Rotating machine diagnosis using acoustic imaging and artificial intelligence

Abstract : Mass production of quality equipment in the automotive industry requires controls throughout the production line. These controls are done through monitoring and validation tools for both production and finished products. The use of signal processing methods, applied to acous tic and vibratory recordings collected during the operating cycle, aims to ensure that they are in good working order, to maintain them and to guarantee the quality of the service provided by a manufacturer to its customers. However, sometimes the techniqu es used do not reach the expected performance, which of course depends on the defect to be recognized but also on the conditions under which the measurements were made. This paper introduces a preliminary study on machine diagnosis by combining both signal processing methods and artificial intelligence. Th is w ork is dedicated to develop a system which allows us to measure several high frequency channels and to transmit them to a computer via USB interface.
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Submitted on : Thursday, July 18, 2019 - 3:44:30 PM
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  • HAL Id : hal-02188560, version 1

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Abdelhakim Darraz, Jérôme Antoni, Pierre Mollon, Gabriel Kirie, Jean-Hugh Thomas, et al.. Rotating machine diagnosis using acoustic imaging and artificial intelligence. Surveillance, Vishno and AVE conferences, INSA-Lyon, Université de Lyon, Jul 2019, Lyon, France. ⟨hal-02188560⟩

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