An algorithmic approach is developed in the present work, which allows: (i) the classification of the measured and unmeasured process variables, (ii) The estimation of the desired unmeasured variables (using available measurements) in a complex chemical plant and (iii) the rectification of the process measurements. The method is very general and unlike the previous works it can be used in conjunction with linear and nonlinear mass and heat balances. The size of the estimation problem has been reduced significantly. Different algorithms are presented which permit the solution of special practical problems, and stochastic tests are proposed to check the consistency of the process data and detect gross measurement errors. Several examples demonstrate the developed algorithms and indicate the usefulness of the proposed approach, in classifying and estimating the processing variables and adjusting the process data through the utilization of mass and heat balances.
ASJC Scopus subject areas
- Chemical Engineering(all)
- Industrial and Manufacturing Engineering