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公斤级共轴反桨无人直升机 F-120","F-120 无人直升机是北航技术团队自主研发的多用途无人直 升机。该机型最大起飞重量 130kg，最大航时 2 小时，在可靠性 连续测试中，其 MTBF（连续无故障时间）可达到 7 小时。该机于 2010 年完成设计，拥有独创的水冷散热系统、气动与冷却的融合 设计、采用体积小，重量轻，振动小的转子发动机等多项先进领 先技术。该无人机可以执行海面、湖面、高海拔地区等复杂环境 的超视距飞行任务，应用领域广泛，包括对地侦查\u002F观测、电力\u002F — 26 — 管道巡检、数据\u002F中继通信、农业\u002F林业测绘、航空测绘\u002F摄影、 警用反恐\u002F防暴等多个领域。 该无人机经试验改进，以其优异的气动效率、重量效率、续 航能力及操稳特性受到农业部和航空植保企业的高度重视，在农 用无人机领域是目前国内载荷最大、性价比最高的无人直升机。 该机喷药 40 亩农田只需 15 分钟，是传统小型无人直升机作业效 率的 3 倍以上，符合我国精准农业、规模化经营的发展趋势。 — 27 — 技术描述： 技术状态： 产品已经完成开发定型，多次执行舰载机起降模拟应答飞行 测试、内蒙古公安反恐抓捕演习、江西核工业测绘院探矿任务、 火箭军某师通信中继任务等多项高难度、高风险的飞行任务，获 得了合作方一致认可。目前已交付用户 10 余架。已获发明专利 18 项，实用新型专利 6 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本项目研制了面向森林灭火、医疗救援、地震搜救、山区救 援、海上搜救等协同训练的智能虚拟现实仿真系统，系统由多台 支持协同任务的多功能应用端组成，支持救援任务场景的快速构 建，并支持飞行员、救援人员等多个角色共同模拟直升机应急救 援任务过程，支持教员实时对任务过程进行评估。 — 13 — 技术描述： 1．系统组成 1）任务想定子系统 任务想定子系统实现了应急救援任务初始化编辑的组件化 技术，通过调用基础资源库中的场景、角色、装备、建筑、触发、 环境 5 大类，共计百余个组件，能快速实现任务脚本的编辑。 2）导教控制子系统 导教控制子系统能够对仿真环境中的环境变量、直升机能力 数据、任务信息等进行实时的全局调整，可以对训练系统做出需 — 14 — 要的改变，用以模拟实际情况中的随机因素，实现对机组人员进 行实时的考核与训练，提高被训练者应对突发情况的反应能力与 思考能力。 3）任务程序评估子系统 任务程序评估子系统用以对任务流程中的关键节点进行自 动或手动的打分，实时监控任务的进行情况，并对任务角色和任 务目标进行相应的观察判断。 4）协同任务训练器子系统 协同任务训练器子系统包含直升机应急救援任务中的机长、 副驾驶、操作员等多种任务角色应用端，支持多机型、多人员利 用任务训练器进行协同训练完成救援任务，基于最新的虚拟现实 技术，实现沉浸式的高逼真度救援任务训练。 2．典型应用场景 1）直升机森林灭火任务程序训练 针对直升机森林灭火的任务特点及训练点，基于系统各类组 件及子系统快速构建，能够进行森林灭火任务中的机长、副驾驶、 操作员协同任务训练及评估。 2）直升机医疗救援任务程序训练 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线、功放、低噪放、基带装置和视频采集装置。该设备关键技术突破 了直升机旋翼阻断通信链路的技术瓶颈，在 Ku 频段静止轨道卫星链 路，可支持传输速率不低于 1Mbps 的数据传输（支持 H.265 高清视 频传输），特别适用于人迹难至区域有视频快速回传需求的场景，如 森林救火、抗灾救援和全局勘测等。 （三）关键技术 直升机旋翼遮挡因素分析。直升机旋翼对卫星通信信号周期性的 遮挡会造成通信链路阻断，遮挡时长直接影响链路通信质量，因此， 对旋翼遮挡的因素进行分析是解决通信链路阻断的前提。 高动态环境下的信号增益控制与同步方法。正常情况下，直升机 — 92 — 由于旋翼遮挡或者姿态调整，都会导致卫星通信信号的强度存在大动 态的变化。针对这个问题，本项目针对性地提出高动态场景下通信信 号的自动增益控制方法和载波、定时同步环路方法。 极低解调门限的差错控制编码方法。直升机旋翼毫秒级的信号发 射窗口，决定了机载卫星通信终端只能采用较短码长的差错控制编码 方法。为实现系统的极低解调门限，本项目采用短码长低码率的低密 度奇偶校验（LDPC）编码方案。考虑到直升机旋翼可能带来的不利 遮挡，本项目还结合喷泉码的技术特点，实现信号的可靠传输。 基带信号波形与调制解调方案。基带信号波形与调制解调是通 信系统必不可少的功能单元，前者决定了通信信号的频谱结构，后者 则直接会影响通信系统的抗噪声性能。针对直升机旋翼遮挡，收发系 统频偏、信号带宽以及视频信息传输等多种因素，本项目设计抗遮挡 的信号波形。 □概念验证 □原理样机 工程样机 □中试 □产业化 合作方式： 联合研发 技术入股 □转让 □授权（许可）面议 — 93 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市与森林防火、管线巡查、国土普查、地质灾害监控等多方面。","西安工业大学","2026-10-09T19:27:16.363Z",[1235,1236,1237,1238,1239,1240,1241,1242],{"code":65,"name":66},{"code":108,"name":109},{"code":184,"name":185},{"code":250,"name":251},{"code":354,"name":355},{"code":721,"name":722},{"code":859,"name":860},{"code":945,"name":946},[66,109,185,251,355,722,860,946],{"resultType":1085,"id":1245,"title":1246,"abstract":1247,"orgName":1248,"province":1202,"date":1249,"trl":815,"transferMode":1250,"keywords":1093,"industry":1251,"patentType":13,"legalStatus":13,"isOpenLicense":1094,"isRevitalized":1094,"techMaturity":13,"starRating":13,"licenseFeeText":13,"patentNo":13,"ipc":13,"inventors":13,"tags":1252,"tagNames":1260},"cmv1bi45e00h3bdd8bouwhabi","知识森林 AR 交互系统","知识森林AR交互系统是国家重点研发计划项目“教育大数据分析挖掘技术及其智慧教育示范应用”（2018YFB1004500）支持下完成的成果。