Fault detection of electric booster based on fractional Fourier filtering

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Journal of Vibration and Shock ›› 2020, Vol. 39 ›› Issue (23) : 263-270.

HUANG Ming, ZHENG Yongjun, WANGYANG Baihui

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Abstract

Due to the influence of strong noise environment, in order tracking analysis, vibration signal generated due to gears variable speed operation in an electric booster can’t accurately reflect fault signal.Aiming at this situation, the linear frequency modulation signal with noise was used to simulate the nonstationary signal produced by variable speed operation of the electric booster.The non-stationary signal was filtered with a fractional Fourier transform and a fractional Fourier domain bandpass filter.The signal spectra before and after filtering were compared to verify that the fractional Fourier filtering can filter out noise component of the non-stationary signal more accurately.Based on conclusions obtained with simulation, an optimization method for fault detection effect of vibration signal generated by variable speed operation of the electric booster was proposed.The fractional Fourier filtering was performed for the actually measured vibration signal generated due to decelerating operation of the electric booster motor.Comparing the signal’s order tracking spectra effects before and after filtering, it was verified that the proposed filtering method has a better filtering effect on gear fault signals measured under strong noise environment; it has a certain practical value and universality.

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fractional Fourier filtering / order tracking / non-stationary signal / strong noise

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HUANG Ming, ZHENG Yongjun, WANGYANG Baihui. Fault detection of electric booster based on fractional Fourier filtering[J]. Journal of Vibration and Shock, 2020, 39(23): 263-270

