| 在线式设备振动状态自动识别系统的研究 |
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| 引用本文： | 胡雄 沈永明. 在线式设备振动状态自动识别系统的研究[J]. 振动与冲击, 1997, 16(4): 6-11 |
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| 作者姓名： | 胡雄 沈永明 |
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| 作者单位： | 上海交通大学机械设备诊断中心(胡雄，陈兆能，佟德纯，朱继梅)，上海海运学院机械系(沈永明，沈一飞) |
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| 摘 要： | 本文应用自组织特征映照模型，以知识处理中的地势搜索原理为出发点，研究并提出了在线式设备状态自动识别系统的工作原理。该系统采用状态映照平面初始化方法，未知模式标定技术和在线识别技术，并结合知识库和规则推理的运用，有效地实现设备状态的分类。
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| 关 键 词： | 神经网络 故障诊断 模式识别 |
STUDY ON ON-LINE AUTO-IDENTIFICATION OF VIBRATION CONDITION OF RUNNING PLANT |
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| Hu Xiong Chen Zhaoneng Tong Decheng Zhu Jimei. STUDY ON ON-LINE AUTO-IDENTIFICATION OF VIBRATION CONDITION OF RUNNING PLANT[J]. Journal of Vibration and Shock, 1997, 16(4): 6-11 |
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| Authors: | Hu Xiong Chen Zhaoneng Tong Decheng Zhu Jimei |
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| Affiliation: | Hu Xiong Chen Zhaoneng Tong Decheng Zhu Jimei (The Center of Plant Diagnosis of Shanghai Jiaotong University)Shen Yongming Shen Yifei (Shanghai Maritime University) |
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| Abstract: | In the paper the principle of on-line automatic identification system of plant condition is studied appling the self-organization network and topography search method in knowledge processing. The system adopts the techniques of initialization of state mapping plane, calibration of unknown pattern and on-line identification and this makes plant condition clustering efficiently. Moreover the system has the property of real-time classification with simple and clear clustering style. The example fully shows the effectiveness of the system offered. |
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| Keywords: | neural network fault diagnosis modal identification |
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