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雷达和船舶自动识别系统(AIS)是保证现代船舶航行安全的重要导航设备。针对1部雷达和1部AIS得到的目标航迹进行融合,提出1种基于模糊理论的雷达/AIS目标数据融合方法,采用模糊数学中的正态隶属函数法来进行航迹相关,数据融合则采用参数加权方法,并将融合后数据进行多项式拟合,用以提高导航数据信息的精度与可靠性。通过仿真实例验证了此方法的可行性与有效性。 相似文献
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针对现有无人水面艇(Unmanned Surface Vehicle,USV)在航行过程中感知周围航行目标时出现的数据源单一、数据延迟、数据丢失等问题,提出一种基于USV搭载的航海雷达和全球定位系统(GPS)数据源的USV海上航行目标感知数据融合方法。基于最小误差法提出雷达原始图像数据解析算法,并采用数据剔除、时间空间统一方法完成对目标数据预处理,构建基于欧氏距离和马氏距离的航迹关联算法模型、基于层次分析法(Analytic Hierarchy Process,AHP)和专家评价法的融合数据权重分配模型。同时,开展USV试验研究,验证整体融合方法。结果表明,目标原始数据预处理方法合理可靠,融合算法稳定可信,可为USV海上航行目标感知、安全航行及快速避碰提供技术和算法支持。 相似文献
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随着大数据、物联网和人工智能技术的发展,近几年自主航行船舶(无人船)研究成为行业研究的热点.MUNIN项目是最早研究无人商船的项目[1-3],该项目研究并验证了自主航行商船的概念和可行性.MUNIN项目引起了多方对自主航行船舶的广泛关注.挪威建立了世界上第一个自主航行船舶测试区,成立了自主航行船舶论坛NFAS[4].Rolls-Royce公司公布了由其引领的"高级无人驾驶船舶应用开发计划"(AAWA)项目[5-6]研究无人船舶,主要研究感知系统(Intelligence System),近期在挪威开展了自主航行船舶的测试[7].Kongsberg公司已经完成了自主航行船舶的水池测试,并且与氮肥料厂商合作开发一条自主航行船Yara Birkeland[8],并与挪威航运巨头威尔森集团成立了自主航行船公司Massterly[9]. 相似文献
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为了实现船舶安全航行,有效解决船舶自动识别系统(AIS)和自动雷达标绘仪因价格昂贵很难大范围普及安装,以及现在激光测距预警系统只能根据预警距离的大小进行非智能化预警的问题,本文基于激光测距、激光定位、激光测速原理设计了一种船舶防撞装置。利用激光传感器获取相对距离、方位角度、相对速度等参数,合理的选择设备和设计安装位置,通过组装调试、可靠性及抗干扰性分析等不同步骤,设计船舶防撞自动分析控制程序,该装置能够自主的感知周围可疑障碍船只或不明物体,并根据不同情况自主的分析判断预警并发出预警信号。系统依托较高的性价比,有利于提高防撞系统在中小型船只中的普及。 相似文献
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The NW Mediterranean experiences, as illustrated by the last decade, strong and rapidly varying storms with severe waves and winds. This has motivated a continuous validation of models and the efforts to improve wave and wind predictions. In this paper we use two atmospherics models, MASS (from SMC-Meteorological Office of Catalunya) and ARPEGE (from Météo-France), to force two third generation wave models: WAM and SWAN. The evaluation and comparison has been carried out for two severe storms registered in November 2001 and March–April 2002.The ARPEGE and MASS models predicted higher 10 m wind speeds than coastal meteorological stations, a fact attributed to local land influences. Regarding the 10 m wind direction, models do not present large differences, although considerable deviations from recorded data were found during some dates. ARPEGE presents less scatter and lower errors than MASS when compared with QuikSCAT data.The 10m wind fields from both atmospheric models were used to force the two selected wave models and analyse the errors and sensitivities when predicting severe wave storms. The wave model simulations show some interesting results; during the storm, the spatial wave pattern using ARPEGE showed a higher maximum, although the values of significant wave height at the buoys were lower than the ones forced by MASS (with both WAM and SWAN). The SWAN simulations show a better agreement in predicting the growing and waning of the storm peaks. The prediction of mean period was improved when using the ARPEGE wind field. However the underestimation by SWAN due to the large energy at high frequencies was evident. Validation of spectral shape predictions showed that it still has considerable error when predicting the full frequency spectra. The storms showed bimodal spectral features which were not always reproduced by wave models and are likely to be responsible for part of the discrepancies. 相似文献
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设计了一种利用推力传感器测量舰船推力轴承块的压力进而计算出螺旋桨推力的装置.其设计包括系统结构设计和系统电磁兼容性设计.系统整体结构包括推力传感器(感测推力大小,转换成电信号;其中4只测量正车推力,2只测量倒车推力)、传感器级联箱(信号传输及偏载误差调整)和推力显示仪(数据采集和显示).系统采用整体电磁兼容性设计,抗干扰能力强、可靠性高.推力传感器采用轮辐式结构,突破了薄式小体积、高精度、大量程高过载、耐潮湿及长寿命等关键技术.推力显示仪针对舰船实际情况,实现了数据采集和实时监测功能,数据采集精度达0.2%等级.系统通过了船用环境试验及电磁兼容性试验,且裕量明显,能够安全、稳定、可靠地运行于舰船上. 相似文献
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