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| 基于EMD-HMM的故障诊断模型及应用 | |
| 引用本文： | 葛小凯,胡剑波,宁江涛,周红建,王世甲.基于EMD-HMM的故障诊断模型及应用[J].数学的实践与认识,2012,42(6):138-144. |
| 作者姓名： | 葛小凯 胡剑波 宁江涛 周红建 王世甲 |
| 作者单位： | 1. 空军工程大学工程学院装备管理系,陕西西安,710038 2. 空军司令部,北京,100072 3. 空军装备研究院总体所,北京,100076 |
| 基金项目： | 2011年空军工程大学工程学院科研创新基金，上海市重点学科建设基金 |
| 摘 要： | 提出了基于经验模式分解(EMD)和隐马尔科夫模型(HMM)的故障诊断模型,为通过设备状态监测数据分析进行基于状态维修和维修决策提供了一种新途径.为了消除EMD的端点效应,使用神经网络拟合延拓原始数据序列端点极值,并通过定义序列复杂度来定性地确定延拓极点数.进一步,采用分解所得的固有模态(IMF)能谱熵作为HMM分类系统的输入,得到一种设备故障诊断方案.通过数值仿真和发动机故障诊断验证了该方法的有效性. |
| 关 键 词： | 经验模式分解 端点效应 隐马尔科夫模型 故障诊断 神经网络 |
Diagnostic Model Based on EMD-HMM and Its Application |
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| GE Xiao-kai , HU Jian-bo , NING Jiang-tao , ZHOU Hong-jian , WANG Shi-jia.Diagnostic Model Based on EMD-HMM and Its Application[J].Mathematics in Practice and Theory,2012,42(6):138-144. | |
| Authors: | GE Xiao-kai HU Jian-bo NING Jiang-tao ZHOU Hong-jian WANG Shi-jia |
| Institution: | 1 (1.Engineering College,Air Force University of Engineering,Xi’an Shaanxi 710038,China) (2.Air Command,Beijing 100072,China) (3.Air Force Equipment Research Academe,Beijing 100076,China) |
| Abstract: | An diagnostic model based on Empirical Mode Decomposition(EMD) and Hidden Markov Model(HMM) is presented,which provides a new way to condition based maintenance and maintenance decision by analyzing condition monitoring data of equipments.In order to eliminate end effect problem of EMD,additional extremums is obtained by neural network and series complexity is defined to identify the numbers to be extended.Further more the Intrinsic Mode Function(IMF) energy entropy is defined which is used as the input of HMM classify diagnostic scheme.The result of numerical simulation and its application in aerial engine diagnosis validate the effectiveness of this method. |
| Keywords: | empirical mode decomposition end effect hidden markov model fault diagnostics neural network |
| 本文献已被 CNKI 万方数据 等数据库收录！ | |