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经物理筛选与相似性去重，形成长尾事故场景数据库。本发明可构建数量丰富且多样化的长尾事故场景数据库，提升自动驾驶汽车对长尾事故的适应能力与行驶安全性，助力其产业化落地。","2026.08.28#公开;2026.09.15#实质审查的生效;2026.09.29#授权","CN202611107354.5","G06N3\u002F094;G06N3\u002F098;G06F18\u002F15;G06F18\u002F214;G06F18\u002F24;G06F18\u002F213;G06F18\u002F25","赵健;李文旭;朱冰;张培兴;黄殷梓",[],[],{"resultType":8,"id":79,"title":80,"abstract":81,"orgName":82,"province":13,"date":14,"trl":15,"transferMode":15,"keywords":15,"industry":15,"patentType":16,"legalStatus":83,"isOpenLicense":18,"isRevitalized":19,"techMaturity":15,"starRating":15,"licenseFeeText":15,"patentNo":84,"ipc":85,"inventors":86,"tags":87,"tagNames":88},"gpi2_0892","一种多阶段漏洞挖掘与威胁溯源方法及系统","一种多阶段漏洞挖掘与威胁溯源方法及系统，涉及网络安全技术领域。解决了攻防演练中现有技术使用的工具之间数据孤立、全量日志扫描资源浪费、测试引导缺乏战术视角的问题。所述方法包括：获取隔离沙箱中的系统调用日志和权限变更日志，进行语义分析得到测试用例；执行测试用例；提取系统调用序列，生成攻击原语第一阶段记录；从全量日志中检索全量日志子集；通过图神经网络进行二分类得到攻击路径候选集，生成攻击原语第二阶段记录；从攻击原语第二阶段记录中提取关键实体，检索情报，将攻击路径、检索情报和MITRE ATT&CK映射结果拼接为推理上下文；生成攻击者画像，标记未覆盖的测试盲区，生成攻击原语第三阶段记录，并将所述测试盲区写入盲区列表。","华易数安科技(吉林省)有限公司","2026.08.25#公开;2026.09.11#实质审查的生效;2026.09.29#授权","CN202611122166.X","H04L9\u002F40;G06N5\u002F04","朱琳;李佳桐;李忆平;宋涛;李雷;王宪辉;刘洋;陈兴钰;姜洋;李志权",[],[],{"resultType":8,"id":90,"title":91,"abstract":92,"orgName":93,"province":13,"date":14,"trl":15,"transferMode":15,"keywords":15,"industry":15,"patentType":16,"legalStatus":94,"isOpenLicense":18,"isRevitalized":19,"techMaturity":15,"starRating":15,"licenseFeeText":15,"patentNo":95,"ipc":96,"inventors":97,"tags":98,"tagNames":99},"gpi2_0275","一种大豆种子缺陷检测模型的构建方法","一种大豆种子缺陷检测模型的构建方法，涉及种子检测领域。解决了现有用于大豆种子检测的模型缺乏对智能精选过程中多目标密集分布、局部接触与局部遮挡条件下的处理能力，容易发生漏检与类别混淆的问题。所述构建方法包括：采集包含大豆种子的原始图像，对所述原始图像进行筛选和类别标注，并按比例划分为训练集、验证集和测试集，得到原始图像数据集；对原始图像数据集进行离线数据增强，得到最终数据集；从最终数据集中读取批量图像进行在线数据增强；将在线数据增强后的训练图像输入至SWDSoybeanNet模型中，计算损失函数并更新模型参数，得到训练后的SWDSoybeanNet模型。