张寿明, 于蕊, 毕贵红, 何冬康. 基于AR和HMM的锅炉泄漏声发射信号识别方法[J]. 云南大学学报(自然科学版), 2016, 38(3): 383-391. doi: 10.7540/j.ynu.20150266
引用本文: 张寿明, 于蕊, 毕贵红, 何冬康. 基于AR和HMM的锅炉泄漏声发射信号识别方法[J]. 云南大学学报(自然科学版), 2016, 38(3): 383-391. doi: 10.7540/j.ynu.20150266
ZHANG Shou-ming, YU Rui, BI Gui-hong, HE Dong-kang. The identify method of boiler leakage acoustic emission signal based on AR and HMM[J]. Journal of Yunnan University: Natural Sciences Edition, 2016, 38(3): 383-391. DOI: 10.7540/j.ynu.20150266
Citation: ZHANG Shou-ming, YU Rui, BI Gui-hong, HE Dong-kang. The identify method of boiler leakage acoustic emission signal based on AR and HMM[J]. Journal of Yunnan University: Natural Sciences Edition, 2016, 38(3): 383-391. DOI: 10.7540/j.ynu.20150266

基于AR和HMM的锅炉泄漏声发射信号识别方法

The identify method of boiler leakage acoustic emission signal based on AR and HMM

  • 摘要: 声发射信号普遍存在于锅炉泄漏事故中,若能在事故发生时及时对泄漏声发射信号分类,采取相应补救措施,则可以有效减少损害.提出一种基于自回归模型(AR)和隐马尔科夫模型(HMM)的锅炉泄漏声发射信号识别方法,首先采集敲击、砂纸和断铅3种模拟泄漏声发射信号,对信号进行分帧处理,然后提取每帧信号AR特征值,最后利用HMM对特征参数进行训练和测试.试验结果表明,该方法识别正确率高达91.1%,证明将AR和HMM相结合可以有效识别敲击、砂纸和断铅3种模拟声发射信号,为锅炉泄漏故障的可视化诊断奠定了一定的基础.

     

    Abstract: Acoustic emission signals exist in the boiler leakage accident widely.It can reduce the harm to boiler if classify acoustic emission signal's type when the accident occurred effectively.It put forward a classification method based on the autoregressive model and hidden Markov model.Firstly we gathered tapping,sand paper and broken lead three kind of simulated leakage acoustic emission signals,and adopted the method of framing to the acoustic emission signals.Then we extracted characteristic value using the autoregressive model (AR) for each frame signal.Finally we used hidden Markov model (HMM) to train and test characteristic parameters.The test results showed that the recognition accuracy is 91.1%.It identifies that the method based on AR and HMM can identify three types of simulated acoustic emission signals effectively.It provided the basis for visual diagnosis of boiler leakage fault.

     

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