综采放顶煤工作面高位巷抽采关键技术研究

为了保证九里山矿1508工作面采空区瓦斯治理效果，通过现场数据测定、实验考察和理论分析，研究了推进度、抽采负压、抽采管网等高位巷抽采关键参数。研究结果表明，工作面煤层越厚、推进度越快，瓦斯涌出量越大；孔抽期间理想抽采负压为25～30 kPa、巷抽期间理想抽采负压为5～10 kPa，高位巷并联支路及管路阻力会影响高位巷的抽采效果。     

Investigation of the residual stress in UO2-Mo composites via a neutron diffraction method

UO₂-Mo composites with a core-shell structure have been considered candidates for the thermal conductivity (TC)-enhanced UO₂ pellets and have demonstrated commercial potential for use in novel high-level safety reactors. Nevertheless, UO₂-Mo composites tend to form micro-cracks that are caused by the presence of residual stress (RS) during manufacturing. In this work, neutron diffraction measurements were employed to analyse the RS in UO₂-Mo core-shell structured composites fabricated by spark plasma sintering (SPS) for the first time. It was found that in the UO₂-Mo composites, the RS state present in the UO₂ matrix was tensile in nature. The RS in the UO₂ matrix increased with increaseing Mo content. There was a maximum value of 148 ± 15 MPa in the UO₂-10 vol% Mo composite. The micro-cracks produced in the high-Mo content composites were explained by the results of the neutron diffraction measurements. These results could provide significant guidance for the manufacturing and improvement of the operational performance of UO₂-Mo composites as next-generation fuels.     

配网工程建设时间控制

时间控制是运用科学的方法、工具,并综合运用现有资源,在规定时间内取得预期效果的一种控制手段。本文从工程时间管理的概念出发,研究了如何运用时间管理方法实现工程施工工期的管理,讨论了时间管理在工程建设中的重要性,为企业配网工程建设时间控制管理提供参考。     

深度学习识别光网络单元故障的设计与应用

为解决依赖装维上门鉴别光网络单元故障带来的不便,可以从机器视觉入手实现自动化故障识别。近年,ImageNet挑战赛的成功推动了物体识别技术的跨越式发展,特别是基于卷积的深度学习技术在视觉识别方面已经达到人类水平,为光网络单元故障的自动识别提供了技术基础。文章对识别光网络单元的工作状态进行了研究,将设备工作状态分为7个场景,提出了利用手机APP采集图片识别故障的解决方案并投入了实际生产;重点阐述了深度学习模块的设计与实现,提出一种通过算法整合的方式综合运用物体检测和图像分类算法,分3阶段逐步求精,解决了图片过滤,光网络单元型号和状态识别等问题,实现了基于计算机视觉自动识别光网络单元故障。从数据上看产品的端到端准确率超过84%,识别速度达到10 FPS,月均提供服务超过1万人次,在减少用户等待的同时节约了人力资源。     

Estimating posterior inference quality of the relational infinite latent feature model for overlapping community detection

Overlapping community detection has become a very hot research topic in recent decades, and a plethora of methods have been proposed. But, a common challenge in many existing overlapping community detection approaches is that the number of communities K must be predefinedmanually. We propose a flexible nonparametric Bayesian generative model for count-value networks, which can allow K to increase as more and more data are encountered instead of to be fixed in advance. The Indian buffet process was used to model the community assignment matrix Z, and an uncollapsed Gibbs sampler has been derived.However, as the community assignment matrix Z is a structured multi-variable parameter, how to summarize the posterior inference results and estimate the inference quality about Z, is still a considerable challenge in the literature. In this paper, a graph convolutional neural network based graph classifier was utilized to help to summarize the results and to estimate the inference quality about Z. We conduct extensive experiments on synthetic data and real data, and find that empirically, the traditional posterior summarization strategy is reliable.     

基于高光谱图像的改进SIFT特征提取与匹配

针对尺度不变特征变换(SIFT)算法所提取图像特征点数量少、误匹率高的问题,提出了一种基于高光谱图像的改进SIFT算法。首先,依据传统SIFT算法中高斯金字塔的构造思想,结合在不同波段下的高光谱图像具有相同宏观特征的特点,首次用高光谱图像作为原始算法中经高斯变换产生的图像,使得检测到的具有实际意义的特征点数量大幅增加;其次,传统SIFT算法以及大量的改进方法都只通过目标象元邻域范围内的像素信息来构造特征描述符,而忽略了像素点的位置信息,文中将目标象元的位置信息纳入了特征描述符,在特征描述符的匹配阶段,在利用邻域范围内的像素信息进行粗匹配之后,利用特征描述符中的位置信息进行精细匹配。仿真实验结果表明在限定最优值与次优值之比的情况下,采用高光谱图像构造高斯金字塔的方式能显著增加特征点的提取数量,更多地挖掘出图像中的极值点;在特征描述符中加入目标象元的位置信息作为特征点匹配第二阶段的判断依据,正确匹配数量达到原方法的59倍以上,极大提升了算法的匹配性能。     

