the optimal filter length and cycle frequency of deconvolution. The obtained optimal parameters combination was used to extract the fault components in the original signal one by one, and the envelope spectrum analysis of the deconvolution signal was carried out to realize the diagnosis of compound fault of the bearing. The analysis results showed that the proposed method can clearly and accurately separate 1—4 times of the inner ring characteristic frequency and 1—6 times harmonic component of the outer ring fault from the measured signal of bearing fault under the background of strong noise, while other common methods can only extract a few fault frequencies with low resolution. The proposed method has obvious diagnostic effect, higher application value and promotion performance.
-
表 1 故障仿真信号参数表
Table 1. Parameters table of fault simulation signal
参数 数值 参数 数值 An/g 1 Tn/s 1/165 Aw/g 1 Tw/s 1/100 βn 1000 f1/Hz 52 βw 800 f2/Hz 73 fn1/Hz 3000 fr/Hz 20 fn2/Hz 2000 Cn 0.5 表 2 滚动轴承技术参数
Table 2. Technical parameters of rolling bearing
参数 数值 轴承节径/mm 38.5 滚子直径/mm 7.5 滚子数量 13 接触角/ (°) 0 -
[1] YASIR M N,KOH B H. Data decomposition techniques with multi-scale permutation entropy calculations for bearing fault diagnosis[J]. Sensors,2018,18(4): 1278. doi: 10.3390/s18041278 [2] MA Haoqun,FENG Zhipeng. Planet bearing fault diagnosis using multipoint Optimal Minimum Entropy Deconvolution Adjusted[J]. Journal of Sound and Vibration,2019,449: 235-273. doi: 10.1016/j.jsv.2019.02.024 [3] ZHENG Kai,YANG Dewei,ZHANG Bin,et al. A group sparse representation method in frequency domain with adaptive parameters optimization of detecting incipient rolling bearing fault[J]. Journal of Sound and Vibration,2019,462: 114931. doi: 10.1016/j.jsv.2019.114931 [4] 李红贤,韩延,吴敬涛,等. 基于ICA包络增强MEMD的滚动轴承故障诊断[J]. 航空动力学报,2021,36(2): 405-412. LI Hongxian,HAN Yan,WU Jingtao,et al. Rolling bearing fault diagnosis based on MEMD with ICA envelop enhancement[J]. Journal of Aerospace Power, 2021,36(2): 405-412. (in ChineseLI Hongxian, HAN Yan, WU Jingtao, et al. Rolling bearing fault diagnosis based on MEMD with ICA envelop enhancement[J]. Journal of Aerospace Power, 2021, 36(2): 405-412. (in Chinese) [5] ENDO H,RANDALL R B. Enhancement of autoregressive model based gear tooth fault detection technique by the use of minimum entropy deconvolution filter[J]. Mechanical Systems and Signal Processing,2007,21(2): 906-919. doi: 10.1016/j.ymssp.2006.02.005 [6] MCDONALD G L,ZHAO Qing,ZUO M J. Maximum correlated Kurtosis deconvolution and application on gear tooth chip fault detection[J]. Mechanical Systems and Signal Processing,2012,33: 237-255. doi: 10.1016/j.ymssp.2012.06.010 [7] 张先辉,李新民,金小强. 基于MED和LMD的自动倾斜器轴承广义Shannon熵谱分析[J]. 航空动力学报,2019,34(4): 764-771. ZHANG Xianhui,LI Xinmin,JIN Xiaoqiang. General Shannon entropy spectrum of swash-plate bearing based on MED and LMD[J]. Journal of Aerospace Power,2019,34(4): 764-771. (in ChineseZHANG Xianhui, LI Xinmin, JIN Xiaoqiang. General Shannon entropy spectrum of swash-plate bearing based on MED and LMD[J]. Journal of Aerospace Power, 2019, 34(4): 764-771. (in Chinese) [8] MIAO Yonghao,ZHAO Ming,LIN Jing,et al. Application of an improved maximum correlated kurtosis deconvolution method for fault diagnosis of rolling element bearings[J]. Mechanical Systems and Signal Processing,2017,92: 173-195. doi: 10.1016/j.ymssp.2017.01.033 [9] BUZZONI M,ANTONI J,D’ELIA G. Blind deconvolution based on cyclostationarity maximization and its application to fault identification[J]. Journal of Sound and Vibration,2018,432: 569-601. doi: 10.1016/j.jsv.2018.06.055 [10] 黄包裕,张永祥,赵磊. 