FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3127518744> ?p ?o ?g. }

• W3127518744 endingPage "1251" @default.
• W3127518744 startingPage "1251" @default.
• W3127518744 abstract "Safety is the most important aspect of railway transportation. To ensure the safety of high-speed trains, various train components are equipped with sensor devices for real-time monitoring. Sensor monitoring data can be used for fast intelligent diagnosis and accurate positioning of train faults. However, existing train fault diagnosis technology based on cloud computing has disadvantages of long processing times and high consumption of computing resources, which conflict with the real-time response requirements of fault diagnosis. Aiming at the problems of train fault diagnosis in the cloud environment, this paper proposes a train fault diagnosis model based on edge and cloud collaboration. The model first utilizes a SAES-DNN (stacked auto-encoders deep neural network) fault recognition method, which can integrate automatic feature extraction and type recognition and complete fault classification over deep hidden features in high-dimensional data, so as to quickly locate faults. Next, to adapt to the characteristics of edge computing, the model applies a SAES-DNN model trained in the cloud and deployed in the edge via the transfer learning strategy and carries out real-time fault diagnosis on the vehicle sensor monitoring data. Using a motor fault as an example, when compared with a similar intelligent learning model, the proposed intelligent fault diagnosis model can greatly improve diagnosis accuracy and significantly reduce training time. Through the transfer learning approach, adaptability of the fault diagnosis algorithm for personalized applications and real-time performance of the fault diagnosis is enhanced. This paper also proposes a visual analysis method of train fault data based on knowledge graphs, which can effectively analyze fault causes and fault correlation." @default.
• W3127518744 created "2021-02-15" @default.
• W3127518744 creator A5001389153 @default.
• W3127518744 creator A5019914789 @default.
• W3127518744 creator A5030299019 @default.
• W3127518744 creator A5031788526 @default.
• W3127518744 creator A5062806935 @default.
• W3127518744 creator A5085838727 @default.
• W3127518744 date "2021-01-29" @default.
• W3127518744 modified "2023-10-01" @default.
• W3127518744 title "A Fault Diagnosis and Visualization Method for High-Speed Train Based on Edge and Cloud Collaboration" @default.
• W3127518744 cites W1529533208 @default.
• W3127518744 cites W1970436661 @default.
• W3127518744 cites W1987581326 @default.
• W3127518744 cites W1998408918 @default.
• W3127518744 cites W2041316884 @default.
• W3127518744 cites W2046182115 @default.
• W3127518744 cites W2076063813 @default.
• W3127518744 cites W2112145487 @default.
• W3127518744 cites W2135099885 @default.
• W3127518744 cites W2136922672 @default.
• W3127518744 cites W2151162785 @default.
• W3127518744 cites W2161944915 @default.
• W3127518744 cites W2404692435 @default.
• W3127518744 cites W2420613574 @default.
• W3127518744 cites W2595141258 @default.
• W3127518744 cites W2603304445 @default.
• W3127518744 cites W2768753204 @default.
• W3127518744 cites W2792853279 @default.
• W3127518744 cites W2808080995 @default.
• W3127518744 cites W2897593833 @default.
• W3127518744 cites W2935727815 @default.
• W3127518744 cites W2950865323 @default.
• W3127518744 cites W2967115638 @default.
• W3127518744 cites W2997658030 @default.
• W3127518744 cites W3026105287 @default.
• W3127518744 cites W3040461295 @default.
• W3127518744 cites W3081301927 @default.
• W3127518744 cites W3085543912 @default.
• W3127518744 cites W3096526468 @default.
• W3127518744 cites W3097663423 @default.
• W3127518744 cites W3106869630 @default.
• W3127518744 cites W3109180935 @default.
• W3127518744 cites W3113008830 @default.
• W3127518744 cites W3116400523 @default.
• W3127518744 cites W3116517911 @default.
• W3127518744 doi "https://doi.org/10.3390/app11031251" @default.
• W3127518744 hasPublicationYear "2021" @default.
• W3127518744 type Work @default.
• W3127518744 sameAs 3127518744 @default.
• W3127518744 citedByCount "9" @default.
• W3127518744 countsByYear W31275187442022 @default.
• W3127518744 countsByYear W31275187442023 @default.
• W3127518744 crossrefType "journal-article" @default.
• W3127518744 hasAuthorship W3127518744A5001389153 @default.
• W3127518744 hasAuthorship W3127518744A5019914789 @default.
• W3127518744 hasAuthorship W3127518744A5030299019 @default.
• W3127518744 hasAuthorship W3127518744A5031788526 @default.
• W3127518744 hasAuthorship W3127518744A5062806935 @default.
• W3127518744 hasAuthorship W3127518744A5085838727 @default.
• W3127518744 hasBestOaLocation W31275187441 @default.
• W3127518744 hasConcept C101738243 @default.
• W3127518744 hasConcept C108583219 @default.
• W3127518744 hasConcept C111919701 @default.
• W3127518744 hasConcept C127313418 @default.
• W3127518744 hasConcept C154945302 @default.
• W3127518744 hasConcept C162307627 @default.
• W3127518744 hasConcept C165205528 @default.
• W3127518744 hasConcept C175551986 @default.
• W3127518744 hasConcept C190839683 @default.
• W3127518744 hasConcept C205649164 @default.
• W3127518744 hasConcept C41008148 @default.
• W3127518744 hasConcept C50644808 @default.
• W3127518744 hasConcept C58640448 @default.
• W3127518744 hasConcept C79403827 @default.
• W3127518744 hasConcept C79974875 @default.
• W3127518744 hasConceptScore W3127518744C101738243 @default.
• W3127518744 hasConceptScore W3127518744C108583219 @default.
• W3127518744 hasConceptScore W3127518744C111919701 @default.
• W3127518744 hasConceptScore W3127518744C127313418 @default.
• W3127518744 hasConceptScore W3127518744C154945302 @default.
• W3127518744 hasConceptScore W3127518744C162307627 @default.
• W3127518744 hasConceptScore W3127518744C165205528 @default.
• W3127518744 hasConceptScore W3127518744C175551986 @default.
• W3127518744 hasConceptScore W3127518744C190839683 @default.
• W3127518744 hasConceptScore W3127518744C205649164 @default.
• W3127518744 hasConceptScore W3127518744C41008148 @default.
• W3127518744 hasConceptScore W3127518744C50644808 @default.
• W3127518744 hasConceptScore W3127518744C58640448 @default.
• W3127518744 hasConceptScore W3127518744C79403827 @default.
• W3127518744 hasConceptScore W3127518744C79974875 @default.
• W3127518744 hasIssue "3" @default.
• W3127518744 hasLocation W31275187441 @default.
• W3127518744 hasOpenAccess W3127518744 @default.
• W3127518744 hasPrimaryLocation W31275187441 @default.
• W3127518744 hasRelatedWork W2669956259 @default.
• W3127518744 hasRelatedWork W2939353110 @default.
• W3127518744 hasRelatedWork W2966001425 @default.

• next