One‐shot radical polymerization of vinyl monomers with different reactivity accompanying spontaneous delay of polymerization for the synthesis of double‐network hydrogels

Double‐network hydrogels were conveniently synthesized by the one‐shot radical polymerization of an ionic monomer for the first network and a non‐ionic monomer for the second network in the presence of crosslinkers by simultaneous addition of the monomers, that is, one‐shot and spontaneous two‐step polymerization accompanying the delay of polymerization of a second network monomer. We analyzed the polymerization process based on the conversion of each monomer during the reaction in the absence of crosslinkers. Then we fabricated the double‐network hydrogels using several polymerization systems consisting of a conjugated monomer and a non‐conjugated monomer in the presence of the dual crosslinkers. We analyzed the swelling, mechanical and viscoelastic properties of hydrogels synthesized by one‐shot radical polymerization to confirm the production mechanism and the network structure of the hydrogels. © 2020 Society of Chemical Industry     

基于高斯混合隐马尔科夫模型与人工神经网络的紧急换道行为预测方法

为了有效降低因驾驶员紧急换道行为而诱发的交通事故，提高道路交通事故链阻断效率，提出一种基于高斯混合隐马尔科夫模型（GMM-HMM）和人工神经网络（ANN）的紧急换道行为预测方法。首先利用GMM-HMM对车辆行驶状态以及驾驶行为连续观察序列进行换道意图辨识，采用ANN预测下一时段的驾驶行为，再预测换道过程中的横向加速度变化率，从而判断紧急换道的危险程度。驾驶员在环仿真实验及实车实验结果表明，该方法预测避险成功率达92.83%，实验避险成功率达90.32%。该方法能有效地对紧急换道行为进行提前警告与干预。     

基于网络数据统计的食品欺诈研究分析

目的 建立符合我国国情的食品欺诈数据库, 补充国际上已建立的经济利益驱动型掺假(economically motivated adulteration, EMA)数据库空白。方法 搜集2001~2019年发生的食品欺诈行为, 初步建立具有中国国情的食品欺诈数据库。对数据库中信息完备的454条欺诈数据进行分析。结果 媒体报道数据占食品欺诈信息总数的71.6%; 食用农产品、酒类、乳制品、肉制品等11类产品是欺诈事件发生较多的食品类别; 产品欺诈(72.2%)高居食品欺诈类型的首位; 2001~2019年食品欺诈事件数量呈现出先上升后降低, 再上升再降低的“M”状趋势; 目前食品欺诈检测技术主要以理化分析技术为主, 针对的食品类别还有限; 食品欺诈信息以中国为主(89.0%), 涉及到世界各个地区。结论 食品欺诈是广泛存在的全球性问题, 本研究建立的食品欺诈数据库为预防食品安全风险起到了重要的技术支撑作用。     

Zone model predictive control for pressure management of water distribution network

In the water distribution network (WDN), although the water demand of the node is changing constantly, the water quantity and water pressure of the node need to be met at each moment. To realize energy saving and consumption reduction, it is proposed to control the nodal water head of WDN in an appropriate narrow range. The frequent large fluctuation of the water demand, which may lead the water pressure exceed the expected range, increases the difficulty of the zone control. To realize optimized WND control, a novel zone predictive control is proposed, where two switching cases are considered. The switching condition is whether there are feasible solutions to keep the pressure within the expected region over the prediction horizon. When the condition is satisfied, the controller minimizes the variation of inputs with constraints of pressure range for ensuring the tank level staying within the expected zone and obtaining optimal economic cost. When the current pressure is out of the expected region or the condition is not satisfied due to the large variation of water demand, a reference trajectory of outputs is introduced, which is combined with the inputs as an optimization variable, and the constraints of expected zone are moved from the output to the introduced reference trajectory. Through minimizing the distance between reference trajectory and output, the controller will keep the tank level from deviating too far from the expected zone and will drive the tank level rapidly into the expected zone once the tank level exceeds the expected range. An application of the proposed zone MPC to WDN in Shinan District of Shanghai is given to illustrate its effectiveness.