2022
DOI: 10.1177/1748006x221129954
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A composite learning approach for multiple fault diagnosis in gears

Abstract: A major part of Prognostic and Health Management of rotating machines is dedicated to diagnosis operations. This makes early and accurate diagnosis of single and multiple faults an economically important requirement of many industries. With the well-known challenges of multiple faults, this paper proposes a new Blended Ensemble Convolutional Neural Network – Support Vector Machine (BECNN-SVM) model for multiple and single faults diagnosis of gears. The proposed approach is obtained by preprocessing the acquire… Show more

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