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 ...
Development of a High-Precision Deep Learning Model: Develop a high-precision model for the early diagnosis of electric motor faults using a CNN autoencoder.
Instantaneous current residual map (ICRM) is proposed for CNN-based fault diagnosis. , ICRM highlights fault-related physical behaviors of stator motor current ...
This study proposes an algorithm to detect faults by introducing convolutional neural networks (CNNs) after converting the fault sound from the rotor into a ...
Oct 29, 2023 , In this study, a one-dimensional convolutional neural network (1D-CNN) based fault diagnosis model is proposed for electric motor fault ...
Oct 8, 2024 , We encode raw vibration signals into two-dimensional images using various encoding methods and use these with a CNN to classify several ...
Secondly, an improved CNN is proposed by using bottleneck layer and special convolutional kernel to further extract features and fuse the multi-sensor data.
Feb 7, 2023 , The findings indicate that this method can classify various fault types efficaciously, and has the benefits of quick diagnosis, high accuracy, ...
Apr 27, 2023 , This paper proposes a neural-network-based framework using Convolutional Neural Network and Long-Short Term Memory (CNN-LSTM) for detecting faults and ...
Sep 5, 2019 , Abstract. This paper presents a comprehensive review on applying various deep learning algorithms to bearing fault diagnostics.