Research on Halcon-based Image Positioning Technology of Reactor Core Detector Assemblies
-
摘要: 华龙一号（HPR1000）反应堆堆芯探测器组件在使用寿命到期后需要全部拆除更换。由于探测器组件自身偏差较大等因素，不能直接使用安装时的理论坐标作为探测器组件拆除时的定位坐标。本文基于机器视觉软件Halcon开发了一种用于堆芯探测器组件图像定位的算法，该算法使用模板匹配的原理在摄像机捕获的探测器组件图像中进行查找，获取探测器组件的精确坐标。实验证明，该算法具有较高的定位精度，能够满足探测器组件拆除工作对图像定位算法的使用要求。Abstract: The reactor core detector assemblies of HPR1000 reactor need to be removed and replaced after their life cycle expires. Due to the large deviation of the detector assemblies themselves and other factors, the theoretical coordinates during installation cannot be directly used as the positioning coordinates during the removal of the detector assemblies. In this paper, an algorithm for image positioning of core detector assembly is developed based on machine vision software Halcon. The algorithm uses the principle of template matching to search in the images of the detector assemblies captured by the camera to obtain the exact coordinates of the detector assemblies. Experiments show that the algorithm has high positioning accuracy and can meet the requirements of the image positioning algorithm for the removal of the detector assemblies.
-
Key words:
- Detector assembly removal /
- Image positioning /
- Template matching /
- Halcon
-
[1] 安彦波,余志伟,李娜,等. 华龙一号反应堆探测器组件拆除系统定位技术研究[J]. 核动力工程,2021, 42(1): 161-166. [2] MVTec Software GmbH. Halcon-the power of machine vision[EB/OL]. (2021-03-14)[2021-03-25]. https://www.mvtec.com/products/halcon. [3] VIOLA P, JONES M J. Robust real-time face detection[J]. International Journal of Computer Vision, 2004, 57(2): 137-154. doi: 10.1023/B:VISI.0000013087.49260.fb [4] DALAL N, TRIGGS B. Histograms of oriented gradients for human detection[C]//Proceedings of 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. San Diego: IEEE, 2005: 886-893. [5] FELZENSZWALB P, MCALLESTER D, RAMANAN D. A discriminatively trained, multiscale, deformable part model[C]//Proceedings of 2008 IEEE Conference on Computer Vision and Pattern Recognition. Anchorage: IEEE, 2008: 1-8. [6] GIRSHICK R, DONAHUE J, DARRELL T, et al. Rich feature hierarchies for accurate object detection and semantic segmentation[C]//Proceedings of 2014 IEEE Conference on Computer Vision and Pattern Recognition. Columbus: IEEE, 2014: 580-587. [7] HE K M, ZHANG X Y, REN S Q, et al. Spatial pyramid pooling in deep convolutional networks for visual recognition[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015, 37(9): 1904-1916. doi: 10.1109/TPAMI.2015.2389824 -
下载:
图(11)
计量
- 文章访问数: 346
- HTML全文浏览量: 120
- PDF下载量: 27
- 被引次数: 0
