A CENTRAL REMOTE TERMINAL DESIGN FOR FAULT DETECTION BASED ON DATA CORRELATION IN FIXED PROCESS MEASUREMENTS

Abstract

This paper introduced the development of a microcontroller based remote terminal unit employed in collecting and transmitting data from multiple data acquisition systems deployed for pollution measurement in an industrial environment. A fault detection model based on standard deviation and data correlation was implemented to determine measured data deviations from a normal range (weighted mean) which indicated a bias fault condition. The model was tested and validated on a pollution database measured from Ife steel plant Ile-Ife, Osun state in 2014. The research showed the benefits of determining measured data confidence with respect to the absence or presence of off-set bias faults.