本发明所述的方法还可应用于玉米、麦穗、花生等其他作物种子的检测。","吉林农业大学","2026.08.21#公开;2026.09.08#实质审查的生效;2026.09.22#授权","CN202611098855.1","G06V20\u002F60;G06V10\u002F44;G06V10\u002F774;G06V10\u002F776;G06V10\u002F82;G06N3\u002F0464;G06N3\u002F08","于合龙;李延松;石磊;吕肇聪;郭靖",[],[],{"resultType":8,"id":101,"title":102,"abstract":103,"orgName":104,"province":13,"date":14,"trl":15,"transferMode":15,"keywords":15,"industry":15,"patentType":16,"legalStatus":83,"isOpenLicense":18,"isRevitalized":19,"techMaturity":15,"starRating":15,"licenseFeeText":15,"patentNo":105,"ipc":106,"inventors":107,"tags":108,"tagNames":109},"gpi2_0778","一种结构视觉监测中的伪位移识别与数据有效性判定方法","本发明属于光学计量与图像处理技术领域，尤其涉及一种结构视觉监测中的伪位移识别与数据有效性判定方法，包括如下步骤：S1：获取监测图像序列、稳定参考区域和辅助状态信息；S2：提取监测测点位移、图像质量和多源状态特征；S3：构建多维一致性指标；S4：判断多维一致性指标是否满足真实结构形变判据；S5：根据可信度和异常类型生成数据有效性等级，并控制数据是否参与安全预警；S6：存储原始图像、伪位移标签、处置过程、最终位移和有效性等级，返回持续监测。本方案能通过联合分析图像、空间、时间、结构、波段及设备状态信息，识别伪位移来源并执行差异化处置，最终输出带有效性等级的结构形变数据。","中国科学院长春光学精密机械与物理研究所","CN202611136668.8","G06F18\u002F20;G06F18\u002F2433;G06T7\u002F246;G06V10\u002F98;G01M11\u002F00;G01C11\u002F04;G01B11\u002F16","孙健维;刘帅凝;宋来运;袁东明;刘学吉",[],[],{"resultType":8,"id":111,"title":112,"abstract":113,"orgName":114,"province":13,"date":14,"trl":15,"transferMode":15,"keywords":15,"industry":15,"patentType":16,"legalStatus":115,"isOpenLicense":18,"isRevitalized":19,"techMaturity":15,"starRating":15,"licenseFeeText":15,"patentNo":116,"ipc":117,"inventors":118,"tags":119,"tagNames":120},"gpi2_0210","一种脑部表面点云重建方法、电子设备及存储介质","本发明属于医学影像处理技术领域，尤其为一种脑部表面点云重建方法、电子设备及存储介质。包括以下步骤：S1：获取样本集，所述点云标签用于指示对应的三向正交MRI切片样本的真实表面特征点云；S2：构建神经网络框架；S3：采用多重几何损失函数训练所述神经网络框架，所述损失函数包括Chamfer距离、改进Hausdorff距离和法向一致性损失；S4：将待重建的三向正交MRI切片输入训练完成的框架，输出包含2048个点的脑部表面点云。本发明利用基于深度学习的脑部表面点云重建模型对三向正交MRI切片图像进行处理，能够充分联合利用多视图MRI数据，有效发掘不同解剖平面之间的潜在空间关联，从而显著提升重建效果和临床适用性。","长春理工大学","2026.08.18#公开;2026.09.04#实质审查的生效;2026.09.18#授权","CN202611097197.4","G06T17\u002F00;G06N3\u002F042;G06N3\u002F0455;G06N3\u002F0464;G06T7\u002F50;G06T19\u002F00;G06V10\u002F70;G06V10\u002F80;G06V10\u002F82","赵家石;王文豪;方旭;程新异;申秀贤;田浩;梁世奇",[],[],{"resultType":8,"id":122,"title":123,"abstract":124,"orgName":51,"province":13,"date":14,"trl":15,"transferMode":15,"keywords":15,"industry":15,"patentType":16,