A method and system for online microwave moisture detection in cigarette packs

Abstract

The invention provides an online microwave moisture detection method and system for a tobacco bale. The method comprises the following steps of: (1) obtaining internal moisture of tobacco bale leaves; (2) obtaining attenuation A and phase difference P measurement components of an online microwave moisture detection device; and (3) establishing a mathematic model of the internal moisture and the attenuation A and phase difference P measurement components; predicating the internal moisture of the tobacco bale by utilizing the mathematic model. The system provided by the invention is used for complementing the method and comprises an analyzer enclosure, and a power supply unit, a control unit, a moisture predication module, a microwave signal transmitter, a transmitting antenna, a receiving antenna and a microwave signal processing unit, which are mounted in the analyzer enclosure. The online microwave moisture detection method and system provided by the invention have the advantages of capability of detecting the whole moisture in the tobacco bale, high detection precision, simplicity in detection, stability in operation, wide applicable range and the like.

Description

technical field [0001] The invention mainly relates to the field of tobacco physical and chemical analysis, in particular to an online microwave moisture detection method and system for cigarette packs. Background technique [0002] "Cigarette pack" is one of the main production raw materials in the silk workshop. The leaves in the cigarette bale go through the unpacking machine and the slicer, and then enter the loose moistening machine for humidification, and mix with a certain amount of liquid. Determining the moisture content of the incoming bale plays a decisive role in the stability of the loose moisture outlet. In order to obtain the internal moisture content of the cigarette package, the oven method can be used to conduct an offline moisture test on the sample. However, this method has high precision, but due to the long time consumption, it cannot meet the needs of silk production. [0003] At present, the online moisture meters used in the tobacco industry mainl...

AI Technical Summary

Problems solved by technology

The near-infrared moisture meter is difficult to measure the internal moisture of the cigarette bale, because: 1. The infrared method can only measure the moisture on the surface of the material, and the moisture on the surface of the cigarette bale cannot represent the actual moisture of the tobacco leaves inside the cigarette bale

Cigarette packs need to be stored in the warehouse of the tobacco factory for a long period of time (one to six years) before they can be put into production. Long-term storage will cause a large difference between the surface moisture of the cigarette pack and the internal moisture

2. The change of material color will significantly affect the measurement results of infrared method

In complex industrial production process, it is difficult to maintain the stability of the above factors

[0006] Conventional microwave moisture measurement devices are difficult to achieve good results in the tobacco industry, especially in the moisture detection of cigarette packs

This is mainly due to: 1) This type of microwave moisture measuring device only directly uses the phase difference (phase shift) or attenuation signal as the detection variable, and the measurement method is single

At the same time, the phase difference (phase shift) and the attenuation signal inevitably have unavoidable random interference, which greatly affects the measurement accuracy

2) It is difficult to establish an effective mathematical model between the moisture inside the cigarette pack and the detected variables

The least squares method needs to assume that the moisture inside the cigarette package and the detected variables conform to a normal distribution, and is easily affected by abnormal observations

At present, there have been literature reports on the method of establishing mathematical models using fuzzy neuron networks based on genetic algorithms. However, this method has a large amount of calculation and is difficult to realize online moisture prediction. At the same time, the fuzzy criteria for establishing decision variables rely on expert knowledge, which is difficult to popularize in practice.

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