研究了Petri网在双组元推进气路系统中的故障诊断问题。针对气路系统故障率相对较高且部分关键信息无法通过传感器获取的问题, 利用时间Petri网在实时系统中的重要作用, 把部分可观时间Petri网和状态类图(SCG）结合, 提出构建修正状态类图(MSCG）的方法。首先根据执行机构是否可观, 分为可观测变迁和不可观测变迁,并结合变迁触发关系(同步、异步）修正各变迁时间区间,建立系统的修正状态类图(MSCG)。然后根据所提的故障诊断算法, 寻找所有满足可观测变迁触发时间和序列信息的路径, 判断所有路径组成的集合是否包含故障变迁, 诊断系统是否发生故障。最后以双组元推进气路系统为例, 结合气路系统各执行机构可观测状态, 建立Petri网模型, 对系统不可观部分进行故障诊断, 验证了算法的有效性。

The fault diagnosis of gas path system in integral bipropellant propulsion is investigated. Aiming at the problems that the failure rate of gas path system is relatively high and some key information can't be obtained through the sensors, a method of building Modified State Class Graph (MSCG) based on Partially Observed Time Petri Nets (POTPN) and State Class Graph (SCG) is presented. Firstly, the transitions are divided into observable and unobservable transitions according to the observability of the actuators, and the time intervals are modified based on the different relationships of the transitions (synchronous and asynchronous).The MSCG is then built with time Petri nets.Based on the proposed fault diagnosis method, all the effective paths that satisfy the observable transition triggering time and sequence information are found out, and it is determined whether the effective paths have fault transitions.Finally, taking the gas path system in integral bipropellant propulsion as an example, and based on the observability of the actuators, a Petri net is built for making fault diagnosis to the unobservable part of the system, which verifies the effectiveness of the algorithm.