Abstract
Machine condition monitoring has gained momentum over the years and becoming an essential component in the today’s industrial units. A cost effective machine condition monitoring system is need of the hour for predictive maintenance. In this paper, we have developed a machine condition monitoring system using smart phone, thanks to the rapidly growing smart-phone market both in scalability and computational power. In spite of certain hardware limitations, this paper proposes a machine condition monitoring system which has the tendency to acquire data, build the fault diagnostic model and determine the type of the fault in the case of unknown fault signatures. Results for the fault detection accuracy are presented which validate the prospects of the proposed framework in future condition monitoring services.
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Gondal, I., Yaqub, M.F., Hua, X. (2012). Smart Phone Based Machine Condition Monitoring System. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7667. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34500-5_58
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DOI: https://doi.org/10.1007/978-3-642-34500-5_58
Publisher Name: Springer, Berlin, Heidelberg
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