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Special Issue on Embedded Sensors for Fault Diagnosis in Electrical Wiring Interconnection Systems, Power Grids, Structural Cables, Pipelines, and Electrical Machines

Abstract : In the era of the Internet of Things (IoT), electrical wiring interconnection systems (EWIS) are massively hosted everywhere in many fields where the transfer of energy and information is a fundamental pillar to guarantee the good performance of a system. In addition, the huge technological and industrial uprising ensured by the emerging fourth Industrial Revolution is forcing electrical machines and instruments toward massive transformations and more complexity than ever before. Accordingly, the health and integrity of any system are essential for the proper operation of any application. Yet, faults and failures are inevitable. They can lead to catastrophic problems on both economical and human levels. Airplane crashes, massive fires, explosions, and so on are examples of such consequences. Accordingly, fault detection, diagnosis, and location have been always substantially important for ensuring safety, security, integrity, and optimal performance for any system. Notably, fault diagnosis of structural cables integrated in dams, bridges, concrete, and so on have also formed a cornerstone in the context of health monitoring of such structures. The same applies for oil and gas pipelines, subsea cables, umbilicals, and so on.
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https://hal-cea.archives-ouvertes.fr/cea-03122280
Contributor : Marie-France Robbe <>
Submitted on : Tuesday, January 26, 2021 - 11:35:09 PM
Last modification on : Saturday, May 1, 2021 - 3:50:42 AM
Long-term archiving on: : Tuesday, April 27, 2021 - 7:54:17 PM

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Cynthia Furse, Moussa Kafal, Reza Razzaghi, Yong-June Shin. Special Issue on Embedded Sensors for Fault Diagnosis in Electrical Wiring Interconnection Systems, Power Grids, Structural Cables, Pipelines, and Electrical Machines. IEEE Sensors Journal, Institute of Electrical and Electronics Engineers, 2021, 21 (2), pp.886-887. ⟨10.1109/JSEN.2020.3035852⟩. ⟨cea-03122280⟩

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