Application of Soft Sensors in Process Monitoring and Control: A Review

Abstract

A major problem in product quality control in process industries is the difficulty of continuous online measurement of certain output variables especially related to composition. Although analytical instruments are available in some cases, significant time delays associated with most of such instruments make timely control difficult and sometimes impossible. Soft sensor is a modeling approach to estimate hard-to-measure process variables (primary variables) from easy-to-measure online process variables (secondary variables). The important steps of soft sensor development are collection of historical plant data for different variables and their processing, development of a model based on the available data and validation of the model. This paper presents the need and advantages of soft sensor implementation in process industries and does a critical review of various techniques available for data handling and modeling.