JP6868954B2 - プロセスプラントでの自動的信号処理ベースの学習、プロセスプラントでビッグデータベースの学習を提供するためのシステム及び方法、プロセスプラントでビッグデータベースの学習を自動的に実施するためのシステム - Google Patents
プロセスプラントでの自動的信号処理ベースの学習、プロセスプラントでビッグデータベースの学習を提供するためのシステム及び方法、プロセスプラントでビッグデータベースの学習を自動的に実施するためのシステム Download PDFInfo
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Description
本開示は、「BIG DATA IN PROCESS CONTROL SYSTEMS」と題され、2013年3月3日に出願された米国特許出願第13/784,041号、「METHOD AND APPARATUS FOR CONTROLLING A PROCESS PLANT WITH LOCATION AWARE MOBILE CONTROL DEVICES」と題され、2013年9月17日に出願された米国特許出願第14/028,785号、「COLLECTING AND DELIVERING DATA TO A BIG DATA MACHINE IN A PROCESS CONTROL SYSTEM」と題され、2014年2月6日に出願された米国特許出願第14/174,413号、「DISTRIBUTED BIG DATA IN A PROCESS CONTROL SYSTEM」と題され、2014年3月14日に出願された米国特許出願第14/212,493号、及び「DETERMINING ASSOCIATIONS AND ALIGNMENTS OF PROCESS ELEMENTS AND MEASUREMENTS IN A PROCESS」と題され、2014年3月14日に出願された米国特許出願第14/212,411号に関連し、各々の開示全体が参照により本明細書に明示的に組み込まれる。
Claims (40)
- プロセスを制御するプロセスプラントでビッグデータベースの学習を提供するためのシステムであって、
信号処理モジュールであって、
前記プロセスプラントと関連付けられた信号源によって生成された信号を、前記信号源がリアルタイムで前記信号を生成するときに受信する入力部であって、前記信号が、物理的機能を実施する少なくとも1つのフィールドデバイスを用いることによって、前記プロセスを制御する前記プロセスプラントに基づいて経時的に変化するパラメータ値を示す、前記入力部と、
前記信号の1つ以上の特性を提供する出力部と、を含み、
前記信号に対して信号処理を実施して、前記信号の前記1つ以上の特性を決定するように構成される、信号処理モジュールと、
分析モジュールであって、
前記信号処理モジュールにより提供される前記信号の前記1つ以上の特性を受信する入力部を含み、
前記プロセスプラントと関連付けられ、かつ前記プロセス内で前記信号の上流である要素の集合を決定し、
前記信号の1つ以上の特性に対する各上流要素の影響のそれぞれの強度を、前記各上流要素により生成された過去のデータの推定解析に基づいて機械学習し、
前記信号の前記1つ以上の特性に対する前記上流要素の集合の元の影響のそれぞれの前記学習された強度の比較に基づいて、前記上流要素の集合の少なくとも1つの元が前記信号の前記1つ以上の特性の1つ以上の源に含まれると決定するように構成され、
前記少なくとも1つの元が前記信号の前記1つ以上の特性の前記1つ以上の源に含まれることを示す学習情報を、1以上の受信者アプリケーションに提供する、出力部をさらに含む、分析モジュールと、を備える前記システム。 - 前記信号源は、前記プロセスの少なくとも一部分を制御するプロセス制御デバイス、プロセス変数、前記プロセスプラントのプロセス制御ビッグデータネットワークに含まれるビッグデータプロバイダノード、前記プロセスプラント内の1台の設備、または前記プロセスプラントの資産のうちの少なくとも1つである、請求項1に記載の前記システム。
- 前記信号処理モジュール及び前記信号源は、一体型デバイスに含まれる、請求項1又は請求項2に記載の前記システム。
- 前記一体型デバイスは、プロセス制御デバイスであり、前記プロセス制御デバイスは、コントローラ、前記プロセスの少なくとも一部分を制御するように物理的機能を実施するフィールドデバイス、または前記コントローラ及び前記フィールドデバイスを通信可能に接続する入力/出力(I/O)デバイスのうちの1つである、請求項3に記載の前記システム。
- 前記一体型デバイスは、前記プロセスプラントのプロセス制御ビッグデータネットワークに含まれるビッグデータノードであり、前記ビッグデータノードは、ローカルビッグデータノード、地域的ビッグデータノード、集中型ビッグデータノード、または別のビッグデータノードのうちの1つである、請求項3又は請求項4に記載の前記システム。
