Ship motion measurement filter design

A procedure is presented for designing Kalman filters to measure linear and angular ship motion parameters using realistic models of the ship motion dynamics. The design is based on the state space modeling of ship motion dynamics. The designed filters exhibited significant accuracy improvement (order of magnitude) over filters which do not model ship dynamics. The sensitivity of the filter mechanization to mismodeling of dynamics is investigated. Bounding filter design techniques are used to minimize the effects of mismodeling. The particular measurement system investigated consisted of linear and angular accelerometers in a strapdown mode. The design techniques are also applicable to inertial instruments in a stable inertial platform mode.     

带乘性噪声广义系统状态最优估计算法

针对带乘性噪声广义系统,提出1种在线性最小方差意义下的状态最优估计算法.首先,采用标准分解将系统变换为2个子系统;其次,通过估计子系统的状态,获得原系统的状态最优滤波.同时,算法还给出了动态噪声与量测噪声的估计.仿真结果表明了该算法的有效性.     

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

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.     

Some methods to obtain the added resistance of a ship advancing in waves

Added resistance in waves is an important part of ship dynamic due to its economical effect on ship exploitation. Can the ship sustain speed in a rough sea state? If not, this will produce delays and economical losses if added resistance is not taken into account in the propulsion design. There are not many simple methods to obtain the added resistance in waves of a ship, and the validity of the results is not always good enough for different ships. In this paper, some theories that can be used to predict the added resistance of a ship are studied and validated against seakeeping tests of some monohull models. Tests and results focus in head seas, which are the most severe for the added resistance. Experimental results are compared with numerical calculations and conclusions about the range of application of the presented theories are obtained.     

测船非匀速直线测量引起的多波束测深误差分析

多波束测深系统作业的基本前提是测船保持匀速直线运动状态,而实际作业中非匀速运动状态下的多波束测量普遍存在,此时常用的基于加速度测量原理的测姿设备会受到影响。为此,在多波束测姿误差分析的基础上,针对直线加速、U型转弯两种情况下的测姿误差进行研究,通过INS测姿与GNSS三天线测姿的数据比较,对非匀速直线运动状态下姿态误差的影响特点及程度进行了分析。实验证明当测船做直线加速运动时,会使纵摇角产生较大误差;当测船转弯时,会使横摇角产生较大误差,这对指导多波束实际测量具有一定的参考价值。     

Measures to diminish the parameter drift in the modeling of ship manoeuvring using system identification

System identification provides an effective way to predict the ship manoeuvrability. In this paper several measures are proposed to diminish the parameter drift in the parametric identification of ship manoeuvring models. The drift of linear hydrodynamic coefficients can be accounted for from the point of view of dynamic cancellation, while the drift of nonlinear hydrodynamic coefficients is explained from the point of view of regression analysis. To diminish the parameter drift, reconstruction of the samples and modification of the mathematical model of ship manoeuvring motion are carried out. Difference method and the method of additional excitation are proposed to reconstruct the samples. Using correlation analysis, the structure of a manoeuvring model is simplified. Combined with the measures proposed, support vector machines based identification is employed to determine the hydrodynamic coefficients in a modified Abkowitz model. Experimental data from the free-running model tests of a KVLCC2 ship are analyzed and the hydrodynamic coefficients are identified. Based on the regressive model, simulation of manoeuvres is conducted. Comparison between the simulation results and the experimental results demonstrates the validity of the proposed measures.     

On the identification of ship coupled heave–pitch motions using neural networks

This paper outlines a procedure for the derivation of the differential equations describing the free response of a heaving and pitching ship from its stationary response to random waves. The coupled heave–pitch motion of a ship in random seas is modelled as a multi-dimensional Markov process. The partial differential equation describing the transition probability density function, known as the Fokker-Planck equation, for this process is derived. The Fokker-Planck equation is used to derive the random decrement equations for the coupled heave–pitch motion. The parameters in these equations are then identified using a neural network approach. The method is validated using numerical simulations and experimental results. The experimental data was obtained using an icebreaker ship model heaving and pitching in random waves. It is shown that the method produces good results when the system is lightly damped. An extension for using this method to identify couple heave–pitch motion in realistic seas is suggested.     

