| 基于改进半监督模糊C-均值聚类的发动机磨损故障诊断 |
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| 引用本文： | 徐超,张培林,任国全,傅建平. 基于改进半监督模糊C-均值聚类的发动机磨损故障诊断[J]. 机械工程学报, 2011, 47(17): 55-60. DOI: 10.3901/JME.2011.17.055 |
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| 作者姓名： | 徐超 张培林 任国全 傅建平 |
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| 作者单位： | 军械工程学院一系 石家庄050003 |
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| 基金项目： | 国家自然科学基金(50705097); 清华大学摩擦学国家重点实验室开放基金(SKLTKF09B06)资助项目 |
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| 摘 要： | 为解决在少量油液样本条件下发动机磨损故障诊断难的问题,提出一种改进半监督模糊C-均值聚类算法(Improvedsemi-supervised fuzzy c-means clustering algorithm,ISS-FCM).定义一种优化的目标函数,将无标签样本与训练样本间的平均距离度量考虑在内并赋予其一定权值,以...
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| 关 键 词： | 半监督模糊C-均值聚类 优化目标函数 AR模型 故障诊断 |
Engine Wear Fault Diagnosis Based on Improved Semi-supervised Fuzzy C-means Clustering |
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| XU Chao,ZHANG Peilin,REN Guoquan,FU Jianping. Engine Wear Fault Diagnosis Based on Improved Semi-supervised Fuzzy C-means Clustering[J]. Chinese Journal of Mechanical Engineering, 2011, 47(17): 55-60. DOI: 10.3901/JME.2011.17.055 |
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| Authors: | XU Chao ZHANG Peilin REN Guoquan FU Jianping |
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| Affiliation: | XU Chao ZHANG Peilin REN Guoquan FU Jianping(Department 1st,Ordnance Engineering College,Shijiazhuang 050003) |
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| Abstract: | A improved semi-supervised fuzzy c-means clustering algorithm(ISS-FCM) is proposed to diagnose engine wear faults with small oil samples.An optimized objective function,which is defined through introducing average distance measure between unlabeled samples and training samples with weighting values,is used to conduct the clustering process.To avoid local extrema originating from initialing partition matrix randomly,the training samples are utilized in partition matrix initialing work.By reason that engine w... |
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| Keywords: | Semi-supervised fuzzy C-means clustering Optimized objective function AR model Fault diagnosis |
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