Coal and rock identification method based on image discrete multi-wavelet transform

Abstract

The invention discloses a coal and rock identification method based on image discrete multi-wavelet transform. The method includes obtaining a group of coal sample images and rock sample images under the same image-forming conditions according to kinds of coal and rocks in a coal mine to be identified; extracting m samples from the images respectively and capturing sub-images f1, f2,..., fm and g1, g2,..., gm which have the same size and contain no backgrounds; performing a first-level Geronimo Hardin Massopust (GHM) multi-wavelet transform respectively on f1, f2,..., fm and g1, g2,..., gm and calculating multi-scale texture energy distribution vectors based on transform domain data for all the sub-images to obtain average multi-scale texture energy distribution vectors Vcoal and Vrock of the coal samples and the rock samples; during a coal and rock classification and identification stage, collecting to-be-identified coal and rock images under the same image-forming conditions, capturing a sub-image fx with the same size with the samples, performing the first-level GHM multi-wavelet transform on fx, and calculating the multi-scale texture energy distribution vector Vx; and determining coal and rock object types according to relations among the Vx, Vcoal and Vrock. According to the method, the coal and rock object types are identified through images, devices for collecting and processing images are convenient to arrange, the reliability and the identification rate are high, and upgrade maintenance of software and hardware is convenient.

Description

technical field [0001] The invention relates to a coal and rock recognition method based on image discrete multi-wavelet transform, belonging to the technical field of image pattern recognition. Background technique [0002] In the underground production process of coal mines, many production links need to distinguish the interface between the coal seam and the rock formation, such as drum coal mining, roadheader mining, top coal caving mining, raw coal gangue, etc. The recognition results of the coal-rock interface can be used as a basis to adjust the height of the rocker arm of the shearer drum or to control the cutting trajectory of the cutting head of the roadheader. Misjudgment of the coal-rock interface will lead to A series of problems are caused: for example, a large number of rock fragments are mixed into the raw coal, resulting in a decline in coal quality; the wear of the shearer drum picks is aggravated, shortening the service life; cutting the roof or floor rock...

AI Technical Summary

Problems solved by technology

The recognition results of the coal-rock interface can be used as a basis to adjust the height of the rocker arm of the shearer drum or to control the cutting trajectory of the cutting head of the roadheader. Misjudgment of the coal-rock interface will lead to A series of problems are caused: for example, a large number of rock fragments are mixed into the raw coal, resulting in a decline in coal quality; the wear of the shearer drum picks is aggravated, shortening the service life; cutting the roof or floor rock formations may produce friction sparks, which can easily cause gas in a high-gas environment Explosion, etc.

These methods need to add various sensors to the existing equipment, resulting in high construction costs of the actual system; in order to collect the vibration information of the shearer, roadheader, etc., it is necessary to install corresponding sensors on the rocker arm of the shearer. The sensor circuit is easily damaged, resulting in poor system reliability; the raw data required by various coal rock identification methods are different, resulting in poor system flexibility

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