[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"patents-list":3},{"list":4,"total":345,"page":346,"pageSize":347,"totalPages":348},[5,25,37,47,58,68,78,90,102,113,125,135,145,157,169,180,192,202,212,223,234,245,256,266,278,288,298,308,322,333],{"id":6,"patentNo":7,"title":8,"applicant":9,"inventors":10,"abstract":11,"ipc":12,"publishDate":13,"sourceUrl":13,"achievementId":13,"createdAt":14,"isOpenLicense":15,"licenseTerm":13,"licenseScope":13,"licenseFeeText":13,"licenseFeeNum":13,"patentType":16,"legalStatus":17,"applicationNo":7,"publicationNo":13,"mainIpc":18,"agency":13,"agent":13,"publishOrg":13,"provinceCode":13,"filingDate":13,"isRevitalized":19,"maintainYears":13,"isFunded":13,"implStatus1":13,"implStatus2":13,"willingness1":13,"willingness2":13,"feeWan":13,"intendedCity":13,"intendedCompany":13,"intendedPrice":13,"techMaturity":13,"starRating":13,"gbIndustryClass":13,"strategicClass":13,"productAdv":13,"prospect":13,"comboName":13,"batch":20,"province":21,"sourceText":22,"tags":23,"tagNames":24},"gpi2_0714","CN202611144398.5","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","中国科学院长春光学精密机械与物理研究所","赵伟超;孙鸽;齐翌辰;李泽","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。","H04L41\u002F0654;H04L9\u002F40;H04L67\u002F10;H04L9\u002F32;H04L41\u002F14;H04L41\u002F147;H04L41\u002F149;H04L41\u002F16",null,"2026-10-12T01:10:42.529Z",false,"发明专利","2026.08.28#公开;2026.09.15#实质审查的生效;2026.09.29#授权","H04L41\u002F0654",true,"gpi新专利1","220000;吉林省","粤港澳知识产权大数据综合服务平台(www.gpic.gd.cn)·广东省知识产权保护中心",[],[],{"id":26,"patentNo":27,"title":28,"applicant":29,"inventors":30,"abstract":31,"ipc":32,"publishDate":13,"sourceUrl":13,"achievementId":13,"createdAt":14,"isOpenLicense":15,"licenseTerm":13,"licenseScope":13,"licenseFeeText":13,"licenseFeeNum":13,"patentType":16,"legalStatus":33,"applicationNo":27,"publicationNo":13,"mainIpc":34,"agency":13,"agent":13,"publishOrg":13,"provinceCode":13,"filingDate":13,"isRevitalized":19,"maintainYears":13,"isFunded":13,"implStatus1":13,"implStatus2":13,"willingness1":13,"willingness2":13,"feeWan":13,"intendedCity":13,"intendedCompany":13,"intendedPrice":13,"techMaturity":13,"starRating":13,"gbIndustryClass":13,"strategicClass":13,"productAdv":13,"prospect":13,"comboName":13,"batch":20,"province":21,"sourceText":22,"tags":35,"tagNames":36},"gpi2_0729","CN202611134103.6","面向侧风工况的商用车尾板分区独立偏转控制装置及方法","吉林大学","王靖宇;王子瑞;史珂源;胡兴军;董春波","本发明适用于车辆空气动力学控制技术领域，提供了面向侧风工况的商用车尾板分区独立偏转控制装置及方法，装置包括：三分区尾板总成、独立设置的执行单元、风速风向传感器、车辆状态感知模块及电子控制单元。在离线阶段通过CFD仿真与高斯过程回归构建气动响应离线映射模型，并生成离线预测表；在线阶段根据实时车速与侧风偏航角，在满足侧向力安全阈值下快速查表寻优，输出减阻最优的尾板角度指令，并驱动各尾板独立执行。本发明能够根据侧风主动调整各尾板姿态，在保证侧风稳定性的同时持续降低气动阻力，具有决策快、鲁棒性强、节油效果明显的优点。","B62D37\u002F02;G06F30\u002F28;G06F30\u002F27;G06F30\u002F15;G05B13\u002F04;G06F111\u002F04;G06F111\u002F06;G06F113\u002F08;G06F119\u002F14;G06F18\u002F27","2026.08.25#公开;2026.09.11#实质审查的生效;2026.09.18#授权","B62D37\u002F02",[],[],{"id":38,"patentNo":39,"title":40,"applicant":29,"inventors":41,"abstract":42,"ipc":43,"publishDate":13,"sourceUrl":13,"achievementId":13,"createdAt":14,"isOpenLicense":15,"licenseTerm":13,"licenseScope":13,"licenseFeeText":13,"licenseFeeNum":13,"patentType":16,"legalStatus":17,"applicationNo":39,"publicationNo":13,"mainIpc":44,"agency":13,"agent":13,"publishOrg":13,"provinceCode":13,"filingDate":13,"isRevitalized":19,"maintainYears":13,"isFunded":13,"implStatus1":13,"implStatus2":13,"willingness1":13,"willingness2":13,"feeWan":13,"intendedCity":13,"intendedCompany":13,"intendedPrice":13,"techMaturity":13,"starRating":13,"gbIndustryClass":13,"strategicClass":13,"productAdv":13,"prospect":13,"comboName":13,"batch":20,"province":21,"sourceText":22,"tags":45,"tagNames":46},"gpi2_0169","CN202611107354.5","一种基于物理信息生成对抗网络的长尾事故场景生成方法","赵健;李文旭;朱冰;张培兴;黄殷梓","本发明属于自动驾驶场景生成技术领域，具体的说是一种基于物理信息生成对抗网络的长尾事故场景生成方法。