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Short-Term Prediction of Photovoltaic Power Generation Based on LMD Permutation Entropy and Singular Spectrum Analysis
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作者 Wenchao Ma 《Energy Engineering》 EI 2023年第7期1685-1699,共15页
The power output state of photovoltaic power generation is affected by the earth’s rotation and solar radiation intensity.On the one hand,its output sequence has daily periodicity;on the other hand,it has discrete ra... The power output state of photovoltaic power generation is affected by the earth’s rotation and solar radiation intensity.On the one hand,its output sequence has daily periodicity;on the other hand,it has discrete randomness.With the development of new energy economy,the proportion of photovoltaic energy increased accordingly.In order to solve the problem of improving the energy conversion efficiency in the grid-connected optical network and ensure the stability of photovoltaic power generation,this paper proposes the short-termprediction of photovoltaic power generation based on the improvedmulti-scale permutation entropy,localmean decomposition and singular spectrum analysis algorithm.Firstly,taking the power output per unit day as the research object,the multi-scale permutation entropy is used to calculate the eigenvectors under different weather conditions,and the cluster analysis is used to reconstruct the historical power generation under typical weather rainy and snowy,sunny,abrupt,cloudy.Then,local mean decomposition(LMD)is used to decompose the output sequence,so as to extract more detail components of the reconstructed output sequence.Finally,combined with the weather forecast of the Meteorological Bureau for the next day,the singular spectrumanalysis algorithm is used to predict the photovoltaic classification of the recombination decomposition sequence under typical weather.Through the verification and analysis of examples,the hierarchical prediction experiments of reconstructed and non-reconstructed output sequences are compared.The results show that the algorithm proposed in this paper is effective in realizing the short-term prediction of photovoltaic generator,and has the advantages of simple structure and high prediction accuracy. 展开更多
关键词 Photovoltaic power generation short term forecast multiscale permutation entropy local mean decomposition singular spectrum analysis
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Impact Analysis of the 2011 Fukushima Nuclear Power Plant Accidents by Running Spectrum Analysis on Newspaper
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作者 Muneyoshi Numada and Kimiro Meguro 《Journal of Geological Resource and Engineering》 2013年第1期1-10,共10页
Huge amount of digital data of the Great East Japan Earthquake is provided by the highly-developed digital data technology. But the method and technique for analysis of these huge digital data are not developed suffic... Huge amount of digital data of the Great East Japan Earthquake is provided by the highly-developed digital data technology. But the method and technique for analysis of these huge digital data are not developed sufficiently. This paper proposes a running spectrum technique for text data and analyzing changes of disaster phase during the disaster management cycle. Impact analysis of the nuclear power plant accidents have been performed by using Fukushima Minpo newspaper for its verification. The result shows the dynamic characteristics of the nuclear power plant accidents. As the time interval B becomes longer, the analysis data is used from wide range period along with the smoothing effect. When observing different time intervals B, fewer keywords have been ranked in the longer time intervals of B. The proposed technique is a powerful tool to effective and efficient disaster response and management. analyze effectively the huge amount of digital data for the 展开更多
关键词 Impact analysis Fukushima nuclear power plant accident running spectrum analysis newspaper.
