回转窑视觉检测方法与优化控制技术研究
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摘要
回转窑是对散状或浆状物料进行烧结处理的大型热工设备,被广泛应用于有色冶金、水泥生产等工业部门,在国民经济建设中发挥着重要作用。由于缺乏有效的接触式传感技术,基于窑头图像的视觉检测技术成为了辨识窑内现场工况参数的有效途径。现有的研究工作大多集中在窑头图像中火焰区的特征提取,以及如何利用火焰图像特征来进行窑温标定和工况辨识,却缺乏对窑头图像中熟料区的视觉检测技术的深入研究。本文在国家自然科学基金的资助下,以工业回转窑熟料图像为研究对象,以保证熟料的正常烧结和窑况稳定为主要目标,对回转窑熟料图像的视觉检测技术以及回转窑系统的优化控制方法进行深入研究。本文完成的主要工作如下：
(1)提出了基于纹理分析的熟料烧结状态定性分析方法。以灰度共生矩阵及其统计学参数作为描述熟料纹理的主要工具,对实际工况下的不同烧结状态的熟料纹理特征进行计算和分析。针对灰度共生矩阵位置算子和特征参数多样性特点,提出基于Fisher系数的灰度共生矩阵最佳位置算子和最有效分类特征参数集判别方法,并利用C4.5决策树对“过烧”、“欠烧”和“正烧”三种不同烧结状态下的熟料纹理进行分类,获取了具体分类规则。
(2)熟料休止角是表征熟料特性的重要参数,为实现熟料烧结度的定量分析,研究了熟料上休止角的图像识别方法。利用边缘检测和直线拟合方法完成单帧图像的熟料动态休止角的计算,结合具体工况下的回转窑窑头视频得到休止角序列变化曲线,引入序列分析思想来实现熟料运动周期中的上休止角检测。对熟料休止角序列变化曲线进行滤波、平滑处理,有效地滤除数据序列中的“野点”,弥补了窑头视野不清时导致的熟料动态休止角检测信息的异常或缺失；基于多峰高斯拟合方法完成了熟料休止角序列变化曲线的正峰值检测,从而精确地计算出熟料运动周期的上休止角。
(3)为实现窑尾来料量和窑温异常检测,研究了熟料填充率的图像测量方法。提出了一种融合空间信息的灰度级自适应FCM快速分割算法以完成熟料区的精细和快速分割,算法采用基于空间信息的线性权重和图像来更新原有灰度处理对象,基于直方图统计和权重计算实现聚类算法初始点的选择,以灰度级为聚类对象提高了FCM分割的速度,并结合形态学的区域生长方法实现了窑头熟料区的灰度区提取、填充空洞并平滑边缘,最终利用像素求和方法完成熟料填充率的计算。结合回转窑工况恒定、烧结带温度异常上升和异常降低这三种不同工况下的视频进行仿真实验,并对熟料填充率曲线变化与来料量和窑内烧结带温度异常情况进行了具体分析。
(4)针对回转窑控制系统中窑温变化和熟料烧结状态变化响应时间常数不同的问题,引入煤粉燃烧过程和熟料烧结过程串级控制思想,提出了基于熟料视觉特征的熟料烧结仿人智能控制和基于DRSPC算法的窑温优化控制方法。首先通过对熟料纹理和上休止角进行模糊融合以实现熟料烧结度的判断,并将其作为控制器的工况反馈,仿人智能控制算法根据熟料烧结度误差的大小、方向及其变化趋势对窑温设定值采用不同的控制模式。其次,提出了一种基于DRSPC算法的工业回转窑窑温优化控制方法。该法采用统计学方法消除窑温测量误差,为回转窑控制系统建立了均值(烧结带温度)和标准差(烧结带、窑头、窑尾三处温度差)两个响应面模型,在优化过程中基于标准差的响应优化结果对烧结带温度均值响应面模型进行适当地约束,保证了优化输出的鲁棒性；控制算法的目标函数以最小化喷煤管转速变化量作为主要优化对象,并兼顾了窑温的期望值和稳定性要求,通过在优化模型目标函数中设定不同目标权重系数以平衡系统的计算开销与处理效率。基于实际工业窑炉获得的现场工况数据,DRSPC优化控制算法处理动态复杂工况的有效性得以证明。
文章从图像处理的基本理论出发,研究回转窑的视觉检测相关技术,提出应用视觉检测信息的控制方法,对于提高工业回转窑的自动控制水平和扩大图像视觉的应用领域,具有重要的科学意义和广阔的应用前景。
An industrial rotary kiln is a large-scale thermal equipment for processing bulk or slurry materials. It is widely employed in many fields such as metallurgical and cements industry and plays an important role in the national economy. Due to the lack of viable online contact sensors under high combustion temperature, contactless image-based visual inspection technology has become an effective method for estimating some key quality parameters of the working condition inside the kiln. Since existing techniques mainly focus on extracting the visual features from the flame and utilizing these features for demarcating the kiln temperature and identifying the working condition, it still needs further investigation on the technology of visual inspection for clinker and the effective method to deal with the complex and dynamic calcinations process. This thesis is supported by National Natural Science Foundation of China, and the clinker image of industrial rotary kiln is choosen as study object. The main purpose of this research is to ensure the normal sinter for clinker and stable control for rotary kiln. Thus, the technology of visual inspection and the optimal control for rotary kiln are deeply studied and the major achievments of this thesis are described as follows:
Firstly, a texture analysis of the clinker image based on GLCM is proposed for predicting the sinter mode of clinker. According to the variety of displacement operator and description features of GLCM, the Fisher coefficient is used to extract the best displacement operator of the GLCM and to reduce the texture measurement sets. Then C4.5decision tree is applied to classify the sampled clinker images into three categories:over-sintering, under-sintering and normal-sintering, whose detailed classification rule was listed.
