A method and device for directional grading of machine-picked fresh tea leaf raw materials

Abstract

The invention discloses a method and a device for directional classification of machine-picked fresh tea leaf raw materials. Existing fresh tea leaf sorting devices cannot separate piles of machine-picked fresh tea leaves into different grades. The present invention disperses and spreads the raw materials of machine-picked fresh tea leaves through wind blowing, dispersion and tiling; arranges the fresh machine-picked tea leaves in a longitudinal arrangement according to individual bud leaves by arranging guide leaves; Separation of length differences; through computer image recognition, the separation of one bud and one leaf and one bud and two leaves can be realized, and the grading of machine-picked fresh leaf raw materials can be completed. The horizontal vibrating machine of the present invention is made up of the first vibrating tank, vibrating arm group, vibrating chassis, vibrating chassis and the first motor; Inclined vibrating classifier comprises vibrating tank group, vibrating frame and base; Arranged in order from high to low to form a vibration groove group. The invention effectively realizes the preliminary separation of machine-picked fresh leaves and the subsequent precise and directional separation of one bud and one leaf and one bud and two leaves.

Description

technical field [0001] The invention belongs to the technical field of tea screening, and in particular relates to a method and device for directional classification of machine-picked fresh tea leaf raw materials. Background technique [0002] At present, there are still many problems in the grading technology of machine-picked fresh leaves at home and abroad. Traditional fresh tea leaf grading technologies mainly include vibrating screening machines, roller screening machines and winnowing machines. For example, in 2012, Tang Xiaolin and others invented a machine-picked fresh tea leaf classifier, which uses a vibrating structure to make the fresh tea leaves continuously vibrate, bounce and flow forward, passing through screens with different apertures in turn to achieve multi-stage sorting. Purpose, this method has less damage to tea leaves; in 2013, Ren Guangxin of Zhejiang University and others designed a throwing bulk fresh tea leaf classifier using the throwing vibrati...

AI Technical Summary

Problems solved by technology

In 2010, Chen Yiqun, Chang Chun and others from the Nanjing Agricultural Mechanization Research Institute of the Ministry of Agriculture applied artificial neural network technology to the classification of fresh tea leaves, and the accuracy rate could reach more than 90%. In 2013, they designed an image analysis method based on neural network The intelligent fresh tea grading machine can distinguish the grades of whole buds, leaf-wrapped buds, one bud with one leaf, and one bud with multiple leaves. The recognition accuracy rate is above 90%. It takes more than ten hours for fresh tea leaves to be sorted

However, the grading results of these algorithms can only be used to evaluate the quality of tea leaves, and cannot separate piles of machine-picked fresh leaves into different grades.

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