Two-Staged Method for Ice Channel Identification Based on Image Segmentation and Corner Point Regression

Identification of the ice channel is the basic technology for developing intelligent ships in ice-covered waters,which is important to ensure the safety and economy of navigation.In the Arctic,merchant ships with low ice class often navigate in channels opened up by icebreakers.Navigation in the ice channel often depends on good maneuverability skills and abundant experience from the captain to a large extent.The ship may get stuck if steered into ice fields off the channel.Under this circumstance,it is very important to study how to identify the boundary lines of ice channels with a reliable method.In this paper,a two-staged ice channel identification method is developed based on image segmentation and corner point regression.The first stage employs the image segmentation method to extract channel regions.In the second stage,an intelligent corner regression network is proposed to extract the channel boundary lines from the channel region.A non-intelligent angle-based filtering and clustering method is proposed and compared with corner point regression network.The training and evaluation of the segmentation method and corner regression network are carried out on the synthetic and real ice channel dataset.The evaluation results show that the accuracy of the method using the corner point regression network in the second stage is achieved as high as 73.33%on the synthetic ice channel dataset and 70.66%on the real ice channel dataset,and the processing speed can reach up to 14.58frames per second.

Combination Operation for Neutral Point of 35 kV Power Grids in Mountainous Area

Based on a lot of measurement and analysis,this paper find that the unbalanced nature of 35 kV grids due to unsymmetrical capacitance values gives difficulty in neutral point operation in mountainous area.Improving compensation of Petersen coil can rectify imbalance of voltage but bring up new problem that Petersen coil can not extinguish grounding arc effectively in fault.To put down contradiction mentioned above,this paper proposes a combination operation for neutral point of 35 kV grids as neutral point insulated in routine operation and grounding through Petersen coil in fault,then EMTP simulation is carried out.Simulation indicates that new neutral operation method can improve lightning withstand level and decrease trip-out rate of grids.

On REE and EER Methods for Mining Corner Points on the Images

This paper reviews, implements and compares two corner detection algorithms for mining corner points on the generic shapes. These corner detectors detect corners by using combination of one rectangle (R) and two ellipses (EE). These algorithms have been used with different combinations: REE and EER together with different parameter settings in their descriptions. REE and EER combinations slide along the boundary of the shape and record number of boundary points in each rectangle and ellipses. REE and EER setup represent both local and global views of the image outlines and present natural corner detection methodologies to detect and mine all true corners accurately. A comparative study demonstrates the superiority of the REE and EER over some of the existing algorithms.

THE DERIVATION OF EXACT STATIC CONDITIONS AT THE CORNER POINTS FOR THE BENDING OF THICK RECTANGULAR PLATES

In this paper, exact static conditions at the corner points for the bending of thickrectangular ptates are strictly. derived from the theorem of minimum potentialenerg[1].

Mining Corner Points on the Generic Shapes

This paper designs and implements a corner detection algorithm for mining corner points on the generic shapes. The proposed corner detector detects corners by using combination of one rectangle and two ellipses (REE) with different parameter settings in their descriptions. REE combination slides along the boundary of the shape and records number of boundary points in each rectangle and ellipses. REE setup represents both local and global views of the image outline. The proposed technique presents a natural corners detection methodology to detect all true corners accurately. This technique is consistent with human vision system.

VIBRATIONS OF RECTANGULAR PLATES SUPPORTED AT CORNER POINTS

This paper discusses by energy theorem the methodof approximate computation for the lowest eigenfrequencies of rechmguhir plates,on which there are symmetrical concentrated masses,supported at corner points,In the case of seseral concentrated masses,by using the prineiple of superposition we mayfiml the reduneed coefficients of masses comveniently.llence we can louain the lowest eigenfrequencies of thin plates.In the paper a good mamy mmerical caleuhting eximples are inustrated

Fine-grained grid computing model for Wi-Fi indoor localization in complex environments

The fingerprinting-based approach using the wireless local area network(WLAN)is widely used for indoor localization.However,the construction of the fingerprint database is quite time-consuming.Especially when the position of the access point(AP)or wall changes,updating the fingerprint database in real-time is difficult.An appropriate indoor localization approach,which has a low implementation cost,excellent real-time performance,and high localization accuracy and fully considers complex indoor environment factors,is preferred in location-based services(LBSs)applications.In this paper,we proposed a fine-grained grid computing(FGGC)model to achieve decimeter-level localization accuracy.Reference points(RPs)are generated in the grid by the FGGC model.Then,the received signal strength(RSS)values at each RP are calculated with the attenuation factors,such as the frequency band,three-dimensional propagation distance,and walls in complex environments.As a result,the fingerprint database can be established automatically without manual measurement,and the efficiency and cost that the FGGC model takes for the fingerprint database are superior to previous methods.The proposed indoor localization approach,which estimates the position step by step from the approximate grid location to the fine-grained location,can achieve higher real-time performance and localization accuracy simultaneously.The mean error of the proposed model is 0.36 m,far lower than that of previous approaches.Thus,the proposed model is feasible to improve the efficiency and accuracy of Wi-Fi indoor localization.It also shows high-accuracy performance with a fast running speed even under a large-size grid.The results indicate that the proposed method can also be suitable for precise marketing,indoor navigation,and emergency rescue.