"legalStatus":94,"isOpenLicense":18,"isRevitalized":19,"techMaturity":15,"starRating":15,"licenseFeeText":15,"patentNo":125,"ipc":126,"inventors":127,"tags":128,"tagNames":129},"gpi2_0947","一种自平衡可变姿态可回收锚固装置","本发明公开了一种自平衡可变姿态可回收锚固装置，属于海洋工程锚固装备技术领域，包括自平衡螺旋桨系统、变向系统、持力增强系统、动力系统和自平衡双钻头系统；持力增强系统由第一持力增强系统和第二持力增强系统组成；自平衡螺旋桨系统用于提供推进力或回收升力；变向系统用于在锚固装置完成钻进锚固后，使变向关节一上部连接的结构能够随缆绳受力方向相对于下部锚固装置偏转；持力增强系统用于在锚固装置钻进至目标土层后向外展开并与周围土体形成相互作用；动力系统用于提供可控的轴向自给进补偿推力；自平衡双钻头系统用于通过内钻头和外钻头的协同反向旋转对目标土层进行破土和排土。","CN202611114407.6","B63B21\u002F26;B63B21\u002F50","高科;袁井泉;赵研;于永平;王治刚;贾瑞;谢晓波;李旭;闻育民;张丛珊;刘奥;刘松赫",[],[],{"resultType":8,"id":131,"title":132,"abstract":133,"orgName":134,"province":13,"date":14,"trl":15,"transferMode":15,"keywords":15,"industry":15,"patentType":16,"legalStatus":135,"isOpenLicense":18,"isRevitalized":19,"techMaturity":15,"starRating":15,"licenseFeeText":15,"patentNo":136,"ipc":137,"inventors":138,"tags":139,"tagNames":140},"gpi2_0463","一种轨道车辆冷弯型钢矫平处理工艺","本发明为一种轨道车辆冷弯型钢矫平处理工艺，涉及冷弯型钢矫平处理技术领域，解决了上矫平辊和下矫平辊之间辊缝磨损补偿效果差的技术问题，包括原材料准备与分条，选取冷轧高耐候钢板作为原材料，辊压冷弯成型，将分条后的条料送入冷弯成型机组的开卷机上，将条料依次通过成型模具，按照先矫平、后逐道次横向弯曲的顺序进行辊压成型，辊缝在线补偿矫平，在矫平作业过程中，实时监测下矫平辊表面磨损状态，四个下矫平辊各自升高与磨损量对应的不同高度，恢复与上矫平辊之间的原始辊缝，本发明通过在下矫平辊因磨损导致上矫平辊和下矫平辊间辊缝增大时，驱动四个下矫平辊同步上升，自动补偿辊缝增量，可实时响应磨损变化，无需停机调整。","长春市新金享冷弯型钢有限公司","2026.08.18#公开;2026.09.04#实质审查的生效;2026.09.25#授权","CN202611092195.6","B21D1\u002F02;B21D43\u002F09","温杰;温博阁",[],[],{"resultType":8,"id":142,"title":143,"abstract":144,"orgName":51,"province":13,"date":14,"trl":15,"transferMode":15,"keywords":15,"industry":15,"patentType":16,"legalStatus":145,"isOpenLicense":18,"isRevitalized":19,"techMaturity":15,"starRating":15,"licenseFeeText":15,"patentNo":146,"ipc":147,"inventors":148,"tags":149,"tagNames":150},"gpi2_0381","一种轨道车辆管接头松动检测方法及系统","本发明公开了一种轨道车辆管接头松动检测方法及系统，属于轨道交通车辆管接头检测领域；该方法包括：局部姿态解耦，检测管接头结构特征并建立局部坐标系、估计局部变换；标记线骨架提取，提取防松标记线候选区域并骨架化得到待检测标记线轨迹和模板标记线轨迹；同源轨迹比较，根据接缝边界划分固定侧、活动侧及跨缝邻域段，将模板标记线轨迹映射为参考标记线轨迹，计算与待检测标记线轨迹的接缝偏差特征；松动判定输出，根据接缝偏差特征及配准可信度计算松动风险评分，输出管接头状态结果。