Reliability Analysis of Cold-standby Systems with Subsystems Using Conditional Binary Decision Diagrams,ERICDATA高等教育知識庫
高等教育出版
熱門: Qiaoyun Zhang  Scopus AI  Helong Xia  美国 通识教育计划  Semi-trusted loader  Zhi-Wei Sun  
高等教育出版
首頁 臺灣期刊 學校系所 學協會 民間出版 大陸/海外期刊 政府機關 學校系所 學協會 民間出版 DOI查詢服務 DOI註冊服務
篇名
Reliability Analysis of Cold-standby Systems with Subsystems Using Conditional Binary Decision Diagrams
並列篇名
Reliability Analysis of Cold-standby Systems with Subsystems Using Conditional Binary Decision Diagrams
作者 Siwei Zhou、Yinghuai Yu、Xiaohong Peng
英文摘要

Cold-standby systems have been widely used for conditions with limited power, which achieve fault tolerance and high-reliability systems. The cold spare (CSP) gate is a common dynamic gate in the dynamic fault tree (DFT). DFT with CSP gates is typically used to model a cold-standby system for reliability analysis. In general, inputs of the CSP gate are considered to be basic events. However, with the requirement of the current system design, the inputs of the CSP gate may be either basic events or top events of subtrees. Hence, the sequence-dependency among basic events in CSP gates becomes much more complex. However, the early conditional binary decision diagram (CBDD) used for the reliability analysis of spare gates does not consider it well. To address this problem, the conditioning event rep is improved to describe the replacement behavior in CSP gates with subtrees inputs, and the related formulae are derived. Further, a combinatorial method based on the CBDD is demonstrated to evaluate the reliability of cold-standby systems modeled by CSP gates with subtrees inputs. The case study is presented to show the advantage of using our method.

 

起訖頁 931-943
關鍵詞 Dynamic fault tree、Conditional binary decision diagram、Conditioning event、Reliability、Dependable computing
刊名 網際網路技術學刊  
期數 202307 (24:4期)
出版單位 台灣學術網路管理委員會
DOI 10.53106/160792642023072404011   複製DOI
QR Code
該期刊
上一篇
Discovery of New Words in Tax-related Fields Based on Word Vector Representation
該期刊
下一篇
A Web Service Clustering Method with Semantic Enhancement Based on RGPS and BTM

高等教育知識庫  新書優惠  教育研究月刊  Ericdata高等教育知識庫