基于可拓学和SVDD的轴箱轴承故障监测

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振动与冲击 ›› 2020, Vol. 39 ›› Issue (4) : 63-68.

论文

基于可拓学和SVDD的轴箱轴承故障监测

赵聪聪1，赵颖慧2，白杨3，刘玉梅4

作者信息 +

Fault monitoring for axlebox bearing based on extenics and support vector data description

ZHAO Congcong1，ZHAO Yinghui2，BAI Yang3，LIU Yumei4

Author information +

文章历史 +

摘要

为监测轴箱轴承的故障状态，提出了一种基于可拓学和支持向量数据描述(SVDD)的轴承故障监测方法。该方法充分利用了可拓学的定性定量描述特性和SVDD的单值分类特性：通过特征提取构建轴箱轴承的运行状态物元；训练SVDD的单值分类器，通过求取最小超球体的支持向量来获取物元模型的特征参数经典域；利用关联函数对轴箱轴承的故障状态进行定性定量评估。通过分析轴箱轴承的实际振动信号，证明了该方法的可行性及有效性。

Abstract

In order to monitor the fault state of axlebox bearings, a fault monitoring method based on extenics and support vector data description (SVDD) was proposed.This method made full use of the qualitative and quantitative description characteristic of extenics and the single value classification characteristic of SVDD.The operating state matter-element of an axlebox bearing was firstly constructed by feature extracting.And then, the single-valued classifier of SVDD was trained, and the classical domains of the feature parameters in the matter-element were obtained by finding the support vectors of the minimum hypersphere.Finally, the correlation function was used to evaluate the axlebox bearing's fault state qualitatively and quantitatively.The real vibration signal analysis of the axlebox bearing verifies the feasibility and effectiveness of the proposed method.

导出引用

赵聪聪1，赵颖慧2，白杨3，刘玉梅4. 基于可拓学和SVDD的轴箱轴承故障监测[J]. 振动与冲击, 2020, 39(4): 63-68

ZHAO Congcong1，ZHAO Yinghui2，BAI Yang3，LIU Yumei4. Fault monitoring for axlebox bearing based on extenics and support vector data description[J]. Journal of Vibration and Shock, 2020, 39(4): 63-68

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