通过模板图像同源参照、局部坐标系消除视角偏差、曲线拓扑结构表征防松标记线，区分画线不规范与真实松动，避免误报和漏报，提升检测准确性和鲁棒性。","2026.08.18#公开;2026.09.04#实质审查的生效;2026.09.15#授权","CN202611091071.6","G06T7\u002F00;G06V10\u002F75;G06V10\u002F34;G06V10\u002F40;G06V10\u002F26;G06T7\u002F136;G06T5\u002F70;G06T5\u002F92","蒋尚佑;田海龙;李鑫;陈晓彬;李修昱",[],[],{"resultType":8,"id":152,"title":153,"abstract":154,"orgName":51,"province":13,"date":14,"trl":15,"transferMode":15,"keywords":15,"industry":15,"patentType":16,"legalStatus":62,"isOpenLicense":18,"isRevitalized":19,"techMaturity":15,"starRating":15,"licenseFeeText":15,"patentNo":155,"ipc":156,"inventors":157,"tags":158,"tagNames":159},"gpi2_0652","一种轮速缺失下双驱动桥电动商用车转矩协调控制方法","本发明适用于电动商用车驱动转矩协调控制技术领域，提供了一种轮速缺失下双驱动桥电动商用车转矩协调控制方法，包括：获取车辆状态信息；利用驱动桥电机转速折算得到轮边等效转速，利用前桥左、右轮速计算车辆基准车速，构建驱动桥滑转率；建立驱动桥地面驱动力估计模型，通过滚动窗口法拟合得到局部斜率，并确定滑转状态；根据滑转状态对参考滑转率和轮边可传递转矩上限进行更新或保持；根据中、后桥滑转状态组合对驾驶员需求轮边驱动转矩进行分配与约束；对过度滑转的驱动桥进行防滑转矩修正；生成并输出目标驱动转矩。本发明实现了桥间驱动转矩的合理分配与过度滑转抑制，适用于部分驱动桥未配备轮速传感器的双驱动桥电动商用车。","CN202611141180.4","B60L15\u002F20;B60L15\u002F32","管欣;薛鹏程;詹军;卢萍萍;田培华;丁淼;杨利国;吴楠;徐国彭",[],[],{"resultType":8,"id":161,"title":162,"abstract":163,"orgName":164,"province":13,"date":14,"trl":15,"transferMode":15,"keywords":15,"industry":15,"patentType":16,"legalStatus":165,"isOpenLicense":18,"isRevitalized":19,"techMaturity":15,"starRating":15,"licenseFeeText":15,"patentNo":166,"ipc":167,"inventors":168,"tags":169,"tagNames":170},"gpi2_0738","偶极子阵列的电磁波相控阵聚焦能量调控方法及系统","本发明涉及相控阵聚焦调控领域，更具体地，本发明公开了一种偶极子阵列的电磁波相控阵聚焦能量调控方法及系统。首先基于医学影像数据及生物组织弛豫参数，构建反映非线性色散特性的宽带复频域介电属性空间分布，基于局部空间信息熵特征的动态边界平滑，抑制影像伪影导致的参数突变，获得修正后的介电属性分布。以此分布通过强制反相替换静态电导率引入虚拟负热力学耗散因子，在目标靶区注入激励并进行拟逆向电磁演化，从而自靶区反向推算抵达各辐射端口截面的波前信息，得到用于精确控制相控阵各辐射通道的延迟相位补偿量与能量分配权重系数。该方法能有效提升对生物组织深部靶区的能量聚焦精度与效率。","吉林省众驰医疗科技有限公司","2026.08.25#公开;2026.09.11#实质审查的生效;2026.09.22#授权","CN202611131805.9","A61N5\u002F00;A61N5\u002F02;G16H20\u002F30;G16H40\u002F60","姜新;王身云;高杨;刘忠刚;李超贵",[],[],{"resultType":8,"id":172,"title":173,"abstract":174,"orgName":104,"province":13,"date":14,"trl":15,"transferMode":15,"keywords":15,"industry":15,"patentType":16,"legalStatus":62,"isOpenLicense":18,"isRevitalized":19,"techMaturity":15,"starRating":15,"licenseFeeText":15,"patentNo":175,"ipc":176,"inventors":177,"tags":178,"tagNames":179},"gpi2_0655","基于GaNFET的高速紫外单光子探测器淬灭复位电路及方法","本发明涉及单光子探测技术领域，尤其涉及一种基于GaNFET的高速紫外单光子探测器淬灭复位电路及方法。