该文基于2阶和4阶统计量,提出了空间高斯白噪声和高斯色噪声的背景下联合MUSIC和ESPRIT的双基地MIMO雷达角度估计算法。在接收端,通过单天线的MUSIC算法和双天线的ESPRIT算法分别估计目标的离开方向(Direction Of Departure,DOD)和波达...该文基于2阶和4阶统计量,提出了空间高斯白噪声和高斯色噪声的背景下联合MUSIC和ESPRIT的双基地MIMO雷达角度估计算法。在接收端,通过单天线的MUSIC算法和双天线的ESPRIT算法分别估计目标的离开方向(Direction Of Departure,DOD)和波达方向(Direction Of Arrival,DOA),且DOD和DOA自动配对。该方法充分利用了MIMO雷达阵列孔径扩展的特征和ESPRIT的子空间旋转不变性,将2维参数估计问题转化为两个1维形式,降低了运算量和系统复杂度。计算机仿真验证了该方法的有效性。展开更多
准确测量管道介质声速有助于分析介质的密度和组分,而传统的声速测量方法重复性低、鲁棒性差。为了实现介质声速的准确测量,首先,基于管道一维声波理论推导出线阵列传感器在管道轴向位置的声信号模型,介绍了空气与水的理论声速计算公式...准确测量管道介质声速有助于分析介质的密度和组分,而传统的声速测量方法重复性低、鲁棒性差。为了实现介质声速的准确测量,首先,基于管道一维声波理论推导出线阵列传感器在管道轴向位置的声信号模型,介绍了空气与水的理论声速计算公式以及不同管材、管径和壁厚对声速衰减的影响;其次,采用MUSIC(multiple signal classification)波束形成算法将多通道时域数据转换至波数频率域,呈现出斜率与声速相关的“声学脊”;最后,使用DN50不锈钢管道分别在水和空气流量标准装置上进行声速测量实验,与理论数据相比,水中声速的相对误差为1.61%,重复性为0.45%,空气中声速的相对误差为0.59%,重复性为1.27%。结果表明MUSIC算法可准确测量管道一维声波的介质声速。展开更多
为解决现有辨识方法在针对耦合的次/超同步振荡参数提取过程中的噪声适应性差和模态混叠问题,该文提出了一种自适应的变分模态分解法(variational mode decomposition,VMD),定义残差损失总熵、中心频率的切比雪夫距离以及边缘熵共同决...为解决现有辨识方法在针对耦合的次/超同步振荡参数提取过程中的噪声适应性差和模态混叠问题,该文提出了一种自适应的变分模态分解法(variational mode decomposition,VMD),定义残差损失总熵、中心频率的切比雪夫距离以及边缘熵共同决定分解模态数和带宽,结合最小二乘-旋转不变技术(total least square-estimating signal parameter via rotational invariance techniques,TLS-ESPRIT)对分解出的振荡分量进行参数辨识,无需另外使用降噪算法。通过复合信号测试法、PSCAD/EMTDC电磁暂态仿真法验证了所提方法的有效性。最后,将所提方法与改进Prony算法、MCEEMD法在不同噪声水平和振荡频率下进行对比,结果表明,所提方法能够有效地抑制原始信号的噪声干扰,对耦合的次/超同步振荡信号分解更加准确,参数辨识结果可靠性较高,对风电系统振荡溯源、改善系统阻尼具有一定的参考意义。展开更多
叶端定时是航空发动机叶片叶端振动非接触测量的有效手段,但其采样模式决定了所采信号具有高度欠采样特征,需要进行抗混叠频谱分析从而提取转子叶片固有频率这一关键指标。利用了前向平滑策略的改进多重信号分类法(multiple sIgnal clas...叶端定时是航空发动机叶片叶端振动非接触测量的有效手段,但其采样模式决定了所采信号具有高度欠采样特征,需要进行抗混叠频谱分析从而提取转子叶片固有频率这一关键指标。利用了前向平滑策略的改进多重信号分类法(multiple sIgnal classification,MUSIC)能实现抗混叠但无法充分发挥平滑方法的优势。因此,提出适用于叶端定时信号处理的前后向平滑MUSIC法,通过建立传感器的对称布局条件,利用前后向平滑方法代替前向平滑方法,得到更准确的自相关矩阵估计,进而提高叶片固有频率估计性能,并通过仿真和试验验证了在样本数量、算法参数等相同的情况下,前后向平滑MUSIC法的混叠与噪声抑制能力得到了提升。展开更多
实际变压器局部放电定位过程中放电源数目是未知的,常利用传统高分辨波达方向(direction of arrival,DOA)估计算法解决放电定位问题,但在信源数欠估计、过估计情况下存在定位精度低、误差大的问题。为此,本文提出了一种基于改进盖氏圆(g...实际变压器局部放电定位过程中放电源数目是未知的,常利用传统高分辨波达方向(direction of arrival,DOA)估计算法解决放电定位问题,但在信源数欠估计、过估计情况下存在定位精度低、误差大的问题。为此,本文提出了一种基于改进盖氏圆(geschgorin disk estimator,GDE)准则联合多重信号分类(multiple signal classification,MUSIC)算法的变压器局部放电多目标定位方法。首先,利用改进盖氏圆准则确定真实放电源数目;然后,在信源数确定的情况下利用MUSIC算法对多个局部放电源的波达方向进行估计。仿真结果表明,本方法定位精度高,且在白噪声和空间色噪声的情况下仍能对放电源的俯仰角和方位角进行准确估计,能够满足实际工程需求。展开更多
With the development of new media technology and the popularity of the TikTok platform in China,a large number of popular vocal music teachers have flocked to online platforms for teaching.Online vocal music education...With the development of new media technology and the popularity of the TikTok platform in China,a large number of popular vocal music teachers have flocked to online platforms for teaching.Online vocal music education in China is undergoing a transformation and facing challenges.This study adopts an exploratory research approach,interviewing students learning pop vocal music,and observing popular pop teachers on TikTok.The advantages,disadvantages,techniques,and methods of domestic TikTok pop vocal music teaching were investigated and studied,and a series of experiences and suggestions for optimizing TikTok teaching were put forward.The results of this study are helpful for understanding the advantages and disadvantages of TikTok pop vocal music teaching and grasping the correct development direction.These guidance and suggestions can stimulate teachers’creativity and improve their vocal music teaching level.展开更多
As a unique form of education,music education influences individuals’thoughts,emotions,and overall qualities through the medium of music.It has become an indispensable component of modern educational systems.Whether ...As a unique form of education,music education influences individuals’thoughts,emotions,and overall qualities through the medium of music.It has become an indispensable component of modern educational systems.Whether viewed broadly as an art form that enhances individuals’aesthetic,moral,and humanistic literacy,or narrowly as systematic instruction within school settings,music education plays a crucial role in students’holistic development.It not only cultivates musical literacy but also promotes intellectual,emotional,and social growth.Thus,music education holds significant social and cultural value in fostering creativity,inspiring emotions,and shaping character.展开更多
With the continuous development and maturation of artificial intelligence(AI)technology,the influence on music artists is becoming increasingly prominent.While a large number of musicians have benefited from AI techno...With the continuous development and maturation of artificial intelligence(AI)technology,the influence on music artists is becoming increasingly prominent.While a large number of musicians have benefited from AI technology and achieved considerable success,there are also many who have fallen into difficulties due to the emergence of AI technology.This article expounds the positive and negative impacts that artificial intelligence technology has brought to modern music artists based on the phenomena in reality.This paper will prompt music artists to think about how to use technological means to bring convenience to themselves.At the same time,they will also take a series of actions to avoid risks and minimize the adverse impact of artificial intelligence technology on music artists.展开更多
文摘该文基于2阶和4阶统计量,提出了空间高斯白噪声和高斯色噪声的背景下联合MUSIC和ESPRIT的双基地MIMO雷达角度估计算法。在接收端,通过单天线的MUSIC算法和双天线的ESPRIT算法分别估计目标的离开方向(Direction Of Departure,DOD)和波达方向(Direction Of Arrival,DOA),且DOD和DOA自动配对。该方法充分利用了MIMO雷达阵列孔径扩展的特征和ESPRIT的子空间旋转不变性,将2维参数估计问题转化为两个1维形式,降低了运算量和系统复杂度。计算机仿真验证了该方法的有效性。
文摘准确测量管道介质声速有助于分析介质的密度和组分,而传统的声速测量方法重复性低、鲁棒性差。为了实现介质声速的准确测量,首先,基于管道一维声波理论推导出线阵列传感器在管道轴向位置的声信号模型,介绍了空气与水的理论声速计算公式以及不同管材、管径和壁厚对声速衰减的影响;其次,采用MUSIC(multiple signal classification)波束形成算法将多通道时域数据转换至波数频率域,呈现出斜率与声速相关的“声学脊”;最后,使用DN50不锈钢管道分别在水和空气流量标准装置上进行声速测量实验,与理论数据相比,水中声速的相对误差为1.61%,重复性为0.45%,空气中声速的相对误差为0.59%,重复性为1.27%。结果表明MUSIC算法可准确测量管道一维声波的介质声速。
文摘为解决现有辨识方法在针对耦合的次/超同步振荡参数提取过程中的噪声适应性差和模态混叠问题,该文提出了一种自适应的变分模态分解法(variational mode decomposition,VMD),定义残差损失总熵、中心频率的切比雪夫距离以及边缘熵共同决定分解模态数和带宽,结合最小二乘-旋转不变技术(total least square-estimating signal parameter via rotational invariance techniques,TLS-ESPRIT)对分解出的振荡分量进行参数辨识,无需另外使用降噪算法。通过复合信号测试法、PSCAD/EMTDC电磁暂态仿真法验证了所提方法的有效性。最后,将所提方法与改进Prony算法、MCEEMD法在不同噪声水平和振荡频率下进行对比,结果表明,所提方法能够有效地抑制原始信号的噪声干扰,对耦合的次/超同步振荡信号分解更加准确,参数辨识结果可靠性较高,对风电系统振荡溯源、改善系统阻尼具有一定的参考意义。
文摘叶端定时是航空发动机叶片叶端振动非接触测量的有效手段,但其采样模式决定了所采信号具有高度欠采样特征,需要进行抗混叠频谱分析从而提取转子叶片固有频率这一关键指标。利用了前向平滑策略的改进多重信号分类法(multiple sIgnal classification,MUSIC)能实现抗混叠但无法充分发挥平滑方法的优势。因此,提出适用于叶端定时信号处理的前后向平滑MUSIC法,通过建立传感器的对称布局条件,利用前后向平滑方法代替前向平滑方法,得到更准确的自相关矩阵估计,进而提高叶片固有频率估计性能,并通过仿真和试验验证了在样本数量、算法参数等相同的情况下,前后向平滑MUSIC法的混叠与噪声抑制能力得到了提升。
