577 related articles for article (PubMed ID: 33276483)
1. Deep Learning-Based Bearing Fault Diagnosis Method for Embedded Systems.
Pham MT; Kim JM; Kim CH
Sensors (Basel); 2020 Dec; 20(23):. PubMed ID: 33276483
[TBL] [Abstract][Full Text] [Related]
2. Bearing Fault Diagnosis Method Based on Deep Convolutional Neural Network and Random Forest Ensemble Learning.
Xu G; Liu M; Jiang Z; Söffker D; Shen W
Sensors (Basel); 2019 Mar; 19(5):. PubMed ID: 30832449
[TBL] [Abstract][Full Text] [Related]
3. Bearing Fault Diagnosis with a Feature Fusion Method Based on an Ensemble Convolutional Neural Network and Deep Neural Network.
Li H; Huang J; Ji S
Sensors (Basel); 2019 Apr; 19(9):. PubMed ID: 31052295
[TBL] [Abstract][Full Text] [Related]
4. WPD-Enhanced Deep Graph Contrastive Learning Data Fusion for Fault Diagnosis of Rolling Bearing.
Liu R; Wang X; Kumar A; Sun B; Zhou Y
Micromachines (Basel); 2023 Jul; 14(7):. PubMed ID: 37512779
[TBL] [Abstract][Full Text] [Related]
5. A Novel End-To-End Fault Diagnosis Approach for Rolling Bearings by Integrating Wavelet Packet Transform into Convolutional Neural Network Structures.
Xiong S; Zhou H; He S; Zhang L; Xia Q; Xuan J; Shi T
Sensors (Basel); 2020 Sep; 20(17):. PubMed ID: 32887331
[TBL] [Abstract][Full Text] [Related]
6. Enhanced Feature Extraction Network Based on Acoustic Signal Feature Learning for Bearing Fault Diagnosis.
Luo Y; Lu W; Kang S; Tian X; Kang X; Sun F
Sensors (Basel); 2023 Oct; 23(21):. PubMed ID: 37960402
[TBL] [Abstract][Full Text] [Related]
7. An Intelligent Fault Diagnosis Method for Bearings with Variable Rotating Speed Based on Pythagorean Spatial Pyramid Pooling CNN.
Guo S; Yang T; Gao W; Zhang C; Zhang Y
Sensors (Basel); 2018 Nov; 18(11):. PubMed ID: 30424001
[TBL] [Abstract][Full Text] [Related]
8. Fault Diagnosis for High-Speed Train Axle-Box Bearing Using Simplified Shallow Information Fusion Convolutional Neural Network.
Luo H; Bo L; Peng C; Hou D
Sensors (Basel); 2020 Aug; 20(17):. PubMed ID: 32878207
[TBL] [Abstract][Full Text] [Related]
9. A Novel Deep Learning Model for the Detection and Identification of Rolling Element-Bearing Faults.
Shenfield A; Howarth M
Sensors (Basel); 2020 Sep; 20(18):. PubMed ID: 32911771
[TBL] [Abstract][Full Text] [Related]
10. A Deep Autoencoder-Based Convolution Neural Network Framework for Bearing Fault Classification in Induction Motors.
Toma RN; Piltan F; Kim JM
Sensors (Basel); 2021 Dec; 21(24):. PubMed ID: 34960552
[TBL] [Abstract][Full Text] [Related]
11. An improved complementary ensemble empirical mode decomposition with adaptive noise and its application to rolling element bearing fault diagnosis.
Cheng Y; Wang Z; Chen B; Zhang W; Huang G
ISA Trans; 2019 Aug; 91():218-234. PubMed ID: 30738582
[TBL] [Abstract][Full Text] [Related]
12. A Novel Bearing Multi-Fault Diagnosis Approach Based on Weighted Permutation Entropy and an Improved SVM Ensemble Classifier.
Zhou S; Qian S; Chang W; Xiao Y; Cheng Y
Sensors (Basel); 2018 Jun; 18(6):. PubMed ID: 29899216
[TBL] [Abstract][Full Text] [Related]
13. Intelligent fault diagnosis algorithm of rolling bearing based on optimization algorithm fusion convolutional neural network.
Wang Q; Sun Z; Zhu Y; Song C; Li D
Math Biosci Eng; 2023 Nov; 20(11):19963-19982. PubMed ID: 38052632
[TBL] [Abstract][Full Text] [Related]
14. A New Dual-Input Deep Anomaly Detection Method for Early Faults Warning of Rolling Bearings.
Kang Y; Chen G; Wang H; Pan W; Wei X
Sensors (Basel); 2023 Sep; 23(18):. PubMed ID: 37766068
[TBL] [Abstract][Full Text] [Related]
15. A Novel Deep Learning Method for Intelligent Fault Diagnosis of Rotating Machinery Based on Improved CNN-SVM and Multichannel Data Fusion.
Gong W; Chen H; Zhang Z; Zhang M; Wang R; Guan C; Wang Q
Sensors (Basel); 2019 Apr; 19(7):. PubMed ID: 30970672
[TBL] [Abstract][Full Text] [Related]
16. Evaluation of Different Bearing Fault Classifiers in Utilizing CNN Feature Extraction Ability.
Xie W; Li Z; Xu Y; Gardoni P; Li W
Sensors (Basel); 2022 Apr; 22(9):. PubMed ID: 35591006
[TBL] [Abstract][Full Text] [Related]
17. Fault Diagnosis of Rolling Bearing Based on HPSO Algorithm Optimized CNN-LSTM Neural Network.
Tian H; Fan H; Feng M; Cao R; Li D
Sensors (Basel); 2023 Jul; 23(14):. PubMed ID: 37514802
[TBL] [Abstract][Full Text] [Related]
18. End-to-End Continuous/Discontinuous Feature Fusion Method with Attention for Rolling Bearing Fault Diagnosis.
Zheng J; Liao J; Chen Z
Sensors (Basel); 2022 Aug; 22(17):. PubMed ID: 36080947
[TBL] [Abstract][Full Text] [Related]
19. Noise Eliminated Ensemble Empirical Mode Decomposition Scalogram Analysis for Rotating Machinery Fault Diagnosis.
Faysal A; Ngui WK; Lim MH; Leong MS
Sensors (Basel); 2021 Dec; 21(23):. PubMed ID: 34884120
[TBL] [Abstract][Full Text] [Related]
20. Health Degradation Monitoring and Early Fault Diagnosis of a Rolling Bearing Based on CEEMDAN and Improved MMSE.
Lv Y; Yuan R; Wang T; Li H; Song G
Materials (Basel); 2018 Jun; 11(6):. PubMed ID: 29904002
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
