| 部分可观Petri网故障的量子贝叶斯诊断 |
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| 引用本文： | 刘久富,张信哲,汪恒宇,TOMAS DIASA.M.,王志胜,杨忠.部分可观Petri网故障的量子贝叶斯诊断[J].北京航空航天大学学报,2022,48(7):1125-1134. |
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| 作者姓名： | 刘久富 张信哲 汪恒宇 TOMAS DIASA.M. 王志胜 杨忠 |
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| 作者单位： | 南京航空航天大学 自动化学院, 南京 211106 |
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| 基金项目： | 国家自然科学基金61473144 |
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| 摘 要： | 针对故障本身构建量子贝叶斯Petri网模型算法，并利用该子网模型进行Petri网系统故障分析。对于部分可观Petri网模型中的不可观故障，根据可达标识图分析变迁点火路径不能判断系统状态，建立量子贝叶斯子网模型，通过不确定路径引起的量子干涉重新标定变迁的条件概率表得到量子概率振幅表。根据故障变迁的前置集合并结合量子贝叶斯推理计算变迁触发的先验概率，由后置集合中的可观变迁修正后验概率，由最大后验概率估计系统所处状态，当故障变迁不唯一时，选取最大概率的故障作为故障源。以实际故障系统建立部分可观Petri网模型，结合可观标签概率序列信息和量子贝叶斯概率估计，对系统不可观部分进行故障诊断验证算法的有效性。
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| 关 键 词： | 故障诊断 Petri网 部分可观 量子贝叶斯 量子干涉 |
| 收稿时间： | 2021-01-08 |
Partial observable Petri nets fault diagnosis with quantum Bayesian learning |
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| Affiliation: | College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China |
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| Abstract: | This paper proposes an algorithm to construct a quantum Bayesian Petri nets model for the fault, and uses the sub net model to analyze the fault of Petri net system. According to the reachability identification diagram, which is the transition firing path can not judge the system state, establish the quantum Bayesian Petri nets subnet model to tackle the unobservable faults in partial observable Petri model. Through the quantum interference caused by the uncertain path, recalibrate the conditional probability table of the transition to obtain the quantum probability amplitude table. According to the pre-set of fault transition and quantum Bayesian reasoning, calculates the firing prior probability of transition. The posterior probability is modified by the observable transition in the post-set, and the state of the system is estimated by the maximum posterior probability. When the fault transition is not unique, the fault with the maximum probability is selected as the fault source. Finally, establishes a partial observable Petri nets model of a real fault system. Combined with the probability sequence information of observable label and quantum Bayesian probability estimation, the fault diagnosis of the unobservable parts of the system is carried out to verify the effectiveness of the algorithm with the data in simulation experiment. |
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