Abstract:Anomaly detection has an important role in industrial systems. Abnormal situations occurring in a system cause anomalies, and the anomalies reduce system performance over time, and may also make the system malfunction. Therefore, the correct and timely detection of anomalies is of critical importance for predictive maintenance. In this study, an autoencoder-based method is proposed for anomaly detection in DC motor body temperature. The performance of the method was examined on a dataset that was created speci… Show more
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