摘要
多波束测深系统是海上风电桩基地形冲刷测量的重要手段,但其测量精度容易受到安装偏差的影响。艏摇偏差作为安装偏差的一种,在实际测量过程中严重影响结果的准确性。为解决这一问题,提出一种顾及海上风电桩特征的艏摇偏差探测及修正方法,以提高测量精度,保障风电桩施工质量和长期运行稳定性。具体方法如下:首先利用区域生长算法进行点云分割,然后基于最小二乘圆柱拟合提取风电桩目标点云,最后通过粗探测和精探测步骤实现艏摇偏差自动探测,结合仿真数据和实测数据实验,验证了方法的有效性。实验结果表明,该方法能够准确探测并修正艏摇偏差,提高了海洋测绘数据的准确性和可靠性,为海上风电桩的准确安装提供了科学依据,也拓展了多波束测深技术在复杂海洋工程中的应用潜力。
A comprehensive review of the literature on bottom acoustic classification using multibeam echosounder methods at home and abroad revealed that these methods can be grouped into three main categories:seabed classification based on acoustic signal features,seabed classification based on undersea sonar image features,and combinatorial methods using multi-source information.Furthermore,the classification methods and their characteristics are presented in detail.The objective of this paper is to gain a comprehensive understanding of the current research priorities in multibeam bottom acoustic classification methods and to identify the limitations of existing classification approaches.In light of the shortcomings of the existing methods,a future development trend for bottom acoustic classification methods is proposed.It is recommended that further research on multibeam bottom acoustic classification methods should prioritize the integration of multi-source information,the enhancement of intelligence and real-time processing capabilities,and so on.
作者
龚权华
朱文博
夏显文
盖圣璐
GONG Quanhua;ZHU Wenbo;XIA Xianwen;GAI Shenglu(New Energy Engineering Co.Ltd,Third Navigation Engineering Bureau of China Communications Construction Group,Shanghai 200137,China;Institute of Marine Science and Technology,Wuhan University,Wuhan 430070,China;New Energy Engineering Co.Ltd,Third Navigation Engineering Bureau of China Communications Construction Group,Shanghai 200032,China;The First Institute of Geographic Information Mapping of the Ministry of Natural Resourse,Xian 710054,China)
出处
《海洋测绘》
北大核心
2025年第3期21-25,共5页
Hydrographic Surveying and Charting
基金
国家重点研发专项(2022YFC2808303)。
关键词
多波束测深
艏摇偏差
偏差探测
偏差修正
自动探测
multibeam measurement
acoustic seabed classification
backscatter intensity
angular response curve
supervised learning
unsupervised learning
