为分析集成三维点云逆向建模方法(integrated 3D point cloud reverse modeling,IPCRM)在建立薄厚型钢构件三维模型时的精度表现,以局部变形角钢为研究对象,利用SfM(structure from motion)-MVS(multi-view stereo)算法建立其三维点云模...为分析集成三维点云逆向建模方法(integrated 3D point cloud reverse modeling,IPCRM)在建立薄厚型钢构件三维模型时的精度表现,以局部变形角钢为研究对象,利用SfM(structure from motion)-MVS(multi-view stereo)算法建立其三维点云模型,借助逆向建模技术生成曲面模型,重点开展了模型精度验证试验.结果表明:各表面形状特征参数的相对误差均在8%以内(吻合度验证);4种角钢模型与实际角钢间无显著性差异(P值,P=0.99),且角钢厚度对模型精度无显著性影响(P值,P=0.95),结论在95%的置信度水平下成立(差异显著性验证).研究结果为后续算法优化及利用此类方法进行合理的钢构件局部变形损伤检测与承载性能评价提供依据.展开更多
提出一种基于核主成分分析与多元多尺度能量熵的气液两相流流动特性分析方法。通过电阻层析成像设备采集垂直管道气液两相流实验数据,采用核主成分分析(kernel principal component analysis,KPCA)和主成分分析分别处理原始数据得到低...提出一种基于核主成分分析与多元多尺度能量熵的气液两相流流动特性分析方法。通过电阻层析成像设备采集垂直管道气液两相流实验数据,采用核主成分分析(kernel principal component analysis,KPCA)和主成分分析分别处理原始数据得到低维时间序列,结合多变量经验模态分解方法提取多元多尺度能量熵(multivariate multiscale energy entropy,MMEE)用以对比降维方法影响并分析流体的动态变化。结果表明,KPCA能保留原始数据中非线性特性并显现在MMEE的数据变化与流型转换关系中;结合熵值10尺度均值与5尺度拟合斜率构建的联合分布能实现高效准确的流型辨识。所提方法为气液两相流流动特性分析提供了兼具经济性与效率性的手段,也为更深层次的分析提供了更多元的可靠参数。展开更多
The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recogni...The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recognized to be limited at data boundaries and high frequencies,which can significantly reduce the signal-to-noise ratio(SNR).To solve this problem,a novel method synergistically integrating Principal Component Analysis(PCA)with SG filtering is proposed in this paper.This approach avoids the is-sue of excessive smoothing associated with larger window sizes.The proposed PCA-SG filtering algorithm was applied to a CO gas sensing system based on Cavity Ring-Down Spectroscopy(CRDS).The perform-ance of the PCA-SG filtering algorithm is demonstrated through comparison with Moving Average Filtering(MAF),Wavelet Transformation(WT),Kalman Filtering(KF),and the SG filter.The results demonstrate that the proposed algorithm exhibits superior noise reduction capabilities compared to the other algorithms evaluated.The SNR of the ring-down signal was improved from 11.8612 dB to 29.0913 dB,and the stand-ard deviation of the extracted ring-down time constant was reduced from 0.037μs to 0.018μs.These results confirm that the proposed PCA-SG filtering algorithm effectively improves the smoothness of the ring-down curve data,demonstrating its feasibility.展开更多
[Objectives]This study was conducted to isolate and identify the components from stems of Polyalthia plagioneura.[Methods]The compounds were isolated and purified by silica gel column,Sephadex LH-20,and C_(18) chromat...[Objectives]This study was conducted to isolate and identify the components from stems of Polyalthia plagioneura.[Methods]The compounds were isolated and purified by silica gel column,Sephadex LH-20,and C_(18) chromatography.Their chemical structures were elucidated on the basis of physicochemical properties and spectral data.[Results]Five compounds were isolated and identified as:di(2-ethylhexyl)phthalate(1),cinnamic anhydride(2),phthalic acid(3),citric acid(4),and syringaldehyde(5).[Conclusions]All compounds were isolated from this plant for the first time.展开更多
文摘为分析集成三维点云逆向建模方法(integrated 3D point cloud reverse modeling,IPCRM)在建立薄厚型钢构件三维模型时的精度表现,以局部变形角钢为研究对象,利用SfM(structure from motion)-MVS(multi-view stereo)算法建立其三维点云模型,借助逆向建模技术生成曲面模型,重点开展了模型精度验证试验.结果表明:各表面形状特征参数的相对误差均在8%以内(吻合度验证);4种角钢模型与实际角钢间无显著性差异(P值,P=0.99),且角钢厚度对模型精度无显著性影响(P值,P=0.95),结论在95%的置信度水平下成立(差异显著性验证).研究结果为后续算法优化及利用此类方法进行合理的钢构件局部变形损伤检测与承载性能评价提供依据.
文摘提出一种基于核主成分分析与多元多尺度能量熵的气液两相流流动特性分析方法。通过电阻层析成像设备采集垂直管道气液两相流实验数据,采用核主成分分析(kernel principal component analysis,KPCA)和主成分分析分别处理原始数据得到低维时间序列,结合多变量经验模态分解方法提取多元多尺度能量熵(multivariate multiscale energy entropy,MMEE)用以对比降维方法影响并分析流体的动态变化。结果表明,KPCA能保留原始数据中非线性特性并显现在MMEE的数据变化与流型转换关系中;结合熵值10尺度均值与5尺度拟合斜率构建的联合分布能实现高效准确的流型辨识。所提方法为气液两相流流动特性分析提供了兼具经济性与效率性的手段,也为更深层次的分析提供了更多元的可靠参数。
文摘The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recognized to be limited at data boundaries and high frequencies,which can significantly reduce the signal-to-noise ratio(SNR).To solve this problem,a novel method synergistically integrating Principal Component Analysis(PCA)with SG filtering is proposed in this paper.This approach avoids the is-sue of excessive smoothing associated with larger window sizes.The proposed PCA-SG filtering algorithm was applied to a CO gas sensing system based on Cavity Ring-Down Spectroscopy(CRDS).The perform-ance of the PCA-SG filtering algorithm is demonstrated through comparison with Moving Average Filtering(MAF),Wavelet Transformation(WT),Kalman Filtering(KF),and the SG filter.The results demonstrate that the proposed algorithm exhibits superior noise reduction capabilities compared to the other algorithms evaluated.The SNR of the ring-down signal was improved from 11.8612 dB to 29.0913 dB,and the stand-ard deviation of the extracted ring-down time constant was reduced from 0.037μs to 0.018μs.These results confirm that the proposed PCA-SG filtering algorithm effectively improves the smoothness of the ring-down curve data,demonstrating its feasibility.
基金Supported by Jiangxi Education Department Project(GJJ201533)University-level Project of Gannan Medical University(YB201902).
文摘[Objectives]This study was conducted to isolate and identify the components from stems of Polyalthia plagioneura.[Methods]The compounds were isolated and purified by silica gel column,Sephadex LH-20,and C_(18) chromatography.Their chemical structures were elucidated on the basis of physicochemical properties and spectral data.[Results]Five compounds were isolated and identified as:di(2-ethylhexyl)phthalate(1),cinnamic anhydride(2),phthalic acid(3),citric acid(4),and syringaldehyde(5).[Conclusions]All compounds were isolated from this plant for the first time.
