Efficient skeleton curve-guided five-axis sweep scanning based on optimal traversing of multiple connected skeleton curves

The five-axis sweep scanning approach is an emerging surface inspection technology which could tremendously boost the inspection efficiency through working in the way of continuous scanning. While inspecting the surfaces with multiple connected skeleton curves, the topological complexity brings conflict between achieving efficient inspection and working in continuous manner. Recently, a skeleton curve-guided five-axis sweep scanning method was proposed to tackle this problem but the resulting inspection path has to inspect the entire surface in a round-trip way. The manner of round-trip inspection pulls down the entire inspection efficiency and should be avoided as much as possible. In this paper, we present an improved skeleton curve-guided five-axis sweep scanning method to generate a more efficient five-axis scanning path for the surface with multiple connected skeleton curves. The proposed method starts from the framework of existing skeleton curve-guided five-axis sweep scanning method. Under the unique kinematic requirements of efficient five-axis sweep scanning, an integer linear programming optimization approach is utilized to optimally connect the inspection paths on independent surface patches and form a shorter skeleton curve-based sweep scanning path as compared with the existing skeleton curve-guided five-axis sweep scanning method. The resulting inspection path is composed of the single-pass inspection for most of the surface and the round-trip inspection for a small part of the surface. The comparison experiments are conducted on two surfaces with multiple connected skeleton curves. Experiment results show that the proposed method significantly outperforms the method provided by the leading commercial software Apexblade and the original skeleton curve-guided five-axis sweep scanning method.     

基于ISSA-Fuzzy-PID算法的无刷直流电机调速控制系统

为了使无刷直流电机(BLDCM)从复杂多变的非线性关系中找出最佳PID参数,提出了一种基于改进麻雀算法(ISSA)优化模糊(fuzzy)控制的调速系统。根据BLDCM工作原理及控制方法在MATLAB平台上搭建仿真模型并加入反向学习策略初始化麻雀种群,形成非线性时变控制系统,并将该优化系统与传统PID以及模糊PID(fuzzy-PID)控制系统进行对比分析。仿真结果表明,基于ISSA-Fuzzy-PID的调速控制系统有较快的动态响应,有效增强了BLDCM转速控制的精度和鲁棒性。     

On trajectory tracking control for nonholonomic mobile manipulators with dynamic uncertainties and external torque disturbances

This paper studies the trajectory tracking control problem of mobile manipulators subject to nonholonomic constraints, operating in task space, with the presence of external torque disturbances and dynamic uncertainties. The proposed controls are robust to external torque disturbances and can overcome the effects of the unknown dynamic parameters. The stability of the closed-loop system and the asymptotic convergences of tracking errors are proved using Lyapunov synthesis. The proposed control strategies have been designed to drive the system motion converges to the desired manifold and, at the same time, guarantees the boundedness of all the closed-loop signals. Simulation results validate that the system trajectory converge to the desired one.     

A cam-quadrilateral mechanism for power transmission of a twin-rotor piston engine

A quadrilateral with four invariable lengths of sides has the characteristic of transforming the variation of the diagonal length to the variation of its interior angle. Thus, the combination of two quadrilaterals with a cam forms the differential velocity drive mechanism (DVDM) of a novel twin-rotor piston engine (TRPE). The DVDM restricts the two coaxial rotors to rotate with periodical but nonuniform velocity, and the volume of working chambers created by the adjacent vane pistons of the two rotors alternately expands and then contracts. The volumetric change of working chambers is used to generate the four-stroke engine cycle. The kinematic model and the detailed position, velocity, and acceleration analysis results of the TRPE are presented. The results show that this novel engine, associated with the advantages of higher uniformity of torque and power density due to multiple power strokes per revolution of the output shaft, has a compact and totally balanced design.     

基于改进的YOLOv5网络的异常行为检测算法研究

各行各业安全问题尤为重要,对人员的异常行为须及时检测并采取相应的措施才能有效预防安全事故的发生。因此本文提出基于改进的YOLOv5网络的异常行为识别算法,通过实时处理视频监控中人员的异常行为,从而保证企业的安全运行。首先,对输入数据集进行特征提取处理,本文使用YOLOv5的backbone特征提取网络提取视频特征,能够在不同图像细粒度上聚合并形成图像特征;其次,送入到时间注意块,因为不同时刻特征的贡献值并不相同,因此加入此模块赋予特征不同的贡献值;最后,送入特征预测网络,该网络由LSTM搭建,对历史特征序列进行解码,以预测当前的特征。以玩手机和吸烟为例对所提出的网络进行验证,训练集准确率高达96.42%,测试集准确率高达95.21%。     

Enhanced hydrodesulphurization of cokes deposited on iron ore by air gasification

The influence on air-gasification of cokes deposited on iron ores were studied in under successive desulphurization at 750 °C under atmospheric hydrogen. Gasification promoted by steam (water: 40 μl min⁻¹) at 350 °C for 125 min gasified 21% of the coke and allowed 25% oxidative desulphurization (based on sulphur in the coke) during the gasification and enhanced the successive hydrodesulphurization level up to 63% giving a total desulphurization of 88%. This level is comparable with that achieved after grinding. Gasification at higher temperatures, which burned more coke, was less effective in enhancing hydrosedulphurization. Gasification increases the access of hydrogen molecules to sulphur atoms in the coke. Gasification, which increases the surface area of the coke and removes the sulphur preferentially, is discussed in terms of reactivity.     

