An Efficient Approach for Automatic Fault Classification Based on Data Balance and One-Dimensional Deep Learning
Ugur Ileri,
Yusuf Altun,
Ali Narin
Abstract:Predictive maintenance (PdM) is implemented to efficiently manage maintenance schedules of machinery and equipment in manufacturing by predicting potential faults with advanced technologies such as sensors, data analysis, and machine learning algorithms. This paper introduces a study of different methodologies for automatically classifying the failures in PdM data. We first present the performance evaluation of fault classification performed by shallow machine learning (SML) methods such as Decision Trees, Sup… Show more
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