海洋船舶的轨迹估计算法

基于用于相同目的的线性位置模型的测量,提出一个基于曲线运动模型的机动海洋船只模型。假定系统状态和测量模型的噪声都是高斯白噪声,提出将扩展卡尔曼滤波器用于估计位置、速度和加速度的自适应滤波器算法,用于预测机动的海洋船舶轨迹。最后,提出的模型被实施,并成功地进行了船舶操纵轨迹预测。     

利用多传感器跟踪机动目标:数据越多总意味着估计越好吗?

在文献中考虑利用多传感器跟踪机动目标一类的问题时,支持特定目标跟踪的传感器数量及类型通常相对于目标假定位置是固定的。然而,在许多多传感器系统中,支持某一特定目标跟踪的传感器数量及类型,可由于各个传感器的机动性、类型及资源的制约而随时变化。这种在传感器系统配置上的变化性,在跟踪机动目标时造成严重的问题,这是由于目标运动模型存有不确定性。卡尔曼滤波器通常用于滤波位置测量,以估计目标的位置,速度和加速度。在设计卡尔曼滤波器时,过程噪声(加速度)方差Q_k的如此选定以致于65％到95％的概率区间能包含目标的最大加速度水平。然而,当目标机动时,加速度以一种确定性方式变化。于是,与过程噪声相关的白噪声假设发生偏离,滤波器在目标机动期间产生状态估计偏差。如果选定一个较大的Q_k,则在机动时的状态估计偏差较小,但当目标不作机动时,此时的Q_k只能粗劣地表征目标运动,而且滤波性能远远偏离最优了。这里,举出了目标在单一坐标系运动的例子,说明了利用多传感器跟踪机动目标存在的问题,从中表明两传感器(在确定条件下,其中包括各传感器的正确配置)具有较之单一传感器更糟糕的跟踪性能。将交互式多模型算法(IMM)应用于该范例中,证明了它是一种解决跟踪滤波器性能问题的潜在方法。     

应用双向递归神经网络的船舶轨迹修复迭代算法

为了解决船舶轨迹修复算法修复效果差、修复偏差大的问题,应用双向递归神经网络实现船舶轨迹修复迭代算法的优化设计。从位置坐标和速度2个方面转换收集的船舶轨迹数据,判定当前轨迹是否存在缺失或异常。以已知端点加速度的计算结果为输入项,应用双向递归神经网络得到实时船舶轨迹的预测结果,最终完成对船舶轨迹的修复。通过测试实验发现设计修复方法得出的轨迹位置与理想轨迹基本重合,且修复后的速度和航向偏差分别为0.1 km/h和0.1°,满足设计与应用要求。     

AIS数据中单船操纵模式辨识

针对当前船舶运动数据的特征过于简单、无法反映单船操纵行为、导致可检测的船舶异常行为类型受限的问题,根据船舶操纵规律和运动学约束条件,利用轨迹中的3个点构建船舶操纵模式模型,提出一种从船舶自动识别系统(Automatic Identification System,AIS)数据中自动辨识单船操纵模式的方法。实际AIS轨迹试验结果表明,该方法能自动提取停留、匀速运动、加速、减速、小幅度左转、小幅度右转、大幅度左转和大幅度右转等8种船舶操纵行为模式,提取出的操纵行为与实际操船意图相符。此外,该方法能有效识别出需重点关注的机动行为,从而为进一步检测船舶异常行为和分析驾驶员行为奠定基础。     

改进灰色模型的船舶航行轨迹自动预测研究

为实现更加精准、自动化的船舶航行轨迹预测,利用改进灰色模型,提出一种基于改进灰色模型的船舶航行轨迹自动预测方法。在船舶航行中的AIS数据中对船舶航行轨迹数据进行提取,其中AIS数据具体包括船舶航程数据、船舶动态数据以及船舶动态数据。通过数据估计算法插补缺失数据,分为2个步骤,第1步是对插补数据进行识别,第2步是对其进行插补。通过改进灰色模型对船舶航行轨迹进行自动预测,主要使用基于缓冲算子改进的灰色模型构建船舶航行轨迹自动预测模型。选取某船舶服务项目中包含的船舶AIS数据作为实验数据,对设计方法进行实例测试。测试结果表明,设计方法的数据提取质量较高、预测模型的误差较小,具有广阔的市场应用前景。     

