### Abstract

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.

Original language | English |
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Title of host publication | Proceedings of SICE Annual Conference 2010, SICE 2010 - Final Program and Papers |

Publisher | Society of Instrument and Control Engineers (SICE) |

Pages | 1230-1234 |

Number of pages | 5 |

ISBN (Print) | 9784907764364 |

Publication status | Published - Jan 1 2010 |

### Publication series

Name | Proceedings of the SICE Annual Conference |
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### Fingerprint

### All Science Journal Classification (ASJC) codes

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

### Cite this

*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).

**Spacecraft telemetry data monitoring by dimensionality reduction techniques.** / Yairi, Takehisa; Inui, Minoru; Yoshiki, Akihiro; Kawahara, Yoshinobu; Takata, Noboru.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Proceedings of SICE Annual Conference 2010, SICE 2010 - Final Program and Papers.*, 5602754, Proceedings of the SICE Annual Conference, Society of Instrument and Control Engineers (SICE), pp. 1230-1234.

}

TY - GEN

T1 - Spacecraft telemetry data monitoring by dimensionality reduction techniques

AU - Yairi, Takehisa

AU - Inui, Minoru

AU - Yoshiki, Akihiro

AU - Kawahara, Yoshinobu

AU - Takata, Noboru

PY - 2010/1/1

Y1 - 2010/1/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=78649305969&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=78649305969&partnerID=8YFLogxK

M3 - Conference contribution

SN - 9784907764364

T3 - Proceedings of the SICE Annual Conference

SP - 1230

EP - 1234

BT - Proceedings of SICE Annual Conference 2010, SICE 2010 - Final Program and Papers

PB - Society of Instrument and Control Engineers (SICE)

ER -