矿体开采对地表的影响预测及技术防范措施

为了保证矿体的安全开采,采用有限差分程序FLAC3D模拟桂家冲铁(铜)矿矿体开采对地表的影响,计算了矿体开采过程中不同区域的地表及建筑物的变形量,并参照我国评判建筑物破坏等级的标准进行评判。模拟结果表明:岩层移动是一个自下而上传递的动态过程。采取合理的采矿方法才是控制地表沉降、防止地面建筑物变形和破坏的有效途径,同时提出了相应的开采工艺和建筑结构的技术防范措施。     

4G核心网和无线网协同的端到端跟踪实现方法

为了解决4G网络中,由于网络架构扁平化,无线接入侧无法独立实现用户跟踪和优化分析的问题,在3GPP协议基础上,提出了构建EPC和LTE无线协同跟踪处理机制及优化方案,解决异厂商场景的应用问题,满足现网用户跟踪和优化分析需求,为进一步实现用户问题定位和重点保障提供平台基础.     

Carbon nanotubes anchored with SnO2 nanosheets as anode for enhanced Li-ion storage

The carbon nanotubes (CNTs) anchored with SnO₂ nanosheets were prepared using a hydrothermal method. The as-prepared products were characterized by X-ray diffraction, fourier transform infrared spectroscopy, thermogravimetric analyses, field emission scanning electron microscope and transmission electron microscope. The electrochemical performances of SnO₂ nanosheets/CNTs composite were measured by galvanostatic charge/discharge cycling, cyclic voltammetry and electrochemical impedance spectroscopy. The results show that the SnO₂ nanosheets/CNTs composite maintains high lithium storage capacity and good cycling stability. The designed structure plays key role in improving electrochemical performance. The CNTs anchored with SnO₂ nanosheets will be an ideal candidate of anode material for lithium ion batteries.     

High-Speed Parallel Plasmonic Direct-Writing Nanolithography Using Metasurface-Based Plasmonic Lens

Simple and efficient nanofabrication technology with low cost and high flexibility is indispensable for fundamental nanoscale research and prototyping. Lithography in the near field using the surface plasmon polariton (i.e., plasmonic lithography) provides a promising solution. The system with high stiffness passive nanogap control strategy on a high-speed rotating substrate is one of the most attractive high-throughput methods. However, a smaller and steadier plasmonic nanogap, new scheme of plasmonic lens, and parallel processing should be explored to achieve a new generation high resolution and reliable efficient nanofabrication. Herein, a parallel plasmonic direct-writing nanolithography system is established in which a novel plasmonic flying head is systematically designed to achieve around 15 nm minimum flying-height with high parallelism at the rotating speed of 8–18 m·s⁻¹. A multi-stage metasurface-based polarization insensitive plasmonic lens is proposed to couple more power and realize a more confined spot compared with conventional plasmonic lenses. Parallel lithography of the nanostructures with the smallest (around 26 nm) linewidth is obtained with the prototyping system. The proposed system holds great potential for high-freedom nanofabrication with low cost, such as planar optical elements and nano-electromechanical systems.     

300MW机组锅炉“四管”泄漏检修分析

对300MW机组锅炉受热面存在的长期或短期过热、材料性能劣化及异种钢焊缝失效,穿墙管密封、磨损腐蚀等问题分别进行了分析,提出了加强锅炉部件内部构件检查防止异物造成管孔堵塞,避免炉墙密封护板与受热面管直接焊接,定期清理不锈钢弯头部位积灰等预防及检修措施。     

40MN挤压机Profibus-DP网络通信故障分析与处理

本文描述了Profibus-DP网络出现通信故障时的现象,分析了故障产生的原因,给出了解决问题的办法。     

考虑设备劣化及返工的质量批量模型研究

为了得到最大质量批量，研究了返工成本边际效应下的期望利润值计算方法，将生产过程分为两个阶段：无需返工和需要返工的连续加工。给出了质量控制策略下批量计算公式以及考虑边际成本下的最大利润所对应的质量批量。采用蒙特卡洛仿真和Design Expert 8.0.6软件拟合，通过数字实验，对比了返工成本与未考虑返工成本情况下的期望利润值。研究显示，考虑返工成本边际效应下的质量批量大于一般的经济批量，所得到期望利润也最大。     

基于轻量级深度神经网络的环境声音识别

针对传统卷积神经网络（CNN）模型存在大量冗余参数的问题,提出了两个基于SqueezeNet核心结构Fire模块的轻量级网络模型Fnet1和Fnet2。之后结合移动端分布式数据采集和处理的特点,在Fnet2模型基础上,依据Dempster-Shafer（D-S）证据理论将Fnet2与深度神经网络（DNN）融合,提出新的网络模型FnetDNN。首先,建立一个具有四层卷积层的神经网络Cent作为基准,以梅尔倒谱系数（MFCC）作为特征输入来对比分析Fnet1、Fnet2和Cent的网络结构特点、计算量、卷积核参数数量及识别准确率,结论是Fnet1仅使用Cnet参数数量的10.3%就可达到86.7%的分类准确率;然后,将MFCC与全局特征向量输入到FnetDNN模型中,使得该模型的识别准确率提高到了94.4%。实验结果表明,Fnet网络模型不仅可以压缩冗余参数,还可以与其他网络相融合,具备模型扩展能力。     

An approach based on discrete wavelet transform to unsupervised change detection in multispectral images

Change vector analysis (CVA) and Spectral Angle Mapper (SAM) are widely used for change detection in multitemporal multispectral images. CVA and SAM describe the difference from the perspective of vector magnitude and spectral angle, respectively. It has been proved that three change categories may occur in a changed pixel; however, CVA or SAM alone can only detect two of the three change categories properly. Hence, we propose a novel approach integrating the advantages of them to acquire a better change map. This approach, based on discrete wavelet transform (ABDWT, i.e. approach based on discrete wavelet transform), obtains two difference images by using CVA and SAM, and then yields a novel difference image by fusing them in the coefficients domains of discrete wavelet transform. Experimental results from a simulated and two real data sets validate the effectiveness of the proposed approach. In the first real data set, the proposed approach can identify 14,916 changed pixels while the best result of other methods is 14,806. In the second real data set, the proposed approach detects 3203 changed pixels, while the maximum of other methods is 3189.