基于压缩感知的高阶MIMO系统信道估值算法

针对通信网络中的天线数量巨大，很难完成对信道的有效计算与估值。借助于高阶多输入多输出（MIMO）系统的可靠性，提出了一种基于压缩感知的信道估值高阶MIMO系统。设计了一种简单的导频结构，以降低计算复杂度；利用导频序列长度可以随着信道稀疏度变化情况自适应的调整，从而节省了导频资源的开销。仿真实验表明，与传统的信道估计算法比较，在相同的信道估计精度条件下，HMCE-CS算法可以降低平均导频序列长度；或者在相同的导频序列长度条件下，HMCE-CS算法可以提高信道估计精度，验证了该算法的有效性。     

基于同轴图像传感的激光焊接过程质量监测技术

针对激光焊接过程中由于参数不匹配、装配误差等原因造成的焊接过程不稳定等焊接缺陷，基于同轴图像传感技术，建立起一套激光焊接过程中的质量在线监测系统，对焊接过程中的熔池图像进行了采集分析及其熔池特征信息的提取. 结果表明，在激光功率为1 500 W的不等厚不锈钢薄板激光焊接试验条件下，焊接过程中的不稳定、下塌缺陷以及焊偏现象与熔池形状各特征信息变化具有一定的相关性. 结合BP神经网络算法对所提特征信息进行分类、识别，基于LabVIEW软件平台，可实现相应缺陷的自动化识别及报警功能.     

我国现状能源与水纽带关系定量识别

以省级行政区为研究对象,以2017年为研究时段,分析我国社会水循环过程耗能及电力生产耗水。结果显示:2017年我国社会水循环过程耗电总量为10 828.1亿kW·h,占当年我国全社会用电总量的17.2%,终端用水是最大的耗能环节;2017年我国电力生产过程耗水量为65.7亿m~3,占当年全社会耗水总量的2%;火电是我国最耗水的电源,其耗水量占全国电力开发耗水总量的78%。基于计算结果,提出了实现能源-水协同安全的相关建议。     

Contactless Spin Switch Sensing by Chemo-Electric Gating of Graphene

Direct electrical probing of molecular materials is often impaired by their insulating nature. Here, graphene is interfaced with single crystals of a molecular spin crossover complex, [Fe(bapbpy)(NCS)₂], to electrically detect phase transitions in the molecular crystal through the variation of graphene resistance. Contactless sensing is achieved by separating the crystal from graphene with an insulating polymer spacer. Next to mechanical effects, which influence the conductivity of the graphene sheet but can be minimized by using a thicker spacer, a Dirac point shift in graphene is observed experimentally upon spin crossover. As confirmed by computational modeling, this Dirac point shift is due to the phase-dependent electrostatic potential generated by the crystal inside the graphene sheet. This effect, named as chemo-electric gating, suggests that molecular materials may serve as substrates for designing graphene-based electronic devices. Chemo-electric gating, thus, opens up new possibilities to electrically probe chemical and physical processes in molecular materials in a contactless fashion, from a large distance, which can enhance their use in technological applications, for example, as sensors.     

Photonic Metamaterial Absorbers: Morphology Engineering and Interdisciplinary Applications

Recent advances in nanofabrication technologies have spurred many breakthroughs in the field of photonic metamaterials that provide efficient ways of manipulating light–matter interaction at subwavelength scales. As one of the most important applications, photonic metamaterials can be used to implement novel optical absorbers. First the morphology engineering of various photonic metamaterial absorbers is discussed, which is highly associated with impendence matching conditions and resonance modes of the absorbers, thus directly determines their absorption efficiency, operational bandwidth, incident angle, and polarization dependence. Then, the recent achievements of various interdisciplinary applications based on photonic metamaterial absorbers, including structural color generation, ultrasensitive optical sensing, solar steam generation, and highly responsive photodetection, are reviewed. This report is expected to provide an overview and vision for the future development of photonic metamaterial absorbers and their applications in novel nanophotonic systems.     

高速列车转向架构架损伤、等效应力及寿命分布特性研究

为分析高速列车转向架构架损伤、等效应力及寿命分布特性，对构架疲劳关键测点进行动应力线路实测并对测点实测时域数据波形进行解析；基于实测应力时间历程及雨流计数法编制二维应力谱，利用Goodman等寿命方程将二维应力谱等效转换为一维应力谱；阐述线性累积损伤及非线性累积损伤模型的建立方法并对实测数据的线性累积损伤及非线性累积损伤进行了计算及对比分析；分别基于线性累积损伤理论及非线性累积损伤理论推导出各理论下的等效应力，基于实测数据对两种等效应力进行了计算及对比分析；通过结合非线性累积损伤及线性累积损伤理论计算的等效应力及不同可靠度下的材料S-N曲线计算并对比分析构架结构的疲劳寿命。研究结果表明，与非线性疲劳分析理论相比，线性疲劳分析理论对高速列车转向架构架的疲劳特性评估偏于保守。     

基于深度语义分割的多源遥感图像海面溢油监测

针对遥感图像海面溢油区域通常受到斑噪声以及强度不均等因素的影响,从而导致溢油区域监测效果较差的问题,本文引入了深度语义分割的方法,将深度卷积神经网络与全连接条件随机场相结合,形成端对端连接。以Resnet结构为基础,首先通过深度卷积神经网络对多源遥感图像粗分割并作为输入,然后经过改进的全连接条件随机场,利用高斯成对势和平均场近似定理,建立条件随机场形成递归神经网络作为输出。通过多源遥感图像对海面溢油区域进行监测,并利用可见光图像估计溢油区域面积。实验在所建立的多源遥感图像数据集上与其它先进模型进行对比,结果表明本文方法提高了溢油区域的分割精度以及精细细节程度,平均交并比为82.1%,监测效果具有明显地改善。     

Sparse decomposition method based on time–frequency spectrum segmentation for fault signals in rotating machinery

The impulse signal in large rotating machinery with damage fault is sparse, weak, coupled, and even nonperiodic in intermittent operation. To extract this complex signal is a key topic in machinery fault diagnosis. Sparse decomposition (SD) has excellent adaptability in describing arbitrary complex signals based on over-complete dictionary. However, the pursuit speed of best atom is a serious drawback. To alleviate this, a method of sparse decomposition based on time–frequency spectrum segmentation (SD-TFSS) is introduced. Generalized S transform (GST) provides the capability to show the distribution of vibration signals, but the resolution is susceptible to noise, multiresolution generalized S-transform (MGST) is developed to generate multiresolution time–frequency spectrums. Then, spectrums fusion with an appropriate threshold is adopted to acquire multiresolution binary spectrums and produce an optimal binary spectrum. From this optimal binary spectrum, all the connectivity areas are extracted and marked by spectrum segmentation. Thus, an optimal library can be constructed by selecting the optimal atoms of every connectivity area, and the signal can be expressed with this library. We conduct simulations and experiments demonstrating that the proposed method performs well with lower pursuit complexity, higher decomposition efficiency, and better approximation precision.