Identification-based simplified model of large container ships using support vector machines and artificial bee colony algorithm     

《Applied Ocean Research》2017

The 6 degrees of freedom (DOF) model with a high degree of complexity for capturing ship dynamics is generally able to track the nonlinear and coupling dynamics of ships. However, the 6 DOF model makes challenges in estimating model coefficients and designing the model-based control. Therefore, simplified ship dynamic models within allowed accuracy are essential. This paper simplified the 6 DOF nonlinear dynamic model of ships into two decoupled models including the speed model and the steering model through reasonable assumptions. Those models were tested through maneuvering simulations of a container ship with a 4 DOF dynamic model. Support vector machines (SVM) optimized by the artificial bee colony algorithm (ABC) was used to identify parameters of speed and steering models by analyzing the rudder angle, propeller shaft speed, surge and sway velocities, and yaw rate from simulated data extracted from a series of maneuvers made by the container ship. Comparisons with the first order linear and nonlinear Nomoto models show that the simplified nonlinear steering model can capture more complicated dynamics and performs better. Additionally, comparisons among three different parameter identification methods demonstrate similar identification results but the different performance involving the applicability and effectiveness. SVM optimized by ABC is relatively convenient and effective for parameter identification of ship simplified dynamic models.  相似文献   

船舶转向避让时机与行动的确定及估算误差的影响     

毕修颖 《广东海洋大学学报》2010,30(4)

从船舶运动数学模型出发,用曲线图的方式给出了确定船舶转向避让时机与行动的方法,以及估算误差对它们的影响。避让时机用最简单的到目标船的距离表示,避让行动是指转向角度的大小。对避碰规则中的"早、大、宽"给出了明确的定量,根据该定量可避免无谓的精神紧张和航程浪费,使驾驶员在采取避让行动前就能够预计避让结果。  相似文献   

基于深度学习的光学遥感影像舰船检测算法对比分析     

夏文辉  万剑华  郑红霞  许明明  曲川萍 《海洋科学》2021,45(5):96-102

舰船目标检测是进行海洋环境监管,保障海上权益的重要手段。基于深度学习的目标检测算法能在复杂环境下保持良好性能,为测试不同深度学习目标检测算法在舰船检测中的效果,本文构建了一个包含3893张图像的数据集,涵盖了复杂背景下不同类型的舰船,基于此数据集分别采用Faster RCNN、SSD、RetinaNet、YOLOv3、YOLOv4算法进行实验,结果表明,YOLOv4 、YOLOv3、RetinaNet、Faster RCNN平均精度均在83%以上,其中YOLOv4最高达到91.77%,Faster RCNN误检较多,而SSD平均精度最低,只有79.23%,总的舰船检测数目偏少。将5种模型训练结果在高分二号影像上进行测试,得到较好的检测效果,对舰船检测未来理论研究的开展具有一定的指导意义。  相似文献   

纵向地震作用下通航渡槽碰撞特征研究     

聂利英  林浩然  李守胜  帅娇娇  汪基伟 《地震工程与工程振动》2020,(2):73-82

通航渡槽与升船机是过坝的快速通道。通航渡槽具有墩高由高到低连续变化、升船机与相邻高墩区渡槽基本周期差异大的结构特点,属于地震下激烈碰撞易发结构。基于有限元模型,对通航渡槽进行碰撞特征、控制因素以及地震响应影响研究。研究结果表明:渡槽与升船机周期差异大是造成剧烈碰撞的主要因素,且此碰撞有明显的传递效应;具有大位移的高墩在相邻渡槽跨周期差异不大时也会造成剧烈的碰撞,是碰撞的另一主要控制因素;有别于桥梁结构中碰撞通常限制墩的位移,通航渡槽中靠近升船机的剧烈碰撞区域,出现了明显的槽墩位移放大现象;碰撞对支座剪力影响程度远大于墩底剪力、弯矩。  相似文献   

海上北斗动态精密定位的性能初步评估     

田英国  程龙  刘童岭  钟明飞  冯均超 《测绘与空间地理信息》2020,(3):16-18,25

航天测量船因其具有较强的机动性,能够有效地弥补陆地测站无法覆盖卫星整个轨道的不足,已逐渐成为我国卫星测控不可或缺的一部分。为了保障海上航天测量任务的顺利完成,精确导航定位是航天测量船的重要基础保障,本文分析了目前北斗卫星导航系统在海上测量数据的质量,并进一步分析了海上北斗动态精密定位服务的基本性能,结果表明:利用当前北斗区域导航系统能够实现分米级海上动态精密定位结果。  相似文献   

基于CFD模拟的单点系泊船型网箱浮架结构分析与设计     

陈俊池  刘祚时  陈俊华  陈炫光 《海洋科学》2020,44(4):116-123

针对单点系泊(SPM)网箱系泊力大于传统网箱,离岸环境承受风浪时风险更高的问题,研究设计了一种相较传统圆形网箱拥有更小系泊力的船型网箱,运用正交原理制定了三因素三水平的试验方案,对网箱浮架进行了计算机数值模拟,分析网箱在波流共同作用下的水动力特性变化。研究表明,在兼顾经济成本与网箱安全性的条件下,长24 m,宽9 m,头部角度为60°的网箱浮架具有较优良的水动力性能和相对较低的养殖成本。该网箱系统能随着潮流改变方向而在锚点周围移动,从而极大减小网箱底部的养殖残渣堆积并降低锚固安装成本,可为我国深水网箱的发展提供一定的理论参考依据。  相似文献   