On the identification of ship coupled heave–pitch motions using neural networks

This paper outlines a procedure for the derivation of the differential equations describing the free response of a heaving and pitching ship from its stationary response to random waves. The coupled heave–pitch motion of a ship in random seas is modelled as a multi-dimensional Markov process. The partial differential equation describing the transition probability density function, known as the Fokker-Planck equation, for this process is derived. The Fokker-Planck equation is used to derive the random decrement equations for the coupled heave–pitch motion. The parameters in these equations are then identified using a neural network approach. The method is validated using numerical simulations and experimental results. The experimental data was obtained using an icebreaker ship model heaving and pitching in random waves. It is shown that the method produces good results when the system is lightly damped. An extension for using this method to identify couple heave–pitch motion in realistic seas is suggested.     

Prediction of design wave loads of the ocean structure by equivalent irregular wave approach

The present study is employing the equivalent irregular wave approach to predict the wave loads for a ship encountering the worst sea state with respect to the critical dynamic loading parameter. Two different hydrodynamic numerical models, i.e. 3D pulsating source technique and 3D translating pulsating source technique, are applied to calculate the corresponding RAO of the ship moving in waves. Incorporating the RAO of the related physical properties, we can calculate the extreme value for the corresponding ship loading factor, which can be regarded as the worst sea state in the service lifetime of the ship. With the time and period of the occurrence of the corresponding extreme value, we can simulate the time history of the wave load in this period, which is so-called equivalent irregular wave approach. Comparing with the results calculated by the traditional equivalent regular wave approach, we find that the equivalent irregular wave approach can simulate the corresponding wave load more realistic, especially for dynamic pressure. Using the equivalent irregular wave approach can offer the effective and practical base for the ship structural analysis.     

不规则波下船舶运动响应特征数值分析

针对不规则波浪作用下Wigley型船的运动响应问题进行了系统的研究,采用统计学方法深入探讨了船舶不规则运动幅值和响应周期的分布规律,并通过傅里叶变换对船舶运动响应进行了频谱特征分析。结果表明,船舶横摇方向与升沉和纵摇方向随机运动的响应特征有显著差异。在升沉与纵摇方向,波浪谱峰频率远离自振频率,前十分之一大振幅运动对应周期离散性较小,基本稳定在波浪谱峰周期附近,但小振幅运动周期分布离散性较大,频谱分析指出船舶升沉与纵摇运动响应频谱在波浪谱峰频率附近出现明显峰值。而在横摇方向,波浪谱峰频率与自振频率相耦合,不同振幅的横摇运动响应周期均稳定在自振周期附近,且周期离散性较小,频谱分析也表明横摇运动响应频谱主要集中于船舶运动自振频率附近。     

Optimized support vector regression algorithm-based modeling of ship dynamics

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.     

波谱仪调制功率谱估计算法性能的仿真研究

基于星载波谱仪海浪方向谱探测原理,仿真了不同海况、风速下的海浪波谱仪接收信号,并采用周期图法、Welch法、AR模型法以及最小方差法共4种不同的调制谱估计方法反演出海浪谱,比较各种调制谱估计方法的海浪方向谱反演性能。仿真结果表明:对于一定方位向下的一维海浪谱反演,不同调制谱估计方法反演海浪谱性能优劣没有绝对的顺序。对于二维海浪谱反演,在成长中海浪条件下周期图法反演性能最差,其他3种方法的反演性能没有绝对优劣顺序;对于成熟风浪,最小方差法在积分能量误差、有效波高误差两个指标上的反演性能最好,在主波波向、主波波长误差上,周期图法反演性能最差,其他3种方法没有绝对优劣顺序。在涌浪条件下,AR模型法反演性能优于其他3种方法。在不同海况下,随着波谱仪中心入射角的下降,反演性能会下降。基于这些仿真结果,本文推荐最小方差法作为充分成长海浪的海浪方向谱反演的调制谱估计方法,AR模型法作为涌浪海浪方向谱反演的调制谱估计方法。     

A method for breach assessment onboard a damaged passenger ship

Reliable analysis of stability and safety level in a flooding emergency onboard a damaged passenger ship is extremely important for making correct decisions on evacuation and abandonment. Thus there is demand for an automated system that detects flooding and analyzes the severity of the situation. This procedure requires estimation of the actual breach in the hull, and calculation of possible progressive flooding to undamaged compartments. A new approach to the breach assessment, based on measurement data from the flood level sensors, is presented. The developed method is complemented by time-domain flooding simulations in order to separate progressive flooding from direct inflow through the breaches in the hull of the damaged ship. The developed approach is tested and demonstrated with a large passenger ship design for various damage scenarios. The results show that the size and location of the breach can be evaluated with reasonable accuracy on the basis of the level sensor data, provided that there are enough well-placed, working level sensors.     