本发明以少量真实事故场景为原型，围绕原型采样车辆初始状态、道路条件和目标碰撞条件；构建条件生成器与条件判别器，生成器同时作为物理信息神经网络，输出多交通参与者的连续状态轨迹与控制量；联合真实轨迹监督、对抗损失、运动学残差、道路边界、控制范围、目标首次碰撞及多样性约束进行训练；最后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。","G06N3\u002F094;G06N3\u002F098;G06F18\u002F15;G06F18\u002F214;G06F18\u002F24;G06F18\u002F213;G06F18\u002F25","G06N3\u002F094",[],[],{"id":48,"patentNo":49,"title":50,"applicant":29,"inventors":51,"abstract":52,"ipc":53,"publishDate":13,"sourceUrl":13,"achievementId":13,"createdAt":14,"isOpenLicense":15,"licenseTerm":13,"licenseScope":13,"licenseFeeText":13,"licenseFeeNum":13,"patentType":16,"legalStatus":54,"applicationNo":49,"publicationNo":13,"mainIpc":55,"agency":13,"agent":13,"publishOrg":13,"provinceCode":13,"filingDate":13,"isRevitalized":19,"maintainYears":13,"isFunded":13,"implStatus1":13,"implStatus2":13,"willingness1":13,"willingness2":13,"feeWan":13,"intendedCity":13,"intendedCompany":13,"intendedPrice":13,"techMaturity":13,"starRating":13,"gbIndustryClass":13,"strategicClass":13,"productAdv":13,"prospect":13,"comboName":13,"batch":20,"province":21,"sourceText":22,"tags":56,"tagNames":57},"gpi2_0650","CN202611143380.3","基于自适应字典约束的面波频散三维层析成像方法","陈祖斌;李志文;丁健洋;周晓华;张林行","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。","G01V1\u002F28;G01V1\u002F34;G01V1\u002F30;G06F18\u002F20;G06F18\u002F15","2026.08.25#公开;2026.09.11#实质审查的生效;2026.09.15#授权","G01V1\u002F28",[],[],{"id":59,"patentNo":60,"title":61,"applicant":29,"inventors":62,"abstract":63,"ipc":64,"publishDate":13,"sourceUrl":13,"achievementId":13,"createdAt":14,"isOpenLicense":15,"licenseTerm":13,"licenseScope":13,"licenseFeeText":13,"licenseFeeNum":13,"patentType":16,"legalStatus":33,"applicationNo":60,"publicationNo":13,"mainIpc":65,"agency":13,"agent":13,"publishOrg":13,"provinceCode":13,"filingDate":13,"isRevitalized":19,"maintainYears":13,"isFunded":13,"implStatus1":13,"implStatus2":13,"willingness1":13,"willingness2":13,"feeWan":13,"intendedCity":13,"intendedCompany":13,"intendedPrice":13,"techMaturity":13,"starRating":13,"gbIndustryClass":13,"strategicClass":13,"productAdv":13,"prospect":13,"comboName":13,"batch":20,"province":21,"sourceText":22,"tags":66,"tagNames":67},"gpi2_0652","CN202611141180.4","一种轮速缺失下双驱动桥电动商用车转矩协调控制方法","管欣;薛鹏程;詹军;卢萍萍;田培华;丁淼;杨利国;吴楠;徐国彭","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。","B60L15\u002F20;B60L15\u002F32","B60L15\u002F20",[],[],{"id":69,"patentNo":70,"title":71,"applicant":9,"inventors":72,"abstract":73,"ipc":74,"publishDate":13,"sourceUrl":13,"achievementId":13,"createdAt":14,"isOpenLicense":15,"licenseTerm":13,"licenseScope":13,"licenseFeeText":13,"licenseFeeNum":13,"patentType":16,"legalStatus":33,"applicationNo":70,"publicationNo":13,"mainIpc":75,"agency":13,"agent":13,"publishOrg":13,"provinceCode":13,"filingDate":13,"isRevitalized":19,"maintainYears":13,"isFunded":13,"implStatus1":13,"implStatus2":13,"willingness1":13,"willingness2":13,"feeWan":13,"intendedCity":13,"intendedCompany":13,"intendedPrice":13,"techMaturity":13,"starRating":13,"gbIndustryClass":13,"strategicClass":13,"productAdv":13,"prospect":13,"comboName":13,"batch":20,"province":21,"sourceText":22,"tags":76,"tagNames":77},"gpi2_0655","CN202611139916.4","基于GaNFET的高速紫外单光子探测器淬灭复位电路及方法","黎大兵;朱虹宇;蒋科;隋延林;陈一仁;孙晓娟","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。","G01J1\u002F44;G01J1\u002F42;H03K17\u002F22;H03K17\u002F081;H03K17\u002F687","G01J1\u002F44",[],[],{"id":79,"patentNo":80,"title":81,"applicant":82,"inventors":83,"abstract":84,"ipc":85,"publishDate":13,"sourceUrl":13,"achievementId":13,"createdAt":14,"isOpenLicense":15,"licenseTerm":13,"licenseScope":13,"licenseFeeText":13,"licenseFeeNum":13,"patentType":16,"legalStatus":86,"applicationNo":80,"publicationNo":13,"mainIpc":87,"agency":13,"agent":13,"publishOrg":13,"provinceCode":13,"filingDate":13,"isRevitalized":19,"maintainYears":13,"isFunded":13,"implStatus1":13,"implStatus2":13,"willingness1":13,"willingness2":13,"feeWan":13,"intendedCity":13,"intendedCompany":13,"intendedPrice":13,"techMaturity":13,"starRating":13,"gbIndustryClass":13,"strategicClass":13,"productAdv":13,"prospect":13,"comboName":13,"batch":20,"province":21,"sourceText":22,"tags":88,"tagNames":89},"gpi2_0532","CN202611176506.7","新能源弱送端异质边界外送安全校核方法","东北电力大学","成龙;孟繁宇;王延旭;张鸿杨;礼元杰;王翀;杨悦;王燕辉;杨文博","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。","H02J3\u002F38;G06F17\u002F10;H02J3\u002F50;H02J3\u002F1842;H02J3\u002F06;G06F123\u002F02;H02J103\u002F30;H02J101\u002F28","2026.09.01#公开;2026.09.18#实质审查的生效;2026.09.29#授权","H02J3\u002F38",[],[],{"id":91,"patentNo":92,"title":93,"applicant":94,"inventors":95,"abstract":96,"ipc":97,"publishDate":13,"sourceUrl":13,"achievementId":13,"createdAt":14,"isOpenLicense":15,"licenseTerm":13,"licenseScope":13,"licenseFeeText":13,"licenseFeeNum":13,"patentType":16,"legalStatus":98,"applicationNo":92,"publicationNo":13,"mainIpc":99,"agency":13,"agent":13,"publishOrg":13,"provinceCode":13,"filingDate":13,"isRevitalized":19,"maintainYears":13,"isFunded":13,"implStatus1":13,"implStatus2":13,"willingness1":13,"willingness2":13,"feeWan":13,"intendedCity":13,"intendedCompany":13,"intendedPrice":13,"techMaturity":13,"starRating":13,"gbIndustryClass":13,"strategicClass":13,"productAdv":13,"prospect":13,"comboName":13,"batch":20,"province":21,"sourceText":22,"tags":100,"tagNames":101},"gpi2_0551","CN202611170523.X","一种仿生柔性触觉传感器阵列及其制备方法","吉林大学;辽宁材料实验室","刘燕;李加琪;李杰;陈士豪;丁振民;杨凯","本发明公开了一种仿生柔性触觉传感器阵列及其制备方法，涉及柔性触觉传感技术领域，包括柔性单电极、压敏导电层、仿生结构层、缓冲层以及柔性阵列电极，压敏导电层的表面间隔阵列分布有多个凸起，仿生结构层的表面对应凸起设置有仿生结构，凸起嵌入仿生结构内部且在未受力状态下，凸起的端面与仿生结构的端面存在预设间隙。