Providing Service Composition to Cyber-Physical System for Industrial Fault Detection

Xiao, Bo; Zhao, Kang; Tang, Haitao

doi:10.1007/978-981-15-0238-5_63

Cited by 1 publication

(1 citation statement)

References 11 publications

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“…It could be necessary to create a network of fault detection to deliver low consistency from a community of processing tools [16] to a surface diagnosis in industrial manufacturing [17]. To ensure low latency, connectivity, and detection, services are allotted to one route [18] according to the corporation's planned statistical data [19]. Such systems support the network with high priority [20] whiles the recollection of detecting information [21,22].…”

Section: Introduction To Industrial Fault Detection and Diagnosis Networkmentioning

confidence: 99%

Fault Detection and Diagnosis of Cyber-Physical System Using the Computer Vision and Image Processing

Yang

Nie

Zhang

et al. 2021

Wireless Pers Commun

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In the techno world, Corporate Business applies new technologies for manufacturing and production with numerous cyber-physical system strategies. This makes the process depend upon multiple computers, machines, and applications with varying specifications, efficiency, and latency. These technological strategies are extremely diverse on cyber-physical systems, from an extensive range of processing technologies is available. The currently available technologies are not well adapted to these processes, which require information management regarding fault detection and diagnosis at a complexity level separated from technology. In this article, the Image Processing assisted Computer Vision Technology for Fault Detection System (IM-CVFD) is suggested to resolve such issues in industrial cyber-physical systems. Group Activation Mapping Algorithm is presented for efficient information collection from the processed output, simplifying the managing of fault details with different needs. Besides achieving the optimized information concerning latency, efficiency, the Uncertainty Reduction algorithm is introduced. In a suitable processing environment, a detailed simulation is conducted. The empirical findings indicate the high efficiency of the IM-CVFDwitha with a minimum error rate, energy usage, and minimized delay with high service. In contrast with conventional methods, the IM-CVFD obtains a better result efficiently.

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Section: Introduction To Industrial Fault Detection and Diagnosis Networkmentioning

confidence: 99%

Fault Detection and Diagnosis of Cyber-Physical System Using the Computer Vision and Image Processing

Yang

Nie

Zhang

et al. 2021

Wireless Pers Commun

View full text Add to dashboard Cite

show abstract

Providing Service Composition to Cyber-Physical System for Industrial Fault Detection

Cited by 1 publication

References 11 publications

Fault Detection and Diagnosis of Cyber-Physical System Using the Computer Vision and Image Processing

Fault Detection and Diagnosis of Cyber-Physical System Using the Computer Vision and Image Processing

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