REDUNDANT SENSOR NETWORK DESIGN FOR LINEAR-PROCESSES

Measurements of process variables have a considerable impact on the co ntrol, optimization, safety, and reliability of chemical processes. In a 1993 article, Ali and Narasimhan developed a systematic graph-theor etic procedure for optimally locating a minimum number of sensors in l inear steady-state processes. The sensor network was designed to maxim ize the probability of estimating variables when sensors are likely to fail. This article extends that procedure for the optimal design of a redundant sensor network for linear processes. The algorithm proposed also accounts for specifications of measurable and important variable s. The efficiency and robustness of the proposed algorithm are demonst rated on realistically large processes.