该工具把一门课程的知识按照层次化、主题化的形式组织成“树叶-树木-森林”形式，并支持 AR 交互。其中，树木对应一个知识点；例如，图1是“堆栈”的分面树。树叶对应知识点上的知识碎片。将不同的知识点树木按照认知关系连接起来，形成知识森林。例如，图2是“数据结构”课程的知识森林（局部）。知识森林能够在不同粒度上展示课程中知识点以及每个知识点中知识碎片，符合人类整体到局部的认知特点。图1 “堆栈”分面树图2 “数据结构”课程的知识森图3是知识树AR交互场景林（局部）我们采用自然语言处理、图像识别等人工智能技术以及AR\u002FVR技术突破了知识森林自动构建、可视化交互等难题，研制了知识森林AR交互系统。图3是知识树的AR交互场景。","西安交通大学","2026-10-09T19:27:13.730Z","面议","人工智能与大数据",[1253,1254,1255,1256,1257,1258,1259],{"code":213,"name":214},{"code":226,"name":227},{"code":292,"name":293},{"code":354,"name":355},{"code":859,"name":860},{"code":929,"name":930},{"code":1035,"name":1036},[214,227,293,355,860,930,1036],{"resultType":1085,"id":1262,"title":1263,"abstract":1264,"orgName":1248,"province":1202,"date":1265,"trl":437,"transferMode":1250,"keywords":1093,"industry":1251,"patentType":13,"legalStatus":13,"isOpenLicense":1094,"isRevitalized":1094,"techMaturity":13,"starRating":13,"licenseFeeText":13,"patentNo":13,"ipc":13,"inventors":13,"tags":1266,"tagNames":1277},"cmv1bi41v00edbdd86zoz60af","宏星遥感大模型","现有的遥感影像人工标注样本效率低，而且数据数量、质量、空间分辨率参差不齐。且往往在局部区域采样，缺乏多样性和变异性，使得训练得到的模型难以扩展到全球尺度。因此，遥感的专业大模型要发展，应该让专业的大模型做专业的事，“不能有了ChatGPT，所有的需求都要泛化”。同时，大模型的泛化一定存在一个临界点，不能持续泛化。宏星遥感图像解译人工智能大模型（简称宏星大模型）具有卫星或无人机航拍遥感图像自动解译，遥感数据变化分析、特定目标检测与跟踪等智能化功能。首先，它通过对遥感图像的像素级精准分割，准确识别并标注出道路、建筑、绿地、河流、农田、森林等区域，输出的智能化数据对各种下游工作，如地图制作、国土资源测绘、城市与行业规划设计等，具有极高的应用价值。其次，宏星大模型能够实时解译出同一个地区在不同时间节点的遥感数据图斑变化情况，可以为土地违规使用检测与执法、环境破坏检测与执法、自然灾害范围检测与损失估计等工作提供客观的证据。另外，宏星大模型还具有自动检测、识别与跟踪特定目标的功能，如飞机、军舰、坦克、大炮、林火等，可广泛应用于军事情报分析、交通流量分析、灾害检测与预警等各种检测与跟踪任务。","2026-10-09T19:27:13.592Z",[1267,1268,1269,1270,1271,1272,1273,1274,1275,1276],{"code":65,"name":66},{"code":177,"name":178},{"code":184,"name":185},{"code":213,"name":214},{"code":226,"name":227},{"code":298,"name":299},{"code":354,"name":355},{"code":678,"name":679},{"code":868,"name":869},{"code":1035,"name":1036},[66,178,185,214,227,299,355,679,869,1036],30,{"list":1280,"total":1293,"page":100,"pageSize":100,"totalPages":1293},[1281],{"id":1282,"name":1283,"orgName":1284,"school":13,"gender":13,"title":13,"degree":13,"honor":1285,"position":1286,"researchDirection":1287,"intro":1288,"province":13,"completeness":155,"avatarAuthorized":1094,"sourceUrl":1289,"nameValid":1290,"tags":1291,"tagNames":1292},"cmv7rhq670185hikyk9jek0tg","肖绪文","中国建筑股份有限公司","ACADEMICIAN","中国建筑科技研发序列首席专家","绿色建造与施工技术方向","肖绪文，建筑工程专家，1953年4月生于陕西商洛，1977年毕业于清华大学。2013年当选中国工程院院士。现任中国建筑股份有限公司首席专家、技术中心顾问总工，兼任中国建筑业协会副会长。长期从事建筑施工、绿色施工与绿色建造、信息化建造研究，主持完成数十项重大工程的设计与施工，主编《建筑施工手册》等专业著作，获国家科技进步二等奖多项，是我国建筑施工技术领域的学术带头人。","chaingraph:\u002F\u002F肖绪文",true,[],[],35218]