JP5026433B2 - プロセスモデルベースの仮想センサシステムおよび方法 - Google Patents
プロセスモデルベースの仮想センサシステムおよび方法 Download PDFInfo
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- JP5026433B2 JP5026433B2 JP2008541159A JP2008541159A JP5026433B2 JP 5026433 B2 JP5026433 B2 JP 5026433B2 JP 2008541159 A JP2008541159 A JP 2008541159A JP 2008541159 A JP2008541159 A JP 2008541159A JP 5026433 B2 JP5026433 B2 JP 5026433B2
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
- F02D—CONTROLLING COMBUSTION ENGINES
- F02D41/00—Electrical control of supply of combustible mixture or its constituents
- F02D41/02—Circuit arrangements for generating control signals
- F02D41/14—Introducing closed-loop corrections
- F02D41/1401—Introducing closed-loop corrections characterised by the control or regulation method
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B17/00—Systems involving the use of models or simulators of said systems
- G05B17/02—Systems involving the use of models or simulators of said systems electric
Description
MDi=(Xi−μx)Σ−1(Xi−μx)’ (1)
ここで、μxはXの平均値であり、およびΣ−1はXの逆分散共分散行列である。MDiは、同一の多変量正常密度輪郭にある観測値が同一の距離を有するように、データ点Xiとその平均値のμxとの距離を重み付けする。このような観測値を用いて、異なる分散を有する別個のデータ群から相関パラメータを特定して選択することが可能である。
Claims (10)
- 仮想センサシステム用の方法であって、
複数の検出パラメータと複数の測定パラメータとの間の相互関係を示す仮想センサプロセスモデルを確立するステップであって、
1つ以上の入力変数と複数の検出パラメータとに関連するデータ記録を得るステップ、
1つ以上の入力変数から複数の測定パラメータを選択するステップ、
複数の測定パラメータと複数の検出パラメータとの間の相互関係を示す計算モデルを生成するステップ、
計算モデルの複数の測定パラメータの所望の統計分布を決定するステップ、及び、
所望の統計分布に基づき複数の測定パラメータを再較正して、所望の入力空間を定義するステップ
を含む、ステップ、
複数の測定パラメータに対応する一組の値を得るステップ、
複数の測定パラメータに対応する一組の値と仮想センサプロセスモデルとに基づいて、複数の検出パラメータの値を同時に計算するステップ、並びに、
複数の検出パラメータの値を制御システムに提供するステップ
を含む方法。 - 選択するステップが、
データ記録を前処理するステップと、
遺伝的アルゴリズムを用いて、データ記録の正常データセットと異常データセットとの間のマハラノビス距離に基づき、1つ以上の入力変数から複数の測定パラメータを選択するステップと、
をさらに含む請求項1に記載の方法。 - 提供するステップが、
物理センサから複数の検出パラメータの値を別々に得るステップと、
物理センサが故障したかを決定するステップと、
複数の検出パラメータの値を仮想センサプロセスモデルから制御システムに提供するステップと、
を含む請求項1に記載の方法。 - 複数の検出パラメータがNOxエミッションレベルを含む請求項1に記載の方法。
- 複数の測定パラメータが、吸気マニホールド温度、吸気マニホールド圧力、周囲湿度、燃料比およびエンジン速度を含む請求項1に記載の方法。
- 機械であって、
機械に動力を供給するように構成された動力源と、
動力源を制御するように構成された制御システムと、
複数の検出パラメータと複数の測定パラメータとの間の相互関係を示す仮想センサプロセスモデルを含む仮想センサシステムであって、
複数の測定パラメータに対応する一組の値を得るように、
複数の測定パラメータに対応する一組の値と仮想センサプロセスモデルとに基づいて複数の検出パラメータの値を同時に計算するように、及び、
複数の検出パラメータの値を制御システムに提供するように構成された仮想センサシステムと、
を備え、仮想センサプロセスモデルが、
1つ以上の入力変数と複数の検出パラメータとに関連するデータ記録を得ることによって、
1つ以上の入力変数から複数の測定パラメータを選択することによって、
複数の測定パラメータと複数の検出パラメータとの間の相互関係を示す計算モデルを生成することによって、
