LLC谐振变换器ZVS开通研究

合理选择LLC谐振变换器的死区时间是实现功率开关管零电压开通的前提。基于基波分析法等效模型,推导出保证功率开关管零电压开通的最小死区时间和最大死区时间,得出保证开关管零电压开通的死区工作区间。通过SABER搭建了一个LLC模型,验证了区间的合理性。     

基于局部约束线性编码的单帧和多帧图像超分辨率重建

基于稀疏表示的超分辨率图像重建是当前典型的算法之一,引入约束性更强的局部约束线性编码(LLC:Locality-constrained Linear Coding)对其进行了改进。首先依据一个高分辨率图像集训练出成对的高分辨率和低分辨率词典,然后根据低分辨率词典对输入的低分辨率图像用LLC方法进行编码,再依据高分辨率词典及编码系数初步重建高分辨率图像,最后添加全局约束重建高分辨率图像,并将该算法推广到多帧图像超分辨率重建层面。分析和对多幅图像的实验结果都表明,新算法相对原算法不仅提高了图像重建的质量还降低了计算复杂度,取得了满意的效果。     

应用于超导储能的双向DC/DC变换器的设计

以超导在电力系统中的应用为背景,超导储能方式具有更有效地提高电力系统稳定性和动态稳定性的优点,以满足超导储能应用的需要为目的,针对性地提出了一种新型应用于超导储能的隔离式的双向DC/DC变换器的电路拓扑结构。针对超导储能线圈的储能特性,设计了独特的双向充放电工作电路,有效保证了能量的双向流动,结合移相PWM技术,能够完全实现超导线圈的充放电功能。同时该变换器具有大功率、大电流、控制简单和全数字化等特点。该文详细地介绍和分析了主电路结构、工作原理和控制方法。根据上述理论设计出了相应的试验装置,并给出了实验结果,验证了应用于超导储能的双向DC/DC变换器的正确性。     

基于控制点的分层双向动态规划立体匹配算法

提出一种基于控制点的分层双向动态规划立体匹配算法．首先，利用改进Volumetric迭代算法获取具有高可靠度的控制点，将其作为具有正确视差的匹配点．其次，在高可靠度控制点的指导下，利用分层双向动态规划算法在DSI（disparity-space image）视差空间图中进行初匹配，进而在Delta DSI（delta disparity-space image）视差变化空间图中进行精匹配，从而获取高密度视差图．实验结果表明，该算法不仅可以改善传统直接动态规划立体匹配算法产生的带状条纹瑕疵，而且计算速度较快，匹配结果也优于传统动态规划的匹配结果．     

A new instrument for passive remote sensing: 2. Measurement of leaf and canopy reflectance changes at 531 nm and their relationship with photosynthesis and chlorophyll fluorescence

A previously described passive remote sensing fluorimeter (see companion paper) was modified to detect changes in the reflectance of vegetation. The utility of this remote sensing technique to measure the Physiological Reflectance Index (PRI) is shown at both leaf level under laboratory conditions and at the canopy level in the field. PRI, defined as the relative changes in reflectance at 531 nm with respect to those at 570 nm (PRI=R531−R570/R531+R570), is related to xanthophyll-related, dynamic changes of non-photochemical quenching of chlorophyll fluorescence. The robustness of this relationship by simultaneous remote sensing of PRI and chlorophyll fluorescence is strengthened. At the leaf level, the existence of two kinetically distinct components of PRI is shown. A fast (within seconds) component that is partly attributed to ΔpH induced chloroplast shrinkage, and a slow (within minutes), main component that is related to xanthophyll de-epoxidation, as demonstrated by its disappearance in the presence of DTT. Overall, PRI correlated better with non-photochemical quenching of chlorophyll fluorescence (NPQ) than with any other measured parameter, including the photochemical efficiency of PSII. Finally, at the canopy level and under field conditions, it is shown that PRI can be a useful tool for remote sensing of water stress in grapevines.     

双向加载情况下工字形SRC柱抗震性能数值分析

为了研究工字形SRC柱在双向水平加载下的抗震性能,采用纤维模型对已有试验进行数值模拟,验证了纤维模型的适用性。基于此模型,考察了轴压比、配钢率、型钢强度等参数对工字形SRC柱在双向水平加载下的承载力、耗能及延性的影响,并与单向水平加载下的情况进行了对比。结果表明:轴压比对工字形SRC柱的抗震性能影响显著,随着轴压比的增大,柱子承载力先增大后减小,而滞回耗能和延性则随轴压比的增大逐步降低;配钢率对工字形SRC柱的抗震性能有一定影响,随配钢率的增大,柱的承载力、耗能及延性均有明显增长;承载力、耗能及延性均随型钢强度的增加而得到一定改善,但增幅较小。此外,双向加载下SRC柱的承载力、耗能及延性均较单向水平加载的低。     

428XL光缆交叉线的工作原理及故障检修方法

428XL光缆交叉线是428XL仪器的重要组成部分,它的问世有效提高了采集数据的传输速度,满足了随着野外采集道数的增加采集数据的数据量越来越大的数传要求。本文从428XL光缆交叉线的基本组成入手,详细剖析了428XL光缆交叉线的传输原理,并介绍了光缆交叉线应用于428XL仪器施工时的工作流程及其在施工中可能出现的故障和相应的检修方法。     

Deep Scalogram Representations for Acoustic Scene Classification

Spectrogram representations of acoustic scenes have achieved competitive performance for acoustic scene classification. Yet, the spectrogram alone does not take into account a substantial amount of time-frequency information. In this study, we present an approach for exploring the benefits of deep scalogram representations, extracted in segments from an audio stream. The approach presented firstly transforms the segmented acoustic scenes into bump and morse scalograms, as well as spectrograms; secondly, the spectrograms or scalograms are sent into pre-trained convolutional neural networks; thirdly, the features extracted from a subsequent fully connected layer are fed into (bidirectional) gated recurrent neural networks, which are followed by a single highway layer and a softmax layer; finally, predictions from these three systems are fused by a margin sampling value strategy. We then evaluate the proposed approach using the acoustic scene classification data set of 2017 IEEE AASP Challenge on Detection and Classification of Acoustic Scenes and Events (DCASE). On the evaluation set, an accuracy of 64.0% from bidirectional gated recurrent neural networks is obtained when fusing the spectrogram and the bump scalogram, which is an improvement on the 61.0% baseline result provided by the DCASE 2017 organisers. This result shows that extracted bump scalograms are capable of improving the classification accuracy, when fusing with a spectrogram-based system.