| 基于故障树和神经网络模型的提升机故障诊断专家系统 |
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| 引用本文： | 周瑾,肖兴明. 基于故障树和神经网络模型的提升机故障诊断专家系统[J]. 矿山机械, 2004, 0(5): 39-41 |
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| 作者姓名： | 周瑾 肖兴明 |
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| 作者单位： | 南京航空航天大学机电学院,江苏南京,210016;南京理工大学机械工程学院;中国矿业大学机电与材料工程学院 |
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| 摘 要： | 根据提升机故障源多、诊断复杂的特点,提出了可提高设备使用率、运行可靠安全的故障诊断专家系统。
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| 关 键 词： | 提升机 故障诊断 专家系统 |
search on Fault Diagnostic Expert System for Mine Hoist Based onFault Tree and Neural Network</b></span></td>
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<td align="left" height="25" valign="top" colspan=2"><author>OU Jin et al.. <title>search on Fault Diagnostic Expert System for Mine Hoist Based onFault Tree and Neural Network[J]. Mining & Processing Equipment, 2004, 0(5): 39-41</td>
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<td align="left" height="25" valign="top" nowrap><b>Authors:</b></td><td width="92%" valign="top" align="left" ><author>OU Jin et al.</td>
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<td align="left" height="25" valign="top" nowrap><b>Affiliation:</b></td><td width="92%" valign="top" align="left" ><author>OU Jin et al.</td>
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<td align="left" height="25" valign="top" nowrap><b>Abstract:</b></td><td width="92%" align="left" valign="top"><abstract>cording to the fault characteristics of the mine hoist, a proper intelligent fault diagnostic expert system is proposed, the paper presents a fault diagnostic method based on fault tree and neural network model. The knowledge representation adopts the shallow and deep knowledge integrated technology, and it is also based upon fault tree and is based on integrating of frame, rule, neural as well. The inference engine is built in forward and backward combined reasoning strategy, and depth-first searching theory. It is proved by practice that the expert system can increase the safety, reliability and efficiency of the mine hoist efficiently.</td>
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<td align="left" valign="top" height="25" nowrap><b>Keywords:</b></td><td width="92%" valign="top" align="left" ></td>
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