An online cigarette tar prediction and early warning method

Abstract

The invention discloses an online cigarette tar predicting and warning method. The method comprises the following steps: acquiring ingredients of cut tobaccos by using near-infrared light, determining critical factors of a tar prediction model, and composing analysis factors; carrying out weighted distribution on the analysis factors, and constructing the tar prediction model; determining a central value according to monitored values of the analysis factors, and calculating upper and lower control limits, so as to form warning threshold values. According to the method, the cigarette tar prediction model is constructed, so that the deviation of a cigarette tar prediction result is small; corresponding relationships between an optical spectrum and parameters to be measured are established by using an online near-infrared technology so as to determine chemical ingredients of the cut tobaccos, thus, the analysis speed is high, the non-destructivity and sample preparation are low, the method is almost applicable to all kinds of samples, and multicomponent and multichannel simultaneous determination is achieved.

Description

technical field [0001] The invention relates to an online cigarette tar prediction and early warning method. Background technique [0002] As consumers pay more and more attention to the internal quality of cigarettes and product quality and safety indicators, cigarette tar control technology has also made great progress. At present, in terms of cigarette tar control, testing is mainly carried out through smoking machines, gas chromatographs and other instruments, and raw materials are adjusted according to the test results to ensure the stability of cigarette tar. [0003] In terms of tar prediction, the first is to establish a mathematical model to predict the tar content of cigarettes through the proportion of tobacco leaf raw materials in each region in the leaf group formula. The second is to establish a mathematical model to predict the tar content of cigarettes by detecting the contents of main chemical components such as total sugar, total nitrogen, reducing sugar a...

AI Technical Summary

Problems solved by technology

[0004] However, in actual production, due to the long detection cycle of finished cigarette tar, it is difficult for quality control personnel to grasp the change of tar in time, and there is no basis for parameter regulation in the process of lean control of tar, which brings certain difficulties to the work of coke control

[0005] Moreover, with the diversification of cigarette specifications, the settings of indicators such as cigarette ventilation rate, filter length, and single weight are different, and the existing cigarette tar prediction models often have deviations in the prediction results of cigarette tar.

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