一种直升机避障电力线检测方法

电力线是一类形状细长、特征稀疏、随着视角的变化容易混淆在大量背景信息中的特殊障碍物，常规电力线检测识别算法得到的目标框对电力线所在位置的估计不够准确。为此，提出了一种相对角度估计方法，基于常规电力线目标检测与识别算法，并结合电力线相对角度估计，从而提高电力线的检测识别过程中所在位置的精度。相比电力线绝对角度回归的方法，提出的相对角度估计方法容易训练易收敛，计算量小，适用于实时性要求较高的应用场合。     

Structural,electrical, and linear/nonlinear optical characteristics of thermally evaporated molybdenum oxide thin films

Homogeneous thin films of Molybdenum oxide (MoO₃) were grown on quartz and glass substrates using the thermal evaporation method. XRD results showed that the MoO₃ powder has a polycrystalline structure with an orthorhombic crystal system whereas the MoO₃ thin films have amorphous nature. SEM images showed that the MoO₃ thin films have a nearly uniform surfaces with worm-like shape grains. The film thickness influences on the linear and nonlinear optical characteristics of MoO₃ thin films that were examined using spectrophotometric measurements and from which, the linear optical constants of the MoO₃ thin films were estimated. The electronic transition type was determined as a direct allowed one. The values of the optical band gap were obtained to be in the range of 3.88–3.72 eV. The dispersion parameters, third-order nonlinear optical susceptibility, and the nonlinear refractive index of the MoO₃ thin films were determined and interpreted in the light of the single oscillator model. The temperature dependence of the DC electrical conductivity and the corresponding conduction mechanism for the MoO₃ films were investigated at temperatures ranging from 303 to 463 K.     

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。     

Effect of the particle size ratio on macro- and mesoscopic shear characteristics of the geogrid-reinforced rubber and sand mixture interface

As a new type of material for civil engineering projects, the rubber and sand mixture is widely used in roadbed fillers, offering environmental benefits over traditional tyre disposal methods. This study uses a large-scale direct shear apparatus to examine the interface shear properties of the geogrid-reinforced rubber and sand mixture, considering different particle size ratios (r), rubber contents, and normal stresses. Based on indoor tests, direct shear models of the mixture with different values of r are established in PFC^3D, revealing the meso-mechanical mechanism of the mixture in the direct shear process. The results show that when r is greater than 1, incorporating a certain amount of rubber particles can increase the shear strength of the mixture. The r values of 15.78, 7.63, and 3.98 correspond to an optimal rubber content of 30%, 10%, and 20%, respectively. When r is less than 1, mixing rubber particles can only reduce the shear strength of the mixture. When the rubber content is low, the smaller the value of r, the greater is the thickness of the shear band. Furthermore, the normal and tangential contact forces are greater. The fabric anisotropy evolution law of the mixture is consistent with the change in the contact force distribution.     

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.     

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.     

Characterization of Bi2O3 thin films for doping photoluminescent Er3+ ions

Undoped and Er³⁺-doped Bi₂O₃ thin films were sputter-deposited on Si(100) substrates. Sufficiently oxidized Bi₂O₃ films with refractive indices between 2.17?2.23 were obtained at a wavelength of 633 nm; these values are comparable to those of bulk Bi₂O₃ crystals. While the film composition was stable for deposition temperatures between room temperature (RT) and 450 °C, the refractive index steeply decreased above 450 °C and reached 1.4 at 600 °C. The lowering of the optical transmittance spectra indicated aggregation of metallic Bi and darkening of the film. All films exhibited X-ray diffraction patterns of α-Bi₂O₃. The direct and indirect bandgap energies derived from the Tauc plots were 3.4–3.7 eV and 1.9–2.5 eV, respectively, depending on the O₂ flow rate and deposition temperature. Upon excitation of Er³⁺-doped Bi₂O₃ films at 532 nm, Er³⁺ emissions peaking at 1537 and 1541 nm appeared, and the photoluminescence spectra included fine structures reflecting crystal-field splitting. Resonant excitation of Er³⁺ 4f levels and indirect excitation via the defect levels of Bi₂O₃ followed by energy transfer to Er³⁺ contributed to the emission. The films deposited at RT with Er concentrations of 2 at.% had the emission intensity of Er³⁺, but concentration quenching strongly suppressed the Er³⁺ emission because the doped Er³⁺ ions stayed inside the Bi₂O₃ crystals. At deposition temperatures above 400 °C, the concentration quenching was mitigated possibly because out-diffusion of Er³⁺ ions reduced the effective number of Er³⁺ ions in the Bi₂O₃ crystalline domains.     

Growth mechanism and gas-sensing characteristics of organic-additive-free zinc oxide of various shapes

Zinc oxide is widely used in gas sensors, solar cells, and photocatalysts because of its wide bandgap and exciton binding energy of 60 meV in various metal oxides. To use ZnO as a gas sensor, it is necessary to synthesize it with surface defects and a large specific surface area. In this study, hydrothermal synthesis without surfactants was employed to obtain organic-additive-free ZnO. For morphology control, we varied the ratio of the hydroxide ion concentration to the zinc ion concentration. To confirm the growth mechanism of ZnO, we performed X-ray diffraction, scanning electron microscopy, and transmission electron microscopy analyses. Raman spectroscopy and photoluminescence measurements were performed to analyze the surface properties. The Brunauer–Emmett–Teller method and probe stations were used to measure the specific surface area and sensitivity of the gas sensor, respectively. The results confirmed that flower-shaped ZnO is the most suitable gas-sensing material.     

Microwave bandpass filter by feedback interference topology

This paper proposes a signal feedback interference topology to control the characteristics of a coupled line bandpass filter. Control is carried out by varying the ratio of the transmission line parameters of the forward and the feedback couplers. The topology produces a compact filter that does not require a complicated design or fabrication. The results of the insertion and return losses show that the feedback‐controlled design has desirable features in terms of the design frequency, fractional bandwidth, stopband rejection level, roll‐off rate and insertion loss. The test results of the fabricated prototype achieved good agreement with the simulation results of the ideal transmission line design model. Several microwave, modern wireless and mobile/satellite communication systems may benefit from such a filter design due to its compactness and flexibility.     

Smart control of the assembly process with a fuzzy control system in the context of Industry 4.0

Assembly line balancing is important for the efficiency of the assembly process, however, a wide range of disruptions can break the current workload balance. Some researchers explored the task assignment plan for the assembly line balancing problem with the assumption that the assembly process is smooth with no disruption. Other researchers considered the impacts of disruptions, but they only explored the task re-assignment solutions for the assembly line re-balancing problem with the assumption that the re-balancing decision has been made already. There is limited literature exploring on-line adjustment solutions (layout adjustment and production rate adjustment) for an assembly line in a dynamic environment. This is because real-time monitoring of an assembly process was impossible in the past, and it is difficult to incorporate uncertainty factors into the balancing process because of the randomness and non-linearity of these factors. However, Industry 4.0 breaks the information barriers between different parts of an assembly line, since smart, connected products, which are enabled by advanced information and communication technology, can intelligently interact and communicate with each other and collect, process and produce information. Smart control of an assembly line becomes possible with the large amounts of real-time production data in the era of Industry 4.0, but there is little literature considering this new context. In this study, a fuzzy control system is developed to analyze the real-time information of an assembly line, with two types of fuzzy controllers in the fuzzy system. Type 1 fuzzy controller is used to determine whether the assembly line should be re-balanced to satisfy the demand, and type 2 fuzzy controller is used to adjust the production rate of each workstation in time to eliminate blockage and starvation, and increase the utilization of machines. Compared with three assembly lines without the proposed fuzzy control system, the assembly line with the fuzzy control system performs better, in terms of blockage ratio, starvation ratio and buffer level. Additionally, with the improvement of information transparency, the performance of an assembly line will be better. The research findings shed light on the smart control of the assembly process, and provide insights into the impacts of Industry 4.0 on assembly line balancing.