Intelligent tobacco leaf grading method

Abstract

The invention belongs to the technical field of tobacco processing, and particularly relates to an intelligent tobacco leaf grading method. The method comprises the following steps: step (1), tobacco leaf loosening: tobacco leaves are preliminarily loosened, and preparation is made for winnowing single-piece processing; (2) winnowing and slicing are conducted, specifically, the tobacco leaves loosened in the step (1) are subjected to winnowing, screening is conducted according to the size of pneumatic buoyancy, the single tobacco leaves are upwards pushed in a floating mode, the tobacco leaves which are not sliced gradually form single leaves under the action of wind power, and the tobacco leaves which cannot be sliced are subjected to manual intervention treatment; (3) intelligent identification: in an air duct, performing image acquisition, analysis and identification classification on the tobacco leaves processed in the step (2) by utilizing a machine vision technology, performing visual identification classification on the tobacco leaves conveyed in a single-piece manner, and outputting the tobacco leaves in different channels; the tobacco leaves recognized and output in the step (3) are conveyed, tidying and straightening out are automatically carried out, the head and the tail are conveyed in order, and the tobacco leaves are divided into warehouses and gathered together.

Description

technical field [0001] The invention belongs to the technical field of tobacco processing, and in particular relates to an intelligent grading method for tobacco leaves. Background technique [0002] At present, the sorting tasks of tobacco leaves in threshing and redrying enterprises are all completed by grading workers according to national standards and relying on human sensory judgment. Human senses can distinguish quality factors such as maturity, leaf structure, identity, oil content, color and length of tobacco leaves. Regardless of whether it is a street-stand or dynamic selection, a lot of manpower and material resources are required, and the selection personnel are often less educated, and the degree of mastery of the tobacco leaf sorting ability after skill training is uneven. Factors such as labor shortage in intensive enterprises directly restrict the efficiency and final quality of tobacco leaf sorting. The ability to re-select tobacco leaves has become the s...

AI Technical Summary

Problems solved by technology

At present, domestic tobacco leaves are basically manually graded, which has a series of problems such as time-consuming, laborious, vague and subjective classification. In addition, due to factors such as normal physical fatigue of graders and busy farming periods, labor shortages in labor-intensive enterprises, etc., Directly restricts the efficiency and final quality of tobacco leaf sorting

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