計算モデルの複数の測定パラメータの所望の統計分布を決定することによって、及び、
所望の統計分布に基づき複数の測定パラメータを再較正して、所望の入力空間を定義することによって確立され、
制御システムが、複数の検出パラメータの値に基づいて動力源を制御する機械。 - 制御システムと仮想センサシステムとの間のデータリンクであって、仮想センサシステムが、データリンクを介して複数の検出パラメータの値を制御システムに提供するデータリンクと、
データリンクを介して、対応する複数の検出パラメータの値を制御システムに別々に提供するように構成された1つ以上の物理センサと、
をさらに含み、
制御システムが、
1つ以上の物理センサが故障したかを決定するように、及び、
仮想センサシステムからの複数の検出パラメータの値に基づいて動力源を制御するようにさらに構成される請求項7に記載の機械。 - 仮想センサプロセスモデルを確立するためのコンピュータシステムにおいて、
仮想センサプロセスモデルに関連する情報をストアするように構成されたデータベース、及び、プロセッサを備え、
該プロセッサが、
1つ以上の入力変数と複数の検出パラメータとに関連するデータ記録を得るように、
1つ以上の入力変数から複数の測定パラメータを選択するように、
複数の測定パラメータと複数の検出パラメータとの間の相互関係を示す計算モデルを生成するように、
計算モデルの複数の測定パラメータの所望の統計分布を決定するように、及び、
所望の統計分布に基づき複数の測定パラメータを再較正して、所望の入力空間を定義するように構成されたコンピュータシステム。 - 仮想センサプロセスモデルを確立するためのコンピュータシステムに使用されるコンピュータ可読記憶媒体であってコンピュータ実行可能命令を有するコンピュータ可読記憶媒体において、該コンピュータ実行可能命令が実行されたときに該コンピュータシステムに、
1つ以上の入力変数と複数の検出パラメータとに関連するデータ記録を得るステップと、
1つ以上の入力変数から複数の測定パラメータを選択するステップと、
複数の測定パラメータと複数の検出パラメータとの間の相互関係を示す計算モデルを生成するステップと、
計算モデルの複数の測定パラメータの所望の統計分布を決定するステップと、
所望の統計分布に基づき複数の測定パラメータを再較正して、所望の入力空間を定義するステップと、
仮想センサプロセスモデルに、制御システムにおいて制御機能を提供するための所望の入力空間を提供するステップと、
を含む方法を実施させるコンピュータ可読記憶媒体。
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US11/281,978 US7499842B2 (en) | 2005-11-18 | 2005-11-18 | Process model based virtual sensor and method |
US11/281,978 | 2005-11-18 | ||
PCT/US2006/035062 WO2007058695A1 (en) | 2005-11-18 | 2006-09-08 | Process model based virtual sensor system and method |
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EP (1) | EP1949312A1 (ja) |
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Cited By (3)
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US11132616B2 (en) | 2016-09-20 | 2021-09-28 | Kabushiki Kaisha Toshiba | Characteristic value estimation device and characteristic value estimation method |
KR102205392B1 (ko) * | 2017-07-28 | 2021-01-19 | 지멘스 악티엔게젤샤프트 | 기술 시스템의 동작을 제어하기 위한 시스템, 방법 및 제어 유닛 |
US11048249B2 (en) | 2017-07-28 | 2021-06-29 | Siemens Aktiengesellschaft | Controlling and maintaining operational status during component failures |
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US7499842B2 (en) | 2009-03-03 |
CN101331504A (zh) | 2008-12-24 |
US20070118338A1 (en) | 2007-05-24 |
EP1949312A1 (en) | 2008-07-30 |
AU2006315933B2 (en) | 2011-12-01 |
WO2007058695A1 (en) | 2007-05-24 |
JP2009520948A (ja) | 2009-05-28 |
AU2006315933A1 (en) | 2007-05-24 |
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