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Flexible time domain averaging technique

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Abstract

Time domain averaging(TDA) is essentially a comb filter, it cannot extract the specified harmonics which may be caused by some faults, such as gear eccentric. Meanwhile, TDA always suffers from period cutting error(PCE) to different extent. Several improved TDA methods have been proposed, however they cannot completely eliminate the waveform reconstruction error caused by PCE. In order to overcome the shortcomings of conventional methods, a flexible time domain averaging(FTDA) technique is established, which adapts to the analyzed signal through adjusting each harmonic of the comb filter. In this technique, the explicit form of FTDA is first constructed by frequency domain sampling. Subsequently, chirp Z-transform(CZT) is employed in the algorithm of FTDA, which can improve the calculating efficiency significantly. Since the signal is reconstructed in the continuous time domain, there is no PCE in the FTDA. To validate the effectiveness of FTDA in the signal de-noising, interpolation and harmonic reconstruction, a simulated multi-components periodic signal that corrupted by noise is processed by FTDA. The simulation results show that the FTDA is capable of recovering the periodic components from the background noise effectively. Moreover, it can improve the signal-to-noise ratio by 7.9 dB compared with conventional ones. Experiments are also carried out on gearbox test rigs with chipped tooth and eccentricity gear, respectively. It is shown that the FTDA can identify the direction and severity of the eccentricity gear, and further enhances the amplitudes of impulses by 35%. The proposed technique not only solves the problem of PCE, but also provides a useful tool for the fault symptom extraction of rotating machinery.

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Authors and Affiliations

  1. School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, 710049, China

    Ming Zhao, Yaguo Lei & Xiufeng Wang

  2. State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong University, Xi’an, 710054, China

    Jing Lin

  3. Shaanxi Key Laboratory of Product Quality Assurance & Diagnosis, Xi’an, 710054, China

    Jing Lin, Yaguo Lei & Xiufeng Wang

Authors
  1. Ming Zhao
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  2. Jing Lin
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  3. Yaguo Lei
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  4. Xiufeng Wang
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Corresponding author

Correspondence to Jing Lin.

Additional information

This project is supported by National Natural Science Foundation of China(Grant Nos. 51125022, 51005173), PhD Programs Foundation of Ministry of Education of China(Grant No. 20110201110025), and the Fundamental Research Funds for the Central Universities of China

ZHAO Ming is currently a doctoral candidate at School of Mechanical Engineering, Xi’an Jiaotong University, China. He received his BS and MS degrees from Xi’an Jiaotong University, China, in 2006 and 2009, respectively. His research interests include non-stationary signal processing, rotor dynamics and fault diagnosis of rotating machinery.

LIN Jing is a professor at State Key Laboratory for Manufacturing System Engineering, Xi’an Jiaotong University, China He obtained his BSc, MSc and PhD degrees respectively in 1993, 1996 and 1999, all in mechanical engineering. He was working as a postdoctoral fellow and research associate from July 2001 to August 2003, respectively in University of Alberta, Canada, and University of Wisconsin-Milwaukee, USA. From September 2003 to December 2008, he was working as a research scientist at Institute of Acoustics, Chinese Academy of Sciences, under the sponsorship of the Hundred Talents Program. He also obtained the National Science Fund for Distinguished Young Scholars in 2011. Now his research directions are non-stationary signal processing, wavelet analysis, fault diagnosis and mechanical system reliability.

LEI Yaguo received his bachelor degree in 2002 and PhD degree in 2007 both in mechanical engineering from Xi’an Jiaotong University, China, and worked as a postdoctoral fellow at Department of Mechanical Engineering, University of Alberta, Canada. He is currently an associate professor in mechanical engineering of Xi’an Jiaotong University, China. His research interests include advanced signal processing techniques, hybrid intelligent prognostics and machinery health condition monitoring and fault diagnosis.

WANG Xiufeng received his BS and PhD degrees from Xi’an Jiaotong University in 2003 and 2009, respectively. He is currently a lecturer in mechanical engineering of Xi’an Jiaotong University, China. His research interests include rotor dynamics and vibration control.

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Zhao, M., Lin, J., Lei, Y. et al. Flexible time domain averaging technique. Chin. J. Mech. Eng. 26, 1022–1030 (2013). https://doi.org/10.3901/CJME.2013.05.1022

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  • DOI: https://doi.org/10.3901/CJME.2013.05.1022

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