水下封底混凝土与钢护筒粘结力试验

通过实地试验，对C25水下混凝土与钻孔桩钢护筒壁之间的粘结力作了测试，得出了比较实用可靠的数据。     

浅谈静水桥梁钻孔桩施工的几点体会

简要介绍了几种静止单排钻孔桩基础的施工方法     

河床基岩裸露条件下桥梁基础施工

针对河床基岩裸露条件下进行桥梁基础施工,提出“先堰后桩”,即先下围堰,后施工桩基的施工方法,避免在基岩裸露河床上打设水中钻孔平台的困难。围堰既是承台施工的围水结构,又作为桩基施工的平台。由于基础埋深较大,围堰下沉前,先进行水下爆破清基,利于围堰下沉、定位。     

水下管汇深水安装力学分析

近些年来随着海洋油气开采规模的扩大,水下设备逐渐被广泛应用到海洋油气开采和运输。通过研究水下管汇的两种不同深水安装方法（钻杆安装法以及绞车安装法）,得出管汇安装相关结论。基于钻杆以及缆绳的材料特性,建立两个理论模型分析并推导钻杆和缆绳在安装过程中的水平偏移以及轴向拉力的求解公式,并根据理论公式编写MATLAB程序。将程序计算结果与OrcaFlex软件模拟结果进行对比分析,验证理论公式的正确性。该理论方法将会对管汇深水安装提供一定参考价值。     

欠驱动AUV的运动控制技术综述

欠驱动水下机器人由于在减轻系统质量、节约成本和能耗以及提高系统可靠性等方面的优点日益成为研究的热点。尤其是在水下机器人在海洋能源开发中发挥着不可或缺作用的今天,利用少于位形空间维数的控制输入控制欠驱动系统的运动具有非常重要的现实意义。结合水下机器人自身的运动特性,归纳了欠驱动AUV的控制特性,包括本质非线性、欠驱动特性、可控性、约束特性、平衡点特性等。综述了目前欠驱动AUV运动控制技术的主要研究成果,主要包括镇定控制和跟踪控制,并对今后欠驱动AUV的理论与应用发展方向进行了展望。     

滨海侵蚀性海滩柔性集装网抛石护滩试验研究

为了探索柔性集装网抛石在沿海侵蚀海岸的防护效果,选择在侵蚀严重的滨海县海堤同时开展混凝土管桩护滩、混凝土块石护滩、柔性集装网抛石护滩等工程效果研究,积累侵蚀性海岸治理经验。该工程的开展对侵蚀海岸防护治理具有重要的现实意义和实用推广价值。     

水下航行器钛合金密封壳体焊接特性研究

密封壳体是水下航行器最重要的部件,本文分析了TC4(Ti6Al4V)的焊接特性,提出了具体的工艺方案,针对密封壳体制定了可行的焊接方案和操作规范。     

基于单片机的水下机器人传感器故障检测仪设计

针对OUTLAND1000无人水下机器人,采用自适应滤波器FIR对水下机器人进行在线自适应建模,利用LMS算法调节和分析滤波器的权系数实时监测水下机器人传感器的故障.以单片机C8051F120为核心设计故障检测器,数据采集和控制信号通过设计的键盘发送给机器人,传感器数据通过RS-232传送到控制器进行数据分析,并在液晶上显示出相应的故障检测结果.     

一种基于模型的水声弱信号检测方法(英文)

Detection of weak underwater signals is an area of general interest in marine engineering. A weak signal detection scheme was developed; it combined nonlinear dynamical reconstruction techniques, radial basis function (RBF) neural networks and an extended Kalman filter (EKF). In this method chaos theory was used to model background noise. Noise was predicted by phase space reconstruction techniques and RBF neural networks in a synergistic manner. In the absence of a signal, prediction error stayed low and became relatively large when the input contained a signal. EKF was used to improve the convergence rate of the RBF neural network. Application of the scheme to different experimental data sets showed that the algorithm can detect signals hidden in strong noise even when the signal-to-noise ratio (SNR) is less than −40d B.     

水下潜器改进S面控制及控制系统仿真(英文)

S surface controllers have been proven to provide effective motion control for an autonomous underwater vehicle (AUV). However, it is difficult to adjust their control parameters manually. Choosing the optimum parameters for the controller of a particular AUV is a significant challenge. To automate the process, a modified particle swarm optimization (MPSO) algorithm was proposed. It was based on immune theory, and used a nonlinear regression strategy for inertia weight to optimize AUV control parameters. A semi-physical simulation system for the AUV was developed as a platform to verify the proposed control method, and its structure was considered. The simulation results indicated that the semi-physical simulation platform was helpful, the optimization algorithm has good local and global searching abilities, and the method can be reliably used for an AUV.