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Aquaporin-4-IgG-seropositive neuromyelitis optica spectrum disorders:progress of experimental models based on disease pathogenesis
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作者 Li Xu Huiming Xu Changyong Tang 《Neural Regeneration Research》 SCIE CAS 2025年第2期354-365,共12页
Neuromyelitis optica spectrum disorders are neuroinflammatory demyelinating disorders that lead to permanent visual loss and motor dysfunction.To date,no effective treatment exists as the exact causative mechanism rem... Neuromyelitis optica spectrum disorders are neuroinflammatory demyelinating disorders that lead to permanent visual loss and motor dysfunction.To date,no effective treatment exists as the exact causative mechanism remains unknown.Therefore,experimental models of neuromyelitis optica spectrum disorders are essential for exploring its pathogenesis and in screening for therapeutic targets.Since most patients with neuromyelitis optica spectrum disorders are seropositive for IgG autoantibodies against aquaporin-4,which is highly expressed on the membrane of astrocyte endfeet,most current experimental models are based on aquaporin-4-IgG that initially targets astrocytes.These experimental models have successfully simulated many pathological features of neuromyelitis optica spectrum disorders,such as aquaporin-4 loss,astrocytopathy,granulocyte and macrophage infiltration,complement activation,demyelination,and neuronal loss;however,they do not fully capture the pathological process of human neuromyelitis optica spectrum disorders.In this review,we summarize the currently known pathogenic mechanisms and the development of associated experimental models in vitro,ex vivo,and in vivo for neuromyelitis optica spectrum disorders,suggest potential pathogenic mechanisms for further investigation,and provide guidance on experimental model choices.In addition,this review summarizes the latest information on pathologies and therapies for neuromyelitis optica spectrum disorders based on experimental models of aquaporin-4-IgG-seropositive neuromyelitis optica spectrum disorders,offering further therapeutic targets and a theoretical basis for clinical trials. 展开更多
关键词 AQUAPORIN-4 experimental model neuromyelitis optica spectrum disorder PATHOGENESIS
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Exploiting fly models to investigate rare human neurological disorders
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作者 Tomomi Tanaka Hyung-Lok Chung 《Neural Regeneration Research》 SCIE CAS 2025年第1期21-28,共8页
Rare neurological diseases,while individually are rare,collectively impact millions globally,leading to diverse and often severe neurological symptoms.Often attributed to genetic mutations that disrupt protein functio... Rare neurological diseases,while individually are rare,collectively impact millions globally,leading to diverse and often severe neurological symptoms.Often attributed to genetic mutations that disrupt protein function or structure,understanding their genetic basis is crucial for accurate diagnosis and targeted therapies.To investigate the underlying pathogenesis of these conditions,researchers often use non-mammalian model organisms,such as Drosophila(fruit flies),which is valued for their genetic manipulability,cost-efficiency,and preservation of genes and biological functions across evolutionary time.Genetic tools available in Drosophila,including CRISPR-Cas9,offer a means to manipulate gene expression,allowing for a deep exploration of the genetic underpinnings of rare neurological diseases.Drosophila boasts a versatile genetic toolkit,rapid generation turnover,and ease of large-scale experimentation,making it an invaluable resource for identifying potential drug candidates.Researchers can expose flies carrying disease-associated mutations to various compounds,rapidly pinpointing promising therapeutic agents for further investigation in mammalian models and,ultimately,clinical trials.In this comprehensive review,we explore rare neurological diseases where fly research has significantly contributed to our understanding of their genetic basis,pathophysiology,and potential therapeutic implications.We discuss rare diseases associated with both neuron-expressed and glial-expressed genes.Specific cases include mutations in CDK19 resulting in epilepsy and developmental delay,mutations in TIAM1 leading to a neurodevelopmental disorder with seizures and language delay,and mutations in IRF2BPL causing seizures,a neurodevelopmental disorder with regression,loss of speech,and abnormal movements.And we explore mutations in EMC1 related to cerebellar atrophy,visual impairment,psychomotor retardation,and gain-of-function mutations in ACOX1 causing Mitchell syndrome.Loss-of-function mutations in ACOX1 result in ACOX1 deficiency,characterized by very-long-chain fatty acid accumulation and glial degeneration.Notably,this review highlights how modeling these diseases in Drosophila has provided valuable insights into their pathophysiology,offering a platform for the rapid identification of potential therapeutic interventions.Rare neurological diseases involve a wide range of expression systems,and sometimes common phenotypes can be found among different genes that cause abnormalities in neurons or glia.Furthermore,mutations within the same gene may result in varying functional outcomes,such as complete loss of function,partial loss of function,or gain-of-function mutations.The phenotypes observed in patients can differ significantly,underscoring the complexity of these conditions.In conclusion,Drosophila represents an indispensable and cost-effective tool for investigating rare neurological diseases.By facilitating the modeling of these conditions,Drosophila contributes to a deeper understanding of their genetic basis,pathophysiology,and potential therapies.This approach accelerates the discovery of promising drug candidates,ultimately benefiting patients affected by these complex and understudied diseases. 展开更多
关键词 ACOX1 Drosophila melanogaster GLIA lipid metabolism model organisms NEUROINFLAMMATION neurologic disorders NEURON rare disease VLCFA
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A promising approach for quantifying focal stroke modeling and assessing stroke progression:optical resolution photoacoustic microscopy photothrombosis
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作者 Xiao Liang Xingping Quan +6 位作者 Xiaorui Geng Yujing Huang Yonghua Zhao Lei Xi Zhen Yuan Ping Wang Bin Liu 《Neural Regeneration Research》 SCIE CAS 2025年第7期2029-2037,共9页
To investigate the mechanisms underlying the onset and progression of ischemic stroke,some methods have been proposed that can simultaneously monitor and create embolisms in the animal cerebral cortex.However,these me... To investigate the mechanisms underlying the onset and progression of ischemic stroke,some methods have been proposed that can simultaneously monitor and create embolisms in the animal cerebral cortex.However,these methods often require complex systems and the effect of age on cerebral embolism has not been adequately studied,although ischemic stroke is strongly age-related.In this study,we propose an optical-resolution photoacoustic microscopy-based visualized photothrombosis methodology to create and monitor ischemic stroke in mice simultaneously using a 532 nm pulsed laser.We observed the molding process in mice of different ages and presented age-dependent vascular embolism differentiation.Moreover,we integrated optical coherence tomography angiography to investigate age-associated trends in cerebrovascular variability following a stroke.Our imaging data and quantitative analyses underscore the differential cerebrovascular responses to stroke in mice of different ages,thereby highlighting the technique's potential for evaluating cerebrovascular health and unraveling age-related mechanisms involved in ischemic strokes. 展开更多
关键词 AGE-DEPENDENT cerebral cortex ischemic stroke mouse model optical coherence tomography angiography photoacoustic microscopy PHOTOTHROMBOSIS vascular imaging
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Reduced mesencephalic astrocyte-derived neurotrophic factor expression by mutant androgen receptor contributes to neurodegeneration in a model of spinal and bulbar muscular atrophy pathology
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作者 Yiyang Qin Wenzhen Zhu +6 位作者 Tingting Guo Yiran Zhang Tingting Xing Peng Yin Shihua Li Xiao-Jiang Li Su Yang 《Neural Regeneration Research》 SCIE CAS 2025年第9期2655-2666,共12页
Spinal and bulbar muscular atrophy is a neurodegenerative disease caused by extended CAG trinucleotide repeats in the androgen receptor gene,which encodes a ligand-dependent transcription facto r.The mutant androgen r... Spinal and bulbar muscular atrophy is a neurodegenerative disease caused by extended CAG trinucleotide repeats in the androgen receptor gene,which encodes a ligand-dependent transcription facto r.The mutant androgen receptor protein,characterized by polyglutamine expansion,is prone to misfolding and forms aggregates in both the nucleus and cytoplasm in the brain in spinal and bulbar muscular atrophy patients.These aggregates alter protein-protein interactions and compromise transcriptional activity.In this study,we reported that in both cultured N2a cells and mouse brain,mutant androgen receptor with polyglutamine expansion causes reduced expression of mesencephalic astrocyte-de rived neurotrophic factor.Overexpressio n of mesencephalic astrocyte-derived neurotrophic factor amelio rated the neurotoxicity of mutant androgen receptor through the inhibition of mutant androgen receptor aggregation.Conversely.knocking down endogenous mesencephalic astrocyte-derived neurotrophic factor in the mouse brain exacerbated neuronal damage and mutant androgen receptor aggregation.Our findings suggest that inhibition of mesencephalic astrocyte-derived neurotrophic factor expression by mutant androgen receptor is a potential mechanism underlying neurodegeneration in spinal and bulbar muscular atrophy. 展开更多
关键词 androgen receptor mesencephalic astrocyte-derived neurotrophic factor mouse model NEURODEGENERATION neuronal loss neurotrophic factor polyglutamine disease protein misfolding spinal and bulbar muscular atrophy transcription factor
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基于SVD-CWT和CNN的水轮发电机转子故障识别 被引量:1
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作者 张彬桥 刘雷 +1 位作者 杨洋 侯成伟 《中国农村水利水电》 北大核心 2024年第2期205-209,共5页
水轮发电机转子振动故障识别是水电站运维的重难点问题,为此提出一种基于转子振动信号的故障识别方法。首先针对发电机转子的非平稳和非线性振动信号,采用奇异值分解(SVD)并结合能量差分谱理论进行降噪预处理;对预处理数据使用连续小波... 水轮发电机转子振动故障识别是水电站运维的重难点问题,为此提出一种基于转子振动信号的故障识别方法。首先针对发电机转子的非平稳和非线性振动信号,采用奇异值分解(SVD)并结合能量差分谱理论进行降噪预处理;对预处理数据使用连续小波变换(CWT)转换为时频图并形成图像数据集;然后将该图像数据集作为卷积神经网络(CNN)输入,通过CNN多层池化及卷积形成分布式故障特征表达,最终实现发电机转子故障模式识别和分类。经实验验证,该方法准确率达到99.5%以上,能有效识别出发电机转子的故障类型。 展开更多
关键词 水轮发电机转子 故障识别 svd CWT 卷积神经网络
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基于向量残差SVD的混凝土超声测试温度效应研究
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作者 郑罡 陈鹏 +2 位作者 彭宇 于吉港 陈伟基 《重庆大学学报》 CAS CSCD 北大核心 2024年第6期15-23,共9页
为研究温度对混凝土超声测试尾波信号的影响规律;将信号向量间的归一化夹角作为波动指标,反映温度效应引起的信号变化;通过向量残差矩阵SVD获得表征温度效应大小的特征向量,建立向量空间映射和温度差的数学关系。在实验室采集混凝土梁... 为研究温度对混凝土超声测试尾波信号的影响规律;将信号向量间的归一化夹角作为波动指标,反映温度效应引起的信号变化;通过向量残差矩阵SVD获得表征温度效应大小的特征向量,建立向量空间映射和温度差的数学关系。在实验室采集混凝土梁尾波信号进行验证,结果表明,随温度升高尾波信号的波形发生后移,文中方法可分段线性量化温度效应;基于量化结果,得到常温下超声尾波信号最敏感的温度区间;任意4.5℃范围内,可去除74%~90%的温度效应。 展开更多
关键词 向量残差 svd 温度效应 混凝土 超声波
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基于DK-SVD的深度学习电阻抗块稀疏成像方法研究
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作者 王琦 杨雨晗 +4 位作者 李秀艳 段晓杰 汪剑鸣 孙玉宽 冯慧 《计量学报》 CSCD 北大核心 2024年第9期1370-1377,共8页
针对电阻抗层析成像逆问题的病态性和非线性,提出一种基于DK-SVD的电阻抗块稀疏图像重建方法。该算法通过多层感知器为每组测量数据提供最优的模型参数,以适应数据集的多样性,进一步提高成像质量,并在稀疏编码阶段采用迭代收缩阈值算法... 针对电阻抗层析成像逆问题的病态性和非线性,提出一种基于DK-SVD的电阻抗块稀疏图像重建方法。该算法通过多层感知器为每组测量数据提供最优的模型参数,以适应数据集的多样性,进一步提高成像质量,并在稀疏编码阶段采用迭代收缩阈值算法加快收敛速度。仿真实验结果表明DK-SVD算法重建图像的结构相似性可达到0.95以上,误差可控制在0.1左右,平均重建速度为0.034 s,有效地提高了电阻抗层析成像的质量和效率,且经进一步实验证明了该算法具有良好的噪声鲁棒性和实际应用价值。 展开更多
关键词 电学计量 电阻抗层析成像 块稀疏 DK-svd 图像重建 深度学习
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采用STAMP-24Model的多组织事故分析
