| 基于HMM在电机故障诊断上的研究 |
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| 引用本文： | 于天剑,;陈雅婷,;陈特放,;陈春阳.基于HMM在电机故障诊断上的研究[J].长沙铁道学院学报,2014(4):103-108. |
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| 作者姓名： | 于天剑 ;陈雅婷 ;陈特放 ;陈春阳 |
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| 作者单位： | [1]中南大学交通运输学院,湖南长沙410075; [2]中南大学信息科学与工程学院,湖南长沙410075 |
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| 基金项目： | 国家自然科学基金资助项目（61273158） |
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| 摘 要： | 提出一种基于隐马尔可夫模型的方法用于故障的诊断与检测,该方法采用HMM与模式识别相结合的方法,通过对电机的电压电流信号进行特征提取和分析,构建电压电流空间模型,并且每个模型可以作为一级,每一级可以提高其判断的准确度,而HMM模型用做一个故障分类器来使用,相比于自适应模糊推理方法（MLFF）和多层前馈网络法（ANFIS）,其准度有了很大提高,并且减少了计算。通过对不同故障诊断实例阐述了基于HMM的故障诊断方法的有效性和可行性。
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| 关 键 词： | 故障诊断 隐马尔可夫模型 感应电机 模式识别 |
Research on motor fault diagnosis based on HMM |
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| Institution: | YU Tianjian, CHEN Yating, CHEN Tefang, CHEN Chunyang( 1. School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China 2. School of Information Science and Engineering, Central South University, Changsha 410075, China) |
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| Abstract: | A method of hidden Markov based on Markov models was proposed in this paper for diagnosis and fault detection. Thereinto,the method combining HMM technique and pattern recognition feature can be utilized to extract and analyze the voltage and current signals of the motor,thereby constructing the voltage and the current space model. Moreover,each model can be regarded as a level which could improve the judging accuracy,while HMM model was used as a fault classifier,and in comparison with the adaptive fuzzy reasoning method（ MLFF）and multilayer feed-forward network（ ANFIS）,its accuracy was improved greatly with less calculation number.Finally,the effectiveness of the method of fault diagnosis based on HMM and the feasibility were verified through the different fault diagnosis examples. |
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| Keywords: | fault diagnosis HMM model induction motor pattern recognition |
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