基于EMD-HMM的BIT间歇故障识别  

Intermittent Fault Diagnosis for Built-in Test System Based on EMD and HMM

作　　者：郭明威[1] 倪世宏[1] 朱家海[1] 

机构地区：[1]空军工程大学工程学院,西安710038

出　　处：《振动．测试与诊断》2012年第3期467-470,518,共4页Journal of Vibration,Measurement & Diagnosis

基　　金：航空科学基金资助项目(编号:20080896009)

摘　　要：针对引起机内测试系统(BIT)虚警的间歇故障,提出了一种基于经验模态分解(EMD)和隐马尔科夫模型(HMM)的间歇故障诊断方法以抑制虚警。首先对原始信号进行EMD分解,选择能量最大的几个固有模式分量函数(IMF)进行特征提取,作为系统状态的观测值;然后将观测值输入到训练好的HMM中进行决策,求取最大似然概率值作为识别结果。结果表明,利用EMD进行特征提取并与HMM方法相结合能很好地分类出各种状态,有效地诊断出间歇故障。An intermittent fault diagnosis approach based on EMD-HMM to restrain false alarm for Built-in test(BIT) is proposed.Firstly,EMD is employed to decompose the original signal,the several energy-dominating intrinsic mode functions(IMFs) are chosen and the energy feature parameters of each IMFs are extracted to form observed vectors of system.Then,the feature vectors are input into the trained HMM for malfunction recognition,the maximum log-likelihood probability is in the fault state.The results show that combining this feature vectors extracted method by EMD with HMM can diagnose intermittent fault effectively.

关 键 词：机内测试 虚警 间歇故障 经验模态分解 隐马尔科夫模型 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置] TH113[自动化与计算机技术—控制科学与工程]