基于广义接触模型的离散元方法及其对船体冰载荷的分析   总被引：1，自引：1，他引：0  

孔帅  季顺迎 《海洋工程》2020,38(3):102-112

冰载荷是影响船舶结构安全的主要环境载荷,因而确定破冰船的冰载荷特征可用于船体结构设计及船舶安全预警分析。海冰作为典型的脆性材料,可采用单元间具有黏结失效效应的离散元方法模拟其破碎行为。为有效地模拟海冰破碎的渐进过程,采用由局部黏结点组成黏结单元的广义接触模型。为分析该模型中直接决定黏结单元失效的强度参数的影响,采用海冰单轴压缩和三点弯曲试验数值模拟进行分析。通过模型试验确定了失效模型中法向黏结强度、切向黏结强度和Mohr-Coulomb准则中的接触摩擦系数的影响。将该数值模型应用于极地科学考察船"雪龙号"的平整冰区冰载荷分析中,并与船舶整体冰阻力经验公式进行了对比验证。  相似文献   

不同波长下KCS船运动响应与波浪增阻数值研究     

郭浩  王建华  万德成 《海洋工程》2020,38(6):11-23

准确预报船舶在波浪中的运动和力可以为船舶性能评估提供参考。采用naoe-FOAM-SJTU求解器,数值模拟固定和放开垂荡、纵摇自由度的KCS船在不同波长的迎浪规则波中的运动。首先运用数值造波方法生成不同波浪周期的Stokes一阶深水规则波,与Stokes波的理论值对比确保造波的准确性;然后计算固定或放开垂荡和纵摇自由度的KCS船在0.65 ≤ λ/L（波长/船长）≤1.95的遭遇波中的运动和阻力,研究KCS船的波浪增阻中绕射和辐射成分,且采用傅里叶分析法研究了运动与阻力的线性和非线性成分分布。结果表明,波浪绕射增阻受波长的影响不大,当波长接近船长时,船舶的垂荡和纵摇幅值以及波浪增阻均达到峰值,这主要由船体剧烈运动引起的辐射增阻导致,应避免船舶在此工况下航行。  相似文献   

Unscented Kalman Filter trained neural network control design for ship autopilot with experimental and numerical approaches     

《Applied Ocean Research》2019

In the recent decades, the application and research of unmanned surface vessels are experiencing considerable growth, which have caused the demands of intelligent autopilots to grow along with the ever-growing requirements. In this study, the design of an autopilot based on Unscented Kalman Filter (UKF) trained Radial Basis Function Neural Networks (RBFNN) was presented. In particular, in order to provide satisfactory control performance for surface vessels with random external disturbances, the modified UKF was utilised as the weights training mechanism for the RBFNN based controller. The configurations of the newly developed free running scaled model, as well as the online signal processing method, were introduced to enable the experimental studies. The experimental and numerical tests were carried out through using the physical scaled model and corresponding mathematical model to validate the capability of the designed control system under various sailing conditions. The results indicated that the UKF RBFNN based autopilot satisfied the functionalities of course keeping, course changing and trajectory tracking only using the rudder as the actuator. It was concluded that the developed control scheme was effective to track the desired states and robust against unpredictable external disturbances. Moreover, in comparison with Back-Propagation (BP) RBFNN and Proportional-Derivative (PD) based autopilots, the UKF RBFNN based autopilot has the comparable capability in the aspects of providing smooth and effective control laws.  相似文献   

Optimized support vector regression algorithm-based modeling of ship dynamics     

《Applied Ocean Research》2019

This study contributes to solving the problem of how to derive a simplistic model feasible for describing dynamics of different types of ships for maneuvering simulation employed to study maritime traffic and furthermore to provide ship models for simulation-based engineering test-beds. The problem is first addressed with the modification and simplification of a complicated and nonlinearly coupling vectorial representation in 6 degrees of freedom (DOF) to a 3 DOF model in a simple form for simultaneously capturing surge motions and steering motions based on several pieces of reasonable assumptions. The created simple dynamic model is aiming to be useful for different types of ships only with minor modifications on the experiment setup. Another issue concerning the proposed problem is the estimation of parameters in the model through a suitable technique, which is investigated by using the system identification in combination with full-scale ship trail tests, e.g., standard zigzag maneuvers. To improve the global optimization ability of support vector regression algorithm (SVR) based identification method, the artificial bee colony algorithm (ABC) presenting superior optimization performance with the advantage of few control parameters is used to optimize and assign the particular settings for structural parameters of SVR. Afterward, the simulation study on identifying a simplified dynamic model for a large container ship verifies the effectiveness of the optimized identification method at the same time inspires special considerations on further simplification of the initially simplified dynamic model. Finally, the further simplified dynamic model is validated through not only the simulation study on a container ship but also the experimental study on an unmanned surface vessel so-called I-Nav-II vessel. Either simulation study results or experimental study results demonstrate a valid model in a simple form for describing the dynamics of different types’ ships and also validate the performance of the proposed parameter estimation method.  相似文献