基于虚拟现实的船舶操纵控制系统设计

为了提高船舶操纵控制过程的性能参数评估场景再现能力,提出基于虚拟现实技术的船舶操纵控制系统设计方法。进行船舶操纵控制的3D几何模型建模,采用Multigen Creator技术生成3D虚拟海洋场景模型和船舶实体模型,在Vega Prime应用程序进行船舶操纵控制的视景仿真平台设计,对船舶操纵控制系统视景仿真模拟是建立在三维虚拟现实仿真软件基础上的,通过船舶操纵控制的三维姿态数据加载和程序控制,在视景仿真平台上对船舶操纵控制进行位置调整和参量优化配置,实现船舶操纵控制的虚拟视景开发和系统优化设计。仿真结果表明,本文设计的船舶操纵控制系统能在虚拟视景下实现精确的船舶操纵,视景的逼真度较高,参数控制精度较高。     

基于计算机视觉的船舶操纵受扰力预测模型

常规船舶操纵受扰力预测模型在高海况预测数据幅值较大的情况下,预测过程引入的误差较大,因此设计一种基于计算机视觉的船舶操纵受扰力预测模型。首先分析船舶水上受力,得到不同坐标系下船舶自由度向量,在一定假设条件下得到船舶受力方程,了解船舶的受力情况后对基于计算机视觉的船舶航行图像的质量进行处理,填充连通图像区域,完成图像形态学处理,提取出与船舶操纵受扰力相关的图像兴趣区域,结合船舶自身的特性,完成船舶操纵受扰力的预测。仿真实验的结果表明,设计的预测模型在高海况不同船舶航行速度下,预测误差均小于常规模型,验证了设计模型的准确度。     

基于MPC-DO的自主水下航行器轨迹跟踪控制

针对欠驱动自主水下航行器在速度约束和未知外界环境干扰下的轨迹跟踪问题,提出一种基于模型预测控制算法和干扰观测器的复合控制方案。首先,基于模型预测控制算法设计一种考虑速度极限约束以及速度增量约束的轨迹跟踪运动学控制器。其次,针对海洋作业环境下存在的外界干扰,设计干扰观测器对其进行实时估计,并基于所设计的干扰观测器,设计精确跟踪期望速度的动力学控制器,并对控制方案进行了严格的理论分析。最后,进行数值仿真,仿真结果证实了该控制方案的有效性。     

船舶航行速度估计的数学模型研究

为解决因船舶航速过度灵活转换而造成的海洋航行事故,提出船舶航行速度估计的数学模型。以直航运动稳定性作为分析前提,建立必要的操纵辨识条件,从而实现船舶航速操纵参数的辨识处理。在此基础上,按照船体的实时受力情况,获取与直向航行相关的物理参数,再按照测速校正原理,完成船舶航行速度估计的数学模型研究。模拟应用实验结果表明,FPS(顺逆转换系数)、SPS(逆顺转换系数)均出现明显下降,船舶航速转换灵活性得到适度抑制,大幅降低海洋航行事故的发生几率。     

一种基于扩展状态观测器的智能船舶Nomoto模型参数辨识方法北大核心CSCD

[目的]为了支持制导、导航、控制等船舶智能化技术的测试验证平台的搭建,利用系统辨识技术得到高精度的智能船舶野本(Nomoto)运动模型参数。[方法]充分结合扩展状态观测器(ESO)以及鲁棒加权最小二乘支持向量回归(RW-LSSVR)算法的优势,提出一种高效低成本的混合参数辨识方法。为解决模型参数辨识中无法直接有效获取某些状态量的问题,构建了基于ESO的状态估计方法。基于估计方法与直接测量的船舶运动状态量,采用具有较强抗异常值干扰的RW-LSSVR对智能船舶二阶线性Nomoto运动模型参数进行辨识。以已知模型的两艘船舶为测验对象,对所提参数估计与辨识方法进行综合测验。[结果]在利用较少传感器的情况下,通过ESO可较精确地估计出非直接测量的船舶运动状态量,并且利用RW-LSSVR辨识得到的参数值十分接近标准值。[结论]利用所提方法获得的估计状态可用于参数辨识,并且辨识模型具有较好的泛化性。     