电路包括淬灭复位模块、TIA跨阻放大模块、比较器整形模块、FPGA主控、数模转换模块及电源模块；淬灭复位模块由SPAD、氮化镓场效应管、第一电容及两只分压电阻构成两级淬灭结构，TIA模块并联RC相位补偿支路抑制环路振荡，比较器输出端配置差分匹配电阻消除信号反射；FPGA分别控制氮化镓场效应管与两路数模转换器，数模转换器调控电源输出两路独立可调高压，分别为SPAD提供静态偏压、为淬灭开关提供淬灭电压。优点在于：实现纳秒级快速淬灭复位；有效减小了单光子探测的死时间，提高了计数率与探测效率。","CN202611139916.4","G01J1\u002F44;G01J1\u002F42;H03K17\u002F22;H03K17\u002F081;H03K17\u002F687","黎大兵;朱虹宇;蒋科;隋延林;陈一仁;孙晓娟",[],[],{"resultType":8,"id":181,"title":182,"abstract":183,"orgName":104,"province":13,"date":14,"trl":15,"transferMode":15,"keywords":15,"industry":15,"patentType":16,"legalStatus":72,"isOpenLicense":18,"isRevitalized":19,"techMaturity":15,"starRating":15,"licenseFeeText":15,"patentNo":184,"ipc":185,"inventors":186,"tags":187,"tagNames":188},"gpi2_0714","基于云边端协同的数字孪生系统性能预测与故障自愈方法","本公开涉及基于云边端协同的数字孪生系统性能预测与故障自愈方法，属于数字孪生领域，包括：在云端构建数字孪生体的全局性能预测模型；在边缘节点部署故障检测模块，采用自适应滑动窗口技术检测传感器数据流中的异常特征，并通过多尺度特征提取算法将异常特征与预测结果比对；建立端设备与边缘节点的双向认证通道；边缘节点识别故障特征，向端设备注入动态修复策略代码包；云端启动虚拟仿真引擎进行故障推演，采用蒙特卡洛树搜索算法生成若干种修复方案，进行仿真验证筛选最优修复方案；将最优修复方案通过区块链下发至边缘节点，采用差分更新机制同步至端设备进行修复；云端动态重构模型的损失函数。本公开的性能预测准确与故障自愈能力强。","CN202611144398.5","H04L41\u002F0654;H04L9\u002F40;H04L67\u002F10;H04L9\u002F32;H04L41\u002F14;H04L41\u002F147;H04L41\u002F149;H04L41\u002F16","赵伟超;孙鸽;齐翌辰;李泽",[],[],{"resultType":8,"id":190,"title":191,"abstract":192,"orgName":104,"province":13,"date":14,"trl":15,"transferMode":15,"keywords":15,"industry":15,"patentType":16,"legalStatus":83,"isOpenLicense":18,"isRevitalized":19,"techMaturity":15,"starRating":15,"licenseFeeText":15,"patentNo":193,"ipc":194,"inventors":195,"tags":196,"tagNames":197},"gpi2_0022","基于时空交互融合的双时相图像变化检测系统及方法","本发明涉及图像处理技术领域，尤其涉及一种基于时空交互融合的双时相图像变化检测系统及方法，首先生成双时相图像的伪视频序列，并对伪视频序列进行多尺度特征提取；对双时相图像的多尺度特征进行空间方向上的差异信息的提取与增强，得到对应尺度的空间特征；将时间特征进行时间方向上的聚合，再将聚合后的特征与空间特征进行融合和门控调制；对得到的时空融合特征进行频域和空域的增强；对得到的每种尺度的多维度增强特征进行逐级上采样解码操作，得到双时相图像的变化概率图。