Ignat'ev Aleksandr Anatol'evich, Doctor of engineering sciences, professor, head of sub-department of automation, control, mechatronics, Institute of Electronic Engineering and Machine Building, Saratov State Technical University named after Y.A. Gagarin (77 Politekhnicheskaya street, Saratov, Russia), email@example.com
Kozlova Tat'yana Dmitrievna, Assistant, sub-department of technical systems control and informatics, Balakovo Institute of engineering, technology and control (branch) of Saratov State Technical University named after Y. A. Gagarin (77 Politekhnicheskaya street, Saratov, Russia), firstname.lastname@example.org
Samoylova Elena Mikhaylovna, Candidate of engineering sciences, associate professor, sub-department of automation, control, mechatronics, Institute of Electronic Engineering and Machine Building, Saratov State Technical University named after Y.A. Gagarin (77 Politekhnicheskaya street, Saratov, Russia), email@example.com
Background. Application of the expert system allows accumulating knowledge of staff and experts on causes of failures and results of elimination thereof, which reduces the time of automatic machine modules restoration and correspondingly increases availability rate. These facts prove topicality of the work.
Materials and methods. The developed method of formation of the knowledge base model for the expert support system of diagnostics of automatic machine modules takes into account the units’ hierarchic structure in the form of subsystems of various levels during formation of all system components (information versatility,
expandability and component internal compatibility), provides formation of recommendations on module functioning malfunction elimination on the basis of the revealed in the course of operation cause-effect relations between the failures and restorations of modules and the expert processing of data by the method of paired
comparison. To form the data base the authors suggested to use an object-oriented model for facts formalization, that allows displaying the objects of the object domain and interrelations thereof, and a production model to formalize procedure knowledge (rules), providing more flexible work organization of the input mechanism.
Results. The authors analyzed and structured the data on automatic machine module failures. The researchers built the expert system knowledge base including a declarative component in the form of the object-oriented model that contains knowledge about module subsystems, diagnostic parameters, data on subsystem failures and ways of elimination thereof, and a procedural component in the form of the production model containing a complex of rules used for processing declarative knowledge, that provides formation of reports on a defective function unit in one or another module subsystem.
Conclusions. The presented knowledge base model of support of automatic machine module diagnostics reflects the problem solving process in determination of failure causes on the basis of diagnostic information analysis and takes into account the hierarchic structure and the diagnostic algorithm.
expert system, automatic machine module, knowledge base, database, failure model.
1. Brzhozovskiy B. M., Ignat'ev A. A., Martynov V. V., Skhirtladze A. G. Nadezhnost' i diagnostika tekhnologicheskikh sistem [Reliability and diagnostics of technological systems]. Staryy Oskol: Izd-vo TNT, 2010, 352 p.
2. Melikhov A. N., Bershteyn L. S., Korovin S. Ya. Situatsionnye sovetuyushchie sistemy s nechetkoy logikoy [Situational advising fuzzy logic system]. Moscow: Nauka, 1990, 272 p.
3. Kozlova T. D., Ignat'ev A. A. Izvestiya vysshikh uchebnykh zavedeniy. Povolzhskiy region. Tekhnicheskie nauki [University proceedings. Volga region. Engineering sciences]. 2013, no. 1 (25), pp. 19–25.
4. Kozlova T. D., Samoylova E. M. Vestnik Saratovskogo gosudarstvennogo tekhnicheskogo universiteta [Bulletin of Saratov State Technical University]. 2011, vol. 3, no. 2 (58), pp. 178–183.
5. Kozlova T. D., Ignat'ev A. A., Samoylova E. M. Vestnik Saratovskogo gosudarstvennogo tekhnicheskogo universiteta [Bulletin of Saratov State Technical University]. 2011, no. 2 (56), pp. 219–225.