Abstract
This paper presents a method to creation of a servicing expert system including an artificial neural network. The theoretical basis was presented with the model of an operation process of objects in the form of the following models: mathematical (analytical), graphical and descriptional. For the tests, a model was developed of an organization of a servicing technical system of those technical objects which require short shutdown times (aircrafts, radiolocation systems, etc.). The mathematical basis was presented for the execution of the task of servicing of a technical object. The idea of the servicing of the object was described as a transformation of the properties of the operational function of the object from the space of the current servicing to the form of the space of the features of the nominal (model) operation of the object. The results were presented of the radar system.
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References
Będkowski L, Dąbrowski T (2006) Podstawy eksploatacji cz. 2. Wyd. WAT, Warszawa (in Polish)
Buchannan B, Shortliffe E (1985) Rule-based expert systems. Addison-Wesley Publishing Company, Reading
Duer S (2004) The concept of assistant system for analogue class technical object servicing. In: Sixth international conference on unconventional electromechanical and electrical system UEES’04. Alushta, The Crimea, Ukraine, pp 687–690
Duer S (2009) Artificial neural network-based technique for operation process control of a technical object. Def Sci J DESIDOC 59(3):305–313
Dhillon BS (2006) Applied reliability and quality, fundamentals, methodos and procedures. Springer, London
Hayer-Roth F, Waterman D, Lenat D (1983) Building expert systems. Addison-Wesley Publishing Company, Reading
Hojjat A, Shih-Lin H (1995) Machine learning, neural networks, genetic algorithms and fuzzy systems. Wiley, New York
Gupta MM, Jin L, Homma N (2003) Static and dynamic neural networks, from fundamentals to advanced theory. Wiley, New York
Mathirajan M, Chandru V, Sivakumar AI (2007) Heuristic algorithms for scheduling heat-treatment furnaces of steel casting industries. Sadahana 32(5)
Nakagawa T (2005) Maintenance theory of reliability. Springer, London
Nakagawa T, Ito K (2000) Optimal inspection policies for a storage system with degradation at periodic tests. Math Comput Model 31:191–195
Tang L, Liu J, Rong A, Yang Z (2002) Modeling and genetic algorithm solution for the slab stack shuffling problem when implementing steel rolling schedules. Int J Prod Res 40(7)
Tang L, Huang L (2007) Optimal and near-optimal algorithms to rolling batch scheduling for seamless steel tube production. Int J Econ 105
Tang L, Liu J (2007) A mathematical programming model and solution for scheduling production orders in Shanghai Boashan Iron & Steel Complex. Eur J Oper Res 182
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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 Comput & Applic 21, 153–160 (2012). https://doi.org/10.1007/s00521-011-0606-6
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DOI: https://doi.org/10.1007/s00521-011-0606-6