基于小角度高位技术的钻孔初采期瓦斯治理

回采工作面初采期瓦斯涌出不均衡,易出现瓦斯超限现象。针对新源煤矿近距离煤层群开采、瓦斯涌出量大等特点,提出了小角度高位钻孔抽采治理初采期瓦斯的方法;2219工作面应用实践表明,初采期内,小角度高位钻孔抽采瓦斯纯量最高5.25m3/min,瓦斯抽采率64.02%,回风流瓦斯浓度最高为0.32%,上隅角最高瓦斯浓度0.96%,未出现瓦斯超限现象,取得了很好的初采期瓦斯治理效果。     

锚栓用量对纯锚固岩棉保温系统抗风压性能的影响

采用ETAG 004:2013《外墙外保温薄抹灰系统欧洲技术认证指南》中规定的静态泡沫块法,测试在单位面积上使用不同数量锚栓的岩棉板外保温系统的抗风压性能。通过试验可以得出:在混凝土墙体上单纯采用敲击式锚栓锚固岩棉板外保温系统时,拉伸强度可达12.9 k Pa;单位面积增加锚栓的使用量可以提高系统的抗拉承载力,但在不同条件下增加相同数量锚栓对系统抗风载能力提高的程度不同;在普通混凝土墙中,单纯锚固岩棉板保温系统破坏时,单个锚栓承载力平均值的最大值约为其拉拔承载力的50.3%。     

Decorative near-infrared transmission filters featuring high-efficiency and angular-insensitivity employing 1D photonic crystals

We present a new scheme for visibly-opaque but near-infrared-transmitting filters involving 7 layers based on one-dimensional ternary photonic crystals, with capabilities in reaching nearly 100% transmission efficiency in the near-infrared region. Different decorative reflection colors can be created by adding additional three layers while maintaining the near-infrared transmission performance. In addition, our proposed structural colors show great angular insensitivity up to ±60° for both transverse electric and transverse magnetic polarizations, which are highly desired in various fields. The facile strategy described here involves a simple deposition method for the fabrication, thereby having great potential in diverse applications such as image sensors, anti-counterfeit tag, and optical measurement systems.

     

Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems

This paper considers a novel distributed iterative learning consensus control algorithm based on neural networks for the control of heterogeneous nonlinear multiagent systems. The system's unknown nonlinear function is approximated by suitable neural networks; the approximation error is countered by a robust term in the control. Two types of control algorithms, both of which utilize distributed learning laws, are provided to achieve consensus. In the provided control algorithms, the desired reference is considered to be an unknown factor and then estimated using the associated learning laws. The consensus convergence is proven by the composite energy function method. A numerical simulation is ultimately presented to demonstrate the efficacy of the proposed control schemes.     

基于图像增强的去雾快速算法的FPGA实现

基于图像增强方法，本文提出了一种使用亮度映射的图像去雾快速算法。此算法通过调整室外多雾场景图像的对比度，提高了雾中物体的辨识度。算法的复杂度低、处理延迟小，实时性高，利于FPGA的实现。实现时不需外存储器，延时为ns级，并提供了强度调节接口，以适应较广的应用环境。