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Spectrum analysis of interval process model and its application in uncertain vibration analysis
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作者 LI JinWu JIANG Chao NI BingYu 《Science China(Technological Sciences)》 SCIE EI CAS CSCD 2024年第8期2549-2564,共16页
In recent years, the authors have extended the traditional interval method into the time dimension to develop a new mathematical tool called the “interval process model” for quantifying time-varying or dynamic uncer... In recent years, the authors have extended the traditional interval method into the time dimension to develop a new mathematical tool called the “interval process model” for quantifying time-varying or dynamic uncertainties. This model employs upper and lower bounds instead of precise probability distributions to quantify uncertainty in a parameter at any given time point. It is anticipated to complement the conventional stochastic process model in the coming years owing to its relatively low dependence on experimental samples and ease of understanding for engineers. Building on our previous work, this paper proposes a spectrum analysis method to describe the frequency domain characteristics of an interval process, further strengthening the theoretical foundation of the interval process model and enhancing its applicability for complex engineering problems. In this approach, we first define the zero midpoint function interval process and its auto/cross-power spectral density(PSD) functions. We also deduce the relationship between the auto-PSD function and the auto-covariance function of the stationary zero midpoint function interval process. Next, the auto/cross-PSD function matrices of a general interval process are defined, followed by the introduction of the concepts of PSD function matrix and cross-PSD function matrix for interval process vectors. The spectrum analysis method is then applied to random vibration problems, leading to the creation of a spectrum-analysis-based interval vibration analysis method that determines the PSD function for the system displacement response under stationary interval process excitations. Finally, the effectiveness of the formulated spectrum-analysis-based interval vibration analysis approach is verified through two numerical examples. 展开更多
关键词 interval process spectrum analysis power spectral density(PSD) time-varying uncertainty uncertain vibration analysis
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The power spectrum and correlation of flow noise for an axisymmetric body in water 被引量:3
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作者 黎雪刚 杨坤德 汪勇 《Chinese Physics B》 SCIE EI CAS CSCD 2011年第6期269-276,共8页