本发明采用压敏导电层与仿生结构层嵌套式初始间隙设计，形成阈值触发式导电通路，传感器在未受外力时使得电极单元与压敏导电层完全隔离，传感器处于零功耗待机状态，区别于传统常通型压阻传感器，显著降低了静态功耗；同时，从根源上避免了传统传感器因预压缩导致的有效灵敏度提前损耗问题，保证了全量程内的灵敏度稳定性。","G01L1\u002F18;G01L5\u002F22","2026.09.04#公开;2026.09.22#实质审查的生效;2026.09.29#授权","G01L1\u002F18",[],[],{"id":103,"patentNo":104,"title":105,"applicant":106,"inventors":107,"abstract":108,"ipc":109,"publishDate":13,"sourceUrl":13,"achievementId":13,"createdAt":14,"isOpenLicense":15,"licenseTerm":13,"licenseScope":13,"licenseFeeText":13,"licenseFeeNum":13,"patentType":16,"legalStatus":17,"applicationNo":104,"publicationNo":13,"mainIpc":110,"agency":13,"agent":13,"publishOrg":13,"provinceCode":13,"filingDate":13,"isRevitalized":19,"maintainYears":13,"isFunded":13,"implStatus1":13,"implStatus2":13,"willingness1":13,"willingness2":13,"feeWan":13,"intendedCity":13,"intendedCompany":13,"intendedPrice":13,"techMaturity":13,"starRating":13,"gbIndustryClass":13,"strategicClass":13,"productAdv":13,"prospect":13,"comboName":13,"batch":20,"province":21,"sourceText":22,"tags":111,"tagNames":112},"gpi2_0642","CN202611149114.1","面向泛在网络生产者移动性的数据平面转发增强方法","长春理工大学","祁晖;从立钢;底晓强;刘旭;孙苏鹏;毕琳;李锦青","本发明涉及命名数据网络的数据平面转发技术领域，具体为面向泛在网络生产者移动性的数据平面转发增强方法。该方法用于解决生产者在泛在网络中切换接入节点时兴趣包仍转向旧路径、PIT回传路径不一致及路由收敛期间兴趣包回溯丢弃的问题；通过在数据平面建立移动绑定表，旧接入节点基于本地控制兴趣包进入代理转发模式，对未满足兴趣条目生成恢复性兴趣包，并将恢复性兴趣包及新到达兴趣包按新接入节点二维坐标标识转发至新接入节点；新接入节点经生产者接入链路转发兴趣包并基于PIT记录回传数据包，同时通过NACK触发前一跳节点重表达回溯兴趣包，适用于低轨卫星网络等生产者移动场景。","H04L45\u002F50;H04L45\u002F645;H04L45\u002F748","H04L45\u002F50",[],[],{"id":114,"patentNo":115,"title":116,"applicant":117,"inventors":118,"abstract":119,"ipc":120,"publishDate":13,"sourceUrl":13,"achievementId":13,"createdAt":14,"isOpenLicense":15,"licenseTerm":13,"licenseScope":13,"licenseFeeText":13,"licenseFeeNum":13,"patentType":16,"legalStatus":121,"applicationNo":115,"publicationNo":13,"mainIpc":122,"agency":13,"agent":13,"publishOrg":13,"provinceCode":13,"filingDate":13,"isRevitalized":19,"maintainYears":13,"isFunded":13,"implStatus1":13,"implStatus2":13,"willingness1":13,"willingness2":13,"feeWan":13,"intendedCity":13,"intendedCompany":13,"intendedPrice":13,"techMaturity":13,"starRating":13,"gbIndustryClass":13,"strategicClass":13,"productAdv":13,"prospect":13,"comboName":13,"batch":20,"province":21,"sourceText":22,"tags":123,"tagNames":124},"gpi2_0892","CN202611122166.X","一种多阶段漏洞挖掘与威胁溯源方法及系统","华易数安科技(吉林省)有限公司","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","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&amp;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。","H04L9\u002F40;G06N5\u002F04","2026.08.25#公开;2026.09.11#实质审查的生效;2026.09.29#授权","H04L9\u002F40",[],[],{"id":126,"patentNo":127,"title":128,"applicant":9,"inventors":129,"abstract":130,"ipc":131,"publishDate":13,"sourceUrl":13,"achievementId":13,"createdAt":14,"isOpenLicense":15,"licenseTerm":13,"licenseScope":13,"licenseFeeText":13,"licenseFeeNum":13,"patentType":16,"legalStatus":121,"applicationNo":127,"publicationNo":13,"mainIpc":132,"agency":13,"agent":13,"publishOrg":13,"provinceCode":13,"filingDate":13,"isRevitalized":19,"maintainYears":13,"isFunded":13,"implStatus1":13,"implStatus2":13,"willingness1":13,"willingness2":13,"feeWan":13,"intendedCity":13,"intendedCompany":13,"intendedPrice":13,"techMaturity":13,"starRating":13,"gbIndustryClass":13,"strategicClass":13,"productAdv":13,"prospect":13,"comboName":13,"batch":20,"province":21,"sourceText":22,"tags":133,"tagNames":134},"gpi2_0022","CN202611120547.4","基于时空交互融合的双时相图像变化检测系统及方法","孙海江;郭超凡;刘巧元;陈周长","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。","G06V20\u002F40;G06V10\u002F44;G06V10\u002F52;G06V10\u002F62;G06V10\u002F77;G06V10\u002F80;G06V10\u002F82;G06N3\u002F045;G06N3\u002F0455;G06N3\u002F0464;G06N3\u002F084;G06N3\u002F09","G06V20\u002F40",[],[],{"id":136,"patentNo":137,"title":138,"applicant":139,"inventors":140,"abstract":141,"ipc":142,"publishDate