Enhancing Bearing Fault Diagnosis With Deep Learning Model Fusion and Semantic Web Technologies
Shichao Chen,
Shiyu Zou
Abstract:Given the limited accuracy of a singular deep learning model in bearing fault diagnosis, this study seeks to investigate and validate the efficacy of a deep learning model fusion strategy. It also aims to enhance the performance of deep learning models in bearing fault diagnosis using semantic web technology. Utilizing a publicly available bearing dataset, we employ semantic web to represent data in a structured format that is easily interpretable by machines. We then train separate convolutional neural networ… Show more
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