Visualization of spacecraft data based on interdependency between changing points in time series

Yuichi Sato, Yoshinobu Kawahara, Takehisa Yairi, Kazuo Machida

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A support technology for spacecraft operators is one of the important themes for reliable operation. We suggest a framework for visualization of relations among sequences based on "changing points". First, we employ auto-regression model for detecting changing points from data. And next, we apply a structure learning of dynamic Bayesian Net to the change-detected data for getting the graph structure, which stands for dependency among sequences. We applied this approach to two kinds of actual telemetry data of a communication satellite, and verified graph structures rightly showed the relation among sequences.

Original languageEnglish
Title of host publication2006 SICE-ICASE International Joint Conference
Pages3414-3418
Number of pages5
DOIs
Publication statusPublished - Dec 1 2006
Externally publishedYes
Event2006 SICE-ICASE International Joint Conference - Busan, Korea, Republic of
Duration: Oct 18 2006Oct 21 2006

Publication series

Name2006 SICE-ICASE International Joint Conference

Other

Other2006 SICE-ICASE International Joint Conference
CountryKorea, Republic of
CityBusan
Period10/18/0610/21/06

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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  • Cite this

    Sato, Y., Kawahara, Y., Yairi, T., & Machida, K. (2006). Visualization of spacecraft data based on interdependency between changing points in time series. In 2006 SICE-ICASE International Joint Conference (pp. 3414-3418). [4108350] (2006 SICE-ICASE International Joint Conference). https://doi.org/10.1109/SICE.2006.315124