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Data-Driven Fault Detection Method for Electronic Boards in Intelligent Remote Dual-Valve System

Title: Data-Driven Fault Detection Method for Electronic Boards in Intelligent Remote Dual-Valve System
Authors: Bhatnagar, Saransh; Lemanissier Cassou, Mathilde; Al Masry, Zeina; Mosallam, Ahmed
Contributors: Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174) (FEMTO-ST); Université de Technologie de Belfort-Montbeliard (UTBM)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Centre National de la Recherche Scientifique (CNRS)-Université de Franche-Comté (UFC); Université Bourgogne Franche-Comté COMUE (UBFC)-Université Bourgogne Franche-Comté COMUE (UBFC); Phuc Do; Steve King; Olga Fink
Source: 6th European Conference of the Prognostics and Health Management Society; https://hal.science/hal-03455020; 6th European Conference of the Prognostics and Health Management Society, Nov 2021, En ligne, France. pp.53-59, ⟨10.36001/phme.2021.v6i1.2903⟩; https://papers.phmsociety.org/index.php/phme/article/view/2903
Publisher Information: CCSD; PHM Society
Publication Year: 2021
Collection: Université de Franche-Comté (UFC): HAL
Subject Terms: [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]; [SPI.AUTO]Engineering Sciences [physics]/Automatic
Subject Geographic: En ligne; France
Description: International audience ; Prognostics and health management (PHM) approach, and theoretical models have had great success for industrial systems. Therefore, this motivates us to think about implementing PHM approach for an intelligent remote dual-valve (IRDV) system. Several tool failures during operations occurred, for which the electronics subsystem of IRDV was suspected without being able to reproduce the issue during failure analysis. The aim of this paper is hence to develop a health analyzer for the electronics subsystem of IRDV. This will help the field users identify if the electronics behaved as expected or not using existing job data, classified as healthy or unhealthy from an electronic point of view. Numerical results using real datasets are provided and discussed.
Document Type: conference object
Language: English
DOI: 10.36001/phme.2021.v6i1.2903
Availability: https://hal.science/hal-03455020; https://hal.science/hal-03455020v1/document; https://hal.science/hal-03455020v1/file/07b2e901-ab6b-480c-8c44-df6558725b66-author.pdf; https://doi.org/10.36001/phme.2021.v6i1.2903
Rights: info:eu-repo/semantics/OpenAccess
Accession Number: edsbas.384F83BF
Database: BASE