Sensor Data Fusion Framework for Improvement of Temperature Sensor Characteristics

Abstract

This paper presents a multi-sensor data fusion model for measurement of temperature. The proposed paper puts forward an objective to develop a temperature measuring instrument (a) having improved performance characteristics like sensitivity and linearity (b) that produces accurate measurement even though a sensor is faulty. The technique is designed using the framework of multi-sensor data fusion consisting of sensor like thermistor, thermocouple, and resistance temperature detector. Output from all these sensors are converted to a common representation format using radiometric normalization. Pau's framework is used for implementing the task of fusion in the proposed paper. Implemented laboratory model is tested for functionality using extensive set of data. Output shows that the proposed technique was able to produce improved linear and sensitive output as compared to system with individual sensor. Root mean square of percentage error obtained for tests conducted is about 0.86%, which is a significant improvement.