Application of machine learning to classify wear level of multi-piston displacement pump

This article specifies application of machine learning for the purpose of classifying wear level of multi-piston displacement pump. A diagnostic experiment that was carried out in order to acquire vibration signal matrices from selected locations within the pump body is described herein. Measured signals were subject to time and frequency analysis. Signal attributes related to time and frequency were grouped in a table in accordance with pump wear level. Subsequently, classification models for the pump wear level were developed through application of Matlab package. Assessment of their accuracy was carried out. A selected model was subject to confirmation. The article includes its summary.

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Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).