基于机器视觉的天轮偏摆检测技术

Head Sheave Deflection Detection Technology Based on Machine Vision

设计了一种基于机器视觉的天轮偏摆检测系统。利用机器视觉系统的CCD摄像机实时采集天轮偏摆运行状态视频;对每一帧图像进行图像滤波和图像增强,采用Mean Shift算法实现天轮偏摆的跟踪;经坐标变换将跟踪目标的像素偏移换算为实际物理尺寸,从而计算出天轮偏摆。试验结果表明,设计的天轮偏摆检测系统现场安装检测方便且能满足精度要求。

A head sheave deflection detection system based on machine vision was designed. First, CCD camera of the machine vision system is used to have the real - time acquisition of the running state video of the head sheave deflection ; then, each frame of image is carried on the filtering and enhancement of the image, and Mean Shift algorithm is used to realize the tracking of the head sheave de- flection; finally, the pixel offset of the track target is converted for the actual physical dimensions to calculate the head sheave deflec- tion through the coordinate transformation. The experimental results show that the field detection and installation of the designed deflec- tion sheave detection system is convenient and can meet the requirements of precision with good practical value. It solves the problem that most mine friction head sheave deflection has difficult detection and high cost.