Local fault detection of RV reducer planetary gears based on IAS signal enhancement

WANG Hongwei, GUO Yu, FAN Jiawei, YANG Xinmin, YIN Xingchao

Journal of Vibration and Shock ›› 2024, Vol. 43 ›› Issue (17) : 324-330.

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PDF(1996 KB)
Journal of Vibration and Shock ›› 2024, Vol. 43 ›› Issue (17) : 324-330.

Local fault detection of RV reducer planetary gears based on IAS signal enhancement

  • WANG Hongwei, GUO Yu, FAN Jiawei, YANG Xinmin, YIN Xingchao
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Abstract

Aiming at the problem that the multi-source coupling of the rotary vector (RV) reducer is serious, the impact caused by local faults is easily overwhelmed by other interference components, and the fault feature extraction is difficult, combined with the advantages of the encoder, a planetary gear fault detection method of RV reducer based on adaptive maximum second order cyclostationarity blind deconvolution (ACYCBD) is proposed. Firstly, the encoder signal is obtained from the built-in optical encoder of the servo motor, and the Instantaneous angular speed (IAS) signal is obtained by using the forward differential. Then, the ACYCBD optimized filter length is adaptively determined based on the Characteristic Evaluation Indicator (CEI) maximization principle, and the IAS signal is enhanced. Finally, the fault detection of the RV reducer is realized by identifying the theoretical number of teeth in the time domain that matches the faulty shock period. Through experimental data analysis, the proposed method is compared with the existing sparse low-rank decomposition algorithm and the enhanced CYCBD algorithm, the effectiveness of the proposed method is verified.

Key words

built-in encoder / instantaneous angular speed / RV reducer / maximum second-order cyclostationarity blind deconvolution

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WANG Hongwei, GUO Yu, FAN Jiawei, YANG Xinmin, YIN Xingchao. Local fault detection of RV reducer planetary gears based on IAS signal enhancement[J]. Journal of Vibration and Shock, 2024, 43(17): 324-330

References

[1] 宋雷, 游东东, 郑振兴等. 基于经验模态分解的RV减速器运动参数降噪研究[J]. 振动与冲击, 2022, 41(18): 266-272+290.
SONG Lei, YOU DONG Dong, ZHENG Zhenxing, et al. Journal of Vibration and Shock, 2022, 41(18): 266-272+290.
[2] 韩特, 李彦夫, 雷亚国, 等. 融合图标签传播和判别特征增强的工业机器人关键部件半监督故障诊断方法[J]. 机械工程学报, 2022,58(17): 116-124.
HAN Te, LI Yanfu, LEI Yaguo, et al. Semi-supervised Fault Diagnosis Method via Graph Label Propagation and Dis-criminative Feature Enhancement for Critical Components of Industrial Robot[J]. Journal of Mechanical Engineering, 2022,58(17): 116-124.
[3] Peng P, Wang J. NOSCNN: A robust method for fault diagnosis of RV reducer[J]. Measurement, 2019, 138: 652-658.
[4] 汪久根, 柯梁亮, 基于残差网络的RV减速器故障诊断[J]. 机械工程学报, 2019, 55(03): 73-80.
WANG Jiugen, KE Liangliang. Fault Diagnosis for RV Re-ducer Based on Residual Network[J]. Journal of Mechanical Engineering, 2019, 55(03): 73-80.
[5] 陈乐瑞, 曹建福, 王晓琪. 结合非线性频谱和核主元分析的机器人用RV减速器故障诊断[J]. 西安交通大学学报, 2020, 54(01): 32-41.
CHEN Lerui, CAO Jianfu, WANG Xiaoqi. Fault Diagnosis for Robot RV Reducer Using Nonlinear Frequency Spectrum and Kernel Principal Component Analysis[J]. Journal of Xi’an Jiaotong University, 2020, 54(01): 32-41.
[6] Zhao M, Jia X, Lin J, et al. Instantaneous speed jitter detection via encoder signal and its application for the diagnosis of planetary gearbox[J]. Mechanical Systems and Signal Processing, 2018, 98: 16-31.
[7] Li B, Zhang X, Wu J. New procedure for gear fault detection and diagnosis using instantaneous angular speed[J]. Mechanical Systems and Signal Processing, 2017, 85: 415-428.
[8] Feng Z, Gao A, Li K, et al. Planetary gearbox fault diagnosis via rotary encoder signal analysis[J]. Mechanical Systems and Signal Processing, 2021, 149: 107325.
[9] 欧曙东, 赵明, 周涛, 等. 基于编码器信号的低转速行星齿轮箱故障诊断技术[J]. 中国电机工程学报, 2021, 41(05): 1885-1894.
OU Shudong, ZHAO Ming, ZHOU Tao, et al. Fault Diagnosis Technology for Low-speed Planetary Gearbox Based on Encoder Signals[J]. Proceedings of the CSEE, 2021, 41(05): 1885-1894.
[10] 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.
[11] 齐咏生, 单成成, 贾舜宇, 等. 一种基于增强型最大二阶循环平稳盲解卷积的齿轮箱复合故障诊断[J]. 中国机械工程, 2022, 33(24): 2927-2941+2952.
QI Yongsheng, SHAN Chengcheng, JIA Shunyu, et al. A Gearbox Composite Fault Diagnosis Based on Enhanced CYCBD[J]. China mechanical engineering, 2022, 33(24): 2927-2941+2952.
[12] Jia X, Zhao M, Di Y, et al. Sparse filtering with the generalized Lp/Lq norm and its applications to the condition monitoring of rotating machinery[J]. Mechanical Systems and Signal Processing, 2018, 102: 198-213.
[13] Wang D. Some further thoughts about spectral kurtosis, spectral L2/L1 norm, spectral smoothness index and spectral Gini index for characterizing repetitive transients[J]. Mechanical Systems and Signal Processing, 2018, 108: 360-368.
[14] 徐宏海, 王文涛, 刘学翱, 等. RV减速器工作频率理论计算与ADAMS仿真[J]. 机械传动, 2015, 39(07): 38-41+46.
XU Honghai, WANG Wentao, LIU Xueao, et al. Theoretical Calculation and ADAMS Simulation of RV Reducer Operating Frequency[J]. Journal of mechanical transmission, 2015, 39(07): 38-41+46.
[15] Antoni J. The infogram: Entropic evidence of the signature of repetitive transients[J]. Mechanical Systems and Signal Processing, 2016, 74: 73-94.
[16] Wang Z, Zhou J, Du W, et al. Bearing fault diagnosis method based on adaptive maximum cyclostationarity blind deconvolution[J]. Mechanical Systems and Signal Processing, 2022, 162: 108018.
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