滚齿机网络化故障诊断专家系统的设计及应用

Networked fault diagnosis expert system of hobbing machine

针对滚齿机生产厂商和用户对提高故障诊断服务质量,降低故障诊断成本的迫切要求,提出了一种滚齿机网络化故障诊断专家系统。探讨了系统的网络化故障诊断运行模式、专家系统的体系结构;分析了系统实现的关键技术,包括系统实现的多源数据采集方法、知识表达和推理机制以及基于P2P(Peer-to-Peer)的网络体系结构,重点研究了基于SPF(System-Phenomenon-Fault)树的滚齿机网络化故障诊断系统的知识表达和推理机制实现方法,包括SPF树的定义、生成方法、树中元件的描述和树干的成长、树的数学描述、自学习过程、SPF树的检索和故障统计方法等。基于上述研究成果的原型系统在某滚齿机生产企业的初步应用表明,系统能够大幅度降低其售后服务成本,提高生产效率。

Aiming at the urgent needs of those manufacturing factories of hobbing machine and their consumers, who want to improve the quality of fault diagnosis in their after services, and reduce the costs of seeking for faults, a networked fault diagnosis expert system for hobbing machine tools based SPF tree （System-Phenomenon-Fault） is put forward. The operation model of this web-based system and the architecture of expert system are brought out firstly. Based on them, some key technologies are discussed, such as the methods of multi-source data acquisition, knowledge representation, the reasoning mechanism of the knowledge system, and the network architecture based on P2P（Peer-to-Peer）. Above all, the implementation methods of knowledge representation and reasoning mechanism based SPF tree are the points, which include the SPF’s definition, birth, description of elements, growth of tree trunk, mathematics description, learning-self process, statistic, retrieving and et al. A prototype system based on this study is tried out in a hobbing machine company and its feasibility has been verified in the application.