Coal-rock interface identifying method and system based on image

Abstract

The invention discloses a coal-rock interface identifying method and system based on an image. The method comprises the following steps of: acquiring multiple color images of coal and rock on a coal mining working face; extracting a vector based on an image characteristic serving as a sample characteristic vector specific to each color image to obtain a known sample set of coal and rock; and establishing a coal-rock classifier model by adopting a Fisher linear judging method and taking the known sample set of the coal and rock as a training sample set. In the working process of a coal mining machine, a color image of the coal and rock which is cut by using a drum is acquired in real time, and the extracted characteristic vector is input into the coal-rock classifier model to identify a coal-rock type. The system consists of a light source module, an imaging module, a processing module and an anti-explosion shell. The coal-rock interface identifying method and the system provided by the invention have the characteristics of simple structure, easiness for distributing, high suitability and the like, the coal-rock type cut by using the drum can be automatically identified in real time, and reliable coal-rock interface information is provided for automatic heightening of the drum of the coal mining machine.

Description

Technical field [0001] The invention relates to an image-based coal-rock interface recognition method and system, which are used to identify the interface between coal seams and roof and floor rock layers of coal mining faces in underground coal mines, and belong to the technical field of image recognition. Background technique [0002] The height adjustment of the shearer drum mainly relies on manual operation, that is, the shearer driver judges whether the shearer drum is cutting coal or rock by visual and hearing noise, and then adjusts the vertical position of the drum. However, the coal mining face has low visibility and high noise, and it is difficult for the shearer driver to accurately judge the cutting status of the shearer. The shearer drum will inevitably cut the roof and floor rocks, which causes a series of problems: ①A large number of cavings The mixed rock mixed with the raw coal causes the decrease of coal quality and the increase of the transportation volume; ②In...

AI Technical Summary

Problems solved by technology

However, the coal mining face has low visibility and high noise, and it is difficult for the driver of the shearer to accurately judge the cutting state of the shearer. The shearer drum will inevitably cut the rocks on the top and floor, which will cause a series of problems: ① A large number of caving The rock is mixed into the raw coal, resulting in a decline in coal quality and an increase in transportation volume; ②Increase the labor intensity and danger of the driver of the shearer; ③Aggravate the wear of the pick and shorten the life of the pick; Sparks are generated, which can easily cause gas explosions in high-gas mines and cause serious accidents; ⑤ Improper adjustment of the drum position may also cause uneven coal remaining on the roof and floor, reducing the recovery rate. It is difficult for the transport plane to move, reducing production efficiency

[0007] The current coal-rock interface identification method has the following problems: ①The structure of the signal acquisition device is complex and the cost is high

In the stress pick method, it is necessary to carry out mechanical transformation on the shearer drum, and install force-measuring picks and force sensors. In the vibration test method, sensors such as acceleration, torsional vibration and torque need to be installed on the shearer. The structure of the device is complex and the cost of modification is high

② Difficult to deploy and poor reliability

During the cutting process, the shearer drum is subjected to complex forces, severe drum vibration, severe wear, and large dust. It is difficult to deploy sensors, which easily leads to damage to mechanical components, sensors and electrical circuits, and poor device reliability.

③ Poor adaptability

For different types of rollers and picks, there is a big difference in the optimal type of sensor and the selection of signal pickup points, which requires personalized customization and poor adaptability of the system

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