Machine vision-based discharged ballast monitoring method for heading machine

Abstract

The invention discloses a machine vision-based discharged ballast monitoring method for a heading machine. The method comprises a surrounding rock discharged ballast crushing degree monitoring step, a conveying belt load monitoring step and a surrounding rock classification monitoring step. In the discharged ballast crushing degree monitoring step, a maximum size, a minimum size and an average size of rock ballast are subjected to statistics, and a surrounding rock crushing capability in a current heading condition is provided; in the conveying belt load monitoring step, a load condition of a current belt machine is assessed by detecting a depth of the discharged ballast in the whole belt machine; and in the surrounding rock classification monitoring step, a current surrounding rock heading condition is judged through surface features of the discharged ballast. By use of a machine vision method, the discharged ballast monitoring efficiency and accuracy are improved; the problems of inaccurate monitoring and the like caused by a severe environment are avoided; and the labor cost also can be reduced.

Description

technical field [0001] The invention relates to the technical field of machine vision applications, in particular to a machine vision-based slag discharge monitoring method for roadheaders. Background technique [0002] The 21st century is an era of informatization, and the realization of modern production and informatization management requires continuous innovation in production methods. The application technology of roadheaders should keep pace with the times and strengthen automation management to meet the requirements of informatization construction. However, the current roadheader detection system is based on various sensors, which realize data reception and analysis through wireless devices or a roadheader status monitoring system based on virtual instruments; in harsh environments, sensors will be affected by environmental factors, resulting in acquisition Problems such as inaccurate data or equipment damage are not conducive to real-time, accurate and stable monito...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to overcome the shortcomings and deficiencies of the prior art, to provide a machine vision-based monitoring method for slag discharge, to improve the efficiency and accuracy of slag discharge monitoring by using machine vision, and to avoid monitoring caused by harsh changing environments Inaccurate and other issues, but also can reduce labor costs

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