Heading machine pose detection system and method based on V-shaped laser target image recognition

Abstract

The invention discloses a heading machine pose detection system and method based on V-shaped laser target image recognition. The system comprises a cross-shaped laser orientation instrument, a semi-transparent V-shaped laser target, a digital camera, an image processing computer and a dust cover. The semi-transparent V-shaped laser target is mounted on a heading machine; a cross-shaped laser imageis formed on the target by utilizing laser emitted by the cross-shaped laser orientation instrument fixedly mounted in a roadway; the digital camera behind the target collects the laser image on thetarget; the image processing computer is used for completing image recognition and processing; by using an established heading machine resolving pose model and adopting a space coordinate resolving method, the roll angle, the pitch angle, the deviation angle and the gravity center deviation parameter of the heading machine are obtained. The system and the method can be used for position deviationrectification in the heading process of the heading machine. The method is easy and convenient to install and debug, high in anti-interference capacity and capable of meeting the requirement for monitoring the pose of the tunneling machine under long-distance roadway tunneling.

Description

technical field [0001] The invention relates to a space position and posture detection system and method of a mine-used cantilever type roadheader, belonging to the field of mining equipment application and machine vision application. Background technique [0002] The cantilever roadheader is a commonly used machine for section cutting and tunneling in coal mines. [0003] At present, the excavation work of the roadheader mainly relies on laser target guidance, manual visual inspection and construction experience. However, a large amount of coal dust and poor lighting environment during the mechanized excavation work can easily affect the workers' vision and decision-making, and eventually lead to roadway failure. Over-excavation or under-excavation may even cause accidents and cause safety problems. Therefore, it is particularly important to realize the intelligent and automatic excavation work of the roadheader, and to realize the automatic excavation work of the roadhead...

AI Technical Summary

Problems solved by technology

[0003]Currently, the tunneling work of the roadheader mainly relies on laser target guidance, manual visual inspection and construction experience, and a large amount of coal dust and poor lighting The environment can easily affect the sightlines and decision-making of workers, and eventually lead to over-excavation or under-excavation of the roadway, and even cause accidents and safety problems

Images