| 双权法LSSVM在旋转设备故障诊断中的应用 |
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| 引用本文： | 刘晓华,朱海燕. 双权法LSSVM在旋转设备故障诊断中的应用[J]. 煤矿机械, 2011, 0(11): 239-241 |
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| 作者姓名： | 刘晓华 朱海燕 |
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| 作者单位： | 海军航空工程学院;山东工商学院计算机科学与技术学院; |
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| 基金项目： | 国家自然科学基金资助项目(60970105); 国家安监总局安全生产科技发展计划项目(07-383) |
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| 摘 要： | 由于旋转设备故障数据样本存在不平衡性,导致传统的LSSVM无法对异常值样本正确分类,为了解决这一问题,首先采用LSSVM从训练集中提取错分样本及其分类的支持向量,再根据各类故障样本数量对惩罚因子进行加权,以减少样本数量不平衡对分类结果的影响;然后根据错分样本到本类边界支持向量的距离,对松弛系数设置不同的权值,使错分的异常值样本分类得以修正。通过煤矿风机故障数据集验证了该算法分类效果明显优于传统的LSSVM方法。它有效地消除了因故障样本数据不平衡、样本分布异常对分类器造成的影响,提高了设备故障诊断的正确率。
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| 关 键 词： | 加权 最小二乘支持向量机(LSSVM) 故障诊断 |
Application of Double Weight LSSVM in Rotating Equipment Fault Diagnosis |
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| LIU Xiao-hua,,ZHU Hai-yan. Application of Double Weight LSSVM in Rotating Equipment Fault Diagnosis[J]. Coal Mine Machinery, 2011, 0(11): 239-241 |
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| Authors: | LIU Xiao-hua ZHU Hai-yan |
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| Affiliation: | LIU Xiao-hua1,2,ZHU Hai-yan2(1.Naval Aeronautical Engineering University,Yantai 264000,China,2.College of Computer Science,Shandong Institute of Business and Technology,Yantai 264005,China) |
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| Abstract: | Since imbalance exists in sample data of rotating equipment failure and traditional LSSVM fails to correctly classify abnormal samples,an imporved method is proposed in this thesis Double Weight LSSVM.First of all LSSVM to extract support vector of wrongly classified samples and their classification in training set,then use regularization factor is weighted on basis of different number of various fault samples to reduce effect of imbalance in sample size on classification.The wronly lassified abnormal sampl... |
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| Keywords: | weighting least squares suport vector machine fault diagnosis |
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