Transmission line detection in aerial images: An instance segmentation approach based on multitask neural networks

Camera-based transmission line detection (TLD) is a fundamental and crucial task for automatically patrolling powerlines by aircraft. Motivated by instance segmentation, a TLD algorithm is proposed in this paper with a novel deep neural network, i.e., CableNet. The network structure is designed based on fully convolutional networks (FCNs) with two major improvements, considering the specific appearance characteristics of transmission lines. First, overlaying dilated convolutional layers and spatial convolutional layers are configured to better represent continuous long and thin cable shapes. Second, two branches of outputs are arranged to generate multidimensional feature maps for instance segmentation. Thus, cable pixels can be detected and assigned cable IDs simultaneously. Multiple experiments are conducted on aerial images, and the results show that the proposed algorithm obtains reliable detection performance and is superior to traditional TLD methods. Meanwhile, segmented pixels can be accurately identified as cable instances, contributing to line fitting for further applications.     

Ir-Pt/C composite with high metal loading as a high-performance anti-reversal anode catalyst for proton exchange membrane fuel cells

Voltage reversal induced by hydrogen starvation can severely corrode the anode catalyst support and deteriorate the performance of proton exchange membrane fuel cells. A material-based strategy is the inclusion of an oxygen evolution reaction catalyst (e.g., IrO₂) in the anode to promote water electrolysis over harmful carbon corrosion. In this work, an Ir-Pt/C composite catalyst with high metal loading is prepared. The membrane-electrode-assembly (MEA) with 80 wt% Ir-Pt(1:2)/C shows a first reversal time (FRT) of up to 20 hours, which is about ten times that of MEA with 50 wt% Ir-Pt(1:2)/C does. Furthermore, the MEA with 80 wt% Ir-Pt(1:2)/C exhibits a minimum cell voltage loss of 6 mV@1 A/cm² when the FRT is terminated in 2 hours, in which the MEA with 50 wt% Ir-Pt(1:2)/C exhibits a voltage loss of 105 mV@1 A/cm². Further physicochemical and electrochemical characterizations demonstrate that the destruction of anode catalyst layer caused by the voltage reversal process is alleviated by the use of the composite catalyst with high metal loading. Hence, our results reveal that the combination of OER catalyst on the Pt/C with high metal loading is a promising approach to alleviate the degradation of anode catalyst layer during the voltage reversal process for PEMFCs.     

超宽带大功率合成器设计北大核心CSCD

在80 MHz~1 GHz频段,单个功率管输出功率能达到100 W以上,为研制输出功率400 W的功率放大器,文中设计了四路功率合成器。该合成器需要实现功率容量大、工作频带宽、体积小的设计目标。在功率容量方面,文中采用悬置带状线结构,其功率容量远远大于微带线结构;在工作频带方面,采用切比雪夫九节阻抗变换器,将工作带宽拓宽为80 MHz~1 GHz;在体积方面,文中合成器的功率合成部分采用Y型节级联实现四路功率合成,阻抗变换部分采用切比雪夫阻抗变换器进行阻抗变换,该结构相较于磁环巴伦功率合成器,不但具有损耗小、平坦度高的优点,而且通过将阻抗变换器设计成曲折的形状,进一步缩小了合成器体积。仿真与实测结果显示该合成器在80 MHz~1 GHz范围内还具有较高的平坦度,合成效率可达90%以上。     

Ferulic acid and EGCG alter the structural characteristics of ovalbumin and its application in mineral loading

This study aims to fabricate mineral-loading nanocarriers using natural materials. The interaction patterns between ovalbumin (OVA) and four water-soluble polyphenols, namely ferulic acid (FA), (-)-Epigallo-catechin 3-gallate (EGCG), gallic acid (GA) and epicatechin (EC), were investigated. Results showed that the optimised conditions for preparing stable OVA–polyphenol complexes are at the OVA–polyphenol ratio of 4:1 at pH 6, under which OVA–FA and OVA–EGCG showed the highest stability and mineral-loading capacity among four OVA–polyphenol complexes. The fluorescence results indicated that the addition of EGCG and FA induced a significant fluorescence quenching to OVA. The interaction between OVA and polyphenols involved hydrogen bonding, hydrophobic interaction and electrostatic interaction. Fourier transform infrared spectroscopy (FTIR) analysis suggested that both FA and EGCG enhanced the stability and orderliness of the structure of OVA. The transmission electron microscopy images also exhibited the spherical structure of OVA after the addition of FA and EGCG. Furthermore, scanning electron microscope–energy dispersive X-ray spectrum results suggested that OVA–FA and OVA–EGCG complexes were better mineral carriers than OVA–GA and OVA–EC. This study may serve as the theoretical support for the promising application of OVA in the fabrication of mineral-loading nanocarriers in functional food and pharmaceutic.     

