Remaining life prediction of rolling bearings based on the WV-EWMA and the Wiener process with random failure thresholds

LI Junxing; FAN Junbiao; FAN Jiahui

doi:10.16579/j.issn.1001.9669.2026.02.004

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Remaining life prediction of rolling bearings based on the WV-EWMA and the Wiener process with random failure thresholds

·Vibration·Noise·Monitoring·Diagnosis· | 更新时间：2026-02-12

- Remaining life prediction of rolling bearings based on the WV-EWMA and the Wiener process with random failure thresholds
- Journal of Mechanical Strength Vol. 48, Issue 2, Pages: 31-39(2026)
- 作者机构：
  
  1.河南科技大学机电工程学院，洛阳 471000
  2.高端轴承河南省协同创新中心，洛阳 471003
- 作者简介：
  
  LI Junxing, E-mail: lijun-xing2008@163.com
- 基金信息：
  
  National Natural Science Foundation of China(52005159);Young Scientists Program of the Joint Fund of Henan Provincial Science and Technology R&D Plan(225200810073);Applied Technology Research Program of the Joint Fund of Henan Provincial Science and Technology R&D Plan(232103810043);Science and Technology Innovation Talent Support Program for Universities of Henan Province(24HASTIT043);Young Backbone Teacher Training Program for Institutions of Higher Education in Henan Province(2021GGJS048);Young Talent Cultivation Program of Henan Province(2023HYTP050)
- DOI：10.16579/j.issn.1001.9669.2026.02.004
  CLC： TH133.33
- Received：24 April 2024，
  
  Published：15 February 2026
- 稿件说明：
移动端阅览
李军星，樊俊彪，樊嘉辉. 基于WV-EWMA与具有随机失效阈值Wiener过程的滚动轴承剩余寿命预测［J］. 机械强度，2026，48（2）：31-39.

LI Junxing，FAN Junbiao，FAN Jiahui. Remaining life prediction of rolling bearings based on the WV-EWMA and the Wiener process with random failure thresholds［J］. Journal of Mechanical Strength，2026，48（2）：31-39.
李军星，樊俊彪，樊嘉辉. 基于WV-EWMA与具有随机失效阈值Wiener过程的滚动轴承剩余寿命预测［J］. 机械强度，2026，48（2）：31-39. DOI： 10.16579/j.issn.1001.9669.2026.02.004.

LI Junxing，FAN Junbiao，FAN Jiahui. Remaining life prediction of rolling bearings based on the WV-EWMA and the Wiener process with random failure thresholds［J］. Journal of Mechanical Strength，2026，48（2）：31-39. DOI： 10.16579/j.issn.1001.9669.2026.02.004.

摘要

目的

针对轴承性能演化过程中平稳和退化2个阶段的特点，实现对滚动轴承剩余寿命的预测。

方法

首先，考虑到平稳阶段性能参数的随机分布有时是未知的这一情况，提出基于赋权方差-指数加权移动平均（Weighted Variance-Exponentially Weighted Moving Average

WV-EWMA）控制图的轴承健康状态监测与变点识别方法，以识别出初始退化时刻；其次，对于退化阶段，建立基于Wiener过程的退化表征模型，并考虑到轴承的个体差异性，假设失效阈值为随机变量，推导出轴承剩余寿命分布模型；再次，利用极大似然估计法和贝叶斯理论在线预测了滚动轴承的剩余寿命；最后，利用16004型滚动轴承试验进行了工程验证。

结果

结果表明，与传统方法相比，建立的方法对滚动轴承剩余寿命预测的精度至少提高了55.98%。

Abstract

Objective

Aiming at the characteristics of stable stage and degradation stage during the performance evolution process of bearings

this study realizes the prediction of the remaining useful life of rolling bearings.

Methods

Firstly

considering that the random distribution of performance parameters in the stable stage is sometimes unknown

a bearing health condition monitoring and change point detection method based on the weighted variance-exponentially weighted moving average (WV-EWMA) control chart was proposed to identify the initial degradation time. Secondly

for the degradation stage

a degradation characterization model based on the Wiener process was established. Taking into account the individual differences of bearings

the failure threshold was assumed to be a random variable

and the remaining useful life distribution model of bearings was derived. Thirdly

the remaining useful life of rolling bearings were predicted online using the maximum likelihood estimation method and Bayesian theory. Finally

engineering verification was conducted via tests of type 16004 rolling bearings.

Results

The results indicate that

compared to traditional methods

the prediction accuracy for the remaining useful life of rolling bearing of the proposed method is improved by at least 55.98%.

关键词

Keywords

references

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