References

[1] Li Qi, Wang Hui A Research Review of Hilbert-Huang Transform Used for Rolling Bearing Fault Diagnosis.[J/OL] Applied Mechanics Materials
2013, 397-400: 2152-2155.
[2] 蔡艳平, 李艾华, 石林锁. 基于EMD与谱峭度的滚动轴承故障检测改进包络谱分析.[J/OL] 振动与冲击. 2011, 30(2): 167-172.
Cai Yan-ping, Li Ai-hua,Shi Lin-suo. Roller bearing fault detection using improved envelope spectrum analysis based on EMD and spectrum kurtosis[J]. Journal of Vibration and Shock. 2011, 30(2): 167-172.
[3] 李方前, 杨斌, 黄永程. 基于小波包——倒频谱的滚动轴承故障检测方法.[J/OL] 电子技术与软件工程. 2018, (3): 90-91.
Li Fang-qian, Yang bing, Huang Yong-cheng. Rolling bearing fault detection method based on wavelet packet-cepst spectrum [J]. Electronic Technology & Software Engineering. 2018, (3): 90-91.
[4] 李英强, 杨明, 龙江. 基于扩展卡尔曼滤波的永磁同步电机无电流传感器预测控制.[J/OL] 电机与控制应用. 2018, 45(1): 107-113.
Li Ying-qiang, Yang Ming, Long Jiang. Current Sensorless Predictive Control Based on Extended Kalman Filter for PMSM Drives [J]. Electric Machines & Control Application. 2018, 45(1): 107-113.
[5] 江志农, 胡明辉, 冯坤. 阶次跟踪能量算子与奇异值分解结合的滚动轴承故障诊断.[J/OL] 轴承. 2018, 468(11): 57-61.
Jiang Zhi-nong, Hu Ming-hui, Feng Kun. Fault Diagnosis of Rolling Bearings Based on Order Tracking Energy Operator and Singular Value Decomposition [J]. BEARING. 2018, 468(11): 57-61.
[6] Liu Ting Wei, Guo Yu, Bin L. I. Envelope order tracking analysis for rolling element bearing faults based on spectral kurtosis.[J/OL] Journal of Vibration Shock. 2012.
[7] Yi Wang, Xu Guanghua, Luo Ailing. An online tacholess order tracking technique based on generalized demodulation for rolling bearing fault detection.[J/OL] Journal of Sound Vibration. 2016, 367(2016): 233-249.
[8] 胡晓依, 何庆复, 王华胜. 基于STFT的振动信号解调方法及其在轴承故障检测中的应用.[J/OL] 振动与冲击. 2008, 27(2): 82-86.
Hu Xiao-yi, He Qing-fu, Wang Hua-sheng. Vibration Signal Demodulation Method Based on STFT and Its Application in Bearing Fault Detection [J]. ournal of Vibration and Shock. 2008, 27(2): 82-86.
[9] 王友仁, 王俊, 黄海安. 基于非线性短时傅里叶变换阶次跟踪的变速行星齿轮箱故障诊断.[J/OL] 中国机械工程. 2018, v.29；No.494(14): 54-61.
Wang You-ren, Wang Jun, Huang Hai-an. Fault Diagnosis of Variable Speed Planetary Gearbox Based on Nonlinear Short Time Fourier Transform Order Tracking. [J]. China Mechanical Engineering. 2018, v.29；No.494(14): 54-61.
[10] 宋军, 刘渝, 朱霞. LFM信号参数估计的插值FRFT算法.[J/OL] 系统工程与电子技术. 2011, 33(10): 2188-2193.
Song Jun, Liu Yu, Zhu Xia. Interpolation FRFT algorithm for LFM signal parameter estimation [J]. Journal of Systems Engineering and Electronics. 2011, 33(10): 2188-2193.
[11] 邓兵, 陶然, 齐林. 分数阶Fourier变换与时频滤波.[J/OL] 系统工程与电子技术
2004, 26(10): 1357-1359.
Deng Bing, Tao Ran, Qi Ling. Fractional Fourier Transform and Time-Frequency Filtering [J]. Journal of Systems Engineering and Electronics. 2004, 26(10): 1357-1359.
[12] 朱继梅. 非稳态振动信号分析(连载).[J/OL] 振动与冲击
2000, 19(3): 88-91.
Zhu Ji-mei. Unsteady vibration signal analysis (serial) [J]. Journal of Vibration and Shock. 2000, 19(3): 88-91.
[13] 黄克武, 陶然, 吴葵. 分数阶傅里叶域与时域联合干扰抑制研究.[J/OL] 中国科学:技术科学. 2011, (10): 1393-1404.
Huang Ke-wu, Tao Ran, Wu Kui. Research on Fractional Fourier Domain and Time Domain Joint Interference Suppression. [M]. Science of China : technology science . 2011, (10): 1393-1404.
[14] Wen Guangrui, Du Xiaowei, Zhang Zhifen. Research Progress of Rotor Startup Estimation with FRFT, 2016.
[15] Barshan Billur, Kutay M. Alper, Ozaktas Haldun M Optimal filtering with linear canonical transformations.[J/OL] Optics Communications. 1997, 135(1–3): 32-36.
[16] 鲁溟峰, 张峰, 倪国强. 工程采样系统的分数阶傅里叶域分析与改进.[J/OL] 电子与信息学报. 2013, 35(9): 2094-2099.
Lu Ming-Feng, Zhang Feng, Ni Guo-Qiang. Fractional Fourier Domain Analysis and Improvement of Engineering Sampling System [J]. Joural of Electronics & Information Technology. 2013, 35(9): 2094-2099.
[17] 郭波, 宋李彬, 周贵良. 分数阶傅里叶滤波在欺骗干扰中的应用研究.[J/OL] 电子学报. 2012, 40(7): 1328-1332.
Guo bo, Song Li-Bing, Zhou Gui-liang. Application Research of Fractional Fourier Filter in Deception Jamming [J]. Acta Electronic Sinica. 2012, 40(7): 1328-1332.
[18] Sharma Kamalesh Kumar, Joshi Shiv Dutt Signal separation using linear canonical and fractional Fourier transforms.[J/OL] Optics Communications. 2006, 265(2): 454-460.