Secondly, the visual recognition of upper repose angle of clinker is developed to quantitatively analyze the sinter degree of clinker. The repose angle of single image sample is calculated by edge detection and linear least square regression. Corresponding to the real-time video captured under industrial rotary kiln, the sequence analysis is needed for the curve of repose angle in order to extract the upper repose angle of each motion period. Noises are filtered and smoothed from the original curve, and then the abnormal and missed data can be removed. Finally, all positive peaks of curve are detected by the method of Guassion-based muti-peak curve fitting. As a result, the upper repose angles are achievmented with these peaks.
Thirdly, the visual-based measurement of filling percentage of clinker is produced. The value of filling percentage of clinker can be used to detect the feeding rate of slurry and the mutation of sinter zone temperature. An innovative FCM method is developed for segmenting the clinker from the whole image accurately and quickly. This segmentation mothod applies local spatial neighborhood information with an adaptive window to generate the linear-weighted sum image, in which the noise is eliminated while the edge is preserved. It is worth noting that the clustering segmentation is based on the number of gray-level rather than pixels of the whole image to reduce the computation complexity. The total clinker region is then recognized by region growing technology based on gray-level connectivity. Consequently, the filling percentage of clinker is calculated by the rate of the pixels number between the clinker region and the total image. The relationship between the curve of filling percentage and the feeding rate of slurry and zone temperature mutation is analyzed by case study and simulation.
Fourthly, the cascade control strategy is proposed to deal with the mismatch change delay between the temperature of the rotary kiln and the sintering status of the clinker. The cascade control consists of two controllers, which are the HISC for the clinker sinter and the DRSPC for the temperature control of rotary kiln. In the automatic control of clinker sinter, the sinter degree of clinker is determined by the fuzzy fusion result of the texture feature and the upper repose angle. HISC switches to different control modes following the variation of the sinter degree error, such as the amplitude, the direction and the trend of the variation. Then, the temperature of the rotary kiln, which is the output response of the HISC, is transmitted to DRSPC as input. The adjustments of the rotation speed of coal burner pipe are used to respond to temperature changes in the kiln. The DRSPC can rapidly provide corresponding optimal and robust outputs to serve the rotation speed of coal burner pipe. In the DRSPC, the measurement errors of the kiln temperature can be statistical eliminated. Two response surface models, one for the mean value and the other for the standard deviation of the kiln temperature, can achieve optimal and robust outputs because of the appropriate constraint given by each other. The objective function of controller is designed for minimizing the variation of the rotation speed of the coal burner pipe, which also considers the requirement of accurate and stable control for the kiln temperature. The weight coefficients are used in the objective function to keep the trade-off between system cost and efficiency. Case study and experiment results validate the efficiency of the controller, which is designed for dynamic and complex induatrial work conditions of roatry kiln.
