基于机器视觉的二次设备运行状态巡检方法研究

Research on the method of inspecting the running status of secondary equipment based on machine vision

为了提高二次设备运行状态的自动检测能力,提出一种基于机器视觉的二次设备运行状态巡检方法,采用机器视觉方法构建二次设备运行状态的成像模型,提取二次设备运行状态的视觉成像特征量,采用边缘轮廓检测方法进行二次设备运行状态机器视觉的边界特征分析,在机器视觉的梯度下降流中构建二次设备运行状态巡检的变结构分布模型,以灰度值较高区域边界像素点为中心,进行二次设备运行状态巡检的视觉重构识别,实现二次设备运行状态自动巡检。仿真结果表明,采用该方法进行二次设备运行状态巡检的智能性较高,特征分辨能力较好,提高了二次设备的巡检能力。

In order to improve the ability of automatic detection of the running state of the secondary equipment,a method of inspecting the running state of the secondary equipment based on machine vision is proposed.The imaging model of the running state of the secondary equipment is constructed by using the method of machine vision.The edge contour detection method is used to analyze the boundary features of the secondary equipment running state machine vision by extracting the visual imaging feature quantity of the secondary equipment running state,and using the edge contour detection method to analyze the boundary feature of the secondary equipment running state machine vision.In the gradient descending flow of machine vision,the variable structure distribution model of the secondary equipment running state inspection is constructed,and the visual reconstruction recognition of the secondary equipment running state inspection is carried out.Taking the pixel point of the region with higher gray value as the center,the automatic inspection of the running state of the secondary equipment is realized.The simulation results show that the method has higher intelligence and better feature resolution,and improves the patrol ability of secondary equipment.