Spacecraft telemetry data monitoring by dimensionality reduction techniques

Takehisa Yairi, Minoru Inui, Akihiro Yoshiki, Yoshinobu Kawahara, Noboru Takata

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

11 引用 (Scopus)

抜粋

In this paper, we consider a "data-driven" anomaly detection framework for spacecraft systems using dimensionality reduction and reconstruction techniques. This method first learns a mapping from the original data space to a low dimensional space and its reverse mapping by applying linear or non-linear dimensionality reduction algorithms to a normal training data set. After the training, it applies the learned pair of mappings to a test data set to obtain a reconstructed data set, and then evaluate the reconstruction errors. We will show the results of applying several representative linear and non-lineardimensionality reduction algorithms with this framework to the electrical power subsystem (EPS) data of actual artificial satellites.

元の言語英語
ホスト出版物のタイトルProceedings of SICE Annual Conference 2010, SICE 2010 - Final Program and Papers
出版者Society of Instrument and Control Engineers (SICE)
ページ1230-1234
ページ数5
ISBN(印刷物)9784907764364
出版物ステータス出版済み - 2010

出版物シリーズ

名前Proceedings of the SICE Annual Conference

All Science Journal Classification (ASJC) codes

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

フィンガープリント Spacecraft telemetry data monitoring by dimensionality reduction techniques' の研究トピックを掘り下げます。これらはともに一意のフィンガープリントを構成します。

  • これを引用

    Yairi, T., Inui, M., Yoshiki, A., Kawahara, Y., & Takata, N. (2010). Spacecraft telemetry data monitoring by dimensionality reduction techniques. : Proceedings of SICE Annual Conference 2010, SICE 2010 - Final Program and Papers (pp. 1230-1234). [5602754] (Proceedings of the SICE Annual Conference). Society of Instrument and Control Engineers (SICE).