For the sake of improving the reliability of measured data

the bi-sensors data fusion method is widely applied to obtain the information on product status in the process control field

and the linearly unbiased estimation theory used as the data fusion method is widely adopted to deal with measurement data. For any estimation process

both variance and bias are the significant indices evaluating the performance of the measurement data. Because the unbiased measurement data possesses unbiased merit

variance can be used to represent the reliability of the unbiased measurement data. However

we can not believe that the unbiased measurement data must be highly reliable. In order to enhance the measurement reliability of the bi-sensors

a novel data fusion method arising from biased estimation was proposed. First

the conclusion that biased measurement could increase the reliability of a single-sensor was proved. Second

the convex combination method was used to derive biased estimation data fusion given the bi-sensors. Finally

the conclusion that the proposed fusion process was always superior to single-sensor measurement in terms of mean square error was proved. Simulation and application in a real plant illustrated that the biased estimation fusion could improve the reliability of the measured data effectively.