Chinese Journal of Mechanical Engineering >

2021 , Vol. 34 >Issue 4: 82 - 82

DOI: https://doi.org/10.1186/s10033-021-00603-1

Intelligent Manufacturing Technology

Acoustics Based Monitoring and Diagnostics for the Progressive Deterioration of Helical Gearboxes

  • Kaibo Lu ,
  • James Xi Gu ,
  • Hongwei Fan ,
  • Xiuquan Sun ,
  • Bing Li ,
  • Fengshou Gu
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  • 1. College of Mechanical and Vehicle Engineering, Taiyuan University of Technology, Taiyuan 030024, China;
    2. School of Engineering, University of Bolton, Bolton BL3 5AB, UK;
    3. College of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an 710054, China;
    4. Centre for Efficiency and Performance Engineering, University of Huddersfield, Huddersfield HD1 3DH, UK;
    5. School of Industrial Automation, Beijing Institute of Technology, Zhuhai 519088, China

收稿日期: 2020-06-02

  修回日期: 2021-04-13

  网络出版日期: 2021-12-21

基金资助

Supported by Shaanxi Key Laboratory of Mine Electromechanical Equipment Intelligent Monitoring, Xi'an University of Science and Technology (Grant No. SKL-MEEIM201904), and National Natural Science Foundation of China (Grant Nos. 51805352, 51605380)

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Acoustics Based Monitoring and Diagnostics for the Progressive Deterioration of Helical Gearboxes

  • Kaibo Lu ,
  • James Xi Gu ,
  • Hongwei Fan ,
  • Xiuquan Sun ,
  • Bing Li ,
  • Fengshou Gu
Expand
  • 1. College of Mechanical and Vehicle Engineering, Taiyuan University of Technology, Taiyuan 030024, China;
    2. School of Engineering, University of Bolton, Bolton BL3 5AB, UK;
    3. College of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an 710054, China;
    4. Centre for Efficiency and Performance Engineering, University of Huddersfield, Huddersfield HD1 3DH, UK;
    5. School of Industrial Automation, Beijing Institute of Technology, Zhuhai 519088, China

Received date: 2020-06-02

  Revised date: 2021-04-13

  Online published: 2021-12-21

Supported by

Supported by Shaanxi Key Laboratory of Mine Electromechanical Equipment Intelligent Monitoring, Xi'an University of Science and Technology (Grant No. SKL-MEEIM201904), and National Natural Science Foundation of China (Grant Nos. 51805352, 51605380)

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摘要

Gearbox condition monitoring (CM) plays a significant role in ensuring the operational reliability and efficiency of a wide range of critical industrial systems such as wind turbines and helicopters. Accurate and timely diagnosis of gear faults will improve the maintenance of gearboxes operating under sub-optimal conditions, avoid excessive energy consumption and prevent avoidable damages to systems. This study focuses on developing CM for a multi-stage helical gearbox using airborne sound. Based on signal phase alignments, Modulation Signal Bispectrum (MSB) analysis allows random noise and interrupting events in sound signals to be suppressed greatly and obtains nonlinear modulation features in association with gear dynamics. MSB coherence is evaluated for selecting the reliable bi-spectral peaks for indication of gear deterioration. A run-to-failure test of two industrial gearboxes was tested under various loading conditions. Two omnidirectional microphones were fixed near the gearboxes to sense acoustic information during operation. It has been shown that compared against vibration based CM, acoustics can perceive the responses of vibration in a larger areas and contains more comprehensive and stable information related to gear dynamics variation due to wear. Also, the MSB magnitude peaks at the first three harmonic components of gear mesh and rotation components are demonstrated to be sufficient in characterizing the gradual deterioration of gear transmission. Consequently, the combining of MSB peaks with baseline normalization yields more accurate monitoring trends and diagnostics, allowing the gradual deterioration process and gear wear location to be represented more consistently.

关键词： Acoustics; Modulation Signal Bispectrum; Helical gearbox; Gear wear

本文引用格式

Kaibo Lu , James Xi Gu , Hongwei Fan , Xiuquan Sun , Bing Li , Fengshou Gu . Acoustics Based Monitoring and Diagnostics for the Progressive Deterioration of Helical Gearboxes[J]. Chinese Journal of Mechanical Engineering, 2021 , 34(4) : 82 -82 . DOI: 10.1186/s10033-021-00603-1

Abstract

Gearbox condition monitoring (CM) plays a significant role in ensuring the operational reliability and efficiency of a wide range of critical industrial systems such as wind turbines and helicopters. Accurate and timely diagnosis of gear faults will improve the maintenance of gearboxes operating under sub-optimal conditions, avoid excessive energy consumption and prevent avoidable damages to systems. This study focuses on developing CM for a multi-stage helical gearbox using airborne sound. Based on signal phase alignments, Modulation Signal Bispectrum (MSB) analysis allows random noise and interrupting events in sound signals to be suppressed greatly and obtains nonlinear modulation features in association with gear dynamics. MSB coherence is evaluated for selecting the reliable bi-spectral peaks for indication of gear deterioration. A run-to-failure test of two industrial gearboxes was tested under various loading conditions. Two omnidirectional microphones were fixed near the gearboxes to sense acoustic information during operation. It has been shown that compared against vibration based CM, acoustics can perceive the responses of vibration in a larger areas and contains more comprehensive and stable information related to gear dynamics variation due to wear. Also, the MSB magnitude peaks at the first three harmonic components of gear mesh and rotation components are demonstrated to be sufficient in characterizing the gradual deterioration of gear transmission. Consequently, the combining of MSB peaks with baseline normalization yields more accurate monitoring trends and diagnostics, allowing the gradual deterioration process and gear wear location to be represented more consistently.

Key words： Acoustics; Modulation Signal Bispectrum; Helical gearbox; Gear wear

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