The SoftMax function layer calculates the probability of the input data belonging to the machine learning state labeled class [26, 28]. The SoftMax function is ...

Instantaneous current residual map (ICRM) is proposed for CNN-based fault diagnosis. ¡¤ ICRM highlights fault-related physical behaviors of stator motor current ...

Oct 29, 2023 ¡¤ In this study, a one-dimensional convolutional neural network (1D-CNN) based fault diagnosis model is proposed for electric motor fault ...

This study proposes an algorithm to detect faults by introducing convolutional neural networks (CNNs) after converting the fault sound from the rotor into a ...

This work presents the development of the Fault Diagnosis Module of the previously proposed data-driven OLM system for reactor operations: the Fault ...

May 5, 2023 ¡¤ In this paper, the issue of predicting electrical machine failures by predicting possible anomalies in the data is addressed through time series analysis.

Knowledge extraction using data mining for multi-class fault diagnosis of induction motor ... Quasi 1D CNN-based fault diagnosis of induction motor drives.

Feb 7, 2023 ¡¤ The findings indicate that this method can classify various fault types efficaciously, and has the benefits of quick diagnosis, high accuracy, ...

Aug 7, 2024 ¡¤ The proposed work combines the power of deep learning-based schemes with model-based approaches to enable fault diagnosis and prediction. The ...

Sep 5, 2019 ¡¤ Abstract. This paper presents a comprehensive review on applying various deep learning algorithms to bearing fault diagnostics.