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作者 曾明荣 秦永莹 +2 位作者 刘小航 栗婧 尚长岭 《安全与环境学报》 CAS CSCD 北大核心 2024年第7期2741-2750,共10页
安全生产事故往往由多组织交互、多因素耦合造成,事故原因涉及多个组织。为预防和遏制多组织生产安全事故的发生,基于系统理论事故建模与过程模型(Systems-Theory Accident Modeling and Process,STAMP)、24Model,构建一种用于多组织事... 安全生产事故往往由多组织交互、多因素耦合造成,事故原因涉及多个组织。为预防和遏制多组织生产安全事故的发生,基于系统理论事故建模与过程模型(Systems-Theory Accident Modeling and Process,STAMP)、24Model,构建一种用于多组织事故分析的方法,并以青岛石油爆炸事故为例进行事故原因分析。结果显示:STAMP-24Model可以分组织,分层次且有效、全面、详细地分析涉及多个组织的事故原因,探究多组织之间的交互关系;对事故进行动态演化分析,可得到各组织不安全动作耦合关系与形成的事故失效链及管控失效路径,进而为预防多组织事故提供思路和参考。 展开更多
关键词 安全工程 系统理论事故建模与过程模型(STAMP) 24model 多组织事故 原因分析
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基于改进24Model-ISM-SNA建筑工人不安全行为关联路径研究
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作者 赵平 刘钰 +1 位作者 靳丽艳 王佳慧 《工业安全与环保》 2024年第7期37-40,共4页
建筑施工现场环境复杂,为有效控制不安全行为发生,基于行为安全“2-4”模型对360份具有代表性的建筑安全事故调查报告进行分析,提取出22个不安全行为的主要影响因素。利用灰色关联分析方法(GRA)改进的集成ISM-SNA模型,将不安全行为风险... 建筑施工现场环境复杂,为有效控制不安全行为发生,基于行为安全“2-4”模型对360份具有代表性的建筑安全事故调查报告进行分析,提取出22个不安全行为的主要影响因素。利用灰色关联分析方法(GRA)改进的集成ISM-SNA模型,将不安全行为风险因素划分为表层、过渡层与深层,然后对风险因素进行可视化分析、中心度分析及凝聚子群分析,揭示了各致因因素间的关联关系和传导路径。结果表明,建筑工人不安全行为影响因素可划分成7级3阶的多级递阶结构,安全意识、现场监管、外部环境是建筑工人不安全行为的关键影响因素,同时现场监管和隐患排查到位能有效降低不安全行为的发生。 展开更多
关键词 建筑工人 不安全行为 24model 解释结构模型(ISM) 社会网络分析(SNA)
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基于24Model的地铁内涝事故原因分析与评估
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作者 张江石 胡馨月 +3 位作者 侯轩 李泳暾 李梓萌 高进东 《安全与环境工程》 CAS CSCD 北大核心 2024年第6期111-117,共7页
为降低地铁内涝事故灾害风险,基于事故致因“2-4”模型,分析了地铁内涝事故致灾因子,采用层次分析法构建了地铁内涝事故原因分析指标体系,确定了各风险因子的权重,并利用模糊综合评价法对地铁内涝事故进行了定量评估,识别出关键的影响... 为降低地铁内涝事故灾害风险,基于事故致因“2-4”模型,分析了地铁内涝事故致灾因子,采用层次分析法构建了地铁内涝事故原因分析指标体系,确定了各风险因子的权重,并利用模糊综合评价法对地铁内涝事故进行了定量评估,识别出关键的影响因素。结果表明:地铁内涝事故一级指标中不安全动作与物态因素最重要,其中影响最大的指标包括擅自更改建筑设计、未按照要求检查水位情况、未及时排水、出入口不符合防汛标准等因素;习惯性不安全行为的权重位居第二,表明该指标因素较为重要,同时安全管理体系得分位居第二,表明该指标因素较易发生。对关键指标采取防范措施,可有效降低风险,从而减少地铁内涝事故的发生。 展开更多
关键词 安全工程 地铁内涝 24model 层次分析法 模糊综合评价法
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基于自适应动态粒子群优化的RAK-SVD方法
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作者 乐友喜 姚晓辰 +1 位作者 付俊楠 葛传友 《石油地球物理勘探》 EI CSCD 北大核心 2024年第3期494-503,共10页
K均值奇异值分解(K-SVD)算法是一种行之有效的地震资料去噪方法,但由于其稀疏分解存在不确定性,需要引入正则项对其改进。为此,在常规粒子群算法的基础上,提出了一种自适应动态粒子群算法优化正则化参数的正则化近似K-SVD(RAK-SVD)去噪... K均值奇异值分解(K-SVD)算法是一种行之有效的地震资料去噪方法,但由于其稀疏分解存在不确定性,需要引入正则项对其改进。为此,在常规粒子群算法的基础上,提出了一种自适应动态粒子群算法优化正则化参数的正则化近似K-SVD(RAK-SVD)去噪方法。首先通过修改字典原子和相关参数,解决了由于常规粒子群算法的惯性参数固定不变,导致后期搜索效率下降的问题;其次将正则化系数引入近似K-SVD(AK-SVD)方法,明显提升了去噪效果;最后利用自适应动态粒子群算法自动优选AK-SVD方法中的正则化参数,提高了稀疏分解的确定性,在对强反射信号进行去噪的同时加强了对弱信号的保护。模型测试和实际应用均表明,该方法有利于弱信号的提取和识别,不仅能够显著改善弱地震信号的去噪效果,还提升了计算效率。该方法具有一定的实际应用价值。 展开更多
关键词 自适应动态粒子群算法 K-svd字典 正则化 去噪
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基于24Model-D-ISM的地铁站火灾疏散影响因素研究
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作者 孙世梅 张家严 《中国安全科学学报》 CAS CSCD 北大核心 2024年第4期153-159,共7页
为预防地铁站火灾事故,深入了解地铁站火灾人员疏散影响因素间的内在联系与层次结构,基于第6版“2-4”模型(24Model)分析63起地铁站火灾疏散事故,充分考虑各个因素之间的交互作用,提取19个影响地铁站人员疏散的关键因素,建立地铁站火灾... 为预防地铁站火灾事故,深入了解地铁站火灾人员疏散影响因素间的内在联系与层次结构,基于第6版“2-4”模型(24Model)分析63起地铁站火灾疏散事故,充分考虑各个因素之间的交互作用,提取19个影响地铁站人员疏散的关键因素,建立地铁站火灾人员疏散影响因素指标体系;采用算子客观赋权法(C-OWA)改进决策试验与评价实验法(DEMATEL),确定地铁站火灾人员疏散的重要影响因素;在此基础上,采用解释结构模型(ISM)分析各个因素间的层次结构及相互作用路径,构建地铁站火灾人员疏散影响因素的多级递阶结构模型。研究结果表明:疏散引导、恐慌从众行为、人员拥挤为地铁站火灾人员疏散的关键影响因素;地铁站火灾人员疏散受表层因素、中间层因素、深层因素共同作用的影响,其中,疏散教育与培训、设施维护与检查、疏散预案等因素是根源影响因素,重视根源影响因素的改善有利于从本质上预防和控制事故的发生。 展开更多
关键词 “2-4”模型(24model) 决策试验与评价实验法(DEMATEL) 解释结构模型(ISM) 地铁站 火灾疏散 影响因素
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基于SVD-ILMD的暂态电能质量扰动定位检测方法
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作者 程江洲 张志强 +3 位作者 闫冉阳 李小来 谢卓然 胡哲豪 《浙江电力》 2024年第8期1-11,共11页
为实现对电网非平稳扰动信号的快速、准确分析,提出了融合SVD(奇异值分解)与ILMD(优化局部均值分解)的暂态电能质量扰动定位检测方法。首先,通过ILMD与模糊隶属度函数阈值处理噪声信息,削弱噪声干扰;然后,构造差值信号并利用滑窗SVD增... 为实现对电网非平稳扰动信号的快速、准确分析,提出了融合SVD(奇异值分解)与ILMD(优化局部均值分解)的暂态电能质量扰动定位检测方法。首先,通过ILMD与模糊隶属度函数阈值处理噪声信息,削弱噪声干扰;然后,构造差值信号并利用滑窗SVD增强扰动特征,进一步抑制噪声干扰;最后,基于特征增强信号提出一种自适应阈值截断的暂态电能质量扰动定位检测方法。经仿真分析与算法对比,验证了所提方法定位准确、抗噪性强、计算量小,对过零与微弱扰动也有较好的定位效果。 展开更多
关键词 暂态电能质量 扰动定位检测 差值信号 奇异值分解 局部均值分解
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基于SVD和1DCNN的滚动轴承故障诊断
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作者 闫锋 肖成军 孙一伟 《中国民航飞行学院学报》 2024年第5期37-42,共6页
为实现轴承故障的诊断,本文提出一种基于奇异值分解(SVD)和一维卷积神经网络(1DCNN)的分类算法,即将一维信号转为二维数据并重构,建立检测模型,将重构信号和原始信号分别输入1DCNN模型检测,最后通过混淆矩阵和准确率评估模型。结果显示,... 为实现轴承故障的诊断,本文提出一种基于奇异值分解(SVD)和一维卷积神经网络(1DCNN)的分类算法,即将一维信号转为二维数据并重构,建立检测模型,将重构信号和原始信号分别输入1DCNN模型检测,最后通过混淆矩阵和准确率评估模型。结果显示,SVD结合1DCNN模型比传统1DCNN模型在不同工况下的准确率提高了1.57%和0.4%,具有一定参考价值。 展开更多
关键词 滚动轴承 故障诊断 奇异值分解 一维卷积神经网络
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基于APSO-SSD-SVD的特高压换流站OLTC振动信号降噪方法
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作者 骆钊 张涛 +3 位作者 阮彦俊 石延辉 林铭良 张杨 《电力系统保护与控制》 EI CSCD 北大核心 2024年第21期13-23,共11页
随着中国特高压交直流换流站的大规模投运,有载分接开关(on-load tap changer, OLTC)已成为特高压换流站中发生故障较多的设备之一。针对强背景噪声环境下特高压换流站OLTC故障特征难以提取的问题,提出一种基于自适应粒子群算法优化奇... 随着中国特高压交直流换流站的大规模投运,有载分接开关(on-load tap changer, OLTC)已成为特高压换流站中发生故障较多的设备之一。针对强背景噪声环境下特高压换流站OLTC故障特征难以提取的问题,提出一种基于自适应粒子群算法优化奇异谱分解和奇异值分解的方法。首先,利用自适应粒子群优化(adaptive particle swarm optimization, APSO)算法对奇异谱分解算法中的模态参数进行优化,选取最优分解模态数。其次,基于最大峭度准则选取最佳奇异谱分量。然后,确定最佳重构阶数,通过奇异值分解重构信号,从而达到信号降噪的目的。将所提方法应用于仿真信号和实验信号,结果表明所提方法的信噪比达到23.302,均方根误差仅为0.004,并且波形相似参数高达0.998,优于其他降噪方法。所提方法能够更有效地实现对特高压换流站OLTC振动信号的降噪,为辅助运维人员诊断OLTC状态提供参考。 展开更多
关键词 有载分接开关 自适应粒子群优化算法 奇异谱分解 奇异值分解 精细复合多尺度散布熵 信号降噪
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基于CRS-LMD和SVD的MMC-HVDC线路故障测距方法 被引量:3
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作者 贺宇阳 马千里 +1 位作者 于飞 刘喜梅 《电力系统保护与控制》 EI CSCD 北大核心 2024年第1期121-132,共12页
直流输电线路故障行波波速不确定、波头提取困难以及噪声干扰等因素制约了直流电网中故障测距技术的应用。为了降低上述因素对定位准确性的影响,提出一种基于局部特征有理样条插值均值分解(LMD based on characteristic rational spline... 直流输电线路故障行波波速不确定、波头提取困难以及噪声干扰等因素制约了直流电网中故障测距技术的应用。为了降低上述因素对定位准确性的影响,提出一种基于局部特征有理样条插值均值分解(LMD based on characteristic rational spline,CRS-LMD)和奇异值分解(singular value decomposition,SVD)的故障测距方法。首先,利用特征尺度选取最优极点系数,结合有理样条插值调节拟合曲线的松紧程度,实现对故障电压行波的局部均值分解。其次,采用奇异值分解对故障行波波头进行准确提取。最后,在PSCAD/EMTDC中搭建了张北±500 kV柔性直流电网的仿真模型,模拟各种故障情况并输出故障数据,利用Matlab对故障数据进行处理并验证定位算法。最后,仿真结果表明,所提故障测距算法在不同故障距离和故障类型下均能实现故障测距,且在叠加噪声和过渡电阻的情况下也能保障较高的精确性。 展开更多
关键词 串柔性直流电网 有理样条插值 局部均值分解 奇异值分解 行波提取 故障测距
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24Model与LCM原因因素定义对比研究 被引量:2
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作者 袁晨辉 傅贵 +1 位作者 吴治蓉 赵金坤 《中国安全科学学报》 CAS CSCD 北大核心 2024年第1期27-34,共8页
为探究损失致因模型(LCM)原因因素定义与事故致因“2-4”模型(24Model)存在的异同和优缺点,梳理2个模型各层面原因和结果的定义,对比定义内容及其对事故原因分析等安全实务的指导作用,并以一起瓦斯爆炸事故为例加以实证分析,获得二者分... 为探究损失致因模型(LCM)原因因素定义与事故致因“2-4”模型(24Model)存在的异同和优缺点,梳理2个模型各层面原因和结果的定义,对比定义内容及其对事故原因分析等安全实务的指导作用,并以一起瓦斯爆炸事故为例加以实证分析,获得二者分析结果之间的差异。研究结果表明:LCM是首个将管理因素纳入事故致因分析的一维事件序列模型,可明确各层面原因因素的定义和因素间的逻辑关系,但部分定义存在交叉重复的问题,并没有揭示安全工作指导思想等深层次事故致因因素;24Model作为系统性事故致因模型,对各类因素的定义均以组织为主体,描述事件、事故、安全的概念内涵,划分个体安全动作、安全能力和组织安全管理体系的类别并给出含义解析,探究组织安全文化层面的问题并以32个元素体现;2个模型的事故原因分析方法均建立在对各层级原因因素定义的基础上,并适用于模型理论体系本身。 展开更多
关键词 “2-4”模型(24model) 损失致因模型(LCM) 事故致因模型 原因因素定义 对比研究
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Evaluation and Improvement of a SVD-Based Empirical Atmospheric Model 被引量:1
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作者 余嘉裕 张振玮 涂建翊 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2011年第3期636-652,共17页
An empirical atmospheric model(EAM) based on the singular value decomposition(SVD) method is evaluated using the composite El Ni(?)o/Southern Oscillation(ENSO) patterns of sea surface temperature (SST) and wind anomal... An empirical atmospheric model(EAM) based on the singular value decomposition(SVD) method is evaluated using the composite El Ni(?)o/Southern Oscillation(ENSO) patterns of sea surface temperature (SST) and wind anomalies as the target scenario.Two versions of the SVD-based EAM were presented for comparisons.The first version estimates the wind anomalies in response to SST variations based on modes that were calculated from a pair of global wind and SST fields(i.e.,conventional EAM or CEAM).The second version utilizes the same model design but is based on modes that were calculated in a region-wise manner by separating the tropical domain from the remaining extratropical regions(i.e.,region-wise EAM or REAM). Our study shows that,while CEAM has shown successful model performance over some tropical areas, such as the equatorial eastern Pacific(EEP),the western North Pacific(WNP),and the tropical Indian Ocean(TIO),its performance over the North Pacific(NP) seems poor.When REAM is used to estimate the wind anomalies instead of CEAM,a marked improvement over NP readily emerges.Analyses of coupled modes indicate that such an improvement can be attributed to a much stronger coupled variability captured by the first region-wise SVD mode at higher latitudes compared with that captured by the conventional one. The newly proposed way of constructing the EAM(i.e.,REAM) can be very useful in the coupled studies because it gives the model a wider application beyond the commonly accepted tropical domain. 展开更多
关键词 singular value decomposition empirical atmospheric model coupled variability
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基于SVD-K-means算法的软扩频信号伪码序列盲估计 被引量:1
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作者 张慧芝 张天骐 +1 位作者 方蓉 罗庆予 《系统工程与电子技术》 EI CSCD 北大核心 2024年第1期326-333,共8页
针对通信中软扩频信号伪码序列盲估计困难的问题,提出一种奇异值分解(singular value decomposition,SVD)和K-means聚类相结合的方法。该方法先对接收信号按照一倍伪码周期进行不重叠分段构造数据矩阵。其次对数据矩阵和相似性矩阵分别... 针对通信中软扩频信号伪码序列盲估计困难的问题,提出一种奇异值分解(singular value decomposition,SVD)和K-means聚类相结合的方法。该方法先对接收信号按照一倍伪码周期进行不重叠分段构造数据矩阵。其次对数据矩阵和相似性矩阵分别进行SVD完成对伪码序列集合规模数的估计、数据降噪、粗分类以及初始聚类中心的选取。最后通过K-means算法优化分类结果,得到伪码序列的估计值。该算法在聚类之前事先确定聚类数目,大大减少了迭代次数。同时实验结果表明,该算法在信息码元分组小于5 bit,信噪比大于-10 dB时可以准确估计出软扩频信号的伪码序列,性能较同类算法有所提升。 展开更多
关键词 软扩频信号 盲估计 奇异值分解 K-MEANS
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Anisotropic time-dependent behaviors of shale under direct shearing and associated empirical creep models 被引量:3
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作者 Yachen Xie Michael Z.Hou +1 位作者 Hejuan Liu Cunbao Li 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2024年第4期1262-1279,共18页
Understanding the anisotropic creep behaviors of shale under direct shearing is a challenging issue.In this context,we conducted shear-creep and steady-creep tests on shale with five bedding orientations (i.e.0°,... Understanding the anisotropic creep behaviors of shale under direct shearing is a challenging issue.In this context,we conducted shear-creep and steady-creep tests on shale with five bedding orientations (i.e.0°,30°,45°,60°,and 90°),under multiple levels of direct shearing for the first time.The results show that the anisotropic creep of shale exhibits a significant stress-dependent behavior.Under a low shear stress,the creep compliance of shale increases linearly with the logarithm of time at all bedding orientations,and the increase depends on the bedding orientation and creep time.Under high shear stress conditions,the creep compliance of shale is minimal when the bedding orientation is 0°,and the steady-creep rate of shale increases significantly with increasing bedding orientations of 30°,45°,60°,and 90°.The stress-strain values corresponding to the inception of the accelerated creep stage show an increasing and then decreasing trend with the bedding orientation.A semilogarithmic model that could reflect the stress dependence of the steady-creep rate while considering the hardening and damage process is proposed.The model minimizes the deviation of the calculated steady-state creep rate from the observed value and reveals the behavior of the bedding orientation's influence on the steady-creep rate.The applicability of the five classical empirical creep models is quantitatively evaluated.It shows that the logarithmic model can well explain the experimental creep strain and creep rate,and it can accurately predict long-term shear creep deformation.Based on an improved logarithmic model,the variations in creep parameters with shear stress and bedding orientations are discussed.With abovementioned findings,a mathematical method for constructing an anisotropic shear creep model of shale is proposed,which can characterize the nonlinear dependence of the anisotropic shear creep behavior of shale on the bedding orientation. 展开更多
关键词 Rock anisotropy Direct shear creep Creep compliance Steady-creep rate Empirical model Creep constitutive model
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