|
|||||
|
|
| 基于支持向量机的火车滚轴故障诊断 | |
| 引用本文： | 田景文,吴浩,高美娟.基于支持向量机的火车滚轴故障诊断[J].机床与液压,2007,35(7):248-250. |
| 作者姓名： | 田景文 吴浩 高美娟 |
| 作者单位： | 1. 北京化工大学信息科学与技术学院,北京,100029;北京联合大学自动化学院,北京,100101 2. 北京化工大学信息科学与技术学院,北京,100029 3. 北京联合大学自动化学院,北京,100101 |
| 摘 要： | 火车故障的60%都是由于滚轴问题引起的,现在的诊断方法都是基于知识的,但故障样本的不足从一定程度上制约了基于知识的方法在实际中的应用,针对这一问题,利用支持向量机在小样本情况下具有较强分类能力的特点,本文提出了一种基于支持向量机的滚轴故障诊断方法.该方法采用小波变换对齿轮的震动信号进行处理来构造特征向量,然后输入到支持向量机分类器中进行模式识别. |
| 关 键 词： | 滚轴 支持向量机 小波变换 故障诊断 支持向量机分类器 火车 滚轴 故障诊断 Support Vector Machine Based Roller Train Diagnosis 模式识别 输入 特征向量 构造 处理 震动信号 齿轮 变换对 小波 基于知识的方法 分类能力 |
| 文章编号： | 1001-3881（2007）7-248-3 |
| 修稿时间： | 2007-03-02 |
Fault Diagnosis of Train Roller Based on Support Vector Machine |
|
| TIAN Jingwen,WU Hao,GAO Meijuan.Fault Diagnosis of Train Roller Based on Support Vector Machine[J].Machine Tool & Hydraulics,2007,35(7):248-250. | |
| Authors: | TIAN Jingwen WU Hao GAO Meijuan |
| Affiliation: | 1. Beijing University of Chemical Technology, Beijing 100029, China; 2. Beijing Union University, Beijing 100101, China |
| Abstract: | The 60% fault of train is attributed to bearing problem. The method used for fault diagnosis is based on knowledge now. But lack of fault samples restricts the application of the methods based on knowledge in practical fault diagnosis to a certain extent. In order to solve this problem, a diagnosis method of bearing fault based on a support vector machine was proposed based on the advantage that a support vector machine has strong classification ability with fewer samples. According to this method, feature vectors were extracted from bearing vibration signals after wavelet transform and they were input into amultiole-fault classifier of the support vector machine for fault identification. |
| Keywords: | Bearing Support vector machine Wavelet transform Fault diagnosis |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |