考虑突变状态检测的齿轮实时剩余寿命预测

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振动与冲击 ›› 2017, Vol. 36 ›› Issue (21) : 173-184.

论文

考虑突变状态检测的齿轮实时剩余寿命预测

石慧1，曾建潮1,2

作者信息 +

A Model for Real Time Remaining Useful Life Prediction of Gear Based on Abrupt Change Detection

SHI Hui1 ZENG Jianchao1,2

Author information +

文章历史 +

摘要

为解决齿轮疲劳退化过程中状态突变后剩余寿命难以准确预测问题，提出一种考虑退化突变点检测与剩余寿命预测相关联的齿轮疲劳实时剩余寿命预测新方法。首先针对齿轮磨损退化过程建立状态空间预测模型，利用接收到的齿轮实时监测振动信息实时更新模型参数，同时对退化过程中的突变状态点进行检测，并根据突变点所提供的寿命信息采用卡尔曼前向滤波及平滑算法结合期望最大化参数估计算法在滤波的同时不断对状态空间模型参数进行修正，改变退化突变后的滤波效果，进行实时状态预测与寿命估计。运用齿轮疲劳寿命试验台的实时监测数据对预测模型进行验证，结果表明利用突变点信息对预测模型进行修正后可以更快的对系统的动态变化进行跟踪，提高预测齿轮退化状态及实时剩余寿命的准确度。

Abstract

In order to solve the gear contact fatigue remaining useful life in the degradation process is difficult to accurately predict problems, a new method of real-time gear contact fatigue remaining useful life prediction is put forward that is a kind of integrated studies of abrupt change detection and remaining life prediction. Firstly, the state-space modelling for predicting degradation states of gear wear was established by using the real time monitoring vibration information received to update the model parameters. Using Kalman forward filtering and smoothing algorithm combined with parameter estimation of expectation–maximization algorithm, the prediction model was modified to change the filtering effect according to the life information of abrupt change detection provided. Using real-time monitoring data of the contact fatigue life of gear test rig to verify this model, the results show that a revised prediction model using abrupt point information can be faster to dynamic tracking system, improve the accuracy of gear degradation state and the real-time remaining useful life prediction.

导出引用

石慧1，曾建潮1,2. 考虑突变状态检测的齿轮实时剩余寿命预测[J]. 振动与冲击, 2017, 36(21): 173-184

SHI Hui1 ZENG Jianchao1,2. A Model for Real Time Remaining Useful Life Prediction of Gear Based on Abrupt Change Detection[J]. Journal of Vibration and Shock, 2017, 36(21): 173-184

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