Research on Optimization Technology for Sequential Diagnostic Strategy based on Improved Quasi-Depth First Search Algorithm

Xiaofeng Lv, Deyun Zhou, Fuqiang Li

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Aiming at the problem that sequential diagnosis strategy optimization techniques for complex avionics systems are currently difficult to obtain optimal solutions quickly and effectively, this paper proposes an improved Quasi-Depth First Search (QDFS) algorithm based on the Rollout algorithm to optimize the design of sequential diagnosis strategies. The algorithm determines a test in two steps. Firstly, the Rollout algorithm is used to construct a temporary diagnostic tree with the selected test as the vertex, and then the "evaluation function"of the improved QDFS algorithm is used to calculate and compare the constructed temporary diagnostic tree to obtain the optimal diagnostic tree. The first test of the diagnostic tree is the current optimal test. Through a case study of sequential diagnosis strategy optimization, the results show that the improved algorithm can obtain a global optimal solution and generate an optimal diagnosis tree compared to the improved QDFS algorithm.

Original languageEnglish
Title of host publicationConference Proceeding - 2023 4th International Conference on Computing, Networks and Internet of Things, CNIOT 2023
PublisherAssociation for Computing Machinery
Pages684-692
Number of pages9
ISBN (Electronic)9798400700705
DOIs
StatePublished - 26 May 2023
Event4th International Conference on Computing, Networks and Internet of Things, CNIOT 2023 - Xiamen, China
Duration: 26 May 202328 May 2023

Publication series

NameACM International Conference Proceeding Series

Conference

Conference4th International Conference on Computing, Networks and Internet of Things, CNIOT 2023
Country/TerritoryChina
CityXiamen
Period26/05/2328/05/23

Keywords

  • Avionics system
  • Diagnostic strategy
  • QDFS algorithm
  • Sequential fault diagnosis
  • Testability model

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