Fault locator of an allyl chloride plant | Zendy

Jelenka Savkovic-Stevanovic | Zendy

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Fault locator of an allyl chloride plant

Author(s) -

Jelenka Savkovic-Stevanovic

Publication year - 2004

Publication title -

hemijska industrija

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.147

H-Index - 19

eISSN - 2217-7426

pISSN - 0367-598X

DOI - 10.2298/hemind0409401s

Subject(s) - troubleshooting , fault tree analysis , fuzzy logic , computer science , reliability engineering , fault (geology) , event (particle physics) , data mining , semantic reasoner , reliability (semiconductor) , artificial intelligence , engineering , power (physics) , physics , quantum mechanics , seismology , geology

Process safety analysis, which includes qualitative fault event identification, the relative frequency and event probability functions, as well as consequence analysis, was performed on an allye chloride plant. An event tree for fault diagnosis and cognitive reliability analysis, as well as a troubleshooting system, were developed. Fuzzy inductive reasoning illustrated the advantages compared to crisp inductive reasoning. A qualitative model forecast the future behavior of the system in the case of accident detection and then compared it with the actual measured data. A cognitive model including qualitative and quantitative information by fuzzy logic of the incident scenario was derived as a fault locator for an ally! chloride plant. The obtained results showed the successful application of cognitive dispersion modeling to process safety analysis. A fuzzy inductive reasoner illustrated good performance to discriminate between different types of malfunctions. This fault locator allowed risk analysis and the construction of a fault tolerant system. This study is the first report in the literature showing the cognitive reliability analysis method

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