Fault feature extraction of low speed roller bearing based on the Teager peak energy

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Journal of Vibration and Shock ›› 2017, Vol. 36 ›› Issue (11) : 124-128.

KE Yan-liang1, WANG Hua-qing1, TANG Gang1, YUAN Hong-fang2, LI Ling-yang1

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Abstract

The peak impact is one of the most significant features in faulty signals of roller bearings and obvious peak impact is helpful to the fault diagnosis. However, when the roller bearings are operated at low speed, the fault features are easily submerged by the noise due to the small vibration energy and weak peak impact. Thus, the fault features cannot be extracted by the traditional methods, such as the envelope analysis. To enhance the peak impact in the weak faulty signals and extract the fault features successfully, a fault feature extraction method based on the Teager peak energy is developed. First, the raw signals are divided into several segments by a sliding window and the peak-to-peak value is utilized to represent each segment, through which the peak-to-peak symptom wave can be obtained, which can enhance the peak impact in the faulty vibration signals. Second, the Teager energy operator is applied to demodulate the symptom wave, which can eliminate the noise and extract the impact component. Finally, the status of the roller bearings can be determined by the spectrum of Teager energy. The experimental results show that the proposed approach can successfully extract the fault features of the low speed roller bearings and identify the performance of roller bearings accurately.

Key words

low speed roller bearing / fault diagnosis / peak-to-peak value symptom wave / Teager energy operator

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KE Yan-liang1, WANG Hua-qing1, TANG Gang1, YUAN Hong-fang2, LI Ling-yang1. Fault feature extraction of low speed roller bearing based on the Teager peak energy[J]. Journal of Vibration and Shock, 2017, 36(11): 124-128

References

[1] 李云，郭瑜，那靖，等. 基于包络同步平均的齿轮故障诊断[J]. 振动与冲击，2013，32(19)：17-21.
Li Yun, Guo Yu, Na Jing, et al. Gear Fault Diagnosis Based on Envelope Synchronous Average [J]. Journal of vibration and shock, 2013, 32(19): 17-21.
[2] 苏文胜，王奉涛，张志新，等. EMD降噪和谱峭度法在滚动轴承早期故障诊断中的应用[J]. 振动与冲击，2010，29(3)：18-21.
SU Wen-sheng, WANG Feng-tao, ZHANG Zhi-xin, et al. Application of EMD Denoising and Spectral Kurtosis in Fault Early Diagnosis of Rolling Element Bearing [J]. Journal of vibration and shock, 2010, 29(3): 18-21.
[3] 张超，陈建军，郭迅. 基于EMD能量熵和支持向量机的齿轮故障诊断方法[J]. 振动与冲击，2010，29(10)：216-220.
ZHANG Chao; CHEN Jian-jun; GUO Xun. A gear fault diagnosis method based on EMD energy entropy and SVM. Journal of vibration and shock, 2010, 29(10): 216-220.
[4] 楼红伟，胡光锐. 基于Teager能量算子和小波变换的语音识别特征参数[J]. 上海交通大学学报，2003，37(S2)：83-85.
LOU Hong-wei, HU Guang-rui. Speech Feature Based on Teager Energy Operator and Dyadic Wavelet Transform [J]. Journal of Shanghai Jiao Tong University, 2003，37(S2)：83-85.
[5] 高云鹏，李峰，陈婧，等. [J]. 基于Teager-Kaiser能量算子Rife-Vincent窗频谱校正的电压闪变测量[J]. 电工技术学报，2014，29(6)：248-256.
GAO Yun-peng, LI Yi, CHEN Jing, et al. Voltage Flicker Measurement Using the Teager-Kaiser Energy Operator Based on Rife-Vincent Window Spectral Correction [J]. Transactions of China Electrotechnical Society, 2014, 29(6): 248-256.
[6] 王晓龙. 基于EEMD和Teager能量算子解调的故障诊断研究[J]. 电力科学与工程，2013，29(3)：18-22.
WANG Xiao-long. Fault Diagnosis Based on EEMD and Teager Energy Operator [J]. Electric Power Science and Engineering, 2013, 29(3): 18-22.
[7] 陈仕琦，康敏，傅秀清. 基于小波包和Teager能量算子的齿轮故障诊断研究[J]. 机械传动，2014，38(12)：99-102.
CHEN Shi-qi, KANG Min, FU Xiu-qing. Study on Gear Fault Diagnosis Based on Wavelet Packet and Teager Energy Operator [J]. Journal of Mechanical Transmission, 2014, 38(12): 99-102.
[8] 胥永刚，崔涛，马朝永，等. 基于LCD和Teager能量算子的滚动轴承故障诊断[J]. 北京工业大学学报，2015, 41(3)：340-346.
XU Yong-gang, CUI Tao, MA Chao-yong, et al. Fault Diagnosis of Bearings Based on LCD and Teager Energy Operator [J]. Journal of Beijing university of technology, 2015, 41(3): 340-346.
[9] 武哲，杨绍普，张建超. 基于LMD自适应多尺度形态学和Teager能量算子方法在轴承故障诊断中的应用[J]. 振动与冲击，2016，35(3)：7-13.
WU Zhe，YANG Shao-pu，ZHANG Jian-chao. Bearing fault feature extraction method based on LMD adaptive multiscale morphological and energy operator demodulating. Journal of vibration and shock, 2016，35(3): 7-13.
[10] 张德祥，汪萍，吴小培，等. 基于经验模式分解和Teager能量谱的齿轮箱故障诊断[J]. 振动与冲击， 2010，29(7)：109-111.
ZHANG De-xiang, WANG Ping, WU Xiao-pei, et al. Gearbox Fault Diagnosis Based on Empirical Mode Decomposition and Teager Energy Spectrum [J], Journal of Sound and Vibration , 2010, 29(7): 109-111.
[11] Solnik S, Rider P, Steinweg K, et al. Teager–Kaiser energy operator signal conditioning improves EMG onset detection[J]. European journal of applied physiology, 2010, 110(3): 489-498.
[12] Cao M, Xu W, Ostachowicz W, et al. Damage identification for beams in noisy conditions based on Teager energy operator-wavelet transform modal curvature[J]. Journal of Sound and Vibration, 2014, 333(6): 1543-1553.