Multiple-Sensor Detection System Design for Tea Identification Based on Mutual Information Array Optimization Scheme

In this article, a multimetal oxide sensor (MOS) detection system is developed for the identification of different grades of tea leaves. To cope with the interference brought by redundant information and further improve the detection capability of the system and reduce the number of sensors, sensor array optimization algorithms are further implemented. The main idea of sensor array optimization is to select sensors according to evaluation index which ranks the importance of sensors. This article optimizes the sensor array based on information theory. Specifically, a weighted modified mutual information (MI) optimization algorithm that simultaneously considers relevancy, redundancy, and complementarity is developed. The experimental results show that the weighted modified MI optimization method can obtain the best system performance with the minimum number of sensors.