The survey of soft computing techniques for reliability prediction

• Autorzy: Smoczek J.
• Języki publikacji: EN

Abstrakty

EN

The objective of reliability prediction is to estimate a time of upcoming nonoperational state at the current operational state of a system through real-time monitoring operational parameters and/or performances. Hence, the predictive (proactive) maintenance in industrial systems involves operational conditions monitoring and online forecasting the useful life of machines equipment to support the decision-making process in selection of the best maintenance action to be carried out. The advanced warning of the failure possibility can bring the attention of machines operators and maintenance personnel to impending danger, and facilitate planning preventive and corrective operations, as well as inventory managing. This problem has been extensively studied in many scientific works, where the predictive models are based on the data-driven approaches that can be generally divided into statistical techniques (regression, ARMA models, Bayesian probability distribution estimation, etc.), grey system theory, and soft computing methods. The artificial intelligence is frequently addressed to the predictive problem by utilizing the learning capability of artificial neural network (ANN), and possibility of nonlinear mapping using fuzzy rules-based system (FRBS) or recognizing and optimizing data-derived pattern by using evolutionary algorithms. The paper is a survey of intelligent methods for failure prediction, and delivers the review of examples of scientific works presenting the computational intelligence-based approaches to predictive problem.

Słowa kluczowe

EN

reliability prediction; artificial intelligence; fuzzy logic; artificial neural network; genetic algorithm

• Wydawca: Łukasiewicz Research Network - Institute of Aviation ; European Science Society of Powertrain and Transport KONES Poland ; Wydawnictwo Instytutu Technicznego Wojsk Lotniczych
• Czasopismo: Journal of KONES
• Rocznik: 2012
• Tom: Vol. 19, No. 3
• Strony: 407--414
• Opis fizyczny: Bibliogr. 43 poz., rys.

Twórcy

autor

Smoczek J.

• AGH University of Science and Technology Faculty of Mechanical Engineering and Robotics Mickiewicza Av. 30, 30-059 Krakow, Poland tel.: [phone]

Bibliografia

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