This thesis is based on the basic theory of image processing, and focuses on the key technology of visual inspection for rotary kiln, provides vision-based optimal control methods, demonstrates important scientific significance and broad application prospect of improving automatic control technology of rotary kiln and expanding the vision application area.
(1)提出了基于纹理分析的熟料烧结状态定性分析方法。以灰度共生矩阵及其统计学参数作为描述熟料纹理的主要工具,对实际工况下的不同烧结状态的熟料纹理特征进行计算和分析。针对灰度共生矩阵位置算子和特征参数多样性特点,提出基于Fisher系数的灰度共生矩阵最佳位置算子和最有效分类特征参数集判别方法,并利用C4.5决策树对“过烧”、“欠烧”和“正烧”三种不同烧结状态下的熟料纹理进行分类,获取了具体分类规则。
(2)熟料休止角是表征熟料特性的重要参数,为实现熟料烧结度的定量分析,研究了熟料上休止角的图像识别方法。利用边缘检测和直线拟合方法完成单帧图像的熟料动态休止角的计算,结合具体工况下的回转窑窑头视频得到休止角序列变化曲线,引入序列分析思想来实现熟料运动周期中的上休止角检测。对熟料休止角序列变化曲线进行滤波、平滑处理,有效地滤除数据序列中的“野点”,弥补了窑头视野不清时导致的熟料动态休止角检测信息的异常或缺失；基于多峰高斯拟合方法完成了熟料休止角序列变化曲线的正峰值检测,从而精确地计算出熟料运动周期的上休止角。
(3)为实现窑尾来料量和窑温异常检测,研究了熟料填充率的图像测量方法。提出了一种融合空间信息的灰度级自适应FCM快速分割算法以完成熟料区的精细和快速分割,算法采用基于空间信息的线性权重和图像来更新原有灰度处理对象,基于直方图统计和权重计算实现聚类算法初始点的选择,以灰度级为聚类对象提高了FCM分割的速度,并结合形态学的区域生长方法实现了窑头熟料区的灰度区提取、填充空洞并平滑边缘,最终利用像素求和方法完成熟料填充率的计算。结合回转窑工况恒定、烧结带温度异常上升和异常降低这三种不同工况下的视频进行仿真实验,并对熟料填充率曲线变化与来料量和窑内烧结带温度异常情况进行了具体分析。
(4)针对回转窑控制系统中窑温变化和熟料烧结状态变化响应时间常数不同的问题,引入煤粉燃烧过程和熟料烧结过程串级控制思想,提出了基于熟料视觉特征的熟料烧结仿人智能控制和基于DRSPC算法的窑温优化控制方法。首先通过对熟料纹理和上休止角进行模糊融合以实现熟料烧结度的判断,并将其作为控制器的工况反馈,仿人智能控制算法根据熟料烧结度误差的大小、方向及其变化趋势对窑温设定值采用不同的控制模式。其次,提出了一种基于DRSPC算法的工业回转窑窑温优化控制方法。该法采用统计学方法消除窑温测量误差,为回转窑控制系统建立了均值(烧结带温度)和标准差(烧结带、窑头、窑尾三处温度差)两个响应面模型,在优化过程中基于标准差的响应优化结果对烧结带温度均值响应面模型进行适当地约束,保证了优化输出的鲁棒性；控制算法的目标函数以最小化喷煤管转速变化量作为主要优化对象,并兼顾了窑温的期望值和稳定性要求,通过在优化模型目标函数中设定不同目标权重系数以平衡系统的计算开销与处理效率。基于实际工业窑炉获得的现场工况数据,DRSPC优化控制算法处理动态复杂工况的有效性得以证明。
文章从图像处理的基本理论出发,研究回转窑的视觉检测相关技术,提出应用视觉检测信息的控制方法,对于提高工业回转窑的自动控制水平和扩大图像视觉的应用领域,具有重要的科学意义和广阔的应用前景。
An industrial rotary kiln is a large-scale thermal equipment for processing bulk or slurry materials. It is widely employed in many fields such as metallurgical and cements industry and plays an important role in the national economy. Due to the lack of viable online contact sensors under high combustion temperature, contactless image-based visual inspection technology has become an effective method for estimating some key quality parameters of the working condition inside the kiln. Since existing techniques mainly focus on extracting the visual features from the flame and utilizing these features for demarcating the kiln temperature and identifying the working condition, it still needs further investigation on the technology of visual inspection for clinker and the effective method to deal with the complex and dynamic calcinations process. This thesis is supported by National Natural Science Foundation of China, and the clinker image of industrial rotary kiln is choosen as study object. The main purpose of this research is to ensure the normal sinter for clinker and stable control for rotary kiln. Thus, the technology of visual inspection and the optimal control for rotary kiln are deeply studied and the major achievments of this thesis are described as follows:
Firstly, a texture analysis of the clinker image based on GLCM is proposed for predicting the sinter mode of clinker. According to the variety of displacement operator and description features of GLCM, the Fisher coefficient is used to extract the best displacement operator of the GLCM and to reduce the texture measurement sets. Then C4.5decision tree is applied to classify the sampled clinker images into three categories:over-sintering, under-sintering and normal-sintering, whose detailed classification rule was listed.
