Deep‐learning‐based nuclear power plant fault detection using remote light‐emitting diode array data transmission

Author:

Choi Yourak1ORCID,Bae Ji‐Hoon2ORCID,Yeo Doyeob3,Cho Dongyun4,Lee Jaecheol1,Lee Jeonghan1,Kwon Ohseok5

Affiliation:

1. Smart Structural Safety & Prognosis Research Division Korea Atomic Energy Research Institute Daejeon South Korea

2. Department of AI and Big Data Engineering Daegu Catholic University Gyeongsan Gyeongbuk South Korea

3. KSB Convergence Research Department Electronics and Telecommunications Research Institute Daejeon South Korea

4. Biomedical Engineering University of Victoria Victoria Canada

5. The Division of Computer Convergence Chungnam National University Daejeon South Korea

Funder

National Research Foundation of Korea

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Condensed Matter Physics,Atomic and Molecular Physics, and Optics,Electronic, Optical and Magnetic Materials

Reference30 articles.

1. Materials Data Portal for Nuclear Application.http://mdportal.kaeri.re.kr/d20120068/ 2012.

2. ShinSH ParkJH YoonDB YukKS ParkSC andKangMS.Apparatus to reduce vibration of piping Kor Patent 101342725 2013.

3. YoonDB ParkJH MoonSS HanSW KangT.Sensor structure apparatus for monitoring the tube wall thinning and method thereof Kor Patent 101833371.2018.

4. YoonDB ParkJH ShinSH.Pipe leakage point estimating system and method free from reflected wave. Kor Patent 101414374 2014.

5. An impact source localization technique for a nuclear power plant by using sensors of different types

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