{"created":"2024-02-22T09:38:22.022633+00:00","id":2000299,"links":{},"metadata":{"_buckets":{"deposit":"e2be6eb1-5bc5-4744-973e-15d1fc1bc7aa"},"_deposit":{"created_by":27,"id":"2000299","owner":"27","owners":[27],"pid":{"revision_id":0,"type":"depid","value":"2000299"},"status":"published"},"_oai":{"id":"oai:jaxa.repo.nii.ac.jp:02000299","sets":["1398:1399:1708576775690","1887:1893","9:10:1695275225494:1708576492834"]},"author_link":[],"item_1692929429513":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":" 安全な衛星運用を実現するため、衛星テレメトリデータの異常を早期に検知することは極めて重要である。2023年9月7日（日本時間）に打ち上げられたXRISM衛星では、異常検知システムATMOS(Automatic Telemetry Monitor Software)が使用されている。しかしATMOS はテレメトリ時系列データの閾値判定を主とした汎用システムであり、データの特性に即した異常検知にはミッションごとの異常検知システムが相補的に必要である。本研究では、XRISM衛星に搭載されたミッション機器Resolveのデータに対する異常検知アルゴリズムの開発を行った。地上試験データを用いて機械学習的な手法を用い、Resolve装置のテレメトリデータに現れる二種の異常—検出器ノイズスペクトルに含まれる異常と、検出器の温度データに含まれる異常—の検知アルゴリズムの開発を通して、同手法の有用性を検証した。","subitem_description_language":"ja","subitem_description_type":"Other"},{"subitem_description":" Early detection of anomalies in spacecraft telemetry data is important for ensuring the safe operation of the spacecraft. The XRISM satellite, launched on September 6, 2023 (UTC), utilizes the Automatic Telemetry Monitor Software (ATMOS) for this purpose. However, ATMOS serves as a general system primarily designed for analyzing time-series telemetry data. Consequently, each mission necessitates dedicated complementary systems. In this article, we present the results of an anomaly detection algorithm applied to the Resolve instrument onboard XRISM. Our methodology entails a machine-learning approach utilizing actual data collected during ground testing. We assess the efficacy of this approach in detecting anomalies in the detector noise spectra and the coldstage temperature data.","subitem_description_language":"en","subitem_description_type":"Other"}]},"item_1692929640552":{"attribute_name":"内容記述","attribute_value_mlt":[{"subitem_description":"形態: カラー図版あり","subitem_description_language":"ja","subitem_description_type":"Other"},{"subitem_description":"Physical  characteristics: Original contains color illustrations","subitem_description_language":"en","subitem_description_type":"Other"}]},"item_1693474141533":{"attribute_name":"資料番号(Local)","attribute_value_mlt":[{"subitem_relation_type_id":{"subitem_relation_type_id_text":"資料番号: AA2330025005","subitem_relation_type_select":"Local"}}]},"item_1694684272217":{"attribute_name":"日付","attribute_value_mlt":[{"subitem_date_issued_datetime":"2023-11-30","subitem_date_issued_type":"Submitted"}]},"item_1695282775758":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_language":"ja","subitem_text_value":"東京大学大学院理学系研究科"},{"subitem_text_language":"ja","subitem_text_value":"宇宙航空研究開発機構宇宙科学研究所 (JAXA)(ISAS)"},{"subitem_text_language":"en","subitem_text_value":"Graduate School of Science, The University of Tokyo"},{"subitem_text_language":"en","subitem_text_value":"Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency (JAXA)(ISAS)"}]},"item_3_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2024-02-27","bibliographicIssueDateType":"Issued"},"bibliographicPageEnd":"55","bibliographicPageStart":"45","bibliographicVolumeNumber":"JAXA-RR-23-007","bibliographic_titles":[{"bibliographic_title":"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13号","bibliographic_titleLang":"ja"},{"bibliographic_title":"JAXA Research and Development Report: Journal of Space Science Informatics Japan: Volume 13","bibliographic_titleLang":"en"}]}]},"item_3_description_33":{"attribute_name":"レポート番号","attribute_value_mlt":[{"subitem_description":"レポート番号: JAXA-RR-23-007","subitem_description_language":"ja","subitem_description_type":"Other"}]},"item_3_identifier_registration":{"attribute_name":"ID登録","attribute_value_mlt":[{"subitem_identifier_reg_text":"10.20637/0002000299","subitem_identifier_reg_type":"JaLC"}]},"item_3_publisher_8":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"宇宙航空研究開発機構 (JAXA)","subitem_publisher_language":"ja"},{"subitem_publisher":"Japan Aerospace Exploration Agency (JAXA)","subitem_publisher_language":"en"}]},"item_3_source_id_22":{"attribute_name":"ISSN ONLINE","attribute_value_mlt":[{"subitem_source_identifier":"2433-2216","subitem_source_identifier_type":"EISSN"}]},"item_3_version_type_30":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_access_right":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"open access","subitem_access_right_uri":"http://purl.org/coar/access_right/c_abf2"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorAffiliations":[{"affiliationNames":[{"affiliationName":"東京大学","affiliationNameLang":"ja"},{"affiliationName":"The University of Tokyo","affiliationNameLang":"en"}]}],"creatorNames":[{"creatorName":"柏崎, 未有","creatorNameLang":"ja"},{"creatorName":"KASHIWAZAKI, Miu","creatorNameLang":"en"}]},{"creatorAffiliations":[{"affiliationNames":[{"affiliationName":"宇宙航空研究開発機構 (JAXA)","affiliationNameLang":"ja"},{"affiliationName":"Japan Aerospace Exploration Agency (JAXA)","affiliationNameLang":"en"}]}],"creatorNames":[{"creatorName":"辻本, 匡弘","creatorNameLang":"ja"},{"creatorName":"TSUJIMOTO, Masahiro","creatorNameLang":"en"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2024-02-27"}],"filename":"AA2330025005.pdf","format":"application/pdf","mimetype":"application/pdf","url":{"url":"https://jaxa.repo.nii.ac.jp/record/2000299/files/AA2330025005.pdf"},"version_id":"154d65a3-ec1b-493a-a96d-3a1148d0cad2"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"XRISM","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Resolve","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"anomaly detection","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"machine learning","subitem_subject_language":"en","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"technical report","resourceuri":"http://purl.org/coar/resource_type/c_18gh"}]},"item_title":"機械学習を用いたXRISM衛星搭載極低温検出器の異常検知アルゴリズムの開発","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"機械学習を用いたXRISM衛星搭載極低温検出器の異常検知アルゴリズムの開発","subitem_title_language":"ja"},{"subitem_title":"Development of the machine learning-based anomaly detection algorithms for the low-temperature detector onboard the XRISM satellite","subitem_title_language":"en"}]},"item_type_id":"40003","owner":"27","path":["1708576492834","1893","1708576775690"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2024-02-27"},"publish_date":"2024-02-27","publish_status":"0","recid":"2000299","relation_version_is_last":true,"title":["機械学習を用いたXRISM衛星搭載極低温検出器の異常検知アルゴリズムの開発"],"weko_creator_id":"27","weko_shared_id":-1},"updated":"2024-02-27T04:30:51.319286+00:00"}