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针对目前的柔性生产线质量诊断模式诊断速度慢、效果差以及不能及时处理不确定性和关联性问题等情况,提出了基于概率理论和图论的贝叶斯网络作为生产线质量诊断模型的方法。阐述了贝叶斯网络的数学模型描述及建立方法;讲述贝叶斯网络的诊断模型的诊断原理与建立过程;并以某缸体生产加工线的质量异常数据作为数据源,结合贝叶斯网络诊断推理建立了柔性生产线质量诊断模型实例,对生产过程进行快速诊断,从而验证模型的有效性。
In view of the fact that the current diagnosis model of flexible production line is slow in diagnosis, ineffective and can not deal with the uncertainties and the related problems in time, a Bayesian network based on probability theory and graph theory is proposed as a method for the quality diagnosis of production lines. The mathematical model description and establishment method of Bayesian network are expounded. The diagnostic principle and establishment process of the diagnostic model of Bayesian network are introduced. With the data of mass anomaly of production line of a certain cylinder as data source, combined with Bayesian network Diagnostic reasoning established a flexible production line quality diagnosis model examples, the rapid diagnosis of the production process to verify the validity of the model.