本发明通过时空特征双分支提取与增强机制，实现时序细节增强、空间精细定位与频率域干扰抑制的统一建模，提升复杂场景下变化检测的精度与可靠性。","CN202611120547.4","G06V20\u002F40;G06V10\u002F44;G06V10\u002F52;G06V10\u002F62;G06V10\u002F77;G06V10\u002F80;G06V10\u002F82;G06N3\u002F045;G06N3\u002F0455;G06N3\u002F0464;G06N3\u002F084;G06N3\u002F09","孙海江;郭超凡;刘巧元;陈周长",[],[],{"resultType":8,"id":199,"title":200,"abstract":201,"orgName":51,"province":13,"date":14,"trl":15,"transferMode":15,"keywords":15,"industry":15,"patentType":16,"legalStatus":83,"isOpenLicense":18,"isRevitalized":19,"techMaturity":15,"starRating":15,"licenseFeeText":15,"patentNo":202,"ipc":203,"inventors":204,"tags":205,"tagNames":206},"gpi2_0780","基于机器学习的减隔震桥梁震致残余位移预测方法及系统","本发明涉及基于机器学习的减隔震桥梁震致残余位移预测方法及系统，属于桥梁性能分析技术领域，解决现有预测方法成本高、速度慢、精度低的问题。首先获取减隔震桥梁基本信息及减隔震装置参数信息；建立减隔震桥梁在地震作用下的仿真模型；采用拉丁超立方抽样方法对表征参数进行抽样，并进行特征处理和仿真模型计算，构建特征参数‑震致残余位移样本集；基于样本集训练Stacking集成模型；采用训练后的Stacking集成模型预测减隔震桥梁的震致残余位移。本发明无需布设大量传感器，能够快速、准确地预测罕遇地震作用下的桥梁震致残余位移，具有成本低、速度快、精度高的优点，为桥梁抗震韧性评估和灾后快速鉴定提供了有效技术手段。","CN202611133281.7","G06F30\u002F27;G06F30\u002F23;G06F18\u002F27;G06F18\u002F214;G06F18\u002F213;G06N20\u002F00;G06F18\u002F25;G06F18\u002F21;G06N7\u002F01;G06N3\u002F0985;G06N3\u002F096;G06F18\u002F22;G06F18\u002F2433;G06N5\u002F01;G06F111\u002F04;G06F119\u002F14","顾正伟;刘朔宬;谭国金;吴春利;梁春雨;周培蕾;秦绪喜;艾永明;王文盛;何昕;都基委;赵鹤松;万肖音",[],[],{"resultType":8,"id":208,"title":209,"abstract":210,"orgName":211,"province":13,"date":14,"trl":15,"transferMode":15,"keywords":15,"industry":15,"patentType":16,"legalStatus":212,"isOpenLicense":18,"isRevitalized":19,"techMaturity":15,"starRating":15,"licenseFeeText":15,"patentNo":213,"ipc":214,"inventors":215,"tags":216,"tagNames":217},"gpi2_0357","基于电网时序约束的新能源消纳能力优化方法","本发明涉及电力系统技术领域，具体涉及一种基于电网时序约束的新能源消纳能力优化方法，通过获取电网运行的多源数据，并提取在不同时间尺度下的多源时序特征；基于在历史时间段内的多源时序特征，生成含多种场景在内的不确定性场景集合；基于未来预测时间段内在不同时间尺度下的多源时序特征，确定动态约束条件，并将不确定性场景集合代入以新能源弃电量最小和电网运行成本最低为目标的随机优化模型中进行求解，得到在不同时间尺度下的新能源消纳基础调度计划，并在不同新能源消纳基础调度计划之间进行限幅协同，获得最终的新能源消纳调节计划。