Evaluation of a sulfidogenic system fed with microalgal biomass of Chlorella pyrenoidosa as an electron donor: Sulfate reduction kinetics

In this study, a sulfidogenic reactor fed with microalgal biomass of Chlorella pyrenoidosa as an electron donor was operated in a continuous mode. This study evaluated the influence of various initial sulfate concentration from 1.0 to 2.5 g/L on anaerobic sulfate reduction kinetics by a sulfidogenic enrichment culture predominantly Desulfovibrio sp. VSV2. It was observed that volumetric sulfate reduction rate (VSRR) was consistently increasing with an increase in volumetric sulfate loading rate (VSLR) across the retention time of 7–10 days. For a retention time of 7 days, the maximum VSRR was noted as 0.0050 g/(L.h) with a corresponding VSLR of 0.0089 g/(L.h). When retention time was maintained for 10 days, a maximum sulfate reduction of 65% and a maximum bacterial concentration of 1.632 g/L were achieved for an initial sulfate concentration of 1.5 g/L. It was concluded that VSLR facilitated through both dilution rate and initial sulfate concentration had a significant influence over sulfate reduction kinetics. The results of the study suggested that the microalgal-fed sulfidogenic system could be effectively employed for reduction of sulfate from sulfate-rich wastewater.     

基于人工神经网络的智能化架空线路应变快速解调方法北大核心

为了提高智能化光纤复合架空线路态势感知的实时性,将人工神经网络方法应用于光纤沿线应变解调,确定了神经网络的结构。编程实现了基于洛伦兹模型的最小二乘谱拟合方法和神经网络方法,采用不同信噪比和布里渊频移的布里渊谱训练神经网络,将它们应用于某光纤复合架空线路沿线光纤应变的测量,从不同角度比较了两种方法的计算结果。计算结果表明,神经网络方法能有效获得光纤沿线的布里渊频移进而获得应变,具有与谱拟合方法相似的准确性,但应变解调时间仅约为谱拟合方法的1/20000。研究结果为提高智能光纤复合架空线路态势感知的实时性提供了参考。     

离线式带钢双面翻转检查站方案设计及实践

针对某酸轧机组检查站穿带困难、检查效率低、产生废品多、故障率高的问题,开发了一种离线式带钢双面检查站。该检查站新增了带钢翻转装置,将在入口分切剪处完成定尺剪切的带钢试样由两侧压板夹紧,中间可升降皮带机落下,翻转装置将带钢试样张紧,并翻转90°或者180°,实现带钢的双面检查。皮带机两侧布置有可升降、可横移的活动操作平台,检测人员站在平台上对带钢进行打磨检查,可同时对带钢上下表面进行检测。由于缩短了带钢的传输距离,有效减少了其他擦划伤的影响,提高了带钢表面质量检测准确性。     

Optical design of the Lyman alpha based beam emission spectroscopy(LAB)diagnostic on the HL-2A tokamak

In this article, we present the optical design of a novel diagnostic on the HL-2 A tokamak, i.e. the20-channel edge Lyman-alpha beam emission spectroscopy, which is a promising solution for edge density turbulence research on tokamaks, as it offers the possibility of density fluctuation measurement with a 3.3 mm spatial resolution while maintains a high temporal resolution of1 μs. The optical path, including the reflective collection optics, the high-dispersion spectrometer, and the linear detector array, is carefully optimized to obtain a good image quality and a high throughput. The maximum root mean square radius of the collection optics is 64 μm.The detected photon flux is estimated to be about 10~(11) photons/s/channel.     

Piecewise constant strain kinematic model of externally loaded concentric tube robots

This paper presents a piecewise constant strain kinematic model for concentric tube robots (CTR) in externally loaded conditions. It discretizes the pre-curved tubes comprising the robot into a finite number of pieces and involves external effects as a set of wrench vectors exerted along the robot backbone. Constant strain lets us describe the pieces with helices in which shear deformation and elongation are neglected. The resulting piecewise helix is the simplest curve that can catch the torsion of tubes that play a crucial role in kinematic behavior. This approximation transforms the conventional boundary value problem (BVP) of CTRs models into a set of nonlinear equations that drastically decreases the model resolution time. The present method uses a Lyapunov function and torsional Jacobian to ensure the distal torsion constraint consistently and, as a result, the solution’s convergence. The paper’s primary purpose is to present a fast, numerically stable, and relatively accurate kinematic model not reliant on measurement data. Experimental results on a two-tube prototype and provided for different tip loading conditions reveal maintaining a balance between adequate accuracy and reasonable running time, about 7 ms for five pieces per section, for real-time applications in the presence of external load.     

基于阶段注意力机制的电力线提取算法

电力系统维护是电力系统稳定运行的重要保障，应用智能算法的无人机电力巡检则为电力系统维护提供便捷。电力线提取是自主电力巡检以及保障飞行器低空飞行安全的关键技术，结合深度学习理论进行电力线提取是电力巡检的重要突破点。本文将深度学习方法用于电力线提取任务，结合电力线图像特点嵌入改进的图像输入策略和注意力模块，提出一种基于阶段注意力机制的电力线提取模型（SA-Unet）。本文提出的SA-Unet模型编码阶段采用阶段输入融合策略（Stage input fusion strategy， SIFS），充分利用图像的多尺度信息减少空间位置信息丢失。解码阶段通过嵌入阶段注意力模块（Stage attention module，SAM）聚焦电力线特征，从大量信息中快速筛选出高价值信息。实验结果表明，该方法在复杂背景的多场景中具有良好的性能。