Secondly, the visual recognition of upper repose angle of clinker is developed to quantitatively analyze the sinter degree of clinker. The repose angle of single image sample is calculated by edge detection and linear least square regression. Corresponding to the real-time video captured under industrial rotary kiln, the sequence analysis is needed for the curve of repose angle in order to extract the upper repose angle of each motion period. Noises are filtered and smoothed from the original curve, and then the abnormal and missed data can be removed. Finally, all positive peaks of curve are detected by the method of Guassion-based muti-peak curve fitting. As a result, the upper repose angles are achievmented with these peaks.
Thirdly, the visual-based measurement of filling percentage of clinker is produced. The value of filling percentage of clinker can be used to detect the feeding rate of slurry and the mutation of sinter zone temperature. An innovative FCM method is developed for segmenting the clinker from the whole image accurately and quickly. This segmentation mothod applies local spatial neighborhood information with an adaptive window to generate the linear-weighted sum image, in which the noise is eliminated while the edge is preserved. It is worth noting that the clustering segmentation is based on the number of gray-level rather than pixels of the whole image to reduce the computation complexity. The total clinker region is then recognized by region growing technology based on gray-level connectivity. Consequently, the filling percentage of clinker is calculated by the rate of the pixels number between the clinker region and the total image. The relationship between the curve of filling percentage and the feeding rate of slurry and zone temperature mutation is analyzed by case study and simulation.
Fourthly, the cascade control strategy is proposed to deal with the mismatch change delay between the temperature of the rotary kiln and the sintering status of the clinker. The cascade control consists of two controllers, which are the HISC for the clinker sinter and the DRSPC for the temperature control of rotary kiln. In the automatic control of clinker sinter, the sinter degree of clinker is determined by the fuzzy fusion result of the texture feature and the upper repose angle. HISC switches to different control modes following the variation of the sinter degree error, such as the amplitude, the direction and the trend of the variation. Then, the temperature of the rotary kiln, which is the output response of the HISC, is transmitted to DRSPC as input. The adjustments of the rotation speed of coal burner pipe are used to respond to temperature changes in the kiln. The DRSPC can rapidly provide corresponding optimal and robust outputs to serve the rotation speed of coal burner pipe. In the DRSPC, the measurement errors of the kiln temperature can be statistical eliminated. Two response surface models, one for the mean value and the other for the standard deviation of the kiln temperature, can achieve optimal and robust outputs because of the appropriate constraint given by each other. The objective function of controller is designed for minimizing the variation of the rotation speed of the coal burner pipe, which also considers the requirement of accurate and stable control for the kiln temperature. The weight coefficients are used in the objective function to keep the trade-off between system cost and efficiency. Case study and experiment results validate the efficiency of the controller, which is designed for dynamic and complex induatrial work conditions of roatry kiln.
This thesis is based on the basic theory of image processing, and focuses on the key technology of visual inspection for rotary kiln, provides vision-based optimal control methods, demonstrates important scientific significance and broad application prospect of improving automatic control technology of rotary kiln and expanding the vision application area.
引文
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