Investigation of Chemiresisitive Electronic Nose for the Analysis of Multiple Analytes Using Pattern Recognition Algorithm

Abstract

The multiple analytes produced during the operation of nuclear facilities are required to monitor the smooth operation of the plant in the environment of high temperature and radioactivity in real time. A chemiresisitive electronic nose was investigated and developed to analyze the multiple analytes generated in the nuclear reactor/allied facilities. An electronic nose consists of chemiresisitive sensor, array, housing, hardware, software, and pattern recognition algorithm. The sensor and array of different semiconductor metal oxides were prepared, processed, and developed to sense the multiple analytes. The hardware and data acquisition software (DAS) was designed and developed to acquire the dynamic responses from the array of four sensors. The hardware provides a low excitation voltage for measurement of the dynamic response of four sensors towards the improvement of the life of the sensor. The various experiments were conducted with multiple analytes at different temperatures to study the analysis of analytes. The performance of the hardware and DAS were tested and evaluated with the sensor array responses towards three analytes, viz., hydrogen (H2), formaldehyde (HCHO), and hydrazine (NH2NH2). Different features evaluated from the response traces were processed to teach the instrument using pattern recognition algorithms. The training and real-time testing of the sensor array realized the qualitative discrimination and quantitative estimation of the analytes.