Karst landforms are widely distributed in China,and are most common in Yunnan,Guizhou and Guangxi.If the development of karst caves at the bottom of the piles cannot be accurately ascertained before the construction o...Karst landforms are widely distributed in China,and are most common in Yunnan,Guizhou and Guangxi.If the development of karst caves at the bottom of the piles cannot be accurately ascertained before the construction of bridge pile foundations,accidents such as hole collapse,slurry leakage,and drill sticking will easily occur.In this paper,the principle and method of sonar detection for detecting karst caves at the bottom of bridge piles was introduced,and the sonar detection data and the cave situation at the bottom of the pile during the construction process in combination with the case of Yunnan Zhenguo Highway Project was analyzed,which verifies the practicability and reliability of sonar detection method reliability.展开更多
The morphological characteristics of small-scale bedforms were measured by means of an acoustic profiling sonar on the Dafeng tidal flat, Jiangsu, in 2009, and in the Jiulong Estuary, Xiamen, in 2010, respectively. T...The morphological characteristics of small-scale bedforms were measured by means of an acoustic profiling sonar on the Dafeng tidal flat, Jiangsu, in 2009, and in the Jiulong Estuary, Xiamen, in 2010, respectively. The ＂multi-threshold value＂ method was utilized to reveal the morphological undulations along which bedforms were present. Analyses of the datasets obtained show that： （1） sand ripples can have irregular shapes, and （2） changes in bedform morphology are small within a single tidal cycle but may be significant over several tidal cycles. Fractal and variogram analyses of the seabed roughness revealed the existence of a significant relationship between current speed and the fractal dimension of the seabed roughness. As current speed increases, seabed roughness increases with a trend of smaller-scale bottom structures being replaced by larger-scale structures. Furthermore, the surface of the larger-scale bottom structures can either become smooth due to the absence of smaller-scale features or become rougher due to the presence of superimposed smaller-scale structures.展开更多
针对测深侧扫声呐进行波达方向(Direction of Arrival,DOA)估计时会受到阵元幅度、相位误差及低信噪比影响的问题,提出一种改进的波束域加权子空间拟合算法。首先,采用总体最小二乘-旋转不变子空间算法进行回波方向预估计;其次,将连续...针对测深侧扫声呐进行波达方向(Direction of Arrival,DOA)估计时会受到阵元幅度、相位误差及低信噪比影响的问题,提出一种改进的波束域加权子空间拟合算法。首先,采用总体最小二乘-旋转不变子空间算法进行回波方向预估计;其次,将连续线阵划分为多个子阵,并将各个子阵在预估计方向做加权波束形成;再次,采用加权子空间拟合(Weighted Subspace Fitting,WSF)算法构造代价函数;最后,采用阻尼牛顿法求解得到高精度的DOA估计结果。仿真结果表明,文中所提算法在阵元出现幅度相位误差条件下的角度估计均方误差相对于WSF算法减少了约0.03°。海试数据分析结果表明,文中所提算法的测深点均方误差整体优于WSF算法,其相对测深精度提高了约9.8个百分点。以上分析结果表明,文中所提算法整体优于WSF算法,可以实现在阵元幅度相位误差及低信噪比情况下的高精度DOA估计。展开更多
近年来,滨海核电冷源取水口致灾生物,特别是毛虾、水母等已成为核电站安全运行的重大隐患,对其监测需求日益迫切。然而,上述致灾生物通常具有透明度高、体型小等特点,加上近海岸水体浊度高,难以通过光学设备进行有效探测。声呐探测因具...近年来,滨海核电冷源取水口致灾生物,特别是毛虾、水母等已成为核电站安全运行的重大隐患,对其监测需求日益迫切。然而,上述致灾生物通常具有透明度高、体型小等特点,加上近海岸水体浊度高,难以通过光学设备进行有效探测。声呐探测因具有良好的方向性和穿透性、对浊度不敏感等优势,成为探测上述致灾生物的理想方案。目前,声呐探测技术主要通过实时检测单张声呐图像中的致灾生物目标来实现。由于海洋环境复杂多变,存在潮汐等干扰,声呐图像中的目标形状往往不清晰、边缘信息容易丢失,造成致灾生物目标的虚检率和漏检率较高。为解决上述难题,本文提出一种基于滑动窗口特征聚合的声呐图像处理技术。首先,对声呐图像进行增强和潮汐干扰去除的预处理操作,减少噪声和潮汐干扰对监测结果的不利影响;然后,以连续的视频帧作为研究对象,利用滑动窗口的方式对其进行特征聚类,确定固定物的位置并排除其干扰;最后,结合帧间差分分析法及交并比(Intersection over Union,IoU)算法、非极大值抑制(Non-Maximum Suppression,NMS)算法,精确识别并检测出近海致灾生物目标。本系统可以实现对近海致灾生物的实时、精确监测,且检出率高达96%。该技术可提升我国在核电站海洋生物监测预警方面的精确度、维护核电站的正常运行。展开更多
文摘Karst landforms are widely distributed in China,and are most common in Yunnan,Guizhou and Guangxi.If the development of karst caves at the bottom of the piles cannot be accurately ascertained before the construction of bridge pile foundations,accidents such as hole collapse,slurry leakage,and drill sticking will easily occur.In this paper,the principle and method of sonar detection for detecting karst caves at the bottom of bridge piles was introduced,and the sonar detection data and the cave situation at the bottom of the pile during the construction process in combination with the case of Yunnan Zhenguo Highway Project was analyzed,which verifies the practicability and reliability of sonar detection method reliability.
