改进的部分可观Petri网系统在线故障诊断器设计

An improved design of online fault diagnosis for partially observed Petri net systems

中文关键词  故障诊断  部分可观Petri网  整数线性规划  广义互斥约束

英文关键词  fault diagnosis  partially observed Petri nets  integer linear programming  generalized mutual exclusion constraints (GMEC)

中文摘要

      本文研究部分可观Petri网建模的离散事件系统的故障检测问题. 针对现有的部分可观Petri网系统的在线故障诊断器存在故障诊断率较低的缺陷, 本文提出了整数线性规划与广义互斥约束集成的部分可观Petri网系统在线故障诊断改进算法. 假定部分可观Petri网系统的结构与初始标识为已知, 故障被建模为不可观变迁. 首先, 算法需要观测接收事件序列, 求解部分可观Petri网的整数线性规划问题, 算法对系统的故障进行初步诊断. 初步诊断为不确定诊断的情形, 采用广义互斥约束的方法进行诊断. 最后, 通过离散事件系统实例分析, 采用本文的算法, 故障诊断率显著提高, 验证了算法的有效性.

英文摘要

      We study the fault diagnosis problem for discrete event systems (DES) which can be modeled by the partially observed Petri net (POPN). To overcome the low diagnosis ability of the currently POPN online fault diagnosis instruments, we propose an improved online fault diagnosis algorithm that integrates the generalized mutual exclusion constraints (GMEC) and Integer Linear Programming (ILP). We assume that the POPN structure and its initial markings are known, and the faults are modeled as unobservable transitions. First, the event sequence is observed and recorded; and then, the ILP problems of POPN are solved for primary diagnosis for the system behavior. If the results in the primary diagnosis are uncertain, we use the GMEC for a further diagnosis. A real discrete event system is taken as an example for analysis; the results show that the proposed algorithm increases the diagnosis ability remarkably and the effectiveness of the proposed algorithm is validated.