Tytuł artykułu
Autorzy
Identyfikatory
Warianty tytułu
Intelligent system renewing of technical objects
Języki publikacji
Abstrakty
W pracy zaprezentowano koncepcję procesu odnawiania obiektów technicznych z wykorzystaniem sztucznej inteligencji. W tym modelu obsługiwania obiektów technicznych są wyróżnione moduły: diagnostyczny i obsługiwania. Moduł diagnostyczny rozpoznaje stany w obiekcie w logice trójwartościowej. Natomiast moduł obsługiwania przetwarza bazę wiedzy diagnostycznej i bazę wiedzy człowieka specjalisty na nową postać bazy wiedzy obsługowej.
The paper presents the concept of the renewal process of technical objects with the use of artificial intelligence. In this model, the use of technical objects are highlighted modules: Diagnostic and use. Diagnostic module recognizes the states of the object in three-valued logic. In contrast, the module processes the use of diagnostic knowledge base and knowledge base of human expert to a new form of knowledge base maintenance.
Czasopismo
Rocznik
Tom
Strony
1474--1480
Opis fizyczny
Bibliogr. 17 poz., rys., tab., pełen tekst na CD
Twórcy
autor
- Politechnika Koszalińska, Wydział Mechaniczny; 75-453 Koszalin; ul. Śniadeckich 2
autor
- Politechnika Koszalińska, Zakład Zastosowań Elektroniki i Elektrotechniki; 75-620 Koszalin; ul. Racławicka 15-17
Bibliografia
- 1. Będkowski L., Dąbrowski T.: Podstawy eksploatacji cz. 2. Wyd. WAT, Warszawa 2006, str. 187.
- 2. Duer S.: Artificial Neural Network-based technique for operation process control of a technical object. Defence Science Journal, 2009, Vol. 59, No. 3, pp. 305-313.
- 3. Duer S.: Diagnostic system with an artificial neural network in diagnostics of an analogue technical object. Neural Computing & Applications, 2010, Vol. 19, No. 1, pp. 55-60.
- 4. Duer S.: Diagnostic system for the diagnosis of a reparable technical object, with the use of an artificial neural network of RBF type. Neural Computing & Applications, 2010, Vol. 19, No. 5, pp. 691-700.
- 5. Duer S., Duer R.: Diagnostic system with an artificial neural network which determines a diagnostic information for the servicing of a reparable technical object. Neural Computing & Applications, 2010, Vol. 19, No. 5, pp. 755-766.
- 6. Duer S.: Investigation of the operation process of a repairable technical object in an expert servicing system with an artificial neural network. Neural Computing & Applications, 2010, Vol. 19, No. 5, pp. 767-774.
- 7. Duer S.: Qualitative evaluation of the regeneration process of a technical object in a maintenance system with an artificial neural network. Neural Computing & Applications. 2011, Vol. 20, No. 5, pp. 741-752.
- 8. Duer S.: Expert knowledge base to support the maintenance of a radar system. Defence Science Journal, 2010, Vol. 60, No. 5, pp. 531-540.
- 9. Duer S.: Modelling of the operation process of repairable technical objects with the use information from an artificial neural network. Expert Systems With Applications. 2011, Vol. 38, pp. 5867-5878.
- 10.Duer S.: Assessment of the quality of decisions worked out by an artificial neural network which diagnoses a technical object. Neural Computing & Applications. 2012, Vol. 21, No 5, pp. 1049-1063.
- 11.Duer S.: Examination of the reliability of a technical object after its regeneration in a maintenance system with an artificial neural network. Neural Computing & Applications. 2012, Vol. 21, No. 3, pp. 523-534.
- 12.Duer S.: Artificial neural network in the control process of object’s states basis for organization of a servicing system of a technical objects. Neural Computing & Applications. 2012, Vol. 21, No. 1, pp. 153-160.
- 13.Duer S.: Inteligentny system wspomagający proces odnawiania cech eksploatacyjnych w złożonych obiektach technicznych. Wydawnictwo Politechniki Koszalińskiej. Koszalin 2012, str. 238.
- 14.Duer S.: Applications of an artificial intelligence for servicing of a technical object. Neural Computing & Applications. 2013, Vol. 23, No. 5, pp. 955-968.
- 15.Duer S., Zajkowski K.: Taking decisions in the expert intelligent system to support maintenance of a technical object on the basis information from an artificial neural network. Neural Computing &Applications. 2013, Vol. 23, No. 7, pp. 2185-2197.
- 16.Duer S., Zajkowski K.: Duer R., Paś J.: Designing of an effective structure of system for the maintenance of a technical object with the using information from an artificial neural network. Neural Computing & Applications. 2013, Vol. 23, No. 3-4, pp. 913-925.
- 17.Nakagawa T.: Maintenance Theory of Reliability. Springer – Verlag London Limited, 2005, p. 264.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-50e4e182-5fdd-4b3a-a686-56cda34e6bb4