本发明有效提升了调度计划应对极端波动的鲁棒性与跨时间尺度执行的平稳性。","国网吉林省电力有限公司经济技术研究院","2026.08.21#公开;2026.09.08#实质审查的生效;2026.09.29#授权","CN202611097399.9","H02J3\u002F466;H02J3\u002F28;H02J3\u002F175;G06F18\u002F15;G06F18\u002F20;H02J101\u002F24;H02J101\u002F28;H02J103\u002F30;H02J105\u002F52;G06F123\u002F02","杜秋实;孟繁波;时雨;姜明磊;吕长会;时圣尧;张圆美;王博闻;张文宝;谌骏哲;赵博;杨爽;张亮;柳禾丰;姚新光;张艳",[],[],{"resultType":8,"id":219,"title":220,"abstract":221,"orgName":51,"province":13,"date":14,"trl":15,"transferMode":15,"keywords":15,"industry":15,"patentType":16,"legalStatus":222,"isOpenLicense":18,"isRevitalized":19,"techMaturity":15,"starRating":15,"licenseFeeText":15,"patentNo":223,"ipc":224,"inventors":225,"tags":226,"tagNames":227},"gpi2_0650","基于自适应字典约束的面波频散三维层析成像方法","本申请属于地震学与地球物理层析成像技术领域，涉及一种基于自适应字典约束的面波频散三维层析成像方法，包括：对研究区域进行三维网格剖分，构建用于表征三维剪切波速度场的模型参数向量，构建走时残差与剪切波速度扰动量之间的线性化灵敏度矩阵方程，获得灵敏度矩阵及灵敏度矩阵的列范数分布，依据贝叶斯定理将最大化联合后验概率密度函数等价转化为最小化，得到由走时数据拟合项、全局‑辅助耦合约束项、图像块稀疏表示误差项三项加权平方和构成的联合反演目标函数，并采用交替最小化策略对联合反演目标函数进行求解，迭代收敛后，输出最终三维剪切波速度结构模型。实现了数据约束与结构先验的最优平衡，实现三维剪切波速度结构的高保真成像。","2026.08.25#公开;2026.09.11#实质审查的生效;2026.09.15#授权","CN202611143380.3","G01V1\u002F28;G01V1\u002F34;G01V1\u002F30;G06F18\u002F20;G06F18\u002F15","陈祖斌;李志文;丁健洋;周晓华;张林行",[],[],{"resultType":8,"id":229,"title":230,"abstract":231,"orgName":232,"province":13,"date":14,"trl":15,"transferMode":15,"keywords":15,"industry":15,"patentType":16,"legalStatus":233,"isOpenLicense":18,"isRevitalized":19,"techMaturity":15,"starRating":15,"licenseFeeText":15,"patentNo":234,"ipc":235,"inventors":236,"tags":237,"tagNames":238},"gpi2_0532","新能源弱送端异质边界外送安全校核方法","一种新能源弱送端异质边界外送安全校核方法，属于新能源电力系统技术领域。本发明的目的是能够在同一外送延拓路径和同一运行平衡点基础上，统一表征异质安全边界，确定其沿给定外送方向临界触发位置的新能源弱送端异质边界外送安全校核方法。本发明构造外送延拓平衡点轨迹和安全裕度，确定对象级临界延拓值、家族级临界延拓值及族内首触发对象集合，构造有效边界集合确定确定安全送出能力参数和最大安全外送功率，并构造共触发判别带，确定唯一首触发边界族和原始次近边界族，统计各边界族的唯一主导边界频率、条件参与频率及共触发或窄间隔状态出现比例。