Understanding the physical features of the flow noise for an axisymmetric body is important for improving the performance of a sonar mounted on an underwater platform. Analytical calculation and numerical analysis of ... Understanding the physical features of the flow noise for an axisymmetric body is important for improving the performance of a sonar mounted on an underwater platform. Analytical calculation and numerical analysis of the physical features of the flow noise for an axisymmetric body are presented and a simulation scheme for the noise correlation on the hydrophones is given. It is shown that the numerical values of the flow noise coincide well with the analytical values. The main physical features of flow noise are obtained. The flow noises of two different models are compared and a model with a rather optimal fore-body shape is given. The flow noise in horizontal symmetry profile of the axisymmetric body is non-uniform, but it is omni-directional and has little difference in the cross section of the body. The loss of noise diffraction has a great effect on the flow noise from boundary layer transition. Meanwhile, based on the simulation, the noise power level increases with velocity to approximately the fifth power at high frequencies, which is consistent with the experiment data reported in the literature. Furthermore, the flow noise received by the acoustic array has lower correlation at a designed central frequency, which is important for sonar system design. 展开更多
关键词 flow noise correlation analysis power spectrum
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Analysis of Turbulence Structure in the Stirred Tank with a Deep Hollow Blade Disc Turbine by Time-resolved PIV 被引量:6
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作者 刘心洪 包雨云 +1 位作者 李志鹏 高正明 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2010年第4期588-599,共12页
The turbulence structure in the stirred tank with a deep hollow blade(semi-ellispe) disc turbine(HEDT) was investigated by using time-resolved particle image velocimetry(TRPIV) and traditional PIV.In the stirred tank,... The turbulence structure in the stirred tank with a deep hollow blade(semi-ellispe) disc turbine(HEDT) was investigated by using time-resolved particle image velocimetry(TRPIV) and traditional PIV.In the stirred tank,the turbulence generated by blade passage includes the periodic components and the random turbulent ones.Traditional PIV with angle-resolved measurement and TRPIV with wavelet analysis were both used to obtain the random turbulent kinetic energy as a comparison.The wavelet analysis method was successfully used in this work to separate the random turbulent kinetic energy.The distributions of the periodic kinetic energy and the random turbulent kinetic energy were obtained.In the impeller region,the averaged random turbulent kinetic energy was about 2.6 times of the averaged periodic one.The kinetic energies at different wavelet scales from a6 to d1 were also calculated and compared.TRPIV was used to record the