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SDG-based hazop and fault diagnosis analysis to the inversion of synthetic ammonia

机译:基于SDG的合成氨反演的危险性及故障诊断分析

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摘要

This paper presents some practical applications of signed directed graphs (SDGs) to computeraided hazard and operability study (HAZOP) and fault diagnosis, based on an analysis of the SDG theory. The SDG is modeled for the inversion of synthetic ammonia, which is highly dangerous in process industry, and HAZOP and fault diagnosis based on the SDG model are presented. A new reasoning method, whereby inverse inference is combined with forward inference, is presented to implement SDG fault diagnosis based on a breadth-first algorithm with consistency rules. Compared with conventional inference engines, this new method can better avoid qualitative spuriousness and combination explosion, and can deal with unobservable nodes in SDGs more effectively. Experimental results show the validity and advantages of the new SDG method.
机译:本文在对SDG理论进行分析的基础上,介绍了有向有向图(SDG)在计算机辅助危害与可操作性研究(HAZOP)和故障诊断中的一些实际应用。 SDG是为合成氨的转化建模的,这在过程工业中是非常危险的,并提出了基于SDG模型的HAZOP和故障诊断。提出了一种新的推理方法,将逆推理与正向推理相结合,以基于具有一致性规则的广度优先算法实现SDG故障诊断。与传统的推理引擎相比,该新方法可以更好地避免定性伪造和组合爆炸,并且可以更有效地处理SDG中无法观察到的节点。实验结果证明了新的SDG方法的有效性和优势。

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