":13,"sourceUrl":13,"achievementId":13,"createdAt":14,"isOpenLicense":15,"licenseTerm":13,"licenseScope":13,"licenseFeeText":13,"licenseFeeNum":13,"patentType":16,"legalStatus":33,"applicationNo":137,"publicationNo":13,"mainIpc":142,"agency":13,"agent":13,"publishOrg":13,"provinceCode":13,"filingDate":13,"isRevitalized":19,"maintainYears":13,"isFunded":13,"implStatus1":13,"implStatus2":13,"willingness1":13,"willingness2":13,"feeWan":13,"intendedCity":13,"intendedCompany":13,"intendedPrice":13,"techMaturity":13,"starRating":13,"gbIndustryClass":13,"strategicClass":13,"productAdv":13,"prospect":13,"comboName":13,"batch":20,"province":21,"sourceText":22,"tags":143,"tagNames":144},"gpi2_0081","CN202611110444.X","一种基于扩张状态观测器的三维高斯泼溅自适应重建方法","长春工业大学","张秀梅;胡俊佑;李慧;程艳妍;王大楠;荣井涛;张立建;贾延逊","本发明公开了一种基于扩张状态观测器的三维高斯泼溅自适应重建方法。针对现有三维高斯泼溅同步定位与地图构建方法中不确定性方差作为静态权重、后端优化为开环结构的缺陷，本发明将所述不确定性方差建模为逐像素动态状态量，构建离散时间状态空间方程，设计逐像素二阶扩张状态观测器，引入非线性误差反馈函数区分高频测量噪声与低频环境退化信号，动态估计逐像素方差估计值与扰动估计值，以所述方差估计值构建渲染损失自适应像素权重，对所述扰动估计值进行空间聚合得到全局退化指标，动态调制优化学习率，当所述扰动估计值超过动态阈值时暂停对应区域致密化操作，从权重、学习率、密度三个维度实现闭环补偿，提升了退化环境下的建图精度。","G06T17\u002F00",[],[],{"id":146,"patentNo":147,"title":148,"applicant":149,"inventors":150,"abstract":151,"ipc":152,"publishDate":13,"sourceUrl":13,"achievementId":13,"createdAt":14,"isOpenLicense":15,"licenseTerm":13,"licenseScope":13,"licenseFeeText":13,"licenseFeeNum":13,"patentType":16,"legalStatus":153,"applicationNo":147,"publicationNo":13,"mainIpc":154,"agency":13,"agent":13,"publishOrg":13,"provinceCode":13,"filingDate":13,"isRevitalized":19,"maintainYears":13,"isFunded":13,"implStatus1":13,"implStatus2":13,"willingness1":13,"willingness2":13,"feeWan":13,"intendedCity":13,"intendedCompany":13,"intendedPrice":13,"techMaturity":13,"starRating":13,"gbIndustryClass":13,"strategicClass":13,"productAdv":13,"prospect":13,"comboName":13,"batch":20,"province":21,"sourceText":22,"tags":155,"tagNames":156},"gpi2_0317","CN202611098943.1","一种光伏发电供热系统用光伏板激光切割装置","吉林省清洁能源开发利用有限公司","王璘;王梓屹;公维康;孙生亮;阚丽媛","本发明涉及光伏板加工技术领域，具体为一种光伏发电供热系统用光伏板激光切割装置，包括作业仓、栅栏架、定位组件、吸附件、调节组件和保护组件。本发明中通过定位组件配合CCD相机形成机械定位配合视觉定位的双重定位，并通过机械定位提高切割时的稳定性，减少因应力变化导致工件边缘形变以及影响切割稳定的问题，并为后续吸附动作提供基准导向，其次借助吸附件的吸附过程降低电池片切割分离时释放应力的影响，提高稳定性和切割精度，同时通过保护组件形成矩形区域保护电池片，避免出现过度切割导致电池片出现损坏的问题，综上，通过加强定位基准、吸附动作减小应力影响和跟随基准保护三重作业相互配合，确保电池片精准切割。","B23K26\u002F02;B23K26\u002F08;B23K26\u002F70;B23K26\u002F38;B23K101\u002F36","2026.08.25#公开;2026.09.11#实质审查的生效;2026.09.25#授权","B23K26\u002F02",[],[],{"id":158,"patentNo":159,"title":160,"applicant":161,"inventors":162,"abstract":163,"ipc":164,"publishDate":13,"sourceUrl":13,"achievementId":13,"createdAt":14,"isOpenLicense":15,"licenseTerm":13,"licenseScope":13,"licenseFeeText":13,"licenseFeeNum":13,"patentType":16,"legalStatus":165,"applicationNo":159,"publicationNo":13,"mainIpc":166,"agency":13,"agent":13,"publishOrg":13,"provinceCode":13,"filingDate":13,"isRevitalized":19,"maintainYears":13,"isFunded":13,"implStatus1":13,"implStatus2":13,"willingness1":13,"willingness2":13,"feeWan":13,"intendedCity":13,"intendedCompany":13,"intendedPrice":13,"techMaturity":13,"starRating":13,"gbIndustryClass":13,"strategicClass":13,"productAdv":13,"prospect":13,"comboName":13,"batch":20,"province":21,"sourceText":22,"tags":167,"tagNames":168},"gpi2_0357","CN202611097399.9","基于电网时序约束的新能源消纳能力优化方法","国网吉林省电力有限公司经济技术研究院","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","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。","H02J3\u002F466;H02J3\u002F28;H02J3\u002F175;G06F18\u002F15;G06F18\u002F20;H02J101\u002F24;H02J101\u002F28;H02J103\u002F30;H02J105\u002F52;G06F123\u002F02","2026.08.21#公开;2026.09.08#实质审查的生效;2026.09.29#授权","H02J3\u002F466",[],[],{"id":170,"patentNo":171,"title":172,"applicant":29,"inventors":173,"abstract":174,"ipc":175,"publishDate":13,"sourceUrl":13,"achievementId":13,"createdAt":14,"isOpenLicense":15,"licenseTerm":13,"licenseScope":13,"licenseFeeText":13,"licenseFeeNum":13,"patentType":16,"legalStatus":176,"applicationNo":171,"publicationNo":13,"mainIpc":177,"agency":13,"agent":13,"publishOrg":13,"provinceCode":13,"filingDate":13,"isRevitalized":19,"maintainYears":13,"isFunded":13,"implStatus1":13,"implStatus2":13,"willingness1":13,"willingness2":13,"feeWan":13,"intendedCity":13,"intendedCompany":13,"intendedPrice":13,"techMaturity":13,"starRating":13,"gbIndustryClass":13,"strategicClass":13,"productAdv":13,"prospect":13,"comboName":13,"batch":20,"province":21