基于Grid-GSA算法的植保无人机路径规划方法

为了提高植保无人机的作业效率,研究了一种路径规划方法。运用栅格法构建环境模型,根据实际的作业区域规模、形状等环境信息和无人机航向,为相应栅格赋予概率,无人机优先选择概率高的栅格行进。基于上述机制实现了在形状不规则的作业区域内进行往复回转式全覆盖路径规划;以每次植保作业距离为变量,根据仿真算法得出返航点数量与位置来确定寻优模型中的变量维数范围,以往返飞行、电池更换与药剂装填等非植保作业耗费时间最短为目标函数,通过采用引力搜索算法,实现对返航点数量与位置的寻优;为无人机设置必要的路径纠偏与光顺机制,使无人机能够按既定路线与速度飞行。对提出的路径规划方法进行了实例检验,结果显示,相比于简单规划与未规划的情况,运用Grid-GSA规划方法得出的结果中往返飞行距离总和分别减少了14%与68%,非植保作业时间分别减少了21%与36%,其它各项指标也均有不同程度的提高。在验证测试试验中,实际的往返距离总和减少了322 m,实际路径与规划路径存在较小偏差。验证了路径规划方法具有合理性、可行性以及一定的实用性。

基于新内点测试与Grid-SCAN的铀尾矿库监测定位算法

面向铀尾矿库放射性核素污染WSN监测中,由于监测环境制约,针对该条件下节点密度低、带状分布网络连通性差等问题,为保证一定定位精度,提出一种新的定位算法。新内点测试利用RSSI值与海伦公式判断是否在三角形内外,无需未知节点周围其他节点信息,并采用Grid-SCAN寻找概率模型选取点,使该算法满足低密度条件的定位并减少其计算量。约束范围内计算网格内各点RSSI值的概率,并以最大概率坐标为定位结果。经过仿真,新算法较APIT算法在定位精度上提高了55%~69%。

GRID转换为TIN的选点算法

GRID和TIN是GIS的两种重要的数据表示方式?该文设计了一种新的GRID 转换为T IN的过程中点的选取算法?该算法根据Delaunay三角形的特点,分别从平面?横向?纵向3 个方面进行判断选取适当的点?在判断过程中,采用"回溯"的方法,尽量减少生成TIN的 点,通过实验验证,与ARC/INFO系统相比,对同样的GRID格式文件转换为TIN格式时选取的 点更少,从而大大减少了数据冗余?

On maximum power point tracking control strategy for variable speed constant frequency wind power generation

Based on the characteristic of AC-excited variable speed constant frequency(VSCF)wind power generation,the vector control technique was applied in a doubly fed induction generator(DFIG).Maximum wind energy or maximum output power point can be tracked by decoupling control of active power and reactive power.The research result shows that the net power of generation system delivered to grid in maximum wind energy tracking mode is not the most.We presented a novel maximum power point tracking(MPPT)control strategy by analyzing the DFIG mathematic model and power relations which delivered the maximum power to the grid.The maximum power point could be tracked automatically without measuring wind speed in the control strategy and the control was independent of optimal turbine power curve,which had excellent dynamic and static performances and robustness.Simulation and experimental results testify the accuracy and validity of the control strategy.

Extended Quality Characterization of Grid Connected PV Inverters

The overall performance of photovoltaic （PV） inverter imphes many different technical issues.One of the key criterias is based on the measurement of the conversion and the maximum power point tracking （MPPT） efficiency and its applicable evaluation in practice.Intense work has been done in the last few years to formulate applicable standards for measuring static and dynamic efficiencies worldwide.Besides that,this work is presenting on novel methods of analysis on non-trivial system characteristics impacting the final evaluation on the overall performance of the PV inverter.The elaborated testing procedures for complex system behavior under highly nonlinear conditions （unintentional partial shading, mismatching of DC strings） are explained and characterized.With the help of experimental results, the exclusive impact on the overall efficiency is illustrated and helpful statements are given on the resulting technical characteristics of MPP strategies.

AUTOMATIC SEARCHING OF CONTROL POINT IN NOAA AVHRR IMAGE

This paper discusses the approaches for automatical searching of control points in the NOAA AVHRR image on the basis of data rearrangement in the form of latitude and longitude grid. The vegetation index transformation and multi-level matching strategies have been proven effective and successful as the experiments show while the control point database is established.

