地铁供电系统中压开关柜电流分析理论和方法

通过分析地铁供电系统不同电压等级的设备电流特征,确定35 kV电压等级设备电流可构造标准曲线,采用机器智能学习算法分析、测算地铁供电系统中各类开关峰谷时段运行电流,以均值-方差方法确定电流的高度异常偏离点,实现异常点数据周期内统计以及实时提醒功能。应用电流实测值分析电流在工作日、节假日的不同曲线,为负荷预测和非正常运行方式下的负荷叠加风险提供预测和评估依据,保障供电系统的安全运行,提高负荷管控效率。     

道路混凝土分层结构评价方法与指标研究(英文)

结合机理探寻、试验分析和对大量实体工程检测数据的提炼集成,系统研究了道路混凝土外分层与内分层结构,建立起混凝土分层结构模型及评价方法。建议采用密度变异性和吸水率变异性指标评价道路混凝土外分层和内分层结构,为工艺控制道路混凝土内、外分层奠定了基础。     

专业油田增产船的开发研究

油田增产船是一型主要用于海上油田增产增注作业的海洋工程船.根据专业油田增产船的船型特点,通过集成化布置,解决了专业设备系统复杂、布置空间有限等技术难题,并结合作业安全防护、推进方案和综合电站的研究,与国外同类优秀船型作对比分析,最终设计出综合性能优良且自动化程度高的专业油田增产船.     

Automatic outer surface extraction of femoral head in CT images

Computer-aided hip surgery planning and implant design applications require accurate segmentation of femoral head and proximal acetabulum. An accurate outer surface extraction of femoral head using marching cubes algorithm remains challenging due to deformed shapes and extremely narrow inter-bone regions. In this paper, we present an automatic and fast approach for segmentation of femoral head and proximal acetabulum which leads to accurate and compact representation of femoral head using marching cubes algorithm. At first, valley-emphasized images are constructed from original images so that valleys stand out in high relief. Otsu’s multiple thresholding technique is applied to seperate the images into bone and non-bone classes. Region growing method and threedimensional (3D) morphological operations are performed to fill holes in the bone. In the reclassification process, the bone regions are further segmented, and the boundaries of the bone regions are further refined based on Bayes decision rule. Finally, marching cubes algorithm is applied to reconstruct a 3D model and extract the outer surface of femoral head and proximal acetabulum. Experimental results show that this method is an accurate segmentation technique for femoral head and proximal acetabulum and it can be applied as a tool in medical practice.     

基于PANDA软件的框架网坐标解算可靠性分析

应用高精度定位解算软件PANDA对框架网进行解算,并与Bernese解进行比较,探讨不同软件模型下框架网的点位坐标解算方法及其精度;通过算例表明PANDA软件的定位解算结果与Bernese的解有较好的一致性,表明PANDA软件有较高的可靠性和稳定性。     

Key technologies of ship remote control system in inland waterways under ship-shore cooperation conditions北大核心CSCD

［Objective ］ To meet the requirements of remotely controlling ship in curved, narrow and crowded inland waterways, this paper proposes an approach that consists of CNN-based algorithms and knowledge based models under ship-shore cooperation conditions. ［Method］On the basis of analyzing the characteristics of ship-shore cooperation, the proposed approach realizes autonomous perception of the environment with visual simulation at the core and navigation decision-making control based on deep reinforcement learning, and finally constructs an artificial intelligence system composed of image deep learning processing, navigation situation cognition, route steady-state control and other functions. Remote control and short-time autonomous navigation of operating ships are realized under inland waterway conditions, and remote control of container ships and ferries is carried out. ［Results］The proposed approach is capable of replacing manual work by remote orders or independent decision-making, as well as realizing independent obstacle avoidance, with a consistent deviation of less than 20 meters. ［Conclusions］The developed prototype system carries out the remote control operation demonstration of the above ship types in such waterways as the Changhu Canal Shenzhou line and the Yangtze River, proving that a complete set of algorithms with a CNN and reinforcement learning at the core can independently extract key navigation information, construct obstacle avoidance and control awareness, and lay the foundation for inland river intelligent navigation systems. © 2022 Journal of Clinical Hepatology. All rights reserved.     

盾构机穿越排气阀井施工方法

对北京市南水北调南干渠盾构机穿越排气阀井施工方法进行了深度分析,通过优化招标图设计方案,采用在施工完成后的排气阀井内回填碎石+土层的方法,较全面地进行了方案设计,安全、快速完成施工任务。     

Travel time estimation oriented freeway sensor placement problem considering sensor failure

Optimal sensor placement on freeway corridor is of great interest to transportation authorities. However, current traffic sensors are easily subject to various failures. Therefore, it is necessary to incorporate sensor failure into the optimal sensor placement model. In this article, a two-stage stochastic model is proposed for the purpose of travel time estimation on freeway corridor. To balance the effectiveness and reliability, a stochastic conditional value at risk (CVaR) model is also proposed. Since both models are too complicated, a customized genetic algorithm is developed. Numerical experiments show that considering sensor failure makes a significant performance improvement in the sensor placement pattern. Sensitivity analysis is also applied to investigate the impact of a number of allowable sensors and different traffic sensor failure probability.     

State estimation in roll dynamics for commercial vehicles

Accurate lateral load transfer estimation plays an important role in improving the performance of the active rollover prevention system equipped in commercial vehicles. This estimation depends on the accurate prediction of roll angles for both the sprung and the unsprung subsystems. This paper proposes a novel computational method for roll-angle estimation in commercial vehicles employing sensors which are already used in a vehicle dynamic control system without additional expensive measurement units. The estimation strategy integrates two blocks. The first block contains a sliding-mode observer which is responsible for calculating the lateral tyre forces, while in the second block, the Kalman filter estimates the roll angles of the sprung mass and those of axles in the truck. The validation is conducted through MATLAB/TruckSim co-simulation. Based on the comparison between the estimated results and the simulation results from TruckSim, it can be concluded that the proposed estimation method has a promising tracking performance with low computational cost and high convergence speed. This approach enables a low-cost solution for the rollover prevention in commercial vehicles.     

Dynamic simulation of train–truck collision at level crossings

Trains crashing onto heavy road vehicles stuck across rail tracks are more likely occurrences at level crossings due to ongoing increase in the registration of heavy vehicles and these long heavy vehicles getting caught in traffic after partly crossing the boom gate; these incidents lead to significant financial losses and societal costs. This paper presents an investigation of the dynamic responses of trains under frontal collision on road trucks obliquely stuck on rail tracks at level crossings. This study builds a nonlinear three-dimensional multi-body dynamic model of a passenger train colliding with an obliquely stuck road truck on a ballasted track. The model is first benchmarked against several train dynamics packages and its predictions of the dynamic response and derailment potential are shown rational. A geometry-based derailment assessment criterion is applied to evaluate the derailment behaviour of the frontal obliquely impacted trains under different conditions. Sensitivities of several key influencing parameters, such as the train impact speed, the truck mass, the friction at truck tyres, the train–truck impact angle, the contact friction at the collision zone, the wheel/rail friction and the train suspension are reported.