Development of software for data reconciliation of chemical and petrochemical processes

Author(s)

Agremis Guinho Barbosa

• Document type: Master's Dissertation
• Press: Campinas, SP.
• Institution: Universidade Estadual de Campinas (UNICAMP). Faculdade de Engenharia Química
• Defense date: 2003-06-11

Examining board members

Rubens Maciel Filho; Gustavo Paim Valença; Denis José Schiozer

• Advisor: Rubens Maciel Filho

Abstract

The purpose of this work is the development of computational routines for conditioning chemical process data in order to represent the process behavior as reliable as possible. Reliable process description is fundamental for any control or optimization system development, since they respond to the process measurements (its description). Thus, data conditioning and correction of process measurement errors, and parameter estimation are a step that should not be neglected in process control and optimization. The data conditioning considered in this work is data reconciliation which has as the main characteristic the use of a constraint model. In general constraint models are mass and energy balances and mass and molar fraction summation, but other models may be used. Under a mathematical point of view, data reconciliation is an optimization subject to constraints. In this work, it is used the formulation of weighed least squares subject to constraints and QR factorization approach to solve the problem. The additional objective of this work is to accommodate the developed routines in such a way to build up an integrated computational tool characterized by its easy to use structure, capability to solve and perform data reconciliation. Its structure takes into account the interaction with data bank, giving it real time interactiveness with process data acquisition systems (AU)