,"sourceText":22,"tags":178,"tagNames":179},"gpi2_0947","CN202611114407.6","一种自平衡可变姿态可回收锚固装置","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","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。","B63B21\u002F26;B63B21\u002F50","2026.08.21#公开;2026.09.08#实质审查的生效;2026.09.22#授权","B63B21\u002F26",[],[],{"id":181,"patentNo":182,"title":183,"applicant":184,"inventors":185,"abstract":186,"ipc":187,"publishDate":13,"sourceUrl":13,"achievementId":13,"createdAt":14,"isOpenLicense":15,"licenseTerm":13,"licenseScope":13,"licenseFeeText":13,"licenseFeeNum":13,"patentType":16,"legalStatus":188,"applicationNo":182,"publicationNo":13,"mainIpc":189,"agency":13,"agent":13,"publishOrg":13,"provinceCode":13,"filingDate":13,"isRevitalized":19,"maintainYears":13,"isFunded":13,"implStatus1":13,"implStatus2":13,"willingness1":13,"willingness2":13,"feeWan":13,"intendedCity":13,"intendedCompany":13,"intendedPrice":13,"techMaturity":13,"starRating":13,"gbIndustryClass":13,"strategicClass":13,"productAdv":13,"prospect":13,"comboName":13,"batch":20,"province":21,"sourceText":22,"tags":190,"tagNames":191},"gpi2_0463","CN202611092195.6","一种轨道车辆冷弯型钢矫平处理工艺","长春市新金享冷弯型钢有限公司","温杰;温博阁","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。","B21D1\u002F02;B21D43\u002F09","2026.08.18#公开;2026.09.04#实质审查的生效;2026.09.25#授权","B21D1\u002F02",[],[],{"id":193,"patentNo":194,"title":195,"applicant":29,"inventors":196,"abstract":197,"ipc":198,"publishDate":13,"sourceUrl":13,"achievementId":13,"createdAt":14,"isOpenLicense":15,"licenseTerm":13,"licenseScope":13,"licenseFeeText":13,"licenseFeeNum":13,"patentType":16,"legalStatus":165,"applicationNo":194,"publicationNo":13,"mainIpc":199,"agency":13,"agent":13,"publishOrg":13,"provinceCode":13,"filingDate":13,"isRevitalized":19,"maintainYears":13,"isFunded":13,"implStatus1":13,"implStatus2":13,"willingness1":13,"willingness2":13,"feeWan":13,"intendedCity":13,"intendedCompany":13,"intendedPrice":13,"techMaturity":13,"starRating":13,"gbIndustryClass":13,"strategicClass":13,"productAdv":13,"prospect":13,"comboName":13,"batch":20,"province":21,"sourceText":22,"tags":200,"tagNames":201},"gpi2_0001","CN202611114283.1","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","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","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。","G01C21\u002F20;G01C21\u002F16;H04W64\u002F00;H04W4\u002F02;H04W4\u002F029;H04W4\u002F33;G06F18\u002F24;G06F18\u002F10;G06F18\u002F25","G01C21\u002F20",[],[],{"id":203,"patentNo":204,"title":205,"applicant":106,"inventors":206,"abstract":207,"ipc":208,"publishDate":13,"sourceUrl":13,"achievementId":13,"createdAt":14,"isOpenLicense":15,"licenseTerm":13,"licenseScope":13,"licenseFeeText":13,"licenseFeeNum":13,"patentType":16,"legalStatus":209,"applicationNo":204,"publicationNo":13,"mainIpc":142,"agency":13,"agent":13,"publishOrg":13,"provinceCode":13,"filingDate":13,"isRevitalized":19,"maintainYears":13,"isFunded":13,"implStatus1":13,"implStatus2":13,"willingness1":13,"willingness2":13,"feeWan":13,"intendedCity":13,"intendedCompany":13,"intendedPrice":13,"techMaturity":13,"starRating":13,"gbIndustryClass":13,"strategicClass":13,"productAdv":13,"prospect":13,"comboName":13,"batch":20,"province":21,"sourceText":22,"tags":210,"tagNames":211},"gpi2_0210","CN202611097197.4","一种脑部表面点云重建方法、电子设备及存储介质","赵家石;王文豪;方旭;程新异;申秀贤;田浩;梁世奇","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。","G06T17\u002F00;G06N3\u002F042;G06N3\u002F0455;G06N3\u002F0464;G06T7\u002F50;G06T19\u002F00;G06V10\u002F70;G06V10\u002F80;G06V10\u002F82","2026.08.18#公开;2026.09.04#实质审查的生效;2026.09.18#授权",[],[],{"id":213,"patentNo":214,"title":215,"applicant":29,"inventors":216,"abstract":217,"ipc":218,"publishDate":13,"sourceUrl":13,"achievementId":13,"createdAt":14,"isOpenLicense":15,"licenseTerm":13,"licenseScope":13,"licenseFeeText":13,"licenseFeeNum":13,"patentType":16,"legalStatus":219,"applicationNo":214,"publicationNo":13,"mainIpc":220,"agency":13,"agent":13,"publishOrg":13,"provinceCode":13,"filingDate":13,"isRevitalized":19,"maintainYears":13,"isFunded":13,"implStatus1":13,"implStatus2":13,"willingness1":13,"willingness2":13,"feeWan":13,"intendedCity":13,"intendedCompany":13,"intendedPrice":13,"techMaturity":13,"starRating":13,"gbIndustryClass":13,"strategicClass":13,"productAdv":13,"prospect":13,"comboName":13,"batch":20,"province":21,"sourceText":22,"tags":221,"tagNames":222},"gpi2_0222","CN202611097619.8","一种基于X射线CT三维孔隙重构的土壤导水能力评价方法","吴宝广;叶俊廷;胡伟;王秋菊;许顺;殷志鹏;聂晓雨;刘玉萍;谢岩松;王振宇","本发明公开了一种基于X射线CT三维孔隙重构的土壤导水能力评价方法，属于土壤物理学与农业土壤结构评价技术领域。