基于布谷鸟搜索算法和最大二阶循环平稳盲解卷积的滚动轴承故障诊断方法[J]. 机械工程学报,2021,57(9): 99-107. HUANG Baoyu, ZAHNG Yongxiang, ZHAO Lei. Research on fault diagnosis method of rolling bearings based on cuckoo search algorithm and maximum second order cyclostationary blind deconvolution[J]. Journal of Mechanical Engineering,2021,57(9): 99-107. (in ChineseHUANG Baoyu, ZAHNG Yongxiang, ZHAO Lei. Research on fault diagnosis method of rolling bearings based on cuckoo search algorithm and maximum second order cyclostationary blind deconvolution[J]. Journal of Mechanical Engineering, 2021, 57(9): 99-107. (in Chinese) [11] 赵晓涛,孙虎儿,姚巍. 基于CYCBD和包络谱的滚动轴承微弱故障特征提取[J]. 机械传动,2020,44(4): 165-169,176. ZHAO Xiaotao,SUN Huer,YAO Wei. Feature Extraction of Weak Fault for Rolling Bearing based on CYCBD and Envelope Spectrum[J]. Journal of Mechanical Transmission,2020,44(4): 165-169,176. (in ChineseZHAO Xiaotao, SUN Huer, YAO Wei. Feature Extraction of Weak Fault for Rolling Bearing based on CYCBD and Envelope Spectrum[J]. Journal of Mechanical Transmission, 2020, 44(4): 165-169, 176. (in Chinese) [12] 朱丹宸,张永祥,何伟,等. 基于自适应CYCBD和互相关谱的滚动轴承复合故障诊断方法[J]. 振动与冲击,2020,39(11): 116-122,128. ZHU Danchen,ZHANG Yongxiang,HE Wei,et al. Compound faults diagnosis of rolling element bearing using adaptive CYCBD and cross-correlation spectrum[J]. Journal of Vibration and Shock,2020,39(11): 116-122,128. (in ChineseZHU Danchen, ZHANG Yongxiang, HE Wei, et al. Compound faults diagnosis of rolling element bearing using adaptive CYCBD and cross-correlation spectrum[J]. Journal of Vibration and Shock, 2020, 39(11): 116-122, 128. (in Chinese) [13] ZHAO Ming,LIN Jing,MIAO Yonghao,et al. Detection and recovery of fault impulses via improved harmonic product spectrum and its application in defect size estimation of train bearings[J]. Measurement,2016,91: 421-439. doi: 10.1016/j.measurement.2016.05.068 [14] 罗忠,徐迪,李雷,等. 基于改进二阶循环平稳解卷积的轴承故障检测方法[J]. 东北大学学报(自然科学版),2021,42(5): 673-678. LUO Zhong,XU Di,LI Lei,et al. Bearing fault detection based on improved CYCBD method[J]. Journal of Northeastern University (Natural Science),2021,42(5): 673-678. (in Chinese doi: 10.12068/j.issn.1005-3026.2021.05.010LUO Zhong, XU Di, LI Lei, et al. Bearing fault detection based on improved CYCBD method[J]. Journal of Northeastern University (Natural Science), 2021, 42(5): 673-678. (in Chinese) doi: 10.12068/j.issn.1005-3026.2021.05.010 [15] WANG Xiaolong,TANG Guiji,HE Yuling. Application of RSSD-OCYCBD strategy in enhanced fault detection of rolling bearing[J]. Complexity,2020,2020: 5424236. [16] 刘宇涛,孙虎儿. 基于粒子群优化的CYCBD在滚动轴承故障特征提取的应用研究[J]. 机械传动,2021,45(2): 171-176. LIU Yutao,SUN Huer. Study on Application of CYCBD based on PSO in Fault Feature Extraction of Rolling Bearing[J]. Journal of Mechanical Transmission,2021,45(2): 171-176. (in ChineseLIU Yutao, SUN Huer. Study on Application of CYCBD based on PSO in Fault Feature Extraction of Rolling Bearing[J]. Journal of Mechanical Transmission, 2021, 45(2): 171-176. (in Chinese) [17] XUE Jiankai,SHEN Bo. A novel swarm intelligence optimization approach: sparrow search algorithm[J]. Systems Science and Control Engineering,2020,8(1): 22-34. doi: 10.1080/21642583.2019.1708830 [18] YUAN Jianhua,ZHAO Ziwei,LIU Yaping,et al. DMPPT control of photovoltaic microgrid based on improved sparrow search algorithm[J]. IEEE Access,2960,9: 16623-16629. -