Performance Evaluation of Three-Dimensional UWB Real-Time Locating Auto-Positioning System for Fire Rescue

Fire rescue challenges and solutions have evolved from straightfor-ward plane rescue to encompass 3D space due to the rise of high-rise city buildings.Hence,this study facilitates a system with quick and simplified on-site launching and generates real-time location data,enabling fire rescuers to arrive at the intended spot faster and correctly for effective and precise rescue.Auto-positioning with step-by-step instructions is proposed when launching the locating system,while no extra measuring instrument like Total Station(TS)is needed.Real-time location tracking is provided via a 3D space real-time locating system(RTLS)constructed using Ultra-wide Bandwidth technology(UWB),which requires electromagnetic waves to pass through concrete walls.A hybrid weighted least squares with a time difference of arrival(WLS/TDOA)positioning method is proposed to address real path-tracking issues in 3D space and to meet RTLS requirements for quick computing in real-world applications.The 3D WLS/TDOA algorithm is theoretically constructed with the Cramer-Rao lower bound(CRLB).The computing complexity is reduced to the lower bound for embedded hardware to directly compute the time differential of the arriving signals using the time-to-digital converter(TDC).The results of the experiments show that the errors are controlled when the positioning algorithm is applied in various complicated situations to fulfill the requirements of engineering applications.The statistical analysis of the data reveals that the proposed UWB RTLS auto-positioning system can track target tags with an accuracy of 0.20 m.

Performance analysis of real-time and post-mission kinematic precise point positioning in marine environments

This article focuses on the performance analysis of both real-time and post-mission kinematic precise point positioning(PPP)in challenging marine environments.For this purpose,a real dynamic experiment lasting 6 h was carried out on a lake dam in?orum City of Turkey.While the kinematic test was continuing,the real-time PPP coordinates were obtained for each measurement epoch with a commercial real-time PPP(RT-PPP)service,namely the Trimble Center Point RTX.Then the post-mission PPP(PM-PPP)coordinates were calculated by using Multi-GNSS data and the Multi-GNSS Experiment(MGEX)precise products.The kinematic RT-PPP and PM-PPP results showed that the PPP coordinates were consistent with the relative solution at centimetre and decimetre level in horizontal and height components,respectively.This study implies that PPP technique is a powerful tool for highly accurate positioning in both real-time and post-mission modes,even for dynamic applications in harsh environments.

Data-driven real-time prediction for attitude and position of super-large diameter shield using a hybrid deep learning approach

The presented research introduces a novel hybrid deep learning approach for the dynamic prediction of the attitude and position of super-large diameter shields-a critical consideration for construction safety and tunnel lining quality.This study proposes a hybrid deep learning approach for predicting dynamic attitude and position prediction of super-large diameter shield.The approach consists of principal component analysis(PCA)and temporal convolutional network(TCN).The former is used for employing feature level fusion based on features of the shield data to reduce uncertainty,improve accuracy and the data effect,and 9 sets of required principal component characteristic data are obtained.The latter is adopted to process sequence data in predicting the dynamic attitude and position for the advantages and potential of convolution network.The approach’s effectiveness is exemplified using data from a tunnel construction project in China.The obtained results show remarkable accuracy in predicting the global attitude and position,with an average error ratio of less than 2 mm on four shield outputs in 97.30%of cases.Moreover,the approach displays strong performance in accurately predicting sudden fluctuations in shield attitude and position,with an average prediction accuracy of 89.68%.The proposed hybrid model demonstrates superiority over TCN,long short-term memory(LSTM),and recurrent neural network(RNN)in multiple indexes.Shapley additive exPlanations(SHAP)analysis is also performed to investigate the significance of different data features in the prediction process.This study provides a real-time warning for the shield driver to adjust the attitude and position of super-large diameter shields.