该方法包括：土壤样品采集与培养、X射线CT扫描、图像预处理、孔隙分割、三维孔隙结构重构及孔隙结构参数提取。利用Avizo软件获取CT孔隙率及孔隙与固体界面比表面积，并在同源土壤体系条件下对Kozeny–Carman模型进行归一化处理，构建基于CT结构参数的无量纲结构导水能力指数，通过对不同处理条件下土壤潜在导水能力进行定量评价，并识别结构导水能力优化阈值。本发明能够提高复杂土壤体系导水能力评价的准确性，可应用于农田土壤结构评价、水分调控及农业土壤优化管理等领域。","G01N15\u002F08;G01N23\u002F046;G06T12\u002F10","2026.08.21#公开;2026.09.08#实质审查的生效;2026.09.18#授权","G01N15\u002F08",[],[],{"id":224,"patentNo":225,"title":226,"applicant":227,"inventors":228,"abstract":229,"ipc":230,"publishDate":13,"sourceUrl":13,"achievementId":13,"createdAt":14,"isOpenLicense":15,"licenseTerm":13,"licenseScope":13,"licenseFeeText":13,"licenseFeeNum":13,"patentType":16,"legalStatus":219,"applicationNo":225,"publicationNo":13,"mainIpc":231,"agency":13,"agent":13,"publishOrg":13,"provinceCode":13,"filingDate":13,"isRevitalized":19,"maintainYears":13,"isFunded":13,"implStatus1":13,"implStatus2":13,"willingness1":13,"willingness2":13,"feeWan":13,"intendedCity":13,"intendedCompany":13,"intendedPrice":13,"techMaturity":13,"starRating":13,"gbIndustryClass":13,"strategicClass":13,"productAdv":13,"prospect":13,"comboName":13,"batch":20,"province":21,"sourceText":22,"tags":232,"tagNames":233},"gpi2_0227","CN202611095756.8","一种上下文剥离与双轨隔离的大语言模型防御方法及系统","长春大学","刘妍秀;赵俊嵩;徐大伟;王一力;林潇","一种上下文剥离与双轨隔离的大语言模型防御方法及系统，涉及大语言模型安全防护领域。解决现有的单轨推理架构下的大模型安全防护方案，仅依靠文本语义规则与模型微调实现风险识别，内存资源占用高、算力传输开销大等计算机底层硬件缺陷，所述方法包括：搭建双GPU显存物理隔离推理架构，接收用户输入token流存入进程内存缓冲区，经硬件路由分发至第一显存分区的目标生成轨进程，加载KV‑cache张量推理生成初始token文本并暂存于流式分片内存缓存。上下文剥离硬件模块剥离诱导上下文内存数据块，提取核心语义数据送入物理隔离的第二显存分区独立审查轨，基于核心语义完成安全判定，根据结果对缓存文本执行放行、清空或改写操作，优化推理硬件资源开销。","G06F21\u002F57;G06N5\u002F04;G06N3\u002F045","G06F21\u002F57",[],[],{"id":235,"patentNo":236,"title":237,"applicant":238,"inventors":239,"abstract":240,"ipc":241,"publishDate":13,"sourceUrl":13,"achievementId":13,"createdAt":14,"isOpenLicense":15,"licenseTerm":13,"licenseScope":13,"licenseFeeText":13,"licenseFeeNum":13,"patentType":16,"legalStatus":176,"applicationNo":236,"publicationNo":13,"mainIpc":242,"agency":13,"agent":13,"publishOrg":13,"provinceCode":13,"filingDate":13,"isRevitalized":19,"maintainYears":13,"isFunded":13,"implStatus1":13,"implStatus2":13,"willingness1":13,"willingness2":13,"feeWan":13,"intendedCity":13,"intendedCompany":13,"intendedPrice":13,"techMaturity":13,"starRating":13,"gbIndustryClass":13,"strategicClass":13,"productAdv":13,"prospect":13,"comboName":13,"batch":20,"province":21,"sourceText":22,"tags":243,"tagNames":244},"gpi2_0275","CN202611098855.1","一种大豆种子缺陷检测模型的构建方法","吉林农业大学","于合龙;李延松;石磊;吕肇聪;郭靖","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。","G06V20\u002F60;G06V10\u002F44;G06V10\u002F774;G06V10\u002F776;G06V10\u002F82;G06N3\u002F0464;G06N3\u002F08","G06V20\u002F60",[],[],{"id":246,"patentNo":247,"title":248,"applicant":29,"inventors":249,"abstract":250,"ipc":251,"publishDate":13,"sourceUrl":13,"achievementId":13,"createdAt":14,"isOpenLicense":15,"licenseTerm":13,"licenseScope":13,"licenseFeeText":13,"licenseFeeNum":13,"patentType":16,"legalStatus":252,"applicationNo":247,"publicationNo":13,"mainIpc":253,"agency":13,"agent":13,"publishOrg":13,"provinceCode":13,"filingDate":13,"isRevitalized":19,"maintainYears":13,"isFunded":13,"implStatus1":13,"implStatus2":13,"willingness1":13,"willingness2":13,"feeWan":13,"intendedCity":13,"intendedCompany":13,"intendedPrice":13,"techMaturity":13,"starRating":13,"gbIndustryClass":13,"strategicClass":13,"productAdv":13,"prospect":13,"comboName":13,"batch":20,"province":21,"sourceText":22,"tags":254,"tagNames":255},"gpi2_0381","CN202611091071.6","一种轨道车辆管接头松动检测方法及系统","蒋尚佑;田海龙;李鑫;陈晓彬;李修昱","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。","G06T7\u002F00;G06V10\u002F75;G06V10\u002F34;G06V10\u002F40;G06V10\u002F26;G06T7\u002F136;G06T5\u002F70;G06T5\u002F92","2026.08.18#公开;2026.09.04#实质审查的生效;2026.09.15#授权","G06T7\u002F00",[],[],{"id":257,"patentNo":258,"title":259,"applicant":29,"inventors":260,"abstract":261,"ipc":262,"publishDate":13,"sourceUrl":13,"achievementId":13,"createdAt":14,"isOpenLicense":15,"licenseTerm":13,"licenseScope":13,"licenseFeeText":13,"licenseFeeNum":13,"patentType":16,"legalStatus":209,"applicationNo":258,"publicationNo":13,"mainIpc":263,"agency":13,"agent":13,"publishOrg":13,"provinceCode":13,"filingDate":13,"isRevitalized":19,"maintainYears":13,"isFunded":13,"implStatus1":13,"implStatus2":13,"willingness1":13,"willingness2":13,"feeWan":13,"intendedCity":13,"intendedCompany":13,"intendedPrice":13,"techMaturity":13,"starRating":13,"gbIndustryClass":13,"strategicClass":13,"productAdv":13,"prospect":13,"comboName":13,"batch":20,"province":21,"sourceText":22,"tags":264,"tagNames":265},"gpi2_0396","CN202611089068.0","长波红外可调谐光学模拟计算器件及其空间频率调控方法","靳淳淇;韦雨婷;陈岐岱","本发明公开了长波红外可调谐光学模拟计算器件及其空间频率调控方法，属于长波红外光学图像处理技术领域，所述长波红外可调谐光学模拟计算器件沿光路依次包括上分布式布拉格反射镜、液晶腔层和下分布式布拉格反射镜，形成可调谐法布里‑珀罗谐振腔；通过外加电场调节液晶腔层的有效折射率，改变谐振腔的光学厚度与相位匹配条件，使透射峰或阻带在空间频率域中动态移动，从而获得低通、高通、带通或带阻等可切换的空间频率传递函数。