First, we use AFEWT to extract the feature of the rolling bearing vibration signal. The hypothesis test of the Gaussian distribution is carried out for the sub- ...
Jun 11, 2018 · First, we use AFEWT to extract the feature of the rolling bearing vibration signal. The hypothesis test of the Gaussian distribution is carried ...
Jun 7, 2018 · In order to verify the effectiveness of AFEWT in feature extraction, we extract signal features using three methods, AFEWT, EWT, and EMD, and ...
Jun 1, 2018 · Experimental results show that the fault signal has the highest recognition rate by using AFEWT for feature extraction, and a fault ...
May 20, 2022 · The proposed integrated ViT model based on the soft voting method can diagnose the different fault categories and fault severities of bearings accurately.
Missing: AFEWT- KDEMI.
Field test acquisition device. Figure 7. Field test... A novel fault diagnosis method of rolling bearings based on AFEWT-KDEMI. Article. Full-text available.
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Intelligent fault diagnosis based on convolutional neural networks (CNNs) has become an effective tool to ensure the reliable operation of rolling bearings.
Apr 23, 2022 · We propose a novel fast fault diagnosis method for rolling bearings, based on extreme learning machine (ELM) and logistic mapping, named logistic-ELM.
Missing: AFEWT- KDEMI.
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2018: A Novel Fault Diagnosis Method of Rolling Bearings Based on AFEWT-KDEMi Entropy 20(6) · Wen, T.; Chen, R.; Tang, L. 2021: Fault Diagnosis of Rolling ...
Oct 12, 2021 · An intelligent fault diagnosis strategy for rolling bearings based on grayscale image transformation, a generative adversative network, and a convolutional ...
Missing: AFEWT- KDEMI.