Experimental investigation on the dynamic responses of a free-hanging water intake riser under vessel motion

A large-scale model test of a free-hanging water intake riser (WIR) is performed in an ocean basin to investigate the riser responses under vessel motion. Top end of the WIR is forced to oscillate at given vessel motion trajectories. Fiber Brag Grating (FBG) strain sensors are used to measure the WIR dynamic responses. Experimental results firstly confirms that the free-hanging WIR would experience out-of-plane vortex-induced vibrations (VIVs) under pure vessel motion even for the case with a KC number as low as 5. Meanwhile, comparison between numerical results and experimental measurements suggests a significant drag amplification by out-of-plane vessel motion-induced VIV. What’s more, further study on WIR response frequencies and cross section trajectories reveals a strong correlation between vessel motion-induced VIV and local KC number distribution, owing to the small KC number effect. The presented work provides useful references for gaining a better understanding on VIV induced by vessel motion, and for the development of future prediction models.     

大型船舶侧推器操纵效能计算

为探讨首侧推器操纵效能,本文在有航速、零速和横移的不同工况下,分别采用三自由度、二自由度数学模型,并对1条12300 t大型滚装船进行了首侧推器操纵效能的实例计算.计算结果表明侧推器操纵效能与航速及桨转速直接有关,零航速最好,且随桨转速增高而增强;结果同时也表明了借助于主推进器、首侧推器和舵的联合操纵可实施纯横移运动.     

Impact scenario models for probabilistic risk-based design for ship–ship collision

A number of authors have proposed probabilistic risk based ship design for ship–ship collision, conditional to the local trading area of a vessel. The probability of collision and consequences are determined based on the traffic conditions in which a vessel is expected to operate. This paper investigates the adequacy of currently available models for impact scenarios, i.e. models linking the traffic conditions to the conditions at the moment of collision. An exploratory statistical model is presented to establish such a link. A probabilistic risk based design case study is performed for a fleet of RoPax vessels trading on a specified route in the Gulf of Finland. The available impact scenario models from the literature are compared with the developed probabilistic evasive maneuvering model. The results show that the impact scenario models have a very significant influence to the calculated hull breach probabilities. No well-justified impact scenario models are presently available and also the presented probabilistic evasive maneuvering model is burdened with uncertainty. Hence, to move toward a probabilistic risk based ship design paradigm for ship–ship collision in a local trading area, more focus and research is needed to establish a credible link.     

大型重载船舶在受限水域操纵中若干问题探讨

大型重载船舶航行在受限水域,不仅缩小了可航水道的宽度,并且富余水深小,浅水效应与岸壁效应明显,增大了操纵难度.此文结合水深、航道宽度等影响因素,阐述了大型重载船舶港内受限水域操纵中,对于船位控制、过弯操纵以及拖轮应急制动等方面的特殊要求,并结合船舶操纵实际,提出在受限水域中的安全操纵要领及注意事项.     

基于LS-SVM的船舶操纵运动在线建模

基于最小二乘支持向量机(LS-SVM)和积分型辨识样本结构开展了船舶操纵运动的在线建模.以整体型Abkow-itz模型为辨识对象,大阪号油轮作为具体研究对象.在操纵运动仿真时,采用40个粘性类水动力导数的Abkowitz模型,但是在参数辨识时,采用了仅具有20个粘性类水动力导数的简化模型.为了对建模方法的有效性进行检验,将辨识得到的水动力导数与其原始值进行了比较,同时也针对辨识模型和原始模型的操纵运动仿真进行了比较.辨识结果表明,使用简化模型进行船舶操纵运动的在线建模是合适的,具有较好的预报效果和较高的精度.     

