Design of fault simulator
Fault simulator is proposed to understand and evaluate all possible fault propagation scenarios, which is an essential part of safety design and operation design and support of chemical/production processes. Process models are constructed and integrated with fault models, which are formulated in qualitative manner using fault semantic networks (FSN). Trend analysis techniques are used to map real time and simulation quantitative data into qualitative fault models for better decision support and tuning of FSN. The design of the proposed fault simulator is described and applied on experimental plant (G-Plant) to diagnose several fault scenarios. The proposed fault simulator will enable industrial plants to specify and validate safety requirements as part of safety system design as well as to support recovery and shutdown operation and disaster management.
Evaluation of the proposed trend fusion algorithm (math heavy)
Modeling and case study
number of homeless loss of economic activitydata for obtaining reliable estimates of the disaster
fault simulator in terms of activity models, system architecture, and proposed fault simulation mechanisms using qualitative and quantitative approaches.
Experimantl plant called G-Plant
Due to the increase of process complexities and loss of major plant experts, it is important to provide solution to construct fault knowledge structures with respect to process knowledge.
The proposed simplified trend fusion algorithm showed acceptable results of classifying normal and abnormal cases adequately.This paper proposes integrated fault simulator that supports the analysis of abnormal situations where fault semantic networks are constructed that represent faults, symptoms, causes, consequences and counteractions for all possible abnormal or risk scenarios of the chemical and petrochemical plants.
This paper proposes design of fault simulator that is used to analyze several process faults in qualitative and quantitative manner which supports safety design and operation of chemical / production plants
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