Consequence Identification for Maloperation in Batch Process

Batch processes are important in chemical industry,in which operators usually play a major role and hazards may arise by their inadvertent acts.In this paper,based on hazard and operability study and concept of qualitative simulation,an automatic method for adverse consequence identification for potential maloperation is proposed.The qualitative model for production process is expressed by a novel directed graph.Possible operation deviations from normal operating procedure are identified systematically by using a group of guidewords.The proposed algorithm is used for qualitative simulation of batch processes to identify the effects of maloperations.The method is illustrated with a simple batch process and a batch reaction process.The results show that batch processes can be simulated qualitatively and hazards can be identified for operating procedures including maloperations.After analysis for possible plant maloperations,some measures can be taken to avoid maloperations or reduce losses resulted from maloperations.

Integrated automatic HAZOP analysis and fault diagnosis based on Petri net

Based on systematically analyzing the procedure of hazard and operability (HAZOP) study, the author introduces a method of modeling fault diagnosis with the Petri net with fuzzy colors, in which the fuzzy information can be represented effectively in the process of analysis. The author proposes the architecture of a knowledge base, which integrates HAZOP analysis and fault diagnosis, and provides the conditions for constructing the knowledge-based expert system. The author also presents a method of knowledge representation for on-line HAZOP analysis and on-line fault diagnosis is presented based on the technology of Petri net with fuzzy colors, which establishes a technological fundamental for integrating the automatic HAZOP analysis and fault diagnosis.

SDG-Based HAZOP and Fault Diagnosis Analysis to the Inversion of Synthetic Ammonia

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.