文摘电磁矢量传感器多输入多输出(electromagnetic vector sensor multiple-input multiple-output,EMVS-MIMO)雷达是一种新兴技术,可实现二维波达角(2D-DOA)估计。针对单基地稀疏阵列EMVS-MIMO雷达,提出一种基于旋转不变性信号参数估计技术ESPRIT(estimation of signal parameters via rotational invariance techniques)的降复杂度(reduced-complexity,RC)信号参数估计算法,能够实现对目标2D-DOA的快速估计。首先,对接收阵列数据进行RC处理,以消除阵列冗余数据;其次,利用ESPRIT可获得高分辨率的俯仰角估计,由于阵列的稀疏性,该估计值具有模糊性;再次,利用矢量叉积技术获得具有无模糊特性的2D-DOA;最后,利用无模糊的俯仰角估计对有周期模糊的估计进行解模糊,获得具有高分辨率、无模糊特性的俯仰角估计。该算法适用于大规模EMVS-MIMO雷达系统,且相比现有的ESPRIT-Like算法拥有更高的估计精度,通过MATLAB仿真验证了算法的有效性。
文摘实际变压器局部放电定位过程中放电源数目是未知的,常利用传统高分辨波达方向(direction of arrival,DOA)估计算法解决放电定位问题,但在信源数欠估计、过估计情况下存在定位精度低、误差大的问题。为此,本文提出了一种基于改进盖氏圆(geschgorin disk estimator,GDE)准则联合多重信号分类(multiple signal classification,MUSIC)算法的变压器局部放电多目标定位方法。首先,利用改进盖氏圆准则确定真实放电源数目;然后,在信源数确定的情况下利用MUSIC算法对多个局部放电源的波达方向进行估计。仿真结果表明,本方法定位精度高,且在白噪声和空间色噪声的情况下仍能对放电源的俯仰角和方位角进行准确估计,能够满足实际工程需求。
文摘With the development of new media technology and the popularity of the TikTok platform in China,a large number of popular vocal music teachers have flocked to online platforms for teaching.Online vocal music education in China is undergoing a transformation and facing challenges.This study adopts an exploratory research approach,interviewing students learning pop vocal music,and observing popular pop teachers on TikTok.The advantages,disadvantages,techniques,and methods of domestic TikTok pop vocal music teaching were investigated and studied,and a series of experiences and suggestions for optimizing TikTok teaching were put forward.The results of this study are helpful for understanding the advantages and disadvantages of TikTok pop vocal music teaching and grasping the correct development direction.These guidance and suggestions can stimulate teachers’creativity and improve their vocal music teaching level.
文摘As a unique form of education,music education influences individuals’thoughts,emotions,and overall qualities through the medium of music.It has become an indispensable component of modern educational systems.Whether viewed broadly as an art form that enhances individuals’aesthetic,moral,and humanistic literacy,or narrowly as systematic instruction within school settings,music education plays a crucial role in students’holistic development.It not only cultivates musical literacy but also promotes intellectual,emotional,and social growth.Thus,music education holds significant social and cultural value in fostering creativity,inspiring emotions,and shaping character.
文摘With the continuous development and maturation of artificial intelligence(AI)technology,the influence on music artists is becoming increasingly prominent.While a large number of musicians have benefited from AI technology and achieved considerable success,there are also many who have fallen into difficulties due to the emergence of AI technology.This article expounds the positive and negative impacts that artificial intelligence technology has brought to modern music artists based on the phenomena in reality.This paper will prompt music artists to think about how to use technological means to bring convenience to themselves.At the same time,they will also take a series of actions to avoid risks and minimize the adverse impact of artificial intelligence technology on music artists.
