| 神经网络信息融合技术在岩石挖掘机系统故障诊断中的应用 |
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| 引用本文： | 康兴无,陈中华,王汉功,张霞. 神经网络信息融合技术在岩石挖掘机系统故障诊断中的应用[J]. 无损检测, 2004, 26(8): 388-390,427 |
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| 作者姓名： | 康兴无 陈中华 王汉功 张霞 |
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| 作者单位： | 第二炮兵工程学院,501室,西安,710025 |
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| 摘 要： | 将信息融合技术与神经网络结合起来，充分利用检测到的各种故障征兆信息准确诊断岩石挖掘机系统的故障。采用混合式数据融合方法，将数据级、特征级和决策级融合通过神经网络的方法综合在一起，解决输入信息不对称性问题，使得小数据量和大数据量的信息融合成为可能。
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| 关 键 词： | 神经网络 信息融合 故障诊断 信号处理 |
| 文章编号： | 1000-6656(2004)08-0388-03 |
INFORMATION FUSION TECHNOLOGY OF ARTIFICIAL NEURAL NETWORK FOR THE FAULT DIAGNOSIS OF TUNNEL BORING SYSTEM |
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| KANG Xing-wu,CHEN Zhong-hua,WANG Han-gong,ZHANG Xia. INFORMATION FUSION TECHNOLOGY OF ARTIFICIAL NEURAL NETWORK FOR THE FAULT DIAGNOSIS OF TUNNEL BORING SYSTEM[J]. Nondestructive Testing, 2004, 26(8): 388-390,427 |
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| Authors: | KANG Xing-wu CHEN Zhong-hua WANG Han-gong ZHANG Xia |
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| Abstract: | Combining of the information fusion with artificial neural networks, various testing information of fault symptoms could be fully used to diagnose the faults of tunnel boring system accurately. By adopting the hybrid data fusion structure method, the original-level, the characteristic-level and the decision-making-level fusions were integrated with artificial neural networks, which solved the problem of dissymmetry of the input information, and made the information fusion of small data quantity and large data quantity to be possible. |
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| Keywords: | Neural network Information fusion Fault diagnosis Signal processing |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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