本发明利用角度透射谱与空间频率的映射关系，在光传输过程中直接对长波红外图像实现去噪、边缘增强、特定频段抑制或尺度选择等处理，具有结构紧凑、可调谐、多模式切换和易于集成于透射式红外成像系统的优点。","G02F1\u002F1335;G02F1\u002F1333;G02F1\u002F133;G02B27\u002F00","G02F1\u002F1335",[],[],{"id":267,"patentNo":268,"title":269,"applicant":270,"inventors":271,"abstract":272,"ipc":273,"publishDate":13,"sourceUrl":13,"achievementId":13,"createdAt":14,"isOpenLicense":15,"licenseTerm":13,"licenseScope":13,"licenseFeeText":13,"licenseFeeNum":13,"patentType":16,"legalStatus":274,"applicationNo":268,"publicationNo":13,"mainIpc":275,"agency":13,"agent":13,"publishOrg":13,"provinceCode":13,"filingDate":13,"isRevitalized":19,"maintainYears":13,"isFunded":13,"implStatus1":13,"implStatus2":13,"willingness1":13,"willingness2":13,"feeWan":13,"intendedCity":13,"intendedCompany":13,"intendedPrice":13,"techMaturity":13,"starRating":13,"gbIndustryClass":13,"strategicClass":13,"productAdv":13,"prospect":13,"comboName":13,"batch":20,"province":21,"sourceText":22,"tags":276,"tagNames":277},"gpi2_0738","CN202611131805.9","偶极子阵列的电磁波相控阵聚焦能量调控方法及系统","吉林省众驰医疗科技有限公司","姜新;王身云;高杨;刘忠刚;李超贵","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。","A61N5\u002F00;A61N5\u002F02;G16H20\u002F30;G16H40\u002F60","2026.08.25#公开;2026.09.11#实质审查的生效;2026.09.22#授权","A61N5\u002F00",[],[],{"id":279,"patentNo":280,"title":281,"applicant":9,"inventors":282,"abstract":283,"ipc":284,"publishDate":13,"sourceUrl":13,"achievementId":13,"createdAt":14,"isOpenLicense":15,"licenseTerm":13,"licenseScope":13,"licenseFeeText":13,"licenseFeeNum":13,"patentType":16,"legalStatus":121,"applicationNo":280,"publicationNo":13,"mainIpc":285,"agency":13,"agent":13,"publishOrg":13,"provinceCode":13,"filingDate":13,"isRevitalized":19,"maintainYears":13,"isFunded":13,"implStatus1":13,"implStatus2":13,"willingness1":13,"willingness2":13,"feeWan":13,"intendedCity":13,"intendedCompany":13,"intendedPrice":13,"techMaturity":13,"starRating":13,"gbIndustryClass":13,"strategicClass":13,"productAdv":13,"prospect":13,"comboName":13,"batch":20,"province":21,"sourceText":22,"tags":286,"tagNames":287},"gpi2_0778","CN202611136668.8","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","孙健维;刘帅凝;宋来运;袁东明;刘学吉","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。","G06F18\u002F20;G06F18\u002F2433;G06T7\u002F246;G06V10\u002F98;G01M11\u002F00;G01C11\u002F04;G01B11\u002F16","G06F18\u002F20",[],[],{"id":289,"patentNo":290,"title":291,"applicant":29,"inventors":292,"abstract":293,"ipc":294,"publishDate":13,"sourceUrl":13,"achievementId":13,"createdAt":14,"isOpenLicense":15,"licenseTerm":13,"licenseScope":13,"licenseFeeText":13,"licenseFeeNum":13,"patentType":16,"legalStatus":121,"applicationNo":290,"publicationNo":13,"mainIpc":295,"agency":13,"agent":13,"publishOrg":13,"provinceCode":13,"filingDate":13,"isRevitalized":19,"maintainYears":13,"isFunded":13,"implStatus1":13,"implStatus2":13,"willingness1":13,"willingness2":13,"feeWan":13,"intendedCity":13,"intendedCompany":13,"intendedPrice":13,"techMaturity":13,"starRating":13,"gbIndustryClass":13,"strategicClass":13,"productAdv":13,"prospect":13,"comboName":13,"batch":20,"province":21,"sourceText":22,"tags":296,"tagNames":297},"gpi2_0780","CN202611133281.7","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","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","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。","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","G06F30\u002F27",[],[],{"id":299,"patentNo":300,"title":301,"applicant":9,"inventors":302,"abstract":303,"ipc":304,"publishDate":13,"sourceUrl":13,"achievementId":13,"createdAt":14,"isOpenLicense":15,"licenseTerm":13,"licenseScope":13,"licenseFeeText":13,"licenseFeeNum":13,"patentType":16,"legalStatus":33,"applicationNo":300,"publicationNo":13,"mainIpc":305,"agency":13,"agent":13