Matches in SemOpenAlex for { <https://semopenalex.org/work/W3090363913> ?p ?o ?g. }
Showing items 1 to 91 of
91
with 100 items per page.
- W3090363913 abstract "The traditional fault diagnosis methods for rolling bearing usually require the test data and training data to follow the same distribution, which cannot be always meet in real-world scenarios, since the working condition of rolling bearing is often variable. Hence, to overcome the low performance of fault diagnosis traditional methods for different data distributions, a fault diagnosis approach based on transfer learning is proposed in this paper. And the main idea of our approach is to combine joint distribution adaptation and support vector machine to diagnose bearing faults under variable working conditions. In this research, kernel-JDA is used to reduce the difference between distributions of datasets taking both the marginal and conditional distributions into consideration, while the parameters of kernel-JDA are optimized to improve the performance. Besides, multi-features including time domain features and the relative wavelet packet energy are constructed at first to prepare for fault diagnosis. After mapping the multi-features through kernel-JDA, SVM is utilized to diagnose faults of rolling bearing under different working conditions. In addition, comparison experiments on vibration signal datasets of rolling bearings are carried out to verify the effectiveness and applicability of this approach for both the normal and small sizes of the sample sets." @default.
- W3090363913 created "2020-10-08" @default.
- W3090363913 creator A5031078607 @default.
- W3090363913 creator A5043291162 @default.
- W3090363913 creator A5068107949 @default.
- W3090363913 creator A5069689855 @default.
- W3090363913 creator A5090815103 @default.
- W3090363913 date "2020-07-01" @default.
- W3090363913 modified "2023-10-14" @default.
- W3090363913 title "Rolling Bearing Fault Diagnosis under Variable Working Conditions Based on Joint Distribution Adaptation and SVM" @default.
- W3090363913 cites W1964551425 @default.
- W3090363913 cites W1985716425 @default.
- W3090363913 cites W1993480322 @default.
- W3090363913 cites W2057266281 @default.
- W3090363913 cites W2077942936 @default.
- W3090363913 cites W2082274261 @default.
- W3090363913 cites W2096943734 @default.
- W3090363913 cites W2107074288 @default.
- W3090363913 cites W2120149881 @default.
- W3090363913 cites W2122838776 @default.
- W3090363913 cites W2341914330 @default.
- W3090363913 cites W2584994008 @default.
- W3090363913 cites W2612554669 @default.
- W3090363913 cites W2735326783 @default.
- W3090363913 cites W2810292802 @default.
- W3090363913 cites W2897895022 @default.
- W3090363913 cites W2912244485 @default.
- W3090363913 cites W2990226288 @default.
- W3090363913 doi "https://doi.org/10.1109/ijcnn48605.2020.9207454" @default.
- W3090363913 hasPublicationYear "2020" @default.
- W3090363913 type Work @default.
- W3090363913 sameAs 3090363913 @default.
- W3090363913 citedByCount "7" @default.
- W3090363913 countsByYear W30903639132021 @default.
- W3090363913 countsByYear W30903639132022 @default.
- W3090363913 countsByYear W30903639132023 @default.
- W3090363913 crossrefType "proceedings-article" @default.
- W3090363913 hasAuthorship W3090363913A5031078607 @default.
- W3090363913 hasAuthorship W3090363913A5043291162 @default.
- W3090363913 hasAuthorship W3090363913A5068107949 @default.
- W3090363913 hasAuthorship W3090363913A5069689855 @default.
- W3090363913 hasAuthorship W3090363913A5090815103 @default.
- W3090363913 hasConcept C114614502 @default.
- W3090363913 hasConcept C119857082 @default.
- W3090363913 hasConcept C121332964 @default.
- W3090363913 hasConcept C12267149 @default.
- W3090363913 hasConcept C124101348 @default.
- W3090363913 hasConcept C127313418 @default.
- W3090363913 hasConcept C153180895 @default.
- W3090363913 hasConcept C154945302 @default.
- W3090363913 hasConcept C165205528 @default.
- W3090363913 hasConcept C175551986 @default.
- W3090363913 hasConcept C198394728 @default.
- W3090363913 hasConcept C199978012 @default.
- W3090363913 hasConcept C33923547 @default.
- W3090363913 hasConcept C41008148 @default.
- W3090363913 hasConcept C62520636 @default.
- W3090363913 hasConcept C74193536 @default.
- W3090363913 hasConceptScore W3090363913C114614502 @default.
- W3090363913 hasConceptScore W3090363913C119857082 @default.
- W3090363913 hasConceptScore W3090363913C121332964 @default.
- W3090363913 hasConceptScore W3090363913C12267149 @default.
- W3090363913 hasConceptScore W3090363913C124101348 @default.
- W3090363913 hasConceptScore W3090363913C127313418 @default.
- W3090363913 hasConceptScore W3090363913C153180895 @default.
- W3090363913 hasConceptScore W3090363913C154945302 @default.
- W3090363913 hasConceptScore W3090363913C165205528 @default.
- W3090363913 hasConceptScore W3090363913C175551986 @default.
- W3090363913 hasConceptScore W3090363913C198394728 @default.
- W3090363913 hasConceptScore W3090363913C199978012 @default.
- W3090363913 hasConceptScore W3090363913C33923547 @default.
- W3090363913 hasConceptScore W3090363913C41008148 @default.
- W3090363913 hasConceptScore W3090363913C62520636 @default.
- W3090363913 hasConceptScore W3090363913C74193536 @default.
- W3090363913 hasLocation W30903639131 @default.
- W3090363913 hasOpenAccess W3090363913 @default.
- W3090363913 hasPrimaryLocation W30903639131 @default.
- W3090363913 hasRelatedWork W2041399278 @default.
- W3090363913 hasRelatedWork W2056016498 @default.
- W3090363913 hasRelatedWork W2136184105 @default.
- W3090363913 hasRelatedWork W2160451891 @default.
- W3090363913 hasRelatedWork W2336974148 @default.
- W3090363913 hasRelatedWork W2347401700 @default.
- W3090363913 hasRelatedWork W3013515612 @default.
- W3090363913 hasRelatedWork W4200255588 @default.
- W3090363913 hasRelatedWork W2187500075 @default.
- W3090363913 hasRelatedWork W2345184372 @default.
- W3090363913 isParatext "false" @default.
- W3090363913 isRetracted "false" @default.
- W3090363913 magId "3090363913" @default.
- W3090363913 workType "article" @default.