基金supported by the National Natural Science Foundation of China (Grant Nos. 40876043,40976051 andJ1103408)Public Science and Technology Research Funds Projects of Ocean (Grant No. 201105001-2)the Priority Academic Program Development of Jiangsu Higher Education Institutions fund
文摘The morphological characteristics of small-scale bedforms were measured by means of an acoustic profiling sonar on the Dafeng tidal flat, Jiangsu, in 2009, and in the Jiulong Estuary, Xiamen, in 2010, respectively. The ＂multi-threshold value＂ method was utilized to reveal the morphological undulations along which bedforms were present. Analyses of the datasets obtained show that： （1） sand ripples can have irregular shapes, and （2） changes in bedform morphology are small within a single tidal cycle but may be significant over several tidal cycles. Fractal and variogram analyses of the seabed roughness revealed the existence of a significant relationship between current speed and the fractal dimension of the seabed roughness. As current speed increases, seabed roughness increases with a trend of smaller-scale bottom structures being replaced by larger-scale structures. Furthermore, the surface of the larger-scale bottom structures can either become smooth due to the absence of smaller-scale features or become rougher due to the presence of superimposed smaller-scale structures.
文摘针对测深侧扫声呐进行波达方向(Direction of Arrival,DOA)估计时会受到阵元幅度、相位误差及低信噪比影响的问题,提出一种改进的波束域加权子空间拟合算法。首先,采用总体最小二乘-旋转不变子空间算法进行回波方向预估计;其次,将连续线阵划分为多个子阵,并将各个子阵在预估计方向做加权波束形成;再次,采用加权子空间拟合(Weighted Subspace Fitting,WSF)算法构造代价函数;最后,采用阻尼牛顿法求解得到高精度的DOA估计结果。仿真结果表明,文中所提算法在阵元出现幅度相位误差条件下的角度估计均方误差相对于WSF算法减少了约0.03°。海试数据分析结果表明,文中所提算法的测深点均方误差整体优于WSF算法,其相对测深精度提高了约9.8个百分点。以上分析结果表明,文中所提算法整体优于WSF算法,可以实现在阵元幅度相位误差及低信噪比情况下的高精度DOA估计。
文摘近年来,滨海核电冷源取水口致灾生物,特别是毛虾、水母等已成为核电站安全运行的重大隐患,对其监测需求日益迫切。然而,上述致灾生物通常具有透明度高、体型小等特点,加上近海岸水体浊度高,难以通过光学设备进行有效探测。声呐探测因具有良好的方向性和穿透性、对浊度不敏感等优势,成为探测上述致灾生物的理想方案。目前,声呐探测技术主要通过实时检测单张声呐图像中的致灾生物目标来实现。由于海洋环境复杂多变,存在潮汐等干扰,声呐图像中的目标形状往往不清晰、边缘信息容易丢失,造成致灾生物目标的虚检率和漏检率较高。为解决上述难题,本文提出一种基于滑动窗口特征聚合的声呐图像处理技术。首先,对声呐图像进行增强和潮汐干扰去除的预处理操作,减少噪声和潮汐干扰对监测结果的不利影响;然后,以连续的视频帧作为研究对象,利用滑动窗口的方式对其进行特征聚类,确定固定物的位置并排除其干扰;最后,结合帧间差分分析法及交并比(Intersection over Union,IoU)算法、非极大值抑制(Non-Maximum Suppression,NMS)算法,精确识别并检测出近海致灾生物目标。本系统可以实现对近海致灾生物的实时、精确监测,且检出率高达96%。该技术可提升我国在核电站海洋生物监测预警方面的精确度、维护核电站的正常运行。
