Abstract
The article provides the results of application of artificial neural networks for diagnosis of the condition of electrical mining machinery as well as the description of data collection and processing of intelligent system structure and a condition of components of mechatronic systems analysis algorithms using neural networks. Information is provided on practical implementation of algorithms in information and diagnostic systems of career excavators developed by Joint Power Co. Ltd., Moscow.
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Malafeev, S.I., Malafeev, S.S., Tikhonov, Y.V. (2018). Intelligent Diagnostics of Mechatronic System Components of Career Excavators in Operation. In: Kryzhanovsky, B., Dunin-Barkowski, W., Redko, V. (eds) Advances in Neural Computation, Machine Learning, and Cognitive Research. NEUROINFORMATICS 2017. Studies in Computational Intelligence, vol 736. Springer, Cham. https://doi.org/10.1007/978-3-319-66604-4_17
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DOI: https://doi.org/10.1007/978-3-319-66604-4_17
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