sequence of instantaneous velocity in the impeller stream.The evolution of the impeller stream was observed clearly and the sequence of the vorticity field was also obtained for the identification of vortices.The slope of the energy spectrum was approximately-5/3 in high frequency representing the existence of inertial subrange and some isotropic properties in stirred tank.From the power spectral density(PSD) ,one peak existed evidently,which was located at f0(blade passage frequency) generated by the blade passage. 展开更多
关键词 stirred tank time-resolved particle image velocimetry wavelet analysis energy spectrum power spectral density turbulent kinetic energy
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Analysis of the common model error on velocity field under Colored noise model by GPS and InSAR: A case study in the Nepal and everest region 被引量:2
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作者 Wei Xu Gang Chen +3 位作者 Kaihua Ding Defang Yang Yanfa Si Xiaoying Yang 《Geodesy and Geodynamics》 CSCD 2022年第4期399-414,共16页
The accuracy of the velocity field will be affected by the noise model and common mode errors through GPS time series analysis.In order to analyze the influence of these two factors on the accuracy of the velocity fie... The accuracy of the velocity field will be affected by the noise model and common mode errors through GPS time series analysis.In order to analyze the influence of these two factors on the accuracy of the velocity field,two kinds of data are used,including the three-year observation from 20 permanent GPS stations with high spatial correlation in the Everest,which is about 650 km from north to south and 1068 km from east to west,and three-year 80 ascending images and 141 descending images from sentinel-1A,which are processed by GAMIT/GLOBK software and Small Baseline Subset-Interferometric Synthetic Aperture Radar method(SBAS-InSAR),respectively.The vertical deformation rate is solved by time series analysis through a self-made adaptive algorithm.In the analysis,the linear change rate,period,half period coefficient,and residual sequence of all stations are solved by using James L.Davis periodic model.The noise type of residual sequence is analyzed by the power spectrum model.The spatio-temporal correlated noise,Common Mode Error(CME),is extracted by the Principal Component Analysis(PCA)and Karhunen-Loeve(KLE)methods.The results show that noises can be best described by“flicker noise+white noise”model.After the removal of CME,the R^(2) estimates of all stations are above 0.8,with RMS value of velocity field decreasing from 1.428 mm/yr to 1.062 mm/yr and 1.063 mm/yr to 0.815 mm/yr,in N and E directions,respectively,indicating that the influence of CME can't be ignored in the extraction of the high-precision velocity field in the Nepal and Everest region. 展开更多
