机械科学与技术2025，Vol.44Issue(5)：840-846,7.DOI:10.13433/j.cnki.1003-8728.20230220
烧结机篦条故障在线监测的图像识别方法
Study on Image Recognition Method for On-line Monitoring of Grate Faults in Sintering Machine
罗柏文 1史天宠 1李宗平 2廖婷婷2
作者信息
- 1. 湖南科技大学海洋矿产资源探采装备与安全技术国家地方联合工程实验室,湖南湘潭 411201
- 2. 中冶长天国际工程有限责任公司,长沙 410006
- 折叠
摘要
Abstract
In order to realize the intelligent online monitoring of grate faults in the sintering machine of steel plant,a grate fault image recognition method based on OpenCV image processing technology is proposed,that is,the number of grate bars,gap width,slope and the proportion of gap sticking are detected by adopting the grate structural feature recognition algorithm to characterize the fault types such as the inclination,fracture and gap sticking of grate bars.In this paper,the grate fault of No.1 sintering plant of Xiangtan Iron and Steel Co.,Ltd.is taken as the online monitoring object.Firstly,the grate images are spliced and binarized adaptively.Then,the grate contour is extracted in the region of interest(ROI)area of the grate image and the number and gap width are counted;Then Hough transform method is used to fit the line of the image,and the line segment where the grate is located is selected.The slope of the grate is calculated by using the two endpoints to obtain the gradient of the grate.Then,the original binary image and the image processed by using the open operation are bitwise and calculated to get the location of the stuck object and its proportion.Finally,to use the multiple opening operations extract the broken position of the grate bar.The experimental results show that the error of the grate gap width detected by using the algorithm is within 4 mm and the error of the inclination rate is within±1 °,and the grate fault can be detected quickly and effectively.关键词
篦条/故障/监测/OpenCV/图像识别Key words
grate bar/fault/monitoring/OpenCV/image recognition分类
信息技术与安全科学引用本文复制引用
罗柏文,史天宠,李宗平,廖婷婷..烧结机篦条故障在线监测的图像识别方法[J].机械科学与技术,2025,44(5):840-846,7.
