1 day ago ¡¤ This study explains the process of electric motor fault diagnosis step by step, covering the stages from data collection to real-time processing and analysis, ...

4 days ago ¡¤ This study proposes an improved few-shot learning model of the Siamese network residual Visual Geometry Group (VGG). This model combined with time–frequency ...

5 days ago ¡¤ This study proposes a novel feature extraction method that leverages multi-strategy optimization algorithms to enhance the accuracy and efficiency of rotating ...

6 days ago ¡¤ An opti- mization algorithm was used in this study to obtain the CNN hyperparameters that maximized the model's robustness and accuracy. Overall, the TDM, model ...

1 day ago ¡¤ This study proposes a physics-based digital twin approach to estimate crack growth by incorporating three techniques: (i) Data pre-processing including ...

4 days ago ¡¤ In the bearing fault diagnosis, common deep learning methods mainly include Convolutional Neural Networks (CNN), Deep Belief Network (DBN), Long Short Term ...

7 days ago ¡¤ Then, a combined principal component analysis (PCA) and convolutional neural network (CNN) is employed as the fault detection method through the optimal ...

4 days ago ¡¤ This paper presents a comprehensive study on the application of ML algorithms for stress detection, with a focus on physiological and behavioral data analysis.

6 days ago ¡¤ The International Journal of Circuit Theory and Applications is an electrical engineering journal using circuit theory to solve engineering problems.

4 days ago ¡¤ Their study focuses on data representation, anomaly detection capabilities, ensemble methods, and training conditions like poisoned data and varying user ...