@techreport{oai:jaxa.repo.nii.ac.jp:00001779,
 author = {梅津, 里香 and 杉江, 卓哉 and 長瀬, 雅之 and 湖海, 亮 and 竹島, 敏明 and 海老沢, 研 and 満田, 和久 and 山本, 幸生 and Umezu, Rika and Sugie, Takuya and Nagase, Masayuki and Kokai, Ryo and Takeshima, Toshiaki and Ebisawa, Ken and Mitsuda, Kazuhisa and Yamamoto, Yukio},
 month = {Mar},
 note = {宇宙機は安全性や信頼性が厳しく問われ, 未然に危険を予知し, 事故防止に繋げる運用環境が望まれる. 宇宙機の運用データに機械学習の技術を適用して故障解析を行い, 不具合を未然に検知する技術を蓄積し, 安定した宇宙機運用に資するための研究を行っている. X線天文衛星「すざく」の運用データを用いた電源系機器の故障の予兆検知を試み, 一定条件下での故障の予兆を検出することが可能であることを確認した., Safety and reliability of the spacecraft are very important. It is desirable to predict possible failures of a spacecraft in advance and to have an operational environment leading to accident prevention. By applying failure analysis utilizing machine learning technology to the operation data of a spacecraft, we accumulate techniques to detect defects beforehand and are doing research to contribute to stable operation of the spacecraft. We tried to detect a sign of failure of the power supply using operational data of the X-ray astronomical satellite 'Suzaku'. As a result, we suggest that it is possible to detect a sign of failure under certain conditions., 形態: カラー図版あり, Physical characteristics: Original contains color illustrations, 資料番号: AA1830035002, レポート番号: JAXA-RR-18-008},
 title = {機械学習を用いた宇宙機の故障の予兆検知},
 year = {2019}
}