Fuzzy logic based decision making system for collision avoidance of ocean navigation under critical collision conditions

This paper focuses on a fuzzy logic based intelligent decision making system that aims to improve the safety of marine vessels by avoiding collision situations. It can be implemented in a decision support system of an oceangoing vessel or included in the process of autonomous ocean navigation. Although Autonomous Guidance and Navigation (AGN) is meant to be an important part of future ocean navigation due to the associated cost reduction and improved maritime safety, intelligent decision making capabilities should be an integrated part of the future AGN system in order to improve autonomous ocean navigational facilities. In this study, the collision avoidance of the Target vessel with respect to the vessel domain of the Own vessel has been analyzed and input, and output fuzzy membership functions have been derived. The if–then rule based decision making process and the integrated novel fuzzy inference system are formulated and implemented on the MATLAB software platform. Simulation results are presented regarding several critical collision conditions where the Target vessel fails to take appropriate actions, as the “Give way” vessel to avoid collision situations. In these situations, the Own vessel is able to take critical actions to avoid collisions, even when being the “Stand on” vessel. Furthermore, all decision rules are formulated in accordance with the International Maritime Organization Convention on the International Regulations for Preventing Collisions at Sea (COLREGs), 1972, to avoid conflicts that might occur during ocean navigation.     

A study on flow field around full ship forms in maneuvering motion

To estimate the maneuvering ability of a ship, an accurate estimation of the hydrodynamic forces and moment acting on the ship's hull is indispensable. For the purpose of developing a numerical method of computing the viscous flow field around a hull and evaluating its validity, the hydrodynamic pressure on the hull and the velocity field were measured. Two full ship models with different hull forms in the aft part were used for the experiment. From the results of pressure measurements, the distribution of hydrodynamic lateral forces was obtained. The simulation method is a numerical solution of the Navier-Stokes equation based on a finitevolume method and applied to the maneuvering motion. The measured and computed results agree qualitatively well, and the method is a valuable tool for estimating the maneuvering ability of a ship. The typical characteristics of the flow field in the steady turning condition are revealed by the numerical simulation, and the mechanism of the relations between hull form, flow field, and hydrodynamic forces are clarified.Translation and combination of articles that appeared in the Journal of the Society of Naval Architects of Japan, vols. 176, 177, 179 (1994–1996): The original article won the SNAJ prize, which is awarded annually to the best papers selected from the SNAJ Journal, JMST, or other quality journals in the field of naval architecture and ocean engineering.This work was conducted as part of the joint SR221 project supported by JSRA (Shipbuilding Research Association of Japan). The authors express their sincere gratitude to the persons concerned, and especially to M. Kanai, S. Eguchi, S. Usami, K. Tatsumi, and T. Kawamura.     

基于神经网络的船舶操纵运动建模研究（英文）

In this paper, Neural Networks(NNs) are used in the modeling of ship maneuvering motion. A nonlinear response model and a linear hydrodynamic model of ship maneuvering motion are also investigated. The maneuverability indices and linear non-dimensional hydrodynamic derivatives in the models are identified by using two-layer feed forward NNs. The stability of parametric estimation is confirmed. Then, the ship maneuvering motion is predicted based on the obtained models. A comparison between the predicted results and the model test results demonstrates the validity of the proposed modeling method.     

Modeling of ship maneuvering motion using neural networks

In this paper, Neural Networks (NNs) are used in the modeling of ship maneuvering motion. A nonlinear response model and a linear hydrodynamic model of ship maneuvering motion are also investigated. The maneuverability indices and linear non-dimensional hydrodynamic derivatives in the models are identified by using two-layer feed forward NNs. The stability of parametric estimation is confirmed. Then, the ship maneuvering motion is predicted based on the obtained models. A comparison between the predicted results and the model test results demonstrates the validity of the proposed modeling method.     

系泊船舶动力学特性的计算机仿真研究

以三阶操纵运动方程为基础，引入定常的风力、潮流作用力和二阶波浪力，建立了系泊系统三自由度的运动微分方程。在此数学模型的基础上．建立了系泊系统的多自由度的计算机仿真模型。在潮流作用、潮流和风作用以及风浪流联合作用等三种情形下，对系泊船舶的动力学响应分别进行了仿真研究。研究表明，系泊系统的动力学行为具有强烈的非线性特征。对于单点系泊船舶而言，在定常的风浪流作用下．顶风顶浪顶流状态并不一定是最为危险的工况。