关键词 GPS time analysis SBAS-InSAR power spectrum analysis PCA KLE CME
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A Numerical Fluid Analysis for Early Nonlinear Mode Evolution of Fast Electron Beams in Dense Plasmas
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作者 S.REHMAN 王晓钢 +2 位作者 刘健 雷奕安 刘悦 《Plasma Science and Technology》 SCIE EI CAS CSCD 2009年第6期661-665,共5页
Nonlinear mode evolution for relativistic electrons in dense plasmas is analyzed in a three-dimensional fluid approach. Similar to the results previously obtained in particle-in-cell simulations, it is found that obli... Nonlinear mode evolution for relativistic electrons in dense plasmas is analyzed in a three-dimensional fluid approach. Similar to the results previously obtained in particle-in-cell simulations, it is found that oblique modes dominate two-stream and filamentation modes in the linear stage. On the other hand a power spectrum analysis shows the nonlinear development of the high wavenumber modes. 展开更多
关键词 relativistic electron beams power spectrum analysis INSTABILITIES
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Statistical Characteristics of Strong Ground Motion Specified by Response Spectrum and Power Spectral Density Function
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作者 Jiang Jinren,Lu Qinnian,and Sun JingjiangInstitute of Engineering Mechanics,SSB,Harbin 150080,ChinaHarbin University of Architecture and Engineering,Harbin 150006,China 《Earthquake Research in China》 1995年第4期26-41,共16页
The statistical characteristics of strong ground motion specified by response spectrum and power spectral density function are studied using 190 strong-motion records of the Haicheng and Tangshan earthquakes in China ... The statistical characteristics of strong ground motion specified by response spectrum and power spectral density function are studied using 190 strong-motion records of the Haicheng and Tangshan earthquakes in China and 138 earthquakes in the western United States.The response spectrum is normalized by the peak ground acceleration(i.e.,represented as spectral magnification factor),and the power spectral density function is described by the Kanai-Tajimi spectrum.The statistics and dependence of parameters are evaluated,and correlations between the spectral magnification factor or Kanai-Tajimi spectral parameters and the site condition,epicentral distance,or local magnitude are investigated.The statistical characteristics of spectra China and the U.S.A.are compared.Based on the results obtained the values of the statistics on spectral parameters for earthquake engineering applications in China are suggested. 展开更多
关键词 STATISTICAL analysis STRONG MOTION RESPONSE spectrum power spectrum
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Frequency-domain Analysis of ECG Signal
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作者 Tu Chengyuan Zeng Yanjun Li Shuxin 《工程科学(英文版)》 2007年第1期90-94,共5页
