氧化铝回转窑火焰图像分割和特征提取技术

Flame Image Segmentation and Feature Extraction in Alumina Rotary Kiln

窑内参数难以准确在线检测是氧化铝回转窑自动控制的瓶颈之一；通过CCD工业摄像头采集窑内火焰图像,采用增强FCM算法对图像进行分割,针对不同情况采用有效的滤波方式,并实时准确提取了火焰温度、熟料温度、料高和黑靶子面积等多个参数,为回转窑自动控制奠定了基础。

Parameter detection was a choke point in the automatic control of rotary kiln. The flame image in rotary kiln was gotten from CCD industrial camera and segmented by AFCM clustering algorithm. During this process, several digital filtering methods were used in response to different conditions. Several parameters were gotten, such as stuff height, flame temperature, stuff temperature and the area of black target and so on, which provided reliable data for the automatic control of rotary kiln.