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Satellite Fault Diagnosis Technology Based on Intelligent Signal Processing

  • Shuo Jiang
  • , Siyue Jiang
  • , Xiaorui Zhang
  • , Jianyu Liu
  • , Hetong Gao
  • , Chengzhao Shan*
  • , Zhuoming Li
  • *Corresponding author for this work
  • Beijing Institute of Technology
  • China Aerospace Science and Technology Corporation
  • School of Electronics and Information Engineering, Harbin Institute of Technology

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

Abstract

This paper investigates the intelligent fault diagnosis technique for the power converter in the main circuit of the Battery Charge and Discharge Regulation (BCDR) module within satellite power supply and distribution systems. To address potential limitations of traditional shallow networks in fault diagnosis, a Deep Belief Network is employed for fault detection. The study also explores the optimization effects of various algorithms on the parameters of the DBN model. The DBN fault diagnosis model proposed in this paper, which is based on the Adam optimization algorithm, offers a simple and feasible solution for satellite fault diagnosis. It can effectively enhance the stability of satellite power control loops and reduce the operational risks of satellites in orbit.

Original languageEnglish
Title of host publicationEEiSS 2025 - 2025 2nd International Conference on Electronic Engineering and Information Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331523299
DOIs
StatePublished - 2025
Externally publishedYes
Event2nd International Conference on Electronic Engineering and Information Systems, EEiSS 2025 - Nanjing, China
Duration: 23 May 202525 May 2025

Publication series

NameEEiSS 2025 - 2025 2nd International Conference on Electronic Engineering and Information Systems

Conference

Conference2nd International Conference on Electronic Engineering and Information Systems, EEiSS 2025
Country/TerritoryChina
CityNanjing
Period23/05/2525/05/25

Keywords

  • Adam Optimization Algorithm
  • Deep Belief Network
  • Satellite Fault Diagnosis

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