A new simple approach to effectively detect QRS-T complexes in ECG curve is described, so as to easily get the P-wave (when AF does not happen) or the f-wave (when AF happens). By means of signal processing techniques... A new simple approach to effectively detect QRS-T complexes in ECG curve is described, so as to easily get the P-wave (when AF does not happen) or the f-wave (when AF happens). By means of signal processing techniques such as the power spectrum function,the auto-correlation function and cross-correlation function, two kinds of ECG signal when AF does or does not happen were successively analyzed, showing the evident differences between them. 展开更多
关键词 ECG curve P-WAVE F-WAVE HISTOGRAM AF(atrial fibrillation) cross-correlation power spectrum auto-correlation
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基于窄带频谱分析的电力线载波通信干扰过滤技术 被引量:1
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作者 李俊 唐智灵 《电子器件》 CAS 2024年第2期442-447,共6页
电力线路载波通信受到背景噪声、脉冲噪声等方面干扰因素影响,导致通信信号质量下降,为此提出一种基于窄带频谱分析的通信干扰过滤技术。首先构建近似模型分析通信信号特征,利用马尔可夫链模拟信道上脉冲噪声状态。然后基于窄带频谱分... 电力线路载波通信受到背景噪声、脉冲噪声等方面干扰因素影响,导致通信信号质量下降,为此提出一种基于窄带频谱分析的通信干扰过滤技术。首先构建近似模型分析通信信号特征,利用马尔可夫链模拟信道上脉冲噪声状态。然后基于窄带频谱分析算法,在信号频谱周期图下,利用正交数据窗分离直接频谱,筛选估计方差以避免频谱泄漏事件的发生。利用傅里叶变换计算特征频谱,估计信号能量的集中特性,分析通信信号,平衡信号振幅和干扰抑制。最后通过时频峰值实施干扰滤波,有效保证电力线载波通信信号质量。经过实验数据分析证明,所提技术的载波干扰幅值最小值为1.1 dB,载波通信信号误码率平均值为1.9%,方法耗时平均值为3.8 s。 展开更多
关键词 电力线载波 信号抗干扰 频谱感知 傅里叶变换 窄带频谱分析
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扫秒式和跳秒式石英钟机芯声发射时频信号分析
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作者 吴海勇 张明建 +4 位作者 林娜 蔡聪艺 陈旸 康淑贤 谢信华 《通化师范学院学报》 2024年第2期1-8,共8页
噪声是评价和改进石英钟机芯内部结构及其材料特性的重要指标,传统的分贝仪无法分析机芯噪声时频特性.该文利用声发射技术检测扫秒式和跳秒式机芯的噪声特征,并对两种机芯的声发射信号进行时域和频域特征分析.研究结果表明,与跳秒式机... 噪声是评价和改进石英钟机芯内部结构及其材料特性的重要指标,传统的分贝仪无法分析机芯噪声时频特性.该文利用声发射技术检测扫秒式和跳秒式机芯的噪声特征,并对两种机芯的声发射信号进行时域和频域特征分析.研究结果表明,与跳秒式机芯相比,扫秒式机芯的上升时间、振铃计数值、能量、幅值、RMS、ASL约分别是其的1.6倍、7.24倍、0.001 9倍、0.74倍、0.043倍和0.59倍;扫秒式机芯声发射时域信号不规则,而跳秒式机芯声发射信号振幅规则且信号强度大;扫秒式机芯功率谱峰值主要在高频段,跳秒式机芯功率谱峰值在低频段且功率损耗更大;经小波分析后,跳秒式机芯声发射时频信号波形呈规则对称分布的橄榄状,而扫秒式机芯声发射时频信号波形呈不对称与不规则特征.声发射信号时频分析可为改进机芯性能提供理论参考依据. 展开更多
关键词 扫秒式 跳秒式 石英钟机芯 声发射 频谱分析 功率谱分析 小波分析
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10 MW级海上风电新型浮式基础结构强度分析
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作者 张敏 赵薇 +2 位作者 李炜 沈侃敏 袁文永 《太阳能学报》 EI CAS CSCD 北大核心 2024年第6期628-636,共9页
针对应用于50 m水深海域的10 MW海上风力机,设计由三浮筒及三立柱组成的新型浮式基础,建立带有骨材结构的有限元分析模型。对于有关此新型浮式基础的设计波参数,一般选用随机性设计波的方法来确定,对波浪载荷工况下的整体结构。重点研... 针对应用于50 m水深海域的10 MW海上风力机,设计由三浮筒及三立柱组成的新型浮式基础,建立带有骨材结构的有限元分析模型。对于有关此新型浮式基础的设计波参数,一般选用随机性设计波的方法来确定,对波浪载荷工况下的整体结构。重点研究浮筒的骨材尺寸以及骨材间距对新型浮式基础强度的影响规律,并得到纵横骨材尺寸组合对新型浮式基础整体强度的影响规律。研究表明,新型浮式基础结构高应力区域位于3个浮筒连接处,浮筒板单元应力水平受骨材尺寸和骨材间距的共同影响,采用合适的尺寸间距组合可在应力水平相当的情况下显著降低用钢量。 展开更多
关键词 半潜式平台 海上风电 谱分析 设计波法 强度校核 骨材布置方案
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基于VMD的MAG焊输入端电信号频域分析