本发明提高新能源外送安全校核结果的准确性、可比性和工程解释性。","东北电力大学","2026.09.01#公开;2026.09.18#实质审查的生效;2026.09.29#授权","CN202611176506.7","H02J3\u002F38;G06F17\u002F10;H02J3\u002F50;H02J3\u002F1842;H02J3\u002F06;G06F123\u002F02;H02J103\u002F30;H02J101\u002F28","成龙;孟繁宇;王延旭;张鸿杨;礼元杰;王翀;杨悦;王燕辉;杨文博",[],[],{"resultType":8,"id":240,"title":241,"abstract":242,"orgName":104,"province":13,"date":14,"trl":15,"transferMode":15,"keywords":15,"industry":15,"patentType":16,"legalStatus":62,"isOpenLicense":18,"isRevitalized":19,"techMaturity":15,"starRating":15,"licenseFeeText":15,"patentNo":243,"ipc":244,"inventors":245,"tags":246,"tagNames":247},"gpi2_0934","用于高精度光学系统的计算机辅助装调去噪方法","本发明涉及一种用于高精度光学系统的计算机辅助装调去噪方法，首先搭建失调光学系统仿真模型，通过差分法计算灵敏度矩阵，构建成像质量评判目标函数；采用干涉仪多个视场多次采集系统波像差，构建多组像差矩阵并拼接生成观测矩阵；依次对观测矩阵实施密集噪声去噪、矩阵行平均处理，拼接得到全视场像差矩阵后进一步完成稀疏噪声去噪；依托灵敏度矩阵求解补偿量，结合目标函数筛选有效补偿量并进行系统装调，装调后测试成像质量，未满足指标则重复波像差测量与去噪流程迭代校正。优点在于：能够有效降低干涉仪测量噪声对装调精度的负面影响，提高高精度光学系统装调精度，且该方法在不同噪声强度下均能保持稳定的去噪性能。","CN202611120542.1","G02B27\u002F62;G02B27\u002F00;G06F30\u002F20;G06F18\u002F10","赵尚男;郑青青;张新;吴庆;叶昊坤;史广维;回佳轩",[],[],{"resultType":8,"id":249,"title":250,"abstract":251,"orgName":51,"province":13,"date":14,"trl":15,"transferMode":15,"keywords":15,"industry":15,"patentType":16,"legalStatus":212,"isOpenLicense":18,"isRevitalized":19,"techMaturity":15,"starRating":15,"licenseFeeText":15,"patentNo":252,"ipc":253,"inventors":254,"tags":255,"tagNames":256},"gpi2_0001","融合超宽带非视距检测与锚点自适应选择的室内定位方法","本发明涉及融合超宽带非视距检测与锚点自适应选择的室内定位方法，属于室内定位技术领域，解决现有定位方法难以实时检测NLOS误差以及锚点缺失导致定位中断的问题。首先获取原始测距数据及采样数据并对齐时间；进行短时惯性积分后得到三维相对位移预测值；根据当前帧和上一帧各锚点的有效测距值计算测距差分序列和方向向量序列；对三维相对位移预测值与实测距离变化量进行一致性校验，判定锚点的NLOS等级；自适应选择定位策略；执行定位策略进行定位解算，得到目标位置估计值；卡尔曼滤波平滑后输出最终定位位置。本发明能够实时检测NLOS误差，并在部分锚点失效时动态调整定位策略，提高复杂遮挡环境下室内定位的鲁棒性与连续性。","CN202611114283.1","G01C21\u002F20;G01C21\u002F16;H04W64\u002F00;H04W4\u002F02;H04W4\u002F029;H04W4\u002F33;G06F18\u002F24;G06F18\u002F10;G06F18\u002F25","李云烽;刘鹏;陈玮峥;樊飞虎;李浩源;魏来;刘芸;赵峥;席嘉璐;邱云圣浩;罗永哲;彭楚尧",[],[],{"resultType":8,"id":258,"title":259,"abstract":260,"orgName":51,"province":13,"date":14,"trl":15,"transferMode":15,"keywords":15,"indu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