Condition recognition method of rotary kiln based on 2D-OTSU image edge detection

The rotary kiln is the core thermal reaction equipment of cement calcination process, whose operation state is closely related to the yield, the quality the energy consumption and of products. Contact temperature measurement can not be installed in the core area inside the kiln due to high temperature and continuous rotation. The rotary kiln shell scanning system, (RKSSS) is available to monitor the temperature of kiln shell and reflect the thermal condition inside the kiln indirectly in real time. Therefore, a new method of abnormal conditions identification based on 2D-OTSU edge-detection is proposed. The fusion model based on gray gradient and local gray standard deviation information is firstly constructed, and the weight coefficient of the model is calculated using the concept of relative entropy. The 1D-OTSU pre-searching strategy is then adopted to improve the efficiency of the algorithm. In addition, a 2D threshold segmentation strategy is proposed to ensure the continuity of the edge. By applying images from the RKSSS, the proposed method is tested and compared with other typical methods. The results demonstrate that the proposed method can make a promotion in detection rate and false alarm probability with robustness, and is available to detect the abnormal condition and to extend operation cycle of the rotary kiln. © 2021, Editorial Office of Control and Decision. All right reserved.