Improved VSVPWM Modulation Method for Three-level NPC Inverter in Rural Power Grid

With the acceleration of agricultural electrification,a lot of nonlinear and shock loads appear in the rural power grid,and the resulting harmonic and reactive currents pollute the rural power grid more and more seriously.To solve the above problem,three-level neutral point clamped(NPC)inverters have been widely used,but their development is greatly restricted by the defect of neutral point voltage imbalance.In this paper,an improved virtual space vector pulse width modulation(VSVPWM)was proposed.Firstly,the mathematical models of various space vectors were established,and the influence of various space vectors on neutral point voltage was analyzed.The sum of the vector current at the neutral point was zero and the voltage control at the neutral point was completed by.introducing the time offset into different switching times of the redundant small vector.This method was simple in design and avoided the redundant calculation of the traditional VSVPWM method and tedious switch sequence design.This balancing control strategy could greatly reduce the influence of virtual vectors on neutral point voltage and effectively control the low-frequency oscillation of neutral point voltage.The validity of the method was verified by establishing a matlab simulation model.

A new approach of extracting vegetation points from urban airborne LiDAR data

Urban vegetation has been an important indicator for the evaluation of eco-cities, which is of great significance to promote eeo-city construction. We study and discuss the commonly used urban vegetation extrac-tion methods. The extraction of vegetation points in this study is completed through mathematical statistics, mean-square error, successive differences and iterative algorithm which are based on the analysis of different spatial morphological characteristics in urban point clouds. Linyi, a city of Shandong Province in China, is se-lected as the study area to test this method and the result shows that the proposed method has a strong practicali- ty in urban vegetation point cloud extraction. Only 3D coordinate properties of the LiDAR point clouds are used in this method and it does not require additional information, for instance, return intensity, which makes the method more applicable and operable.

基于法线微分的3维声呐点云自适应简化方法

在不损失原始点云数据质量的前提下,大幅约简点云数据量是减少存储空间、降低后期计算强度的重要预处理步骤。针对这一需求,提出了针对水下3维声呐点云数据的自适应简化方法。首先,定义法线微分算子来识别点云中几何尺度的骤变,从而实现原始点云中边界部分点云和主体部分点云的分割。其次,对于点云的边界部分,应用移动最小二乘法来对边界点进行优化,降低噪点的影响,并保持其曲面的几何一致性;基于体素栅格结构,在边界上使用八叉树进行降采样,并在此基础上实施局部最远点采样,在实现均匀简化的同时保证已简化点云的边界部分具有各向同性,有效保留边界部分点云的几何特征信息。再次,对于点云的主体部分,为保持简化后点云整体的各向同性,使用体素中心采样法来减少数据量。然后,通过高斯滤波平滑点云表面,最后,整合简化后的边界点云和主体点云,得到简化结果。实验结果表明,提出的简化方法计算成本低、处理速度快,在与现行典型算法保持一致简化率的情况下,对水下点云数据的简化速度提高了约32%。另外,通过表面密度对比与几何失真分析,证明了提出方法对水下3维点云边界点及整体分布的优化作用。综上,此方法能提高水下作业目标探测效率,得到保留重要几何特征信息并具有各向同性的水下任务目标点云简化结果。

融合角点检测的点云配准研究

为提高点云配准效率,提出一种基于点云曲率信息的Harris角点提取算法,通过引入曲率约束,对传统Harris角点提取做出改进;计算每个点的曲率值并与整幅点云的平均曲率作比较,保留曲率值大于平均曲率的点云,实现对配准价值较低的点的剔除,为后续点云配准减少计算量;构建所提取角点之间的特征匹配,结合采样一致性(sample consensus initial alignment, SAC-IA)粗配准和正态分布变换(normal distributions transform, NDT)精配准,寻找最优的变换矩阵,实现源点云和目标点云的重合。通过比较不同算法在公开数据集上进行实验验证,结果表明该方法对复杂点云、多拐点点云都有较好的表现,对初始位置相差较大的点云也有良好的适用性。

非结构化网格下海洋流场的特征提取与种子点选取算法

对于非结构化网格流场数据,现有研究存在不能定位流场中临界点的具体位置、无法对临界点精细分类以及缺乏适用于非结构化网格的种子点选取算法等问题。针对上述问题,基于非结构化网格流场数据,分别在临界点提取和种子点选取方法上进行改进创新。提出非结构化网格中临界点的定位及分类方法,通过庞加莱指数法判断存在临界点的三角网格。构造质心迭代法定位临界点在网格中的准确位置,并设计三角网格内雅克比矩阵的构造方法,将临界点精细分类。基于非结构化网格提出基于最大得分和网格密度的种子点选取算法,先比较相邻格点的标量值大小来计算每个格点的得分,形成“最大得分”标量场,再按照网格密度动态设置阈值,将得分大于阈值的格点选为种子点,接着以种子点为起始点生成流线,生成的流线可以表达出流场的关键特征与全局信息。基于多个海域流场数据的实验结果表明,临界点分类的准确率可达99%以上,证明了临界点提取算法的准确性以及种子点选取算法对提升流场可视化效果的有效性。