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An Approach to Accidents Diagnosis Based on Fuzzy Petri Net

机译:一种基于模糊Petri网的事故诊断方法

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To reduce difficulty to obtain accurate in-situ sampling data and enhance correctness of accident diagnosis, a new method of establishing fuzzy Petri net model by transferring a fuzzy fault tree into a fuzzy Petri net model is put forward based on that a fuzzy fault tree and a fuzzy Petri net model have the same characteristics of cause-and-effect link which describes occurrence of events, a fuzzy analysis is made to a fault tree based on its corresponding Petri net model. The method can not only estimate all kinds of characteristic values of root event, but also make accident diagnosis by fuzzy inference algorithm of its Petri net model, therefore a tight link between a Petri net model and a fault tree is formed so that accident diagnosis is more suitable for in-site circumstances. The fuzzy set theory is introduced into analytical methods of fault tree where fuzzy numbers represents firing possibilities of events so that difficulty to obtain accurate firing possibilities of bottom events is reduced, errors from statistic data of accidental possibilities are corrected to some extent. The method can put in-site sampling data and experiences of experts together so as to keep analytical results to approximate to engineering fact.
机译:为了减少难以获得准确的原位采样数据并增强事故诊断的正确性,基于这种模糊故障树,提出了一种通过将模糊断层净模型转移到模糊的Petri网络模型中建立模糊培养净净模型的新方法。模糊的Petri网模型具有相同的原因和效果链路特征,描述事件发生,基于其对应的Petri网模型对故障树进行模糊分析。该方法不仅可以估计根事件的各种特征值,还通过模糊推理算法对其培养的净模型进行事故诊断,因此形成了Petri网模型与故障树之间的紧密联系,使得事故诊断是更适合现场的情况。将模糊集理论引入故障树的分析方法,其中模糊数表示事件的射击可能性,以便难以获得底部事件的准确射击可能性,从某种程度上纠正了意外可能性的统计数据的错误。该方法可以将现场采样数据和专家的经验放在一起,以便保持分析结果近似于工程事实。

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