基于回转窑图像的熟料填充率测量

Measurement of filling percentage of clinker using rotary kiln image

现场采集的实际回转窑窑头图像中熟料填充率直接反映了回转窑内料层的厚薄和传输情况,测量熟料填充率的大小和变化可用于判定窑内工况如给料量大小、烧结带温度异常波动。为了快速有效分割出熟料区,采用自适应窗口叠加空间信息生成线性权重和图像,消除了原图像的噪声同时有效地保留了边缘信息,将传统的FCM算法基于像素个数的聚类转化为基于灰度级聚类,降低计算的复杂度,利用灰度连通性采用区域生长的方法恢复熟料区,并实现熟料填充率的实时测量。最后通过对工况实例的分析来证明此方法的实用性。

The filling percentage of clinker in the real image recorded from the discharge end of rotary kiln directly indicates the thickness and transportation of material in rotary kiln. The measurement result of filling percentage of clinker can be used to reflect the real-time industrial conditions such as the feeding rate of raw slurry and the mutation of sintering zone temperature. In order to fast and accurately extract the region of clinker from the image, this paper develops an innovative FCM method that applies local spatial neighborhood information with adaptive window to generate the linear-weighted sum image, in which the noise is eliminated while the edge is preserved. It is worth to note that the clustering segmentation used in this paper is based on the number of gray-level rather than the number of pixels of the image to reduce the computational complexity. The total clinker region is then recognized by region growing technology based on gray-level connectivity. Finally, real-time measurement of filling percentage of clinker is completed by calculating the rate of number of pixels between clinker region and the total discharge end of rotary kiln. Case study demonstrates the applicability of the proposed approach.