&nbsp;Rotating machinery fault diagnosis based on maximum correlation kurtosis deconvolution and reassigned wavelet scalogram

PDF(2025 KB)

Journal of Vibration and Shock ›› 2015, Vol. 34 ›› Issue (7) : 156-161.

Rotating machinery fault diagnosis based on maximum correlation kurtosis deconvolution and reassigned wavelet scalogram

Aiming at the problem that the rotating machinery composite faults signal is difficult to be extracted and segmented from strong noise background，a fault diagnosis method for rotating machinery based on maximum correlated kurtosis deconvolution (MCKD) and reassigned wavelet scalogram was proposed. The noise in the rotating machinery vibration signal would reduced readability of its time-frequency representation，so the noise should be reduced by using MCKD，and the fault components were separated from the vibration signal, and then envelopes were obtained by Hilbert transform, finally envelopes were analyzed with the reassigned wavelet scalogram and the composite faults of rotating machinery were diagnosed according to the periods of impulse components in the scalogram, algorithm simulation and application examples validate the method.

Author information +

History +

Abstract

Aiming at the problem that the rotating machinery composite faults signal is difficult to be extracted and segmented from strong noise background，a fault diagnosis method for rotating machinery based on maximum correlated kurtosis deconvolution (MCKD) and reassigned wavelet scalogram was proposed. The noise in the rotating machinery vibration signal would reduced readability of its time-frequency representation，so the noise should be reduced by using MCKD，and the fault components were separated from the vibration signal, and then envelopes were obtained by Hilbert transform, finally envelopes were analyzed with the reassigned wavelet scalogram and the composite faults of rotating machinery were diagnosed according to the periods of impulse components in the scalogram, algorithm simulation and application examples validate the method.

Key words

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

ZHONG Xian-you，ZHAO Chung-hua，CHEN Bao-jia，TIAN Hong-liang. Rotating machinery fault diagnosis based on maximum correlation kurtosis deconvolution and reassigned wavelet scalogram[J]. Journal of Vibration and Shock, 2015, 34(7): 156-161

References

[1] PURUSHOTHAM V, NARAYANANA S, PRASAD A N. Multi-fault diagnosis of rolling bearing elements using wavelet analysis and hidden Markov model based fault recognition [J]. Journal of NDT&E International, 2005, 38：654-664.
[2] V.Sugumaran, V. Muralidharan, K. I. Ramachandran. Feature selection using Decision Tree and classification through Proximal Support Vector Machine for fault diagnostics of roller bearing [J]. Mechanical Systems and Signal Processing，2007，21(2)：930-942.
[3] 雷亚国，何正嘉，訾艳阳. 基于混合智能新模型的故障诊断[J]. 机械工程学报，2008，44(7)：112-117.
LEI Ya-guo, HE Zheng-jia, ZI Yan-yang. Fault diagnosis based on novel hybrid intelligent model [J]. Chinese Journal of Mechanical Engineering, 2008，44(7)：112-117.
[4] Antoni J. Blind separation of vibration components: principles and demonstrations [J]. Mechanical Systems and Signal Processing, 2005, 19(6): 1166-1180.
[5] 叶红仙，杨世锡，杨将新. 多振源卷积混合的时域盲源分离算法[J]. 机械工程学报，2009，45(1)：189-194.                                   YE Hong-xian，YANG Shi-xi，YANG Jiang-xin. Temproral blind source separation algorithm for convolution mixtures with multi vibration sources [J]. Journal of Mechanical Engi- neering，2009，45(1)：189-194.
[6] WANG Junfeng，SHI Tielin，HE Lingsong，et al. Frequency overlapped signal identification using blind source separation [J]. Chinese Journal of Mechanical Engineering，2006，19(2)：286-289.
[7] 王宇, 迟毅林, 伍星, 等. 基于盲信号处理的机械噪声监测与故障诊断[J].振动与冲击, 2009, 28(6): 32-41,193.    Wang Y, Chi Y L, Wu X, et al. Machine noise monitoring and fault diagnosis based on blind signal processing[J]. Journal of Vibration and Shock, 2009, 28(6) : 32-41,193.
[8] 李志农, 吕亚平, 范涛, 等. 基于经验模态分解的机械故障欠定盲源分离方法[J]. 航空动力学报, 2009, 24(8): 1886- 1892.
LI Zhi-nong, Lü Ya-ping, FAN Tao, et al. Underdetermined blind source separation method of machine faults based on empirical mode decomposition[J]. Journal of Aerospace Power, 2009, 24(8): 1886-1892.
[9] 李蓉，于德介，陈向民等. 基于线调频小波路径追踪算法与EEMD的齿轮箱复合故障诊断方法[J].振动与冲击，2014, 33 (3): 51-56.
LI Rong，YU De-jie，CHEN Xiang-min, et al. A compound fault diagnosis method for gearboxes based on chirplet path pursuit and EEMD [J]. Journal of Vibration and Shock, 2014, 33 (3): 51-56.
[10] 杨杰, 郑海起, 关贞珍等. 基于核形态成分分析的齿轮箱复合故障诊断研究[J]. 振动与冲击，2012，31(10): 97-101.
YANG Jie，ZHENG Hai-qi，GUAN Zhen-zhen, et al. compound fault diagnosis for gearbox based on kernel morphological component analysis [J]. Journal of Vibration and Shock, 2012，31 (10): 97-101.
[11] 李辉，郑海起，唐力伟. 基于改进形态分量分析的齿轮箱轴承多故障诊断研究[J]. 振动与冲击，2012，31(12): 135-140.
   LI Hui，ZHENG Hai-qi，TANG Li-wei. Bearing multi-fault diagnosis based on improved morphological component analysis [J]. Journal of Vibration and Shock, 2012，31(12): 135-140.
[12] 莫代一，崔玲丽，王婧，等. 并联双重Q因子在齿轮箱复合故障净化提取与盲分离中的应用[J].仪器仪表学报, 2013，    34(9)：273-279.
Mo Dai-yi，Cui Ling-li，Wang Jing, et al. Application of parallel dual-Q-factors in extraction and blind separation of gearbox composite faults [J].Chinese Journal of Scientific Instrument, 2013，34(9)：273-279.
[13] Geoff L. McDonald，QING Zhao，ZUO Ming J. Maximum correlated Kurtosis deconvolution and application on gear tooth chip fault detection [J]. Mechanical Systems and Signal Processing，2012，33：237−255.
[14] 廖传军，李学军，刘德顺．小波再分配尺度谱在声发射信号特征提取中的应用[J]．机械工程学报，2009，45(2)：273-279.                                       LIAO CH J，LI X J，LIU D SH．Application of reasigned wavelet scalngram in feature extraction based on aeoustic emission signal[J]．Journal of Mechanical Engineering，2009，45(2)：273-279.
[15] 陈向民，于德介，李蓉. 基于信号共振稀疏分解与重分配小波尺度谱的转子碰摩故障诊断方法[J].振动与冲击，2013, 32 (13): 27-33.
CHEN Xiang-min，YU De-jie，LI Rong. Rub-impact diagnosis of rotors with resonance-based sparse signal decomposition and reassigned wavelet scalogram[J]. Journal of Vibration and Shock, 2013, 32 (13): 27-33.
[16] WANG Xiaodong，ZI Yanyang，HE Zhengjia. Multiwavelet construction via an adaptive symmetric lifting scheme and its applications for rotating machinery fault diagnosis [J]. Measurement Science and Technology，2009，20：04103.