Application of HSMM on NC Machine's State Recognition

机译：HSMM在数控机床状态识别中的应用

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It is significant to identify the running-states of NC machines for ensuring the machining accuracy and running stability. Vibration diagnosis is an on-line prognostics and diagnosis technique by picking-up the frequency characters of the vibration signal on NC machine. In the paper, combining with the wavelet noise reduction and character extraction with varying scales, the Hidden Semi-Markov model is built by the example of headstock bearing abrasion to recognize the running-states effectively. According to experiment and simulation researches, it indicates that the veracity of identification is 96.7% in the 120 test samples after training the HSMM with 80 training samples. This fault diagnosis method is satisfied for the engineering demand, and it can be applied for vibration analysis for other complex machineries.

机译：确定数控机床的运行状态对于确保加工精度和运行稳定性具有重要意义。振动诊断是一种在线故障诊断技术，它通过在数控机床上获取振动信号的频率特性来进行诊断。本文结合小波降噪和不同尺度的特征提取，以车头轴承磨损为例，建立了隐半马尔可夫模型，有效地识别了运行状态。通过实验和仿真研究表明，用80个训练样本训练HSMM后，在120个测试样本中，识别的正确率为96.7％。该故障诊断方法可以满足工程需求，可用于其他复杂机械的振动分析。

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来源
《2010 International Conference on E-Health Networking, Digital Ecosystems and Technologie.;vol. 1.》|2010年|p.189-191|共3页
会议地点 Shenzhen(CN);Shenzhen(CN)
作者
Huang Qiang; Ding Zhihua; Zhang Xiao;
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作者单位

School of Mechanical and Materials Engineering Jiujiang University Jiangxi, P.R.China;

School of Mechanical and Materials Engineering Jiujiang University Jiangxi, P.R.China;

School of Mechanical and Materials Engineering Jiujiang University Jiangxi, P.R.China;

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中图分类计算机网络;计算机网络;计算机网络;
关键词
NC machine; state recognition; Hidden Semi-Markov Model;

机译：数控机床状态识别隐半马尔可夫模型;

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Application of HSMM on NC Machine's State Recognition

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