基于云模型与证据理论的故障诊断方法

发布时间：2018-01-05 06:10

本文关键词：基于云模型与证据理论的故障诊断方法　出处：《组合机床与自动化加工技术》2017年04期 　论文类型：期刊论文

【摘要】：针对单一传感器无法对复杂设备进行故障诊断和证据理论难以合理获取BPA的问题,提出了一种基于云模型与证据理论的多传感器数据融合故障诊断方法;首先求取每个故障模型下各个特征参数的云模型参数,建立故障诊断云模型知识库;然后结合云模型知识库,求取各个测量参数的隶属度值,并转换为各个诊断证据体;最后通过证据理论组合规则将各个证据进行融合,在融合决策条件下求出诊断结果。实验结果表明,该方法能合理并有效地对复杂设备进行故障诊断。
[Abstract]:A multi-sensor data fusion fault diagnosis method based on cloud model and evidence theory is proposed to solve the problem that the single sensor can not diagnose the complex equipment and the evidence theory is difficult to obtain BPA reasonably. Firstly, the cloud model parameters of each characteristic parameter under each fault model are obtained, and the knowledge base of fault diagnosis cloud model is established. Then combined with cloud model knowledge base, the membership value of each measurement parameter is obtained and transformed into each diagnostic evidence body. Finally, each evidence is fused by the rule of evidence theory combination, and the diagnosis results are obtained under the condition of fusion decision. The experimental results show that the method is reasonable and effective in fault diagnosis of complex equipment.
【作者单位】：贵州大学现代制造技术教育部重点实验室;贵州大学机械工程学院;
【基金】：国家自然科学基金资助项目(51475097) 贵州省基础研究重大项目(黔科合JZ字[2014]2001)
【分类号】：TP212;TP277
【正文快照】： 0引言故障诊断技术往往是通过传感器对设备或产品进行监测,采集其状态数据,并在一定的判定规则下,通过与专家知识库进行对比判断,从而决断出故障的所在。在设备与产品都逐渐趋于复杂的今天,引起故障的因素也越来越复杂,同一故障可能会是不同的多个因素引起的,一个因素也可能引

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