141 related articles for article (PubMed ID: 37998242)
1. Fault Diagnosis of Rotating Machinery Using Kernel Neighborhood Preserving Embedding and a Modified Sparse Bayesian Classification Model.
Lu L; Wang W; Kong D; Zhu J; Chen D
Entropy (Basel); 2023 Nov; 25(11):. PubMed ID: 37998242
[TBL] [Abstract][Full Text] [Related]
2. A hybrid intelligent multi-fault detection method for rotating machinery based on RSGWPT, KPCA and Twin SVM.
Liu Z; Guo W; Hu J; Ma W
ISA Trans; 2017 Jan; 66():249-261. PubMed ID: 27837907
[TBL] [Abstract][Full Text] [Related]
3. Rotating Machinery Fault Diagnosis Based on Improved Multiscale Amplitude-Aware Permutation Entropy and Multiclass Relevance Vector Machine.
Chen Y; Zhang T; Zhao W; Luo Z; Lin H
Sensors (Basel); 2019 Oct; 19(20):. PubMed ID: 31635428
[TBL] [Abstract][Full Text] [Related]
4. Fault Diagnosis for Rotating Machinery: A Method based on Image Processing.
Lu C; Wang Y; Ragulskis M; Cheng Y
PLoS One; 2016; 11(10):e0164111. PubMed ID: 27711246
[TBL] [Abstract][Full Text] [Related]
5. 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]
6. Fault Diagnosis for Rotating Machinery Using Vibration Measurement Deep Statistical Feature Learning.
Li C; Sánchez RV; Zurita G; Cerrada M; Cabrera D
Sensors (Basel); 2016 Jun; 16(6):. PubMed ID: 27322273
[TBL] [Abstract][Full Text] [Related]
7. Multi-Sensor Data Fusion Using a Relevance Vector Machine Based on an Ant Colony for Gearbox Fault Detection.
Liu Z; Guo W; Tang Z; Chen Y
Sensors (Basel); 2015 Aug; 15(9):21857-75. PubMed ID: 26334280
[TBL] [Abstract][Full Text] [Related]
8. Bayesian-Optimized Hybrid Kernel SVM for Rolling Bearing Fault Diagnosis.
Song X; Wei W; Zhou J; Ji G; Hussain G; Xiao M; Geng G
Sensors (Basel); 2023 May; 23(11):. PubMed ID: 37299863
[TBL] [Abstract][Full Text] [Related]
9. Fault diagnosis of rotating machinery with ensemble kernel extreme learning machine based on fused multi-domain features.
Pang S; Yang X; Zhang X; Lin X
ISA Trans; 2020 Mar; 98():320-337. PubMed ID: 31492472
[TBL] [Abstract][Full Text] [Related]
10. A Novel Method for Fault Diagnosis of Rotating Machinery.
Tang M; Liao Y; Luo F; Li X
Entropy (Basel); 2022 May; 24(5):. PubMed ID: 35626565
[TBL] [Abstract][Full Text] [Related]
11. A Multimodal Feature Fusion-Based Deep Learning Method for Online Fault Diagnosis of Rotating Machinery.
Zhou F; Hu P; Yang S; Wen C
Sensors (Basel); 2018 Oct; 18(10):. PubMed ID: 30340412
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. Deep residual learning-based fault diagnosis method for rotating machinery.
Zhang W; Li X; Ding Q
ISA Trans; 2019 Dec; 95():295-305. PubMed ID: 30598323
[TBL] [Abstract][Full Text] [Related]
14. Feature Space Transformation for Fault Diagnosis of Rotating Machinery under Different Working Conditions.
Jang GB; Cho SB
Sensors (Basel); 2021 Feb; 21(4):. PubMed ID: 33670547
[TBL] [Abstract][Full Text] [Related]
15. A Novel Image-Based Diagnosis Method Using Improved DCGAN for Rotating Machinery.
Gao Y; Piltan F; Kim JM
Sensors (Basel); 2022 Oct; 22(19):. PubMed ID: 36236633
[TBL] [Abstract][Full Text] [Related]
16. Fault Diagnosis for Rotating Machinery Using Multiscale Permutation Entropy and Convolutional Neural Networks.
Li H; Huang J; Yang X; Luo J; Zhang L; Pang Y
Entropy (Basel); 2020 Jul; 22(8):. PubMed ID: 33286622
[TBL] [Abstract][Full Text] [Related]
17. Research on rolling bearing fault diagnosis based on multi-dimensional feature extraction and evidence fusion theory.
Li J; Ying Y; Ren Y; Xu S; Bi D; Chen X; Xu Y
R Soc Open Sci; 2019 Feb; 6(2):181488. PubMed ID: 30891276
[TBL] [Abstract][Full Text] [Related]
18. Supervised Manifold Learning Based on Multi-Feature Information Discriminative Fusion within an Adaptive Nearest Neighbor Strategy Applied to Rolling Bearing Fault Diagnosis.
Wang H; Yao L; Wang H; Liu Y; Li Z; Wang D; Hu R; Tao L
Sensors (Basel); 2023 Dec; 23(24):. PubMed ID: 38139669
[TBL] [Abstract][Full Text] [Related]
19. A periodic-modulation-oriented noise resistant correlation method for industrial fault diagnostics of rotating machinery under the circumstances of limited system signal availability.
Hou Y; Wu P; Wu D
ISA Trans; 2024 Jun; ():. PubMed ID: 38851927
[TBL] [Abstract][Full Text] [Related]
20. A Sparsity-Promoted Method Based on Majorization-Minimization for Weak Fault Feature Enhancement.
Ren B; Hao Y; Wang H; Song L; Tang G; Yuan H
Sensors (Basel); 2018 Mar; 18(4):. PubMed ID: 29597280
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]