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作者 吕小青 苏浩洋 《天津大学学报(自然科学与工程技术版)》 EI CAS CSCD 北大核心 2024年第4期394-402,共9页
通过电信号采集平台,对焊机输入输出端电信号进行同步采集.分析弧焊电源整流电路,对输入电信号进行整流处理得到输入电压与电流,最终计算得到弧焊电源的输入功率.经过对比发现输出电流与瞬时输入功率峰值变化趋势基本一致.论述了变分模... 通过电信号采集平台,对焊机输入输出端电信号进行同步采集.分析弧焊电源整流电路,对输入电信号进行整流处理得到输入电压与电流,最终计算得到弧焊电源的输入功率.经过对比发现输出电流与瞬时输入功率峰值变化趋势基本一致.论述了变分模态分解(VMD)原理及方法,并对瞬时输入功率进行分解,得到一系列特征BLIMFs信号.通过对不同过渡模式(大滴过渡、短路过渡和混合过渡)下瞬时输入功率信号、特征IMF信号和焊接输出电流信号在频域上的对比分析,发现VMD能够有效得到低频(IMF1)、中频(IMF2)和高频信号(IMF3),且中频和高频信号表现出了焊机不控整流的脉动信息(300 Hz)以及电网的干扰.而低频IMF1信号与焊接输出电流信号频域一致性良好,并在时域上也有良好的一致性.结果表明了通过对输入瞬时功率的VMD,其低频分量能够有效表征焊接过程,从而为从输入端评定过渡过程稳定性提供了一种新思路. 展开更多
关键词 MAG焊 瞬时输入功率 变分模态分解 频谱分析
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基于SSA-LSTM模型的水电站能效综合评价方法 被引量:2
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作者 闫孟婷 陶湘明 +3 位作者 王胜军 金艳 黄炜斌 马光文 《水电能源科学》 北大核心 2024年第2期177-182,共6页
随着我国电力体制改革不断深化,水电已告别传统粗放型发展模式,亟需配套更为成熟、通用的能效评价体系指导水电运行调度工作。因此,提出一种基于深度学习的水电站能效综合评价方法,引入长短期记忆网络(LSTM)构建水电站理论发电量模型,... 随着我国电力体制改革不断深化,水电已告别传统粗放型发展模式,亟需配套更为成熟、通用的能效评价体系指导水电运行调度工作。因此,提出一种基于深度学习的水电站能效综合评价方法,引入长短期记忆网络(LSTM)构建水电站理论发电量模型,对于给定的原始发电序列,利用奇异谱分析(SSA)提取出其趋势项、周期项及噪声,对前二者分别构建LSTM网络模拟后叠加得到理论发电量计算结果,在此基础上提出相对增发效益指标、能效相对提高率指标,利用熵权法得到水电站综合得分值,进而对南部某省12座电站进行能效评价。结果表明,该方法可以充分反映水电在调度运行中的能效特点,研究结果对优化水电站调度策略、提高水电调度水平具有借鉴意义。 展开更多
关键词 水电站 理论发电量 能效评价 奇异谱分析 长短期记忆网络
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Geminga TeV晕周围星际介质的湍动特性
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作者 程皓麟 朱辉 +4 位作者 陈天禄 田文武 崔晓红 吴丹 高启 《中国科学院大学学报(中英文)》 CAS CSCD 北大核心 2024年第3期306-311,共6页
空间功率谱分析是研究星际介质湍动特性的常用方法。以此方法利用GALFA HI巡天数据分析Geminga附近一块中性氢云的湍动特性,其21 cm谱线积分亮温度图的空间功率谱符合幂律分布,谱指数为-4.0±0.1。与银河系内本地星际介质的功率谱(... 空间功率谱分析是研究星际介质湍动特性的常用方法。以此方法利用GALFA HI巡天数据分析Geminga附近一块中性氢云的湍动特性,其21 cm谱线积分亮温度图的空间功率谱符合幂律分布,谱指数为-4.0±0.1。与银河系内本地星际介质的功率谱(谱指数大于-3.0)相比,该云的功率谱较陡。分析陡谱的成因,排除了中性氢云在视线方向所取的速度宽度不足、云周围存在垂直于视线方向的有序磁场、能量传递过程中有损失等因素的影响。这个结果暗示Geminga周围可能存在一个区域,其内部湍动特性与银河系其他区域的湍动特性不同,进而导致了Geminga TeV晕中较低的扩散系数。 展开更多
关键词 星际介质 湍动 GEMINGA 空间功率谱分析
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双馈风电机组传动系统神经网络建模及参数预测
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作者 丁新虎 潘学萍 +2 位作者 孙晓荣 和大壮 陈海东 《现代电力》 北大核心 2024年第2期201-208,共8页
传动系统是双馈风电机组的重要组成部分,其模型对电力系统同步稳定及频率稳定分析具有重要影响,准确的传动系统模型参数是分析新能源电力系统动态特性的前提。为解决因大扰动量测信息不充裕导致模型参数难以辨识的困难,提出利用机组正... 传动系统是双馈风电机组的重要组成部分,其模型对电力系统同步稳定及频率稳定分析具有重要影响,准确的传动系统模型参数是分析新能源电力系统动态特性的前提。为解决因大扰动量测信息不充裕导致模型参数难以辨识的困难,提出利用机组正常运行状态时随机小扰动激励下丰富的历史响应数据,根据响应数据与模型参数的对应关系构建神经网络模型,并根据当前响应数据进行驱动系统模型参数预测。首先讨论了基于BP神经网络进行数据建模的基本流程;针对含双馈风电机组的无穷大系统仿真算例,提取随机风速扰动下响应信号受扰轨迹的功率谱特征;定义功率谱灵敏度指标,提出选取功率谱灵敏度较大的参数作为重点参数;最后基于BP神经网络构建响应信号功率谱与模型参数之间的非线性映射,基于训练得到的BP网络辨识新响应下的模型参数。通过分析BP神经网络动态模型的误差,验证数据驱动建模方法的可行性。 展开更多
关键词 双馈风电机组 参数预测 功率谱特征 可辨识性 BP神经网络
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脑电图在脑卒中后认知功能评定中的应用 被引量:2
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作者 晁静 巩尊科 +3 位作者 王世雁 欧香灵 顾成晨 周文欣 《中国康复》 2024年第3期150-154,共5页
