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In this paper, we consider a SDMS (Self-Diagnostic Monitoring System) for a reciprocating pump for the purpose of not only diagnosis but also prognosis. We have replaced a multi class estimator that selects only the most probable one with a multi label estimator such that we are able to see the state of each of the components. We have introduced a measure called certainty so that we are able to represent the symptom and its state. We have built a flow loop for a reciprocating pump system and presented some results. With these changes, we are not only able to detect both the dominant symptom as well as others but also to monitor how the degree of severity of each component changes. About the dominant ones, we found that the overall recognition rate of our algorithm is about 99.7% which is slightly better than that of the former SDMS. Also, we are able to see the trend and to make a base to find prognostics to estimate the remaining useful life. With this we hope that we have gone one step closer to the final goal of prognosis of SDMS.

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권호기사 목록 테이블로 기사명, 저자명, 페이지, 원문, 기사목차 순으로 되어있습니다.
기사명 저자명 페이지 원문 목차
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Derivation of preliminary derived concentration guideline level (DCGL) by reuse scenario for Kori unit 1 using RESRAD-BUILD Sang June Park, Jihyang Byon, Doo Hyun Ban, Suhee Lee, Wook Sohn, Seokyoung Ahn p. 1231-1242

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참고문헌 (20건) : 자료제공( 네이버학술정보 )

참고문헌 목록에 대한 테이블로 번호, 참고문헌, 국회도서관 소장유무로 구성되어 있습니다.
번호 참고문헌 국회도서관 소장유무
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13 J. Sun, H. Li, B. Xu, Prognostic for hydraulic pump based upon DCT-composite spectrum and the modified echo state network, SpringerPlus 5(2016), 1293, DOI 10.1186/s40064-016-2933-7. 미소장
14 P. Baraldi, G. Bonfanti, E. Zio, Differential evolution-based multi-objective optimization for the definition of a health indicator for fault diagnostics and prognostics, Mech. Syst. Signal Process. 102 (2018) 382-400. 미소장
15 Using Two-Class Classifiers for Multiclass Classification 네이버 미소장
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