Open AccessGenerate troubleshooting strategies based on knowledge modeling
Author(s) -
Valery Dimitrov,
Lyudmila V. Borisova,
Kaprel Khubiian
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/723/3/032093
Subject(s) - troubleshooting , fault tree analysis , knowledge base , computer science , decision table , table (database) , sequence (biology) , basis (linear algebra) , truth table , base (topology) , decision tree , tree (set theory) , data mining , reliability engineering , artificial intelligence , algorithm , engineering , mathematics , rough set , mathematical analysis , genetics , geometry , biology , operating system
The article discusses the issues of modeling knowledge of troubleshooting in units and systems of a combine harvester. Based on the approach using tables of fault functions, the analysis of the subject area is carried out. As an illustration of the application of the proposed strategy for finding the causes of a malfunction, one of the subsystems of electrical equipment of a modern combine harvester is considered, for which a diagram has been formed to build a structural-logical model. As a result of the analysis of the table of malfunction functions, sets of elementary checks are determined. To find the optimal sequence of elementary checks by the method of analysis of hierarchies, the analysis of the weight of these checks was carried out on the basis of four evaluation criteria. As a result of the calculation, the optimal sequence of checks was determined and a decision tree was built to find the cause of the malfunction in the considered subsystem of electrical equipment. The decision tree is the basis for the formation of the knowledge base of an intelligent information system. A fragment of the developed knowledge base is given.