制造过程不确定质量异常诊断的Stateflow方法

Stateflow-based uncertain quality abnormity diagnosis for manufacturing process

模糊推理Petri网可以对制造过程不确定质量异常诊断进行有效建模,但其复杂的图形表示及模糊推理逻辑结构使模型难于进行仿真分析.通过建立模糊推理规则与Stateflow元素之间的映射关系,将模糊推理Petri网模型转换为便于仿真的Stateflow模型,模型以质量控制图异常模式数据作为输入,实现不确定质量异常诊断过程的动态展示.某工件加工过程不确定质量异常诊断的仿真结果表明,模型可以输出引发控制图实时异常的异常原因的贡献度,为异常消除提供决策支持.

Fhzzy reasoning Petri nets （FRPNs） can model the uncertain quality abnormity diagnosis of manufacturing process effectively. But it is hard to simulate the model because of its complex graphical notation and logic structure of fuzzy reasoning. A mapping relation between the fuzzy reasoning rules and elements of Stateflow was designed, so the FRPNs model was converted into Stateflow model that can be simulated conveniently. The Stateflow model took quality abnormal pattern data of control chart as input, and showed the uncertain quality abnormity diagnosis process dynamically. Taking uncertain quality abnormity diagnosis of some workpiece as an example, the application process of proposed approach was introduced in detail. The experimental results show that this model can output the contribution degree of assignable causes to current control chart abnormity, and offers decision support for eliminating the abnormity.