| 捕获设备故障信号的神经网络模型 |
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| 引用本文： | 关惠玲 韩捷. 捕获设备故障信号的神经网络模型[J]. 振动、测试与诊断, 1998, 18(4): 252-255 |
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| 作者姓名： | 关惠玲 韩捷 |
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| 作者单位： | 郑州工业大学振动工程研究所!郑州450002 |
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| 基金项目： | 河南省自然科学基金资助项目!(编号 :974 0 4 0 50 0 ) |
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| 摘 要： | 探索和尝试以轴心轨迹为依据 ,以全等度、相似度和扩散度三个特征参数为输入的神经网络捕获设备故障信号模型 ,可大大提高故障症兆提取的效率和质量 ,并以大型化工装置透平压缩机组的监测系统为例做了应用说明
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| 关 键 词： | 智能监测 神经网络 故障症兆 故障诊断 |
A Neural Network Model for Capturing Machine Fault Signal |
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| Guan H uiling H an Jie L iang Chuan Yang Jincai. A Neural Network Model for Capturing Machine Fault Signal[J]. Journal of Vibration,Measurement & Diagnosis, 1998, 18(4): 252-255 |
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| Authors: | Guan H uiling H an Jie L iang Chuan Yang Jincai |
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| Abstract: | In order to greatly improve the efficiency and quaulity of extracting fault symp- tom,a neural network model forcapturing fault signals is developed by using three character- istic parameters defined in the paper as the input of the network,i.e.the equality,similarity and expansivity of the shaft centre orbit of a machine compared to the orbit of the shaft aquired under fault- free conditions.A practical application of the network to a monitoring system of a large turbin- compressor is made. |
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| Keywords: | monitoring intelligently neural network fault diagnosis fault symptom |
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