,"publishOrg":13,"provinceCode":13,"filingDate":13,"isRevitalized":19,"maintainYears":13,"isFunded":13,"implStatus1":13,"implStatus2":13,"willingness1":13,"willingness2":13,"feeWan":13,"intendedCity":13,"intendedCompany":13,"intendedPrice":13,"techMaturity":13,"starRating":13,"gbIndustryClass":13,"strategicClass":13,"productAdv":13,"prospect":13,"comboName":13,"batch":20,"province":21,"sourceText":22,"tags":306,"tagNames":307},"gpi2_0934","CN202611120542.1","用于高精度光学系统的计算机辅助装调去噪方法","赵尚男;郑青青;张新;吴庆;叶昊坤;史广维;回佳轩","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。","G02B27\u002F62;G02B27\u002F00;G06F30\u002F20;G06F18\u002F10","G02B27\u002F62",[],[],{"id":309,"patentNo":310,"title":311,"applicant":312,"inventors":313,"abstract":314,"ipc":315,"publishDate":13,"sourceUrl":13,"achievementId":13,"createdAt":316,"isOpenLicense":15,"licenseTerm":13,"licenseScope":13,"licenseFeeText":13,"licenseFeeNum":13,"patentType":16,"legalStatus":317,"applicationNo":310,"publicationNo":13,"mainIpc":318,"agency":13,"agent":13,"publishOrg":13,"provinceCode":13,"filingDate":13,"isRevitalized":19,"maintainYears":13,"isFunded":13,"implStatus1":13,"implStatus2":13,"willingness1":13,"willingness2":13,"feeWan":13,"intendedCity":13,"intendedCompany":13,"intendedPrice":13,"techMaturity":13,"starRating":13,"gbIndustryClass":13,"strategicClass":13,"productAdv":13,"prospect":13,"comboName":13,"batch":319,"province":21,"sourceText":22,"tags":320,"tagNames":321},"gpi_01327","CN201010103353.6","侧链含喹啉类配体铱配合物的红光共轭聚合物及发光器件","中国科学院长春应用化学研究所","王利祥;马志华;丁军桥;王斌;隋丹","本发明提供了一种侧链含喹啉类配体铱配合物的红光共轭聚合物，并提供由该红光聚合物制成的有机电致发光器件及制备方法，该有机电致发光器件的阳极和阴极之间涂有与阴极相连接的至少一层具有侧链含喹啉类配体铱配合物的红光共轭聚合物的发光层，发光效率较高，且性能稳定。","C08G61\u002F02;C08G61\u002F12;C09K11\u002F06;H01L51\u002F50;H01L51\u002F54;H01L51\u002F56","2026-10-12T00:54:35.109Z","2010.07.14#公开;2010.09.15#实质审查的生效;2012.07.11#授权","C08G61\u002F02","gpi5份",[],[],{"id":323,"patentNo":324,"title":325,"applicant":312,"inventors":326,"abstract":327,"ipc":328,"publishDate":13,"sourceUrl":13,"achievementId":13,"createdAt":316,"isOpenLicense":15,"licenseTerm":13,"licenseScope":13,"licenseFeeText":13,"licenseFeeNum":13,"patentType":16,"legalStatus":329,"applicationNo":324,"publicationNo":13,"mainIpc":330,"agency":13,"agent":13,"publishOrg":13,"provinceCode":13,"filingDate":13,"isRevitalized":19,"maintainYears":13,"isFunded":13,"implStatus1":13,"implStatus2":13,"willingness1":13,"willingness2":13,"feeWan":13,"intendedCity":13,"intendedCompany":13,"intendedPrice":13,"techMaturity":13,"starRating":13,"gbIndustryClass":13,"strategicClass":13,"productAdv":13,"prospect":13,"comboName":13,"batch":319,"province":21,"sourceText":22,"tags":331,"tagNames":332},"gpi_00742","CN200910066679.3","一种医用快速吸液泡沫材料的制备方法","潘艳雄;王伟财;彭超;罗云霞;姬相玲","本发明涉及一种医用快速吸液泡沫材料的制备方法。将聚乙烯醇水溶液，醛，成孔剂，混合搅拌均匀；再加入酸，继续搅拌，将混合液倒入模具中，固化成型；洗涤，干燥，得到目标物。采用机械打泡和成孔剂配合使用的办法使材料具有丰富的相互贯通的开孔结构；制备的材料生物相容性好，具有优良的亲水性，吸液能力远高于一般的棉纱和纸张，对蒸馏水、生理盐水、尿液具有快速而大量吸收的能力，吸液后成为柔软、强韧、有弹性的海绵。材料耐热、耐紫外线，可用多种方式进行消毒。制备的泡沫材料干态时为硬质泡沫材料，湿态时为柔软的海绵状材料，表观密度0.04－0.09g\u002Fcm3，吸液率1800－2800％，可在医科手术中应用。","A61L15\u002F24;C08F8\u002F28;C08J9\u002F04","2009.08.19#公开;2009.10.14#实质审查的生效;2012.11.14#授权","A61L15\u002F24",[],[],{"id":334,"patentNo":335,"title":336,"applicant":337,"inventors":338,"abstract":339,"ipc":340,"publishDate":13,"sourceUrl":13,"achievementId":13,"createdAt":316,"isOpenLicense":15,"licenseTerm":13,"licenseScope":13,"licenseFeeText":13,"licenseFeeNum":13,"patentType":16,"legalStatus":341,"applicationNo":335,"publicationNo":13,"mainIpc":342,"agency":13,"agent":13,"publishOrg":13,"provinceCode":13,"filingDate":13,"isRevitalized":19,"maintainYears":13,"isFunded":13,"implStatus1":13,"implStatus2":13,"willingness1":13,"willingness2":13,"feeWan":13,"intendedCity":13,"intendedCompany":13,"intendedPrice":13,"techMaturity":13,"starRating":13,"gbIndustryClass":13,"strategicClass":13,"productAdv":13,"prospect":13,"comboName":13,"batch":319,"province":21,"sourceText":22,"tags":343,"tagNames":344},"gpi_01353","CN201010110523.3","一种蒽醌类化合物及其赖氨酸盐的制备方法及医药用途","东北师范大学","李玉新;张玉伟;孟祥颖;鲍永利;林华;郑丽华;乌垠;于春雷","本发明涉及一种蒽醌类化合物楸皮酸及其结构修饰物赖氨楸皮酸，其结构通式如式(1)所示。本发明提供了上述两种化合物的制备方法，蒽醌类化合物楸皮酸为从核桃楸中提取所得，赖氨楸皮酸是将楸皮酸进行结构修饰和改造所得。同时本发明还涉及这两种化合物作为药物，尤其是作为抗肿瘤药物的用途。","C07C66\u002F02;C07C229\u002F26;C07C51\u002F42;C07C227\u002F18;A61K31\u002F192;A61K31\u002F205;A61P35\u002F00;A61P35\u002F02","2010.07.28#公开;2010.09.22#实质审查的生效;2013.11.06#授权","C07C66\u002F02",[],[],39,1,30,2]