Design of a real-time monitoring system for blending ratio and purity of tobacco for hyperspectral imaging

In recent years, hyperspectral imaging technology has a large application prospect in quality inspection in the tobacco industry. The study is based on near infrared spectroscopy technology and partial least squares regression method to establish mathematical analysis model of tobacco adulteration ratio of four components, such as expanded tobacco, stalked tobacco, large threaded tobacco and small threaded tobacco, and carry out internal and external inspection. At the same time, TLBO algorithm is used in the optimization of ELM tobacco purity grade determination model to realize the design of tobacco purity monitoring method, and then build the real-time monitoring system of tobacco blending ratio and purity. Tobacco with different purity grades were selected for experimental testing and model comparison analysis. The results show that the constructed PLS model can accurately predict the adulteration content of the four components in tobacco, and the correlation coefficients between the predicted and actual values are above 0.95 (p < 0.01), and the relative deviation of the prediction is below 3%.The accuracy of the TLBO-ELM model for identifying tobacco with different grades of purity is 88%, and the classification accuracy in the validation set is improved by 9.32% compared with the ELM model, which is within the acceptable range. It shows a better classification effect than PLS-DA in an acceptable range, which proves that the proposed method can be used for discriminating and monitoring the purity of tobacco. The monitoring system in this paper can be used in the analysis of tobacco blending ratio and purity detection.