| 基于优化的支持向量机的机械设备多故障诊断模型 |
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| 引用本文： | 蒋维,钟小强,陈开,李炎.基于优化的支持向量机的机械设备多故障诊断模型[J].计算机应用与软件,2009,26(1). |
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| 作者姓名： | 蒋维 钟小强 陈开 李炎 |
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| 作者单位： | 中国科学技术大学精密机械与精密仪器系,安徽,合肥,230027 |
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| 基金项目： | 中国科学院知识创新工程重要方向项目 |
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| 摘 要： | 提出了一种基于遗传算法优化支持向量机的故障诊断模型.它利用遗传算法对支持向量机同时对传统的时域特征参量子集和核参数同时优化,以达到选择最优的设备故障主导特征参数组合的目的,实现对机器不同类型故障的识别.对齿轮故障诊断的结果表明它有效提高了多分类支持向量机的故障分类准确性.
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| 关 键 词： | 支持向量机 遗传算法 特征选择 故障诊断 |
MECHANICAL EQUIPMENT FAULT DETECTION MODEL BASED ON GA OPTIMIZATION AND SVM |
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| Jiang Wei,Zhong Xiaoqiang,Chen Kai,Li Yan.MECHANICAL EQUIPMENT FAULT DETECTION MODEL BASED ON GA OPTIMIZATION AND SVM[J].Computer Applications and Software,2009,26(1). |
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| Authors: | Jiang Wei Zhong Xiaoqiang Chen Kai Li Yan |
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| Affiliation: | Department of Precision Machinery and Precision Instrumentation;University of Science and Technology of China;Hefei 230027;Anhui;China |
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| Abstract: | A new classification model based on genetic programming(GA) and support vector machine(SVM) for machine fault diagnosis is proposed.The model adopts the hybrid GA-SVM strategy which simultaneously performs the optimization of conventional time domain features parameters subset and core parameters for achieving the goal of selecting the optimal feature parameters combination related to fault of mechanical equipment,and realizing the recognition of different kinds of faults of machines.Experiments of gears fa... |
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| Keywords: | Support vector machine Genetic algorithm Feature selection Fault detection |
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