基于Petri网的加工单元异常状态追溯方法  

Method for Tracing Abnormal State of Processing Cell Based on Petri Net

作　　者：赵家泰 李鹏忠[1] 罗亮[2] 

机构地区：[1]同济大学机械与能源工程学院 [2]同济大学中德学院

出　　处：《工程机械》2024年第4期7-12,I0012,共7页Construction Machinery and Equipment

摘　　要：智能生产系统中出现低于警戒线的异常指标时,由于加工单元受多设备生产状态的同时影响,很难从海量耦合的生产数据中准确识别加工单元的实际状态,并探究引起异常的根本原因。基于KPI计算模块和数据采集模块设计异常追溯模块。基于Petri网技术,首先建立加工单元多设备状态融合模型,再通过状态码转化规则,将状态标识矩阵转化为加工单元状态码,并赋予准确统一的语义,进而建立加工单元的生产状态空间。针对生产系统异常指标,通过分析异常状态码,可以查询生产状态空间,得到异常的根本原因,从而验证了异常追溯模块的实用性。When abnormal indicators below the alert line appear in the intelligent manufacturing system.It is difficult to accurately identify the actual state of the processing cell from the massive coupled manufacturing data and explore the root cause of the abnormality due to the fact that the processing cell is affectedsimultaneously by the manufacturing states of multiple devices.Based on the KPI calculation module and data acquisition module,an abnormality tracing module is designed.Based on the Petri net technology,a multidevice state fusion model for the processing cell is firstly established,then through the state code transformation rules,the state identification matrix is transformed into the processing cell state code,and accurate and unified semantics are assigned to establish the manufacturing state space of the processing cell.Regarding the abnormal indicators of the manufacturing system,by analyzing the abnormal state code,the manufacturing state space can be queried to find the root cause of the abnormality,thereby verifying the practicality of the abnormality tracing module.

关 键 词：KPI指标 PETRI网 加工单元 状态融合 异常追溯 

分 类 号：TH16[机械工程—机械制造及自动化] TP301.1[自动化与计算机技术—计算机系统结构]