A new CNN based on LeNet-5 is proposed for fault diagnosis which can extract the features of the converted 2-D images and eliminate the effect of handcrafted ...
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Multisensor data fusion for gearbox fault diagnosis using 2-D convolutional neural network and motor current signature analysis, Mech. Syst. Sig. Process ...
Aug 10, 2022 ， using 2-D convolutional neural network and motor ... Ciaburro, Time series data analysis using deep learning methods for smart cities monitoring,.
Sep 4, 2023 ， In the fault diagnosis of electric vehicle driving motor, the core idea of deep learning is to use multi-layer neural network to simulate the ...
Nov 15, 2017 ， In this study, a deep learning method based on short-time Fourier transform (STFT) [22] and a convolutional neural network (CNN) is proposed ...
Li, Multi-mode data augmentation and fault diagnosis of rotating machinery using modified ACGAN designed with new framework, Adv. Eng. Inf., ∇ 52
Nov 12, 2022 ， Fault diagnosis performance analysis for data from the same device ... A motor current signal-based bearing fault diagnosis using deep learning ...
Feb 1, 2022 ， ... training of phase tracker to improve its accuracy with regard to actual data. ... fault diagnosis using state-transition-algorithm-based adaptive.
Inspired by the previous work and combined with the requirement of fast and accurate fault diagnosis with minimal human influence, this study presents a novel ...
May 5, 2023 ， While the data employed in this analysis is derived from a three-phase motor, the ... Machine learning-based fault diagnosis for single-and multi- ...