JP6789848B2 - アイソレーション管理システムおよびアイソレーション管理方法 - Google Patents
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Description
Claims (7)
- 少なくとも遮断器と断路器と分電盤とから成る複数の要素を用いて構築されたプラントに関する少なくとも設計図書を含む情報が記憶されたデータベースと、
前記プラントにおけるアイソレーション作業の対象箇所の指定を受け付ける受付部と、
前記指定された対象箇所に関する前記要素の状態を変化させたときに、他の箇所の前記要素で生じる状態の変化のパターンを前記データベースに記憶された情報に基づいて解析する解析部と、
前記解析された変化のパターンが複数あり、これらの変化のパターンから特定のパターンを深層学習に基づいて抽出する深層学習部と、
前記抽出された特定のパターンに基づいて作業計画を生成する計画生成部と、
前記生成された作業計画を出力する出力部と、
を備え、
前記深層学習部は、
多層のニューラルネットワークから成る中間層と、
学習済みの前記多層のニューラルネットワークを構築するための学習データを生成する学習データ生成部と、
を備え、
前記学習データ生成部は、
前記解析部で解析された前記遮断器および前記断路器の開放状態または遮断状態を0または1で表現した第1行列データを生成する第1行列データ生成部と、
前記解析部で解析された前記遮断器および前記断路器の前記開放状態または前記遮断状態に対応する前記分電盤の導通状態または非導通状態を0または1で表現した第2行列データを生成する第2行列データ生成部と、
を備え、
前記深層学習部は、前記第1行列データおよび前記第2行列データを含む前記学習データを前記多層のニューラルネットワークに学習させて、この学習済みの前記多層のニューラルネットワークにより前記変化のパターンの特徴量を取得し、この特徴量に基づいて前記特定のパターンを抽出するアイソレーション管理システム。 - 前記作業計画に従って前記対象箇所に関する前記要素の状態を変化させたときに、他の箇所の前記要素で生じる状態の変化のパターンを前記データベースに記憶された情報に基づいて検証する検証部を備える請求項1に記載のアイソレーション管理システム。
- 過去のアイソレーション作業で用いた作業計画の情報が前記データベースに記憶されており、
前記学習データ生成部は、前記データベースに記憶された前記過去の作業計画に基づいて前記学習データを生成する請求項1または請求項2に記載のアイソレーション管理システム。 - 前記深層学習部は、
前記データベースに記憶された情報に報酬関数を設定する報酬関数設定部と、
複数の前記特定のパターンを抽出し、これらの特定のパターンから前記報酬関数に基づいて価値が最も高くなるものを抽出する強化学習部と、
を備える請求項1から請求項3のいずれか1項に記載のアイソレーション管理システム。 - 前記深層学習部は、前記抽出された特定のパターンに基づいて前記アイソレーション作業の操作手順を抽出する操作手順抽出部を備え、
前記計画生成部は、前記抽出された操作手順に基づいて前記作業計画を生成する請求項1から請求項4のいずれか1項に記載のアイソレーション管理システム。 - 前記解析部は、アナログ回路の解析を行うアナログ回路解析部と、論理回路の解析を行う論理回路解析部と、経路探索の解析を行う経路探索解析部との少なくともいずれかを備える請求項1から請求項5のいずれか1項に記載のアイソレーション管理システム。
- 少なくとも遮断器と断路器と分電盤とから成る複数の要素を用いて構築されたプラントに関する少なくとも設計図書を含む情報をデータベースに記憶する記憶ステップと、
前記プラントにおけるアイソレーション作業の対象箇所の指定を受け付ける受付ステップと、
前記指定された対象箇所に関する前記要素の状態を変化させたときに、他の箇所の前記要素で生じる状態の変化のパターンを前記データベースに記憶された情報に基づいて解析する解析ステップと、
前記解析された変化のパターンが複数あり、これらの変化のパターンから特定のパターンを深層学習に基づいて抽出する深層学習ステップと、
前記抽出された特定のパターンに基づいて作業計画を生成する計画生成ステップと、
前記生成された作業計画を出力する出力ステップと、
を含み、
多層のニューラルネットワークから成る中間層と、
学習済みの前記多層のニューラルネットワークを構築するための学習データを生成する学習データ生成部と、
を備える深層学習部が、
前記解析ステップで解析された前記遮断器および前記断路器の開放状態または遮断状態を0または1で表現した第1行列データを生成し、
前記解析ステップで解析された前記遮断器および前記断路器の前記開放状態または前記遮断状態に対応する前記分電盤の導通状態または非導通状態を0または1で表現した第2行列データを生成し、
前記第1行列データおよび前記第2行列データを含む前記学習データを前記多層のニューラルネットワークに学習させて、
前記深層学習ステップにて、前記学習済みの前記多層のニューラルネットワークにより前記変化のパターンの特徴量を取得し、この特徴量に基づいて前記特定のパターンを抽出するアイソレーション管理方法。
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JP2017034494A JP6789848B2 (ja) | 2017-02-27 | 2017-02-27 | アイソレーション管理システムおよびアイソレーション管理方法 |
KR1020180016036A KR20180099469A (ko) | 2017-02-27 | 2018-02-09 | 아이솔레이션 관리 시스템 및 아이솔레이션 관리 방법 |
GB1802549.4A GB2561073B (en) | 2017-02-27 | 2018-02-16 | Isolation management system and isolation management method |
CA2996576A CA2996576A1 (en) | 2017-02-27 | 2018-02-26 | Isolation management system and isolation management method |
RU2018106748A RU2678146C1 (ru) | 2017-02-27 | 2018-02-26 | Система управления отключениями и способ управления отключениями |
US15/905,237 US20180246478A1 (en) | 2017-02-27 | 2018-02-26 | Isolation management system and isolation management method |
CN201810160566.9A CN108508852B (zh) | 2017-02-27 | 2018-02-27 | 隔离管理***与隔离管理方法 |
FR1851684A FR3063369B1 (fr) | 2017-02-27 | 2018-02-27 | Dispositif de gestion de l'isolement et procede de gestion de l'isolement |
KR1020200074438A KR20200074936A (ko) | 2017-02-27 | 2020-06-18 | 아이솔레이션 관리 시스템 및 아이솔레이션 관리 방법 |
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JP7141320B2 (ja) * | 2018-12-05 | 2022-09-22 | 株式会社日立製作所 | 強化学習支援装置、保守計画立案装置、及び強化学習支援方法 |
JP7179600B2 (ja) * | 2018-12-07 | 2022-11-29 | 株式会社東芝 | アイソレーション管理装置、方法及びプログラム |
JP7118916B2 (ja) * | 2019-03-20 | 2022-08-16 | 株式会社東芝 | アイソレーション作業の計画立案支援装置、方法及びプログラム |
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CN108508852A (zh) | 2018-09-07 |
RU2678146C1 (ru) | 2019-01-23 |
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CA2996576A1 (en) | 2018-08-27 |
FR3063369A1 (fr) | 2018-08-31 |
GB2561073A (en) | 2018-10-03 |
JP2018142060A (ja) | 2018-09-13 |
GB201802549D0 (en) | 2018-04-04 |
KR20200074936A (ko) | 2020-06-25 |
GB2561073B (en) | 2020-10-14 |
FR3063369B1 (fr) | 2023-12-01 |
CN108508852B (zh) | 2021-08-03 |
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