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J. Hefei Univ. Tech. (Nat. Sci.)

合肥工业大学学报(自然科学版)

JOURNAL OF HEFEI UNIVERSITY OF TECHNOLOGY (NATURAL SCIENCE)

Competent Authorities: Ministry of Education of the People's Republic of China

Sponsor by: Hefei University of Technology

ISSN 1000-1646, CN 34-1001/N

Study of calibration method for binocular photogrammetry of main girder deflection of portal crane

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门式起重机主梁挠度双目摄影测量的标定方法研究

Journal Information

J. Hefei Univ. Tech. (Nat. Sci.), Aug.2024, Vol.47 No.8: 1042-1048

DOI: 10.3969/j.issn.1003-5060.2024.08.006

Authors

KUANG Xiangning, QIU Faju, XU Shengyong, QIU Jiajie, DING Gaoyao

(Ningbo Special Equipment Inspection and Research Institute, Ningbo 315048, China)

Abstract and Keywords

Abstract: The existing portal crane main girder deflection measurement method has many problems such as complicated operation, insufficient safety, long downtime and unstable accuracy. This paper proposes a fast, safe and accurate method for measuring the deflection of main girders based on binocular photogrammetry. Camera calibration is one of the most important influences on the accuracy of binocular photogrammetry. A cosine function convergence factor is introduced into the traditional grey wolf optimizer (GWO) to improve the global and local search capabilities of the algorithm, and a proportional weighting strategy based on Euclidean distance is used to speed up the convergence of the algorithm to obtain improved grey wolf optimizer (IGWO). The improved algorithm is applied to the calibration parameter search of the binocular camera to obtain the optimal calibration value. The simulation and field experiment results show that the proposed method is accurate and fast, and the deflection detection error is within 1%, which fully meets the engineering measurement requirements of portal crane deflection.

Keywords: portal crane; main girder deflection measurement; binocular photogrammetry; grey wolf optimizer (GWO)

作者信息

邝湘宁，邱法聚，徐圣永，仇佳捷，丁高耀

（宁波市特种设备检验研究院，浙江宁波315048）

摘要和关键词

摘要: 针对现有门式起重机主梁挠度测量方法存在操作复杂、不够安全、停机检测时间长和精度不稳定等问题，文章提出一种基于双目摄影测量的主梁挠度快速、安全与精准测量方法。相机标定是双目摄影测量精度的最重要影响之一，在传统灰狼算法(grey wolf optimizer, GWO)中引入余弦函数收敛因子以提升算法的全局和局部搜索能力，并使用基于欧式距离的比例权重策略加快算法收敛速度，获得改进灰狼算法(improved grey wolf optimizer, IGWO)。将改进算法应用于双目相机的标定参数寻优中，获得最优标定值。通过仿真与现场试验进行验证，结果表明：该方法标定精确且快速，挠度检测误差在1%以内，满足门式起重机挠度的工程测量要求。

关键词: 门式起重机；主梁挠度测量；双目摄影测量；灰狼算法（GWO）

Funding

国家市场监督管理总局科技计划资助项目（2020MK116）

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