Pingdingshan Zhongxuan Automation Co., Ltd.
School of ChemicalEngineering and Technology, China University of Mining and Technology

目前矿物组成等影响煤泥水絮凝沉降效果的重要参数缺乏有效的在线检测手段,而浓缩池溢流浊度和界面又存在滞后性问题,限制了选煤厂煤泥水智能加药的发展。针对该问题,提出了基于图像灰度识别的煤泥水絮凝沉降速率快速检测方法。利用CCD相机在线采集煤泥水沉降过程图像,并通过均值滤波法进行降噪,计算图像的平均灰度和平均灰度变化率,利用沉降速率与平均灰度变化率的关系得到沉降速率。通过絮凝沉降实验提取图像的灰度、能量、对比度、方差和相关度等特征值,进行分析验证。分析结果表明:①5种图像特征中,平均灰度的变化符合煤泥水批次沉降过程中沉降速率的变化规律,即存在缓冲区、线性区和稳定区,且变化特征可以在30s内获得。②平均灰度变化率与沉降速率存在较好的线性相关性,煤泥水质量浓度为20g/L时,不同絮凝剂添加量下图像平均灰度变化率与沉降速率的线性相关系数达0.9772;煤泥水质量浓度5~25g/L、絮凝剂添加量为0.1~0.2kg/t条件下,图像平均灰度变化率与沉降速率的线性相关系数为0.9441。③平均灰度变化率可以在较大范围内适应煤泥水絮凝沉降状态的变化,可用于快速检测煤泥水絮凝沉降速率并作为煤泥水加药智能调节的依据。

At present, there is a lack of effective online detection methods for important parameters such asmineral composition that affect the flocculation and sedimentation effect of slime water. There are also laggingissues in the turbidity and interface of the overflow of the concentration tank, which limits the development ofintelligent dosing for slime water in coal preparation plants. In order to solve the above problems, a fast detectionmethod for slime water flocculation and sedimentation rate based on image grayscale recognition is proposed.Using a CCD camera to collect images of the sedimentation process of slime water online, and using the meanfiltering method for noise reduction, the average grayscale and average grayscale change rate of the image are calculated. The sedimentation rate is obtained by using the relationship between the sedimentation rate and theaverage grayscale change rate. The method extracts feature values such as grayscale, energy, contrast, variance,and cross-correlation from images through flocculation sedimentation experiments for analysis and verification.The analysis results show the following points. ① Among the five image features, the change in grayscale meanconforms to the variation law of sedimentation rate during the sedimentation process of slime water batches. Thereare buffer zones, linear zones, and stable zones, and the variation features can be obtained within 30 seconds.② There is a good linear correlation between the average grayscale change rate and sedimentation rate. When theconcentration of slime water is 20 g/L, the linear correlation coefficient between the average grayscale change rateof the image and sedimentation rate under different flocculant addition amounts is 0.977 2. Under the conditionsof slime water concentration of 5-25 g/L and flocculant addition amounts of 0.1-0.2 kg/t, the linear correlationcoefficient between the two is 0.944 1. ③ The average grayscale change rate can adapt to the changes in theflocculation and sedimentation state of slime water within a large range. The average grayscale change rate can beused to quickly detect the flocculation and sedimentation rate of slime water and serve as the basis for intelligentadjustment of slime water dosing.

国家自然科学基金项目(51604273)

耿延兵,王章国. 基于图像灰度识别的煤泥水絮凝沉降速率快速检测方法[J]. 工矿自动化,2023,49(12):87-93.

GENG Yanbing, WANG Zhangguo. A fast detection method for slime water flocculation and sedimentation rate based on imagegrayscale recognition[J]. Journal of Mine Automation,2023,49(12):87-93.