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基于贝叶斯网络的数控机床电主轴故障分析

发表时间:2017-04-27  浏览量:1319  下载量:298
全部作者: 王泽星,李德宝,何其昌,唐火红
作者单位: 合肥工业大学机械工程学院;上海交通大学机械与动力工程学院
摘 要: 数控机床故障分析对提升数控机床可靠性具有重要意义。针对数控机床电主轴,结合故障树分析法(fault tree analysis,FTA)和贝叶斯网络进行故障分析。首先分析电主轴结构,建立其故障树;然后将故障树转变为贝叶斯网络,并修改网络节点状态数,以弥补故障树存在的不足;最后基于Matlab的贝叶斯网络工具箱,结合历史数据构建贝叶斯网络模型,并通过试验验证该模型的有效性。
关 键 词: 机械设计;电主轴;故障树分析法;贝叶斯网络;贝叶斯网络工具箱
Title: Fault analysis of motorized spindle of CNC machine tools based on Bayesian network
Author: WANG Zexing, LI Debao, HE Qichang, TANG Huohong
Organization: School of Mechanical Engineering, Hefei University of Technology; School of Mechanical Engineering, Shanghai Jiao Tong University
Abstract: The failure analysis of computer numerical control (CNC) machine tools is of great significance to improve the reliability of CNC machine tools. Combined with fault tree analysis (FTA) and Bayesian network, this paper aims at the fault analysis of motorized spindle of CNC machine tools. First of all, we analyzed the structure of motorized spindle, then established its own fault tree. Secondly, we transformed the fault tree into a Bayesian network, and modifed the numbers of nodes’ statuses in the network to make up the deficiency of the fault tree as well. Finally, we built the Bayesian network model based on the Bayesian network toolbox of Matlab as well as combing with the historical data and verified the effectiveness of the model by experiments.
Key words: machine design; motorized spindle; fault tree analysis; Bayesian network; Bayesian network toolbox
发表期数: 2017年4月第8期
引用格式: 王泽星,李德宝,何其昌,等. 基于贝叶斯网络的数控机床电主轴故障分析[J]. 中国科技论文在线精品论文,2017,10(8):823-829.
 
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