The invention provides a model for representing
smoke CO release amount based on a cigarette
microstructure and application of the model. According to the model, a 3D-mu CT scanning technology is adopted to construct a high-resolution fault sequence image in a cigarette sample, a cigarette three-dimensional structure model is established according to the fault sequence image, cigarette structure characteristic parameters are obtained, a cigarette three-dimensional pore
throat ball-stick model is established according to the cigarette structure characteristic parameters, and the cigarette three-dimensional pore
throat ball-stick model is established according to the cigarette structure characteristic parameters. And finally, regression
processing is carried out on the model and the characteristic parameters, then a BP neural
network model is established, neural
network model training and optimization are carried out according to a
CO release amount
data set of the cigarette, and the method is obtained. The model has the advantages of being high in precision, high in speed, small in needed calculation force and the like, tests show that after the model is trained for 1000 times, the average absolute error of a
test set is 0.0016, the average deviation of a
training set is-0.0002, the average deviation of the
test set is-0.0003, and the application requirement for adjusting the cigarette
microstructure and quantitatively controlling the
smoke CO release amount can be met.