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機械学習を用いた宇宙機の故障の予兆検知
https://doi.org/10.20637/JAXA-RR-18-008/0002
https://doi.org/10.20637/JAXA-RR-18-008/000246379fb6-9686-4be9-b0cb-68befc30813c
名前 / ファイル | ライセンス | アクション |
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AA1830035002.pdf (1.2 MB)
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Item type | テクニカルレポート / Technical Report(1) | |||||
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公開日 | 2019-03-08 | |||||
タイトル | ||||||
タイトル | 機械学習を用いた宇宙機の故障の予兆検知 | |||||
言語 | ||||||
言語 | jpn | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | machine learning | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | failure analysis | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | spacecraft | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | Suzaku | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_18gh | |||||
資源タイプ | technical report | |||||
ID登録 | ||||||
ID登録 | 10.20637/JAXA-RR-18-008/0002 | |||||
ID登録タイプ | JaLC | |||||
その他のタイトル(英) | ||||||
その他のタイトル | Detection of failure sign of spacecraft using machine learning | |||||
著者 |
梅津, 里香
× 梅津, 里香× 杉江, 卓哉× 長瀬, 雅之× 湖海, 亮× 竹島, 敏明× 海老沢, 研× 満田, 和久× 山本, 幸生× Umezu, Rika× Sugie, Takuya× Nagase, Masayuki× Kokai, Ryo× Takeshima, Toshiaki× Ebisawa, Ken× Mitsuda, Kazuhisa× Yamamoto, Yukio |
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著者所属 | ||||||
株式会社セック | ||||||
著者所属 | ||||||
株式会社セック | ||||||
著者所属 | ||||||
株式会社セック | ||||||
著者所属 | ||||||
株式会社セック | ||||||
著者所属 | ||||||
宇宙航空研究開発機構宇宙科学研究所(JAXA)(ISAS) | ||||||
著者所属 | ||||||
宇宙航空研究開発機構宇宙科学研究所(JAXA)(ISAS) | ||||||
著者所属 | ||||||
宇宙航空研究開発機構宇宙科学研究所(JAXA)(ISAS) | ||||||
著者所属 | ||||||
宇宙航空研究開発機構宇宙科学研究所(JAXA)(ISAS) | ||||||
著者所属(英) | ||||||
en | ||||||
Systems Engineering Consultants Co., LTD. | ||||||
著者所属(英) | ||||||
en | ||||||
Systems Engineering Consultants Co., LTD. | ||||||
著者所属(英) | ||||||
en | ||||||
Systems Engineering Consultants Co., LTD. | ||||||
著者所属(英) | ||||||
en | ||||||
Systems Engineering Consultants Co., LTD. | ||||||
著者所属(英) | ||||||
en | ||||||
Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency (JAXA)(ISAS) | ||||||
著者所属(英) | ||||||
en | ||||||
Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency (JAXA)(ISAS) | ||||||
著者所属(英) | ||||||
en | ||||||
Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency (JAXA)(ISAS) | ||||||
著者所属(英) | ||||||
en | ||||||
Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency (JAXA)(ISAS) | ||||||
出版者 | ||||||
出版者 | 宇宙航空研究開発機構(JAXA) | |||||
出版者(英) | ||||||
出版者 | Japan Aerospace Exploration Agency (JAXA) | |||||
書誌情報 |
宇宙航空研究開発機構研究開発報告: 宇宙科学情報解析論文誌: 第8号 en : JAXA Research and Development Report: Journal of Space Science Informatics Japan: Volume 8 巻 JAXA-RR-18-008, p. 11-20, 発行日 2019-03-08 |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | 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. | |||||
抄録(英) | ||||||
内容記述タイプ | Other | |||||
内容記述 | 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. | |||||
内容記述 | ||||||
内容記述タイプ | Other | |||||
内容記述 | 形態: カラー図版あり | |||||
内容記述(英) | ||||||
内容記述タイプ | Other | |||||
内容記述 | Physical characteristics: Original contains color illustrations | |||||
ISSNONLINE | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 2433-2216 | |||||
資料番号 | ||||||
内容記述タイプ | Other | |||||
内容記述 | 資料番号: AA1830035002 | |||||
レポート番号 | ||||||
内容記述タイプ | Other | |||||
内容記述 | レポート番号: JAXA-RR-18-008 |