A Methodology to Handle Spectral Smearing in Gearboxes Using Adaptive Mode Decomposition and Dynamic Time Warping

被引:17
作者
Choudhury, Madhurjya D. [1 ]
Hong, Liu [2 ]
Dhupia, Jaspreet S. [1 ]
机构
[1] Univ Auckland, Dept Mech Engn, Auckland 1010, New Zealand
[2] Wuhan Univ Technol, Sch Mech & Elect Engn, Wuhan 430070, Peoples R China
关键词
Fault detection; gearbox; order tracking; signal processing; speed fluctuation;
D O I
10.1109/TIM.2021.3056737
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Tacho-less order tracking is an effective tool for fault detection in gearboxes operating under speed fluctuations. This technique's performance depends on extracting instantaneous shaft speed information from a complex multicomponent gearbox signal, which is first preprocessed by a bandpass filter. However, spectral overlap resulting from the time-varying frequency components makes it challenging to isolate the shaft speed harmonic mono-component using this approach. In order to overcome such issues, an adaptive tacho-less order-tracking (OT) method combining the variational mode decomposition (VMD) and the fast dynamic time warping (FDTW) is proposed in this article. The proposed method first decomposes the measured gearbox vibration signal using VMD to estimate the instantaneous shaft speed profile to construct the shaft vibration signal. The gearbox vibration signal is then resampled based on the optimal warping path obtained by FDTW, which performs an "elastic" stretching and compression along the time axis of the extracted shaft vibration signal with respect to a sinusoidal reference signal with a constant shaft rotational frequency. Finally, the presence of gear fault is detected by constructing the order spectrum of the resampled vibration signal. The effectiveness of the proposed algorithm is demonstrated using both simulation analysis and experimental validation using measurements from two different wind-turbine gearboxes collected under test and field conditions, respectively.
引用
收藏
页数:10
相关论文
共 26 条
[1]  
[Anonymous], wind-turbine-gearbox-failures
[2]  
Bechhoefer E, 3 MW WIND TURBINE HI
[3]   Warped Variational Mode Decomposition With Application to Vibration Signals of Varying-Speed Rotating Machineries [J].
Chen, Shiqian ;
Yang, Yang ;
Dong, Xingjian ;
Xing, Guanpei ;
Peng, Zhike ;
Zhang, Wenming .
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2019, 68 (08) :2755-2767
[4]   Nonstationary Signal Denoising Using an Envelope-Tracking Filter [J].
Chen, Shiqian ;
Dong, Xingjian ;
Xiong, Yuyong ;
Peng, Zhike ;
Zhang, Wenming .
IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2018, 23 (04) :2004-2015
[5]   Application of frequency family separation method based upon EMD and local Hilbert energy spectrum method to gear fault diagnosis [J].
Cheng, Junsheng ;
Yu, Dejie ;
Tang, Jiashi ;
Yang, Yu .
MECHANISM AND MACHINE THEORY, 2008, 43 (06) :712-723
[6]  
Choudhury MD, 2018, IEEE ASME INT C ADV, P1124, DOI 10.1109/AIM.2018.8452406
[7]   Variational Mode Decomposition [J].
Dragomiretskiy, Konstantin ;
Zosso, Dominique .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2014, 62 (03) :531-544
[8]   Planetary Gearbox Fault diagnosis via Joint Amplitude and Frequency Demodulation Analysis Based on Variational Mode Decomposition [J].
Feng, Zhipeng ;
Zhang, Dong ;
Zuo, Ming J. .
APPLIED SCIENCES-BASEL, 2017, 7 (08)
[9]   Vibration signal models for fault diagnosis of planetary gearboxes [J].
Feng, Zhipeng ;
Zuo, Ming J. .
JOURNAL OF SOUND AND VIBRATION, 2012, 331 (22) :4919-4939
[10]   Application of tentative variational mode decomposition in fault feature detection of rolling element bearing [J].
Gong, Tingkai ;
Yuan, Xiaohui ;
Yuan, Yanbin ;
Lei, Xiaohui ;
Wang, Xu .
MEASUREMENT, 2019, 135 :481-492