A synthetic aperture radar sea surface distribution estimation by n-order Bézier curve and its application in ship detection

To dates,most ship detection approaches for single-pol synthetic aperture radar(SAR) imagery try to ensure a constant false-alarm rate(CFAR).A high performance ship detector relies on two key components:an accurate estimation to a sea surface distribution and a fine designed CFAR algorithm.First,a novel nonparametric sea surface distribution estimation method is developed based on n-order Bézier curve.To estimate the sea surface distribution using n-order Bézier curve,an explicit analytical solution is derived based on a least square optimization,and the optimal selection also is presented to two essential parameters,the order n of Bézier curve and the number m of sample points.Next,to validate the ship detection performance of the estimated sea surface distribution,the estimated sea surface distribution by n-order Bézier curve is combined with a cell averaging CFAR(CA-CFAR).To eliminate the possible interfering ship targets in background window,an improved automatic censoring method is applied.Comprehensive experiments prove that in terms of sea surface estimation performance,the proposed method is as good as a traditional nonparametric Parzen window kernel method,and in most cases,outperforms two widely used parametric methods,K and G0 models.In terms of computation speed,a major advantage of the proposed estimation method is the time consuming only depended on the number m of sample points while independent of imagery size,which makes it can achieve a significant speed improvement to the Parzen window kernel method,and in some cases,it is even faster than two parametric methods.In terms of ship detection performance,the experiments show that the ship detector which constructed by the proposed sea surface distribution model and the given CA-CFAR algorithm has wide adaptability to different SAR sensors,resolutions and sea surface homogeneities and obtains a leading performance on the test dataset.     

波浪作用下缆船拖带系统非线性运动数值模拟

基于船舶操纵性运动方程和拖缆的三维动力学运动方程,提出了被拖点位置匹配的方法,建立了拖船—拖缆—被拖船系统整体非线性拖带动力学模型。为了考察被拖船航向稳定性与横向稳性的关系以及波浪载荷作用的影响,被拖船采用水平面四自由度运动方程,并引入了波浪的作用力和力矩。拖船采用PD控制方法较真实地模拟了拖船航向改变的运动过程。对一个拖船—拖缆—被拖船系统(5 000 t的拖船和3 000 t的被拖船)在时域内进行了规则波浪作用下拖带运动的模拟,计算结果表明被拖带船舶在波浪中运动呈现运动稳定、不稳定和临界状态3种可能的特性。根据模拟计算结果,认为波浪中拖带航向稳定是被拖带船舶保持稳性的必要条件。     

Parametric model identification of high-speed craft dynamics

Parametric models of heave, pitch and roll dynamics of a high-speed craft have been estimated for different wave incidence angles in the frequency domain. Several issues that make the identification problem interesting are the following: type of parameterization, starting values, non-quadratic functions, excitation signals and short data record. The method employed guarantees a fine linear approximation of the nonlinear dynamics of a fast ship for the ultimate goal of stabilization control to reduce motion sickness associated with heave, pitch and roll accelerations. In addition, the approach achieves high-quality starting values and avoids non-quadratic terms in the cost function, which results in less computational load and significantly more accurate models when compared with a previous method employed for the same problem.     

惯性技术视角下动态重力测量技术评述(三):惯性导航与重力测量的融合

动态重力仪和惯性导航系统的核心元件都是惯性元件,即陀螺仪和加速度计(重力传感器可以认为是一种特殊的加速度计),因此重力测量与惯性导航具有紧密的联系。从比力测量、物理与数学平台、惯性手段辅助重力测量,以及重力辅助惯性导航等方面分析了重力仪与惯性导航系统的紧密联系。并对惯性导航与重力测量的融合应用进行了分析。     

Adaptive output feedback control based on DRFNN for AUV

The tracking control problem of AUV in six degrees-of-freedom (DOF) is addressed in this paper. In general, the velocities of the vehicles are very difficult to be accurately measured, which causes full state feedback scheme to be not feasible. Hence, an adaptive output feedback controller based on dynamic recurrent fuzzy neural network (DRFNN) is proposed, in which the location information is only needed for controller design. The DRFNN is used to online estimate the dynamic uncertain nonlinear mapping. Compared to the conventional neural network, DRFNN can clearly improve the tracking performance of AUV due to its less inputs and stronger memory features. The restricting condition for the estimation of the external disturbances and network's approximation errors, which is often given in the existing literatures, is broken in this paper. The stability analysis is given by Lyapunov theorem. Simulations illustrate the effectiveness of the proposed control scheme.