Precursor Gas Sensor Detection and Recognition Based On Metrology Method

In the detection of drugs in the field, because the inclusion complex environment exists, the obtained signal often has a poor signal to noise ratio, and the intrinsic characteristics of the target material is often drowned signal formed in the package material in the background. According to the obtained experimental data, proposed one kind based on the principal component analysis and support vector machine algorithm of gas chromatography identification sensor signal processing and recognition; the method used for detection and identification of the air in the precursor gases combine tester self-developed, obtained very good result. This paper designed and developed a chromatographic separation and sensor based on the combination of gas detection instruments, to multi gas detection instrument. On separation characteristics using chromatography, to solve the traditional single common precursor gas detection. The use of a preprocessing based on domestication, principal component analysis for feature extraction method of all kinds of gas data. This effectively avoids the sensor substrate fluctuation and gas concentration effects on body recognition, and reduces the gas sample feature vector dimension.