Data validation and reconciliation

Industrial process data validation and reconciliation, or more briefly, data validation and reconciliation (DVR), is a technology that uses process information and mathematical methods in order to automatically correct measurements in industrial processes. The use of DVR allows for extracting accurate and reliable information about the state of industry processes from raw measurement data and produces a single consistent set of data representing the most likely process operation.

Industrial processes, for example chemical or thermodynamic processes in chemical plants, refineries, oil or gas production sites, or power plants, are often represented by two fundamental means:

Models can have different levels of detail, for example one can incorporate simple mass or compound conservation balances, or more advanced thermodynamic models including energy conservation laws. Mathematically the model can be expressed by a nonlinear system of equations ${\displaystyle F(y)=0\,}$ in the variables ${\displaystyle y=(y_{1},\ldots ,y_{n})}$, which incorporates all the above-mentioned system constraints (for example the mass or heat balances around a unit). A variable could be the temperature or the pressure at a certain place in the plant.

Normally distributed measurements without bias.

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