Positively selected genes of the Chinese tree shrew （Tupaia belangeri chinensis） locomotion system

While the recent release of the Chinese tree shrew （Tupaia belangeri chinensis） genome has made the tree shrew an increasingly viable experimental animal model for biomedical research, further study of the genome may facilitate new insights into the applicability of this model. For example, though the tree shrew has a rapid rate of speed and strong jumping ability, there are limited studies on its locomotion ability. In this study we used the available Chinese tree shrew genome information and compared the evolutionary pattern of 407 locomotion system related orthologs among five mammals （human, rhesus monkey, mouse, rat and dog） and the Chinese tree shrew. Our analyses identified 29 genes with significantly high co （Ka/Ks ratio） values and 48 amino acid sites in 14 genes showed significant evidence of positive selection in the Chinese tree shrew. Some of these positively selected genes, e.g. HOXA6 （homeobox A6） and AVP （arginine vasopressin）, play important roles in muscle contraction or skeletal morphogenesis. These results provide important clues in understanding the genetic bases of locomotor adaptation in the Chinese tree shrew.

Design of trotting controller for the position-controlled quadruped robot

This work presents a controller designed for position-controlled quadrupedal dynamic locomotion,aiming at simple and robust trotting control. The controller takes the torso attitude angles and velocities into planning foot trajectories. Firstly design of the servo motor actuated quadruped robot is introduced and the kinematic equations are deduced. Then a scheme is presented for controlling the robot torso attitude based on the virtual leg model. Furthermore,it demonstrates the design of the controller which enables the robot to have a wide range of trotting gaits and omni-directional motions. Finally,results of robust trotting in various speeds,path tracking and push recovery in simulation are reported,and results of trotting on real quadruped robots will be studied.

Quality monitoring of real-time GNSS precise positioning service system

The Real-Time Global Navigation Satellite System(GNSS)Precise Positioning Service(RTPPS)is recognized as the most promising system by providing precise satellite orbit and clock correc-tions for users to achieve centimeter-level positioning with a stand-alone receiver in real-time.Although the products are available with high accuracy almost all the time,they may occasionally suffer from unexpected significant biases,which consequently degrades the positioning perfor-mance.Therefore,quality monitoring at the system-level has become more and more crucial for providing a reliable GNSS service.In this paper,we propose a method for the monitoring of realtime satellite orbit and clock products using a monitoring station network based on the Quality Control(QC)theory.The satellites with possible biases are first detected based on the outliers identified by Precise Point Positioning(PPP)in the monitoring station network.Then,the corresponding orbit and clock parameters with temporal constraints are introduced and esti-mated through the sequential Least Square(LS)estimator and the corresponding Instantaneous User Range Errors(IUREs)can be determined.A quality indicator is calculated based on the IUREs in the monitoring network and compared with a pre-defined threshold.The quality monitoring method is experimentally evaluated by monitoring the real-time orbit and clock products generated by GeoForschungsZentrum(GFZ),Potsdam.The results confirm that the problematic satellites can be detected accurately and effectively with missed detection rate 4×10^(-6) and false alarm rate 1:2×10^(-5).Considering the quality alarms,the PPP results in terms of RMS of positioning differences with respect to the International GNSS Service(IGS)weekly solution in the north,east and up directions can be improved by 12%,10%and 27%,respectively.

Efficient Harmonic Analysis Technique for Prediction of IGS Real-Time Satellite Clock Corrections

Real-time satellite orbit and clock corrections obtained from the broadcast ephemerides can be improved using IGS real-time service (RTS) products. Recent research showed that applying such corrections for broadcast ephemerides can significantly improve the RMS of the estimated coordinates. However, unintentional streaming interruption may happen for many reasons such as software or hardware failure. Streaming interruption, if happened, will cause sudden degradation of the obtained solution if only the broadcast ephemerides are used. A better solution can be obtained in real-time if the predicted part of the ultra-rapid products is used. In this paper, Harmonic analysis technique is used to predict the IGS RTS corrections using historical broadcasted data. It is shown that using the predicted clock corrections improves the RMS of the estimated coordinates by about 72