基于威布尔分布及最小二乘支持向量机的滚动轴承退化趋势预测

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振动与冲击 ›› 2014, Vol. 33 ›› Issue (20) : 52-56.

论文

基于威布尔分布及最小二乘支持向量机的滚动轴承退化趋势预测

陈昌，汤宝平，吕中亮

作者信息 +

Degradation trend prediction of rolling bearing based on Weibull distribution and least squares support vector machine

CHEN Chang，TANG Bao-ping，Lü Zhong-liang

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文章历史 +

摘要

为有效描述滚动轴承的退化趋势，提出结合威布尔分布及最小二乘支持向量机的滚动轴承退化趋势预测新方法。用威布尔分布形状参数作为滚动轴承的性能退化指标，将该指标作为最小二乘支持向量机的输入构造退化趋势预测模型。鉴于最小二乘支持向量机模型参数对模型的推广预测能力影响较大，选粒子群算法(PSO)优化最小二乘支持向量机模型参数，并用实测滚动轴承全寿命实验数据进行检验。结果表明该方法能获得准确的预测结果。

Abstract

A new prediction method is proposed based on Weibull distribution and least squares support vector machine to describe the rolling bearing degradation trend. The shape parameter of Weibull distribution is used as bearing recession performance indicators. The indicators act as the input of the least squares support vector machine and then a prediction model is constructed. Due to the model parameters of least square support vector machine has an important influence on the predictive ability of the model, the proposed method choose particle swarm(PSO) algorithm to optimize the model parameters. The rolling bearing run-to-failure tests are carried out to inspect the prediction model, and the results demonstrate the effectiveness and accurateness of the proposed method.

导出引用

陈昌;汤宝平;吕中亮. 基于威布尔分布及最小二乘支持向量机的滚动轴承退化趋势预测[J]. 振动与冲击, 2014, 33(20): 52-56

CHEN Chang;TANG Bao-ping;Lü Zhong-liang. Degradation trend prediction of rolling bearing based on Weibull distribution and least squares support vector machine[J]. Journal of Vibration and Shock, 2014, 33(20): 52-56