Gear Contact Fatigue Life Prediction based on Multifractal Spectrum and Grey Model GM（1,1）

Zhang Ruiliang; Yan Tianxiao; Wang Tie; Liu Yaqiong

doi:10.16578/j.issn.1004.2539.2017.07.021

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Gear Contact Fatigue Life Prediction based on Multifractal Spectrum and Grey Model GM（1,1）

更新时间：2022-10-20

- Gear Contact Fatigue Life Prediction based on Multifractal Spectrum and Grey Model GM（1,1）
- Vol. 41, Issue 7, Pages: 97-101(2017)
- 作者机构：
  
  1. 太原理工大学齿轮研究所
  2. 上汽通用五菱汽车股份有限公司
  3. 广东威灵电机制造有限公司
- 作者简介：
- 基金信息：
- DOI：10.16578/j.issn.1004.2539.2017.07.021
  CLC：
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[1]张瑞亮,颜天晓,王铁,刘亚琼.基于多重分形谱和灰色模型GM(1,1)的齿轮接触疲劳寿命预测[J].机械传动,2017,41(07):97-101.

Zhang Ruiliang, Yan Tianxiao, Wang Tie, et al. Gear Contact Fatigue Life Prediction based on Multifractal Spectrum and Grey Model GM（1,1）. [J]. 41(7):97-101(2017)
[1]张瑞亮,颜天晓,王铁,刘亚琼.基于多重分形谱和灰色模型GM(1,1)的齿轮接触疲劳寿命预测[J].机械传动,2017,41(07):97-101. DOI： 10.16578/j.issn.1004.2539.2017.07.021.

Zhang Ruiliang, Yan Tianxiao, Wang Tie, et al. Gear Contact Fatigue Life Prediction based on Multifractal Spectrum and Grey Model GM（1,1）. [J]. 41(7):97-101(2017) DOI： 10.16578/j.issn.1004.2539.2017.07.021.

摘要

开展齿轮接触疲劳寿命预测对齿轮传动系统维护和使用具有重要意义。基于渐开线直齿轮接触疲劳台架运转试验采集的振动信号,应用多重分形去趋势分析对振动信号进行了分析,得到了多重分形谱,并构建了多重分形谱宽度指标用来表征齿轮接触疲劳退化;在此基础上,应用灰色模型GM（1,1）,建立了齿轮接触疲劳寿命预测模型;结合试验数据对寿命预测结果进行了验证。结果表明,提出的寿命预测方法具有较高的预测精度,预测结果可作为齿轮寿命估计的参考。

Abstract

The implement of gear contact fatigue life prediction（ CFLP） is critically important for maintenance and operation of gear transmission system. A novel method for gear CFLP based on vibration data collected from the run-to-failure test of involute spur gear is proposed. The multifractal detrended fluctuation analysis（ MF-DFA） is used to analyzed vibration data. As a result,the multifractal spectrum（ MFS） are obtained and the indicator for assessing gear contact condition deterioration is designed based on the width of MFS. Subsequently,the gear CFLP model is developed based on the proposed indicator and GM（ 1,1） model. The efficiency of this model is demonstrated by using experimental results. The results show that the proposed method delivers satisfactory performances with high precision and the prediction results can be used as a reference to gear life estimation.

关键词

齿轮接触疲劳寿命预测多重分形谱振动信号灰色模型

Keywords

Gear contact fatigueLife predictionMultifractal spectrumVibration signalGrey model

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