磁流变智能结构的微粒群优化控制

在磁流变智能结构的减震控制中,结构的位移控制和加速度控制是其减震控制的两个重要控制目标,这就使得磁流变智能结构的减震控制成为了一多目标优化控制。为此,本文采用微粒群优化控制算法同时对磁流变智能结构的位移和加速度进行了最优控制分析,实现了磁流变智能结构多目标的优化减震控制。并对一每层各安装一个磁流变阻尼器的五层钢结构分别采用微粒群优化控制算法、ON控制算法和OFF控制算法进行了实例对比分析,结果表明：采用微粒群优化控制可显著地减小结构的位移反应,同时也可一定程度地减小结构的加速度反应。     

Numerical analysis on the combined transport effects of H2 and CO2 on the laminar premixed flame characteristics of biogas-hydrogen blends

The combined and respective transport effects of H₂ and CO₂ on the flame structure, laminar flame speed and radical pool of the BG40H60 blends at different equivalence ratios are investigated quantitatively with the numerical simulation in this study. The results show that H₂ transport dominates the decrease and enhancement of HRR and mole fractions of minor species at the fuel-lean and fuel-rich conditions. However, H₂ or CO₂ transport hardly affects concentrations of major species expect for H₂ and CO₂. Besides, the dominated H₂ transport contributes to the decreased/increased laminar flame speed at the fuel-lean/fuel-rich condition, while the OH radical can reflect the laminar flame speed variation caused by the H₂ and CO₂ transport. Based on the rate-of-production (ROP) analysis of OH radical, the most sensitive reactions to H₂ and CO₂ transport are OH + H₂H₂O + H/H + O₂O + OH and OH + CH₂OHCO + H₂O at the fuel-lean and fuel-rich conditions respectively. The major production reactions (H + O₂O + OH, H + HO₂ = 2OH, O + H₂H + OH, 2OH = O + H₂O) of OH radical are suppressed or improved more significantly with the H₂ and CO₂ transport at the fuel-lean or fuel-rich condition, leading to the suppressed or improved OH radical pool and the flame propagation at the fuel-lean or fuel-rich condition. Furthermore, it is demonstrated that CO₂ transport suppresses the reaction of OH + H₂H₂O + H considerably to improve the OH radical pool at the fuel-rich condition and cannot be neglected when investigating the flame propagation of biogas-hydrogen blends.     

Security in Mobile IPv6: A survey

Secure mobile communication is essential for the pervasive accessibility of critical information infrastructure. Connecting control systems with the business enterprise, wireless telemetry and mobile user interaction with critical infrastructure systems are examples of services that motivate the need for secure mobile communication. Mobile IPv6 is being touted to provide communication support for such services. The security of Mobile IPv6 poses key challenges impeding its wide-scale adoption. Several security mechanisms have been proposed in the literature. This paper surveys security vulnerabilities of Mobile IPv6, provides a taxonomy for the main existing and proposed solutions, and then extends to outline some open issues.     

Single image dehazing using improved cycleGAN

Haze is an aggregation of very fine, widely dispersed, solid and/or liquid particles suspended in the atmosphere. In this paper, we propose an end-to-end network for single image dehazing, which enhances the CycleGAN model by introducing a transformer architecture within the generator, which is specific for haze removal. The proposed model is trained in an unpaired fashion with clear and hazy images altogether and does not require pairs of hazy and corresponding ground-truth clear images. Furthermore, the proposed model does not depend on estimating the parameters of the atmospheric scattering model. Rather, it uses a K-estimation module as the generator’s transformer for complete end-to-end modeling. The feature transformer introduced in the proposed generator model transforms the encoded features into desired feature space and then feeds them into the CycleGAN decoder to create a clear image. In the proposed model we further modified the cycle consistency loss to include the SSIM loss along with pixel-wise mean loss to produce a new loss function specific for the reconstruction task, which enhances the performance of the proposed model. The model performs well even on the high-resolution images provided in the NTIRE 2019 challenge dataset for single image dehazing. Further, we perform experiments on NYU-Depth and reside beta datasets. Results of our experiments show the efficacy of the proposed approach compared to the state-of-the-art in removing the haze from the input image.