Abstract: A virtual sensor system and method for the estimation of an amount or concentration of particulate matter resulting from natural or man made processes comprising two or more empirical models arranged for being trained using empirical data from the processes, for receiving one or more signal input values from one or more sensors of the processes and calculating a signal output value based on the signal input values where the signal output value represents an intermediate amount or concentration of particulate matter. Further a combination function is arranged for receiving the signal output values and continuously calculating the amount or concentration of PM.

Abstract: An empirical ensemble based virtual sensor system (VS) for the estimation of an amount of water (C) or oil (A) in a fluid mixture, said virtual sensor comprising two or more empirical models (NN1, NN2, . . . , NNn). The amount is estimated in each of the empirical models (NN1, NN2, . . . , NNn), and a combination function combines (f) the results from the empirical models (NN1, NN2, . . . , NNn) to provide a combined estimate for the amount (yR) that is more accurate than the estimated amount (y1, y2, . . . , yn) from each of the individual empirical models (NN1, NN2, . . . , NNn). The total performance of the virtual sensor system may be increased by increasing the number of empirical models (NN1, NN2, . . . , NNn).

Abstract: An empirical ensemble based virtual sensor system (VS) for the estimation of an amount of a gas (G) resulting from a combustion process (CP) comprising two or more empirical models (NN1, NN2, . . . , NNn). The amount of gas (G) is estimated in each of the empirical models (NN1, NN2, . . . , NNn), and a combination function (f) combines the results from the empirical models (NN1, NN2, . . . , NNn) to provide a combined estimate for the amount of gas (G) that is more accurate than the estimated amount of gas from each of the individual empirical models (y1, y2, . . . , ym). The total performance of the virtual sensor system (VS) may be increased by increasing the number of empirical models (y1, y2, . . . , ym).