Identification method of cigar clothing drying stage based on comprehensive accumulated humidity method

Tobacco industry is an important part of our country's economy and cigar is one of the best economic benefits of the product. The accurate identification and process parameter control of cigar drying stage have a vital influence on the quality of finished cigar, and also affect the economic benefit of the whole tobacco industry. However, at present, the most prominent problem in the process of drying cigar is that the identification of drying stage is not accurate, which affects the quality of drying cigar, and then affects the quality of cigar. In this paper, the identification technology and application of tobacco curing stage were studied, and the data of temperature and humidity, tobacco images and water loss rate were used to identify the curing stage of tobacco leaves. The identification model of drying stage is based on the integrated humidity accumulation method, which is used to identify the drying process of cigar. The modeling method is to use the data of tobacco drying process as input after comprehensive humidity accumulation method, and use variable length rolling neural network to construct and train, so as to realize the accurate identification of drying stage. This study can identify the drying stage more accurately, so as to accelerate the automatic and intelligent cigar drying process and improve the quality of cigar drying. At the same time, this research can also be applied to similar application scenarios in other similar industries.