目的:探讨脑卒中后认知障碍(PSCI)患者脑电图谱与认知评定量表评分的相关性,分析其临床意义。方法:选取脑卒中患者75例,采用简易精神状态检查量表(MMSE)评定筛查,随机分为认知障碍组(PSCI组)和非认知障碍组(非PSCI组),每组30例,另选30... 目的:探讨脑卒中后认知障碍(PSCI)患者脑电图谱与认知评定量表评分的相关性,分析其临床意义。方法:选取脑卒中患者75例,采用简易精神状态检查量表(MMSE)评定筛查,随机分为认知障碍组(PSCI组)和非认知障碍组(非PSCI组),每组30例,另选30例健康人为对照组。3组均行脑电图检查、蒙特利尔认知量表(MoCA)及洛文斯顿作业疗法认识评定量表(LOTCA)评定。使用Spearman等级相关分析脑电图特征变化与MoCA、LOTCA评分的相关性,比较3组评定结果。结果:MMSE、MoCA、LOTCA认知量表评分比较,PSCI组明显低于于非PSCI组、健康对照组(P<0.05),非PSCI组明显低于健康对照组(P<0.05)。αAP和αRP两个脑电指标比较,PSCI组低于非PSCI组和健康对照组(P<0.05),非PSCI组低于健康对照组(P<0.05)。DTABR指标比较,健康对照组明显低于非PSCI组、PSCI组(P<0.05),非PSCI组明显低于PSCI组(P<0.05)。αAP与MoCA、LOTCA之间呈正相关(r=0.734,r=0.922,P<0.05);αRP与MoCA、LOTCA之间呈正相关(r=0.575,r=0.630,P<0.05);DTABR与MoCA、LOTCA之间呈负相关(r=-0.569,r=-0.614,P<0.05)。结论:基于频域功率谱分析的脑电数据可作为脑卒中后认知功能的评估办法,且与认知评估量表之间具有相关性,二者结合能更客观全面地评估认知障碍的存在。 展开更多
关键词 脑卒中 认知障碍 脑电图 频域功率谱分析 洛文斯顿作业疗法 MOCA 认知评估量表
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基于改进CEEMDAN在电能质量复合扰动去噪中的应用
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作者 余雷 刘宏伟 庞宇 《现代电子技术》 北大核心 2024年第1期153-158,共6页
为提高噪声环境下电能质量复合扰动识别精度,提出一种基于改进自适应噪声完备经验模态分解(CEEMDAN)去噪算法。首先通过CEEMDAN方法将含噪信号分解为若干本征模态函数(IMF);然后将改进兰氏距离与多重分形去趋势波动分析(MFDFA)结合,把若... 为提高噪声环境下电能质量复合扰动识别精度,提出一种基于改进自适应噪声完备经验模态分解(CEEMDAN)去噪算法。首先通过CEEMDAN方法将含噪信号分解为若干本征模态函数(IMF);然后将改进兰氏距离与多重分形去趋势波动分析(MFDFA)结合,把若干IMF分量分为信号IMF分量、噪声和信号混叠IMF分量、噪声IMF分量。对于混叠IMF分量、噪声IMF分量分别采用改进奇异谱分析(SSA)、小波阈值(WT)去噪;最后,将经去噪处理的IMF分量与信号IMF分量进行重构。实验表明:与对比算法相比,含噪扰动经新算法去噪后,信噪比显著提高,去噪效果良好。 展开更多
关键词 电能质量复合扰动 CEEMDAN MFDFA 改进兰氏距离 改进奇异谱分析 去噪
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基于改进Cao算法的SSA与误差修正的超短期风电功率预测
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作者 张开伟 文中 +2 位作者 杨生鹏 胡梓涵 丁剑 《国外电子测量技术》 2024年第8期37-46,共10页
针对风电历史信息运用不充分和未充分挖掘机器学习模型潜力的问题,提出一种特征奇异谱分析和模型误差修正的超短期功率预测。首先,利用随机森林分析不同特征对输出功率的影响程度,并利用累积贡献率进行特征提取。其次,通过改进的Cao算... 针对风电历史信息运用不充分和未充分挖掘机器学习模型潜力的问题,提出一种特征奇异谱分析和模型误差修正的超短期功率预测。首先,利用随机森林分析不同特征对输出功率的影响程度,并利用累积贡献率进行特征提取。其次,通过改进的Cao算法确定奇异谱分析最佳嵌入维数,对提取的特征实现降噪处理,从而构建风电功率预测模型。最后,利用预测值与真实值的误差构建误差预测模型,通过预测的误差来修正功率预测的结果。以国内某小型风电场算例结果表明,所提方法较卷积神经网络-长短期记忆(CNN-LSTM)预测模型均方根误差(RSME)和均方误差(MSE)分别降低45%和53%,验证了所提模型的有效性。 展开更多
关键词 奇异谱分析 超短期功率预测 随机森林 累积贡献率 Cao算法 误差修正
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基于响应谱传递比估计误差的结构模态参数识别精度分析
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作者 孙倩 颜王吉 任伟新 《湖南大学学报(自然科学版)》 EI CAS CSCD 北大核心 2024年第7期72-82,共11页
为了研究响应谱估计误差及其传递对振动响应功率谱密度传递比(Power Spectrum Density Transmissibility,PSDT)估计的影响,基于摄动理论和统计矩定义,推导了两个变量比例函数的均值和方差近似表达式;将响应谱估计统计矩代入,可以推导出... 为了研究响应谱估计误差及其传递对振动响应功率谱密度传递比(Power Spectrum Density Transmissibility,PSDT)估计的影响,基于摄动理论和统计矩定义,推导了两个变量比例函数的均值和方差近似表达式;将响应谱估计统计矩代入,可以推导出由响应相干函数、谱估计中信号平均分段数,近似表征的PSDT估计幅值的均值和方差解析公式.基于此,揭示了共振频率处PSDT估计幅值误差规律,并实现了模态振型幅值的精度度量.研究发现,共振频率处PSDT幅值方差存在极小值,且变异系数小于相关响应谱.通过数值框架数据验证了文中误差公式的准确性.此外,还研究了参考响应的选择、响应时长、窗函数类型对PSDT和模态振型估计的影响.结果表明,以PSDT两组响应作为参考响应,能得到较好PSDT和模态分析结果;同时模态振型估计标准差随测试数据时长的增加,也随之降低至一定水平. 展开更多
关键词 频谱误差 响应功率谱传递比 模态识别 误差分析 摄动法
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