A Comparative Study of Wear Debris and Vibration-Based Gear Damage Detection Methods Applied to Mild Wear in a Spur Gear System

被引:2
|
作者
Jangra, Dharmender [1 ]
Hirani, Harish [2 ]
机构
[1] Vivekananda Inst Profess Studies, Dept Appl Sci, Tech Campus, Delhi, India
[2] Indian Inst Technol, Dept Mech Engn, Delhi, India
关键词
Spur gear; Mild wear; Wear debris monitoring; Vibration parameters; PROGRESSION; FAILURE;
D O I
10.1007/s42417-024-01524-8
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Mild wear in gear transmission systems accounts for 41% of the gear flank surface failure mechanisms. Vibration detection parameters and wear debris methods are widely used for the condition monitoring of gear transmission systems experiencing mild wear. In this study an attempt has been made to predict the effectiveness of wear debris damage detection and vibration parameters in estimating the mild wear progressive failure which is a precursor of breakdown. The vibration parameters root mean square (RMS), kurtosis, crest factor, energy ratio (ER), FM0, and correlation coefficient of residual signal (CCR) are obtained from the time-averaged vibration data for two sets of run-to-failure experiments for the EN24 steel spur gear system. Each of these experiments are performed at a constant speed (1200 RPM) and torque (40 Nm). Wear debris monitoring is performed online. The ER and FM0 have been found to consistently increase after 140 h, indicating initiation of progressive failure. The RMS and CCR values are found to be inconsistent in indicating initiation of failure. The kurtosis and crest factor parameters possessed constant behavior with respect to time. The number of wear debris particles changes at 110 h and 160 h respectively, showing the initiating and limiting values before the occurrence of severe wear for the first set of the experiment; similarly, 110 h and 140 h for the second set of experiment. Overall, it is found that the wear debris method could effectively predict the failure mechanism much earlier in comparison to parallelly obtained vibration indicators ER and FM0.
引用
收藏
页码:9077 / 9087
页数:11
相关论文
共 50 条
  • [1] A Comparative Study of Wear Debris and Vibration-Based Gear Damage Detection Methods Applied to Mild Wear in a Spur Gear System (aug, 10.1007/s42417-024-01524-8, 2024)
    Jangra, Dharmender
    Hirani, Harish
    JOURNAL OF VIBRATION ENGINEERING & TECHNOLOGIES, 2024, 12 : 2405 - 2405
  • [2] Investigation of spur gear fatigue damage using wear debris
    Dempsey, PJ
    Morales, W
    Afjeh, AA
    LUBRICATION ENGINEERING, 2002, 58 (11): : 18 - 22
  • [3] Investigation of spur gear fatigue damage using wear debris©
    Dempsey, Paula J.
    Morales, Wilfredo
    Afjeh, Abdollah A.
    2002, Society of Tribologists and Lubrication Engineers (58):
  • [4] Vibration-Based System Degradation Monitoring under Gear Wear Progression
    Feng, Ke
    Ni, Qing
    Zheng, Jinde
    COATINGS, 2022, 12 (07)
  • [5] A review of vibration-based gear wear monitoring and prediction techniques
    Feng, Ke
    Ji, J. C.
    Ni, Qing
    Beer, Michael
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2023, 182
  • [6] Vibration-based monitoring and prediction of surface profile change and pitting density in a spur gear wear process
    Feng, Ke
    Smith, Wade A.
    Randall, Robert B.
    Wu, Hongkun
    Peng, Zhongxiao
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2022, 165
  • [7] Vibration-based monitoring and prediction of surface profile change and pitting density in a spur gear wear process
    Feng, Ke
    Smith, Wade A.
    Randall, Robert B.
    Wu, Hongkun
    Peng, Zhongxiao
    Mechanical Systems and Signal Processing, 2022, 165
  • [8] Use of an improved vibration-based updating methodology for gear wear prediction
    Feng, Ke
    Smith, Wade A.
    Peng, Zhongxiao
    ENGINEERING FAILURE ANALYSIS, 2021, 120 (120)
  • [9] The effect of tooth wear on the vibration spectrum of a spur gear pair
    Kuang, JH
    Lin, AD
    JOURNAL OF VIBRATION AND ACOUSTICS-TRANSACTIONS OF THE ASME, 2001, 123 (03): : 311 - 317
  • [10] Spur gear wear analysis as applied for tribological based predictive maintenance diagnostics
    Raadnui, Surapol
    WEAR, 2019, 426 : 1748 - 1760