- 前記信号処理モジュールは、前記信号源が含まれる第2のデバイスに結合された第1のデバイスに含まれる、請求項1又は請求項2に記載の前記システム。
- 前記第2のデバイスは、前記プロセスの少なくとも一部分を制御するプロセス制御デバイスであり、前記プロセス制御デバイスは、コントローラ、前記プロセスの前記少なくとも前記一部分を制御するように物理的機能を実施するフィールドデバイス、または前記コントローラ及び前記フィールドデバイスを通信可能に接続する入力/出力(I/O)デバイスのうちの1つである、請求項6に記載の前記システム。
- プレゼンテーションモジュールをさらに備え、前記プレゼンテーションモジュールは、
前記分析モジュールから前記学習情報を受信する入力部と、
前記学習情報を前記1つ以上の受信者アプリケーションに提供する出力部と、を含み、
前記学習情報は、前記少なくとも1つの元が前記信号の前記1つ以上の特性の前記1つ以上の源に含まれることを示す学習情報、および前記分析モジュールによって学習した他の情報のうちの少なくとも1つを含む、請求項1〜請求項7の何れか1項に記載の前記システム。 - 前記プレゼンテーションモジュールは、前記1つ以上の受信者アプリケーションを決定するように構成される、請求項8に記載の前記システム。
- 前記分析モジュールは、第1の分析モジュールであり、前記第1の分析モジュールは、(i)前記信号の前記1つ以上の特性に対する前記上流要素の集合の前記元の影響の前記それぞれの強度、及び(ii)他の分析モジュールによって提供された情報に基づいて、前記信号の前記1つ以上の特性の前記1つ以上の源を決定する、請求項1〜請求項9の何れか1項に記載の前記システム。
- 前記他の分析モジュールは、プロセス要素アライメントモジュールを含む、請求項10に記載の前記システム。
- 前記信号処理モジュール及び前記分析モジュールはともに、前記プロセスプラントのネットワークに通信可能に接続される単一のビッグデータノードに含まれる、請求項1〜請求項11の何れか1項に記載の前記システム。
- 前記信号処理モジュールは、前記プロセスプラントに対応する第1のノードに含まれ、前記分析モジュールは、前記プロセスプラントに対応する第2のノードに含まれ、前記第2のノードは、前記第1のノードに通信可能に接続される、請求項1〜請求項11の何れか1項に記載の前記システム。
- 前記第1のノードは、前記信号源をさらに含み、前記第2のノードは、前記プロセスプラントのプロセス制御ビッグデータネットワークに含まれるビッグデータノードである、請求項13に記載の前記システム。
- プロセスを制御するプロセスプラントでビッグデータベースの学習を自動的に実施するためのシステムであって、
信号処理モジュールであって、
信号源によって生成された信号であって、それぞれの物理的機能を実施する少なくとも1つのフィールドデバイスを用いることによって前記プロセスを制御する前記プロセスプラントに基づいて経時的に変化するパラメータ値を示す、前記信号を、前記信号源がリアルタイムで前記信号を生成するときに受信することと、
前記信号を受信しつつ前記信号に対してリアルタイムで信号処理を実施して、前記信号の1つ以上の特性を決定することと、を行うように構成された前記信号処理モジュールと、
分析モジュールであって、
前記信号処理モジュールによって決定された前記1つ以上の特性を受信することと、
前記プロセスプラントと関連付けられ、かつ前記プロセス内で前記信号の上流である要素の集合を決定することと、
前記信号の1つ以上の特性に対する各上流要素のそれぞれの影響を、前記各上流要素により生成された過去のデータの推定解析に基づいて機械学習することと、
前記信号の前記1つ以上の特性の1つ以上の源を決定することであって、前記1つ以上の源が前記上流要素の集合の1つ以上の元であり、上流要素の集合の前記1つ以上の元の各々が、前記1つ以上の元に含まれない前記上流要素の集合の少なくとも1つの他の元の学習されたそれぞれの影響より大きい、前記信号の前記1つ以上の特性に対する学習されたそれぞれの影響を有する、前記決定することと、
前記少なくとも1つの元が前記信号の前記1つ以上の特性の前記1つ以上の源に含まれることを示す学習情報を受信者アプリケーションに提供させることであって、前記受信者アプリケーションが、ユーザインターフェースアプリケーションまたは別のアプリケーションである、前記提供させることと、を行うように構成された前記分析モジュールと、を備える、前記システム。 - 前記受信者アプリケーションは、第1の受信者アプリケーションであり、
前記システムは、前記分析モジュールの出力を受信し、前記出力を決定された受信者アプリケーションの集合に送達させるように構成されたプレゼンテーションモジュールをさらに備え、
前記第1の受信者アプリケーションは、前記決定された受信者アプリケーションの集合に含まれ、
前記少なくとも1つの元が前記信号の前記1つ以上の特性の前記1つ以上の源に含まれることを示す学習情報は、前記分析モジュールの前記出力に含まれる、請求項15に記載の前記システム。 - 前記分析モジュールの出力は、様々な学習段階にわたって前記分析モジュールによって決定された追加の学習した知識をさらに含む、請求項15又は請求項16に記載の前記システム。
- 前記学習情報は、前記信号、前記信号源、または前記信号の前記1つ以上の特性のうちの少なくとも1つが、前記受信者アプリケーションに提供されることを特定する情報を含む、請求項15〜請求項17の何れか1項に記載の前記システム。
- 前記信号処理モジュールは、第1のノードに含まれ、前記分析モジュールは、前記第1のノードに通信可能に結合された第2のノードに含まれる、請求項15〜請求項18の何れか1項に記載の前記システム。
- 前記信号源は、前記第1のノードに含まれる、請求項19に記載の前記システム。
- 前記第1のノードは、
前記プロセスの少なくとも一部分を制御するように動作するプロセス制御デバイスであって、前記プロセスの少なくとも一部分を制御するように物理的機能を実施するフィールドデバイス、コントローラ、もしくは前記フィールドデバイス及び前記コントローラを通信可能に接続する入力/出力(I/O)デバイスのうちの1つである、前記プロセス制御デバイス、または
前記プロセスプラントのプロセス制御ビッグデータネットワークに含まれる第1のビッグデータプロバイダノード、のうちの少なくとも1つであり、
前記第2のノードは、前記プロセス制御ビッグデータネットワークに含まれる第2のビッグデータノードである、請求項19又は請求項20に記載の前記システム。 - 前記信号処理モジュール及び前記分析モジュールは、一体型デバイスまたはノードに含まれる、請求項15〜請求項18の何れか1項に記載の前記システム。
- 前記一体型デバイスまたはノードは、
前記プロセスの少なくとも一部分を制御するように動作するプロセス制御デバイスであって、前記プロセスの少なくとも一部分を制御するように物理的機能を実施するフィールドデバイス、コントローラ、もしくは前記フィールドデバイス及び前記コントローラを通信可能に接続する入力/出力(I/O)デバイスのうちの1つである、前記プロセス制御デバイス、または
前記プロセスプラントのプロセス制御ビッグデータネットワークに含まれるビッグデータノード、のうちの少なくとも1つである、請求項22に記載の前記システム。 - 前記パラメータ値は、プロセス制御デバイスの出力信号、プロセス変数、測定値、エネルギーのバランス、質量のバランス、またはビッグデータ分析関数または分析モジュールによって生成された出力のうちの1つの値を示す、請求項1〜請求項23の何れか1項に記載の前記システム。
- 前記信号に対して実施された前記信号処理は、フィルタリング、大きさもしくは振幅分析、電力分析、強度分析、位相分析、周波数分析、スペクトラムもしくはスペクトル分析、相関分析、畳み込み、平滑化、ヒルベルト変換、レベル検出、線形信号処理、非線形信号処理、または別の信号処理技術のうちの少なくとも1つを引き起こすことを含む、請求項1〜請求項24の何れか1項に記載の前記システム。
- 前記信号の前記1つ以上の特性は、前記信号の卓越周波数、n次周波数(nは1より大きい整数である)、調波、分数調波、または分岐のうちの少なくとも1つを含む、請求項1〜請求項25の何れか1項に記載の前記システム。
- 前記信号の前記1つ以上の特性の前記1つ以上の源は、プロセス制御デバイス、プロセス変数、1台の設備、または前記プロセスプラントに対応し、かつ前記信号源の上流である資産のうちの少なくとも1つを含む、請求項1〜請求項26の何れか1項に記載の前記システム。
- 前記分析モジュールは、第1の分析モジュールであり、前記システムは、第2の分析モジュールをさらに含み、少なくとも1つの受信者アプリケーションは、第2の分析モジュールに含まれる、請求項1〜請求項27の何れか1項に記載の前記システム。
- 前記システム又は前記信号処理モジュールの少なくとも1つは、ユーザ入力を使用せずにリアルタイムで自律的に動作する、請求項1〜請求項28の何れか1項に記載の前記システム。
- 前記パラメータ値の前記経時的な変化は、1つ以上の振動を含む、請求項1〜請求項29の何れか1項に記載の前記システム。
- プロセスを制御するプロセスプラントでビッグデータベースの学習を提供するための方法であって、
信号処理ベースの学習システムで、パラメータ値の経時的な変化を取得することであって、前記パラメータ値の経時的な前記変化が、信号源によって生成された信号であり、前記パラメータ値の経時的な前記変化が、前記プロセスプラントで前記プロセスを制御することに基づいて生成され、前記信号が、前記信号源がリアルタイムで前記信号を生成するときに取得される、前記取得することと、
前記信号源がリアルタイムで前記信号を生成しつつ、前記信号処理ベースの学習システムによって、1つ以上の信号処理機能を前記信号にリアルタイムで適用させることと、
前記信号処理ベースの学習システムによって、前記1つ以上の信号処理機能の前記適用に基づいて前記信号の少なくとも1つの特性を決定することと、
前記信号処理ベースの学習システムによって、前記プロセスプラントと関連付けられ、かつ前記プロセス内で前記信号の上流である要素の集合を決定することと、
前記信号の少なくとも1つの特性に対する各上流要素の影響のそれぞれの強度を、前記各上流要素により生成された過去のデータの推定解析に基づいて機械学習することと、
前記上流要素の集合の少なくとも部分集合を前記信号の前記少なくとも1つの特性の1つ以上の源であると決定することであって、前記少なくとも前記部分集合の前記決定が、前記信号の前記少なくとも1つの特性に対する上流要素の前記集合の影響のそれぞれの学習された強度に基づいている、前記決定することと、
前記信号処理ベースの学習システムによって、前記信号の前記少なくとも1つの特性の前記1つ以上の源を受信者アプリケーションに提供させることであって、前記受信者アプリケーションがユーザインターフェースアプリケーションまたは別のアプリケーションである、前記提供させることと、を含む、前記方法。 - 前記パラメータ値の経時的な前記変化を取得することは、プロセス制御デバイスの出力信号、プロセス変数、測定値、エネルギーのバランスを示すパラメータ、質量のバランスを示すパラメータ、または前記プロセスプラントによって生成されたビッグデータに対して実施された分析関数の出力のうちの1つの値の経時的な変化を取得することを含む、請求項31に記載の前記方法。
- 信号処理を前記信号に対して実施させることは、フィルタリング、大きさもしくは振幅分析、電力分析、強度分析、位相分析、周波数分析、スペクトラムもしくはスペクトル分析、相関分析、畳み込み、平滑化、ヒルベルト変換、レベル検出、線形信号処理、非線形信号処理、または別の信号処理技術のうちの少なくとも1つを前記信号に対して実施させることを含む、請求項31又は請求項32に記載の前記方法。
- 前記信号処理機能を前記信号に適用させて前記信号の前記少なくとも1つの特性を決定することは、前記信号処理機能を前記信号に対して実施させて、卓越周波数、n次周波数(nは1より大きい整数である)、調波、分数調波、または分岐のうちの少なくとも1つを決定することを含む、請求項31〜請求項33の何れか1項に記載の前記方法。
- 前記信号処理機能に基づいて前記信号の前記少なくとも1つの特性を決定することは、前記信号処理機能に基づき、かつ前記プロセスの少なくとも一部分がオンラインである間に取得された測定値、前記プロセスの前記少なくとも一部分がオフラインである間に取得された測定値、または前記プロセスの前記少なくとも前記一部分のモデルから取得されたデータ、のうちの少なくとも1つに基づいて、前記信号の前記少なくとも1つの特性を決定することを含む、請求項31〜請求項34の何れか1項に記載の前記方法。
- 前記上流要素の集合の前記少なくとも前記部分集合を前記信号の前記少なくとも1つの特性の前記1つ以上の源であると決定することは、プロセス制御デバイス、1台の設備、プロセス変数、または前記信号の前記少なくとも1つの特性の前記1つ以上の源である資産、のうちの少なくとも1つを決定することを含む、請求項31〜請求項35の何れか1項に記載の前記方法。
- 前記方法が1秒以下の期間にわたって実施されるか、または
前記方法が監視されていない方法であるか、のうちの少なくとも1つである、請求項31〜請求項36の何れか1項に記載の前記方法。 - 前記パラメータ値の経時的な前記変化を取得することが、前記パラメータ値の経時的な前記変化を検出することを含むか、または
前記信号の経時的な前記変化を取得することが、前記信号に含まれる1つ以上の振動を取得することを含むか、のうちの少なくとも1つである、請求項31〜請求項37の何れか1項に記載の前記方法。 - 前記信号処理ベースの学習システムは、信号処理モジュールに結合された分析モジュールを含み、
前記信号処理ベースの学習システムによって、前記信号の前記少なくとも1つの特性の前記1つ以上の源を決定することは、前記信号処理ベースの学習システムの前記分析モジュールによって、前記信号の前記少なくとも1つの特性の前記1つ以上の源を決定することを含む、請求項31〜請求項38の何れか1項に記載の前記方法。 - 前記分析モジュールは、第1の分析モジュールであり、
前記信号を取得することが第2の分析モジュールから信号を取得することを含むか、または
前記信号の前記少なくとも1つの特性の前記1つ以上の源を前記受信者アプリケーションに提供させることが、前記信号の前記少なくとも1つの特性の前記1つ以上の源を前記第2の分析モジュールもしくは第3の分析モジュールに提供させることを含むか、のうちの少なくとも1つである、請求項39に記載の前記方法。
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