Using precedents for the overhead crane diagnosis
Abstract
It has been found that using precedents for the solution of not formalized tasks for overhead cranes diagnostics allows to simplify the acquisition of knowledge from experts, reducing the time to find a solution and implement a self-learning. The model of the precedent and the cprecedent database, which allows to describe the current condition of the overhead crane during diagnostics, are proposed. It is shown that the use of ontologies of the precedents improves the quality of decision-making through the use of knowledge from many experts in the field of technical diagnostics. A structural diagram of a decision support system for overhead cranes diagnostics has been proposed. The main components that reflect it functionality, are: the precedent database, the block of its settings and precedents search. The decision support system for diagnostics of overhead crane met-alware has been developed. Using of the decision support system allowed reduce the information load on the decision-making person, reduce the impact of personal factors in the analysis of the current crane state, reduce the time required for the decision.References
Aamodt A., Plaza E. Case-based reasoning: Foundational issues, methodological variations, and system approaches // AI Communications. — 7, Issue 1. — 1994. — Р. 39–59.
Varshavs’kiy P.R., Eremeyev А.P. Modelirovaniye rassuzhdeniy na osnove pretsedentov v intellektual’nykh sistemakh podderzhki prinyatiya resheniy // Iskusstvennyy intellekt i prinyatiye resheniy. — 2009. — № 1. — S. 45–57.
Ul’shin V.А., Klimchik S.А. Model’ diagnostiki kranov mostovogo tipa // Tr. Luganskogo otdeleniya Mezhdunar. Аkad. Informatizatsii. — 2009. — № 2 (20). — S. 61–71.
Rohushyna Yu.V., Hryshanova I.Yu. Vykorystannya metodu induktyvnoho vyvedennya dlya vdoskonalennya ontolohiyi predmetnoyi oblasti poshuku // Systemni doslidzhennya ta informatsiyni tekhnolohiyi. — 2007. — № 1. — S. 62–70.
Anguel F., Sellami M. Knowledge management for fault diagnosis of gas turbines using case based reasoning // Communications of the IBIMA. — 2009. — 10, № 24. — Р. 186–190.