| 基于故障树和双向联想记忆神经网络的桥式起重机故障诊断方法 |
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| 引用本文： | 李煜,刘波峰,谭阳红,杨纯兴,陈湘林,詹国镇. 基于故障树和双向联想记忆神经网络的桥式起重机故障诊断方法[J]. 自动化与信息工程, 2014, 0(5): 1-6 |
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| 作者姓名： | 李煜 刘波峰 谭阳红 杨纯兴 陈湘林 詹国镇 |
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| 作者单位： | 1. 湖南大学电气与信息工程学院
2. 广州金仪自动化有限公司 |
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| 基金项目： | 国家自然科学基金(50277010)；广东省-教育部产学研结合项目(2012B09110340)；湖南省自然科学基金(07JJ6132)。 |
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| 摘 要： | 针对桥式起重机的故障诊断系统,提出一种基于故障树(FTA)和双向联想记忆神经网络(BAM)相结合的故障诊断方法。通过FTA建立系统故障树,收集桥式起重机所有故障模式,进而归纳出BAM的学习样本,然后对样本学习联想,得到系统诊断结果。两种方法的结合,不但可完成单个故障的诊断,还可实现多种故障的综合处理,提高诊断能力。
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| 关 键 词： | 桥式起重机 故障诊断 故障树 双向联想记忆神经网络 |
Fault Diagnosis System of Bridge Crane Based on FTA and BAM Neural Networks |
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| Li Yu,Liu Bofeng,Tan Yanghong,Yang Chunxing,Chen Xianglin,Zhan Guozhen. Fault Diagnosis System of Bridge Crane Based on FTA and BAM Neural Networks[J]. Automation & Information Engineering, 2014, 0(5): 1-6 |
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| Authors: | Li Yu Liu Bofeng Tan Yanghong Yang Chunxing Chen Xianglin Zhan Guozhen |
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| Affiliation: | Li Yu, Liu Bofeng, Tan Yanghong, Yang Chunxing, Chen Xianglin, Zhan Guozhen (1 .College of Electrical and Information Engineering in Hunan University 2.Guangzhou Jinyi Automation Co., Ltd.) |
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| Abstract: | The paper introduces a fault diagnosis system of Bridge Crane based on FTA and BAM neural networks. The FTA collects all the failure modes and inductive learning samples of BAM. Then BAM learns samples and gets system fault diagnosis. By combining the two methods, diagnostic capability is improved that it is not only to diagnose a single fault but also to handle multiple failures. |
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| Keywords: | Bridge Crane Fault Diagnosis FTA BAM Neural Networks |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
