Reconciling continuum and non-continuum data with industrial application

In order to perform data reconciliation, it is important that noises in the data have well-defined distributions. The motivation behind this study was to enable the comparison between a discrete and continuous data set so that means can be compared for gross error over the short term; this required that local variables exhibit similar distributions.A case study was done on a system where non-continuum loads from a dump truck were to be reconciled with two downstream continuum weightometers. An algorithm was developed using the binomial distribution and time delay in order to simulate the effect of the dump pocket.Regression analysis based on principal components was used to evaluate the performance of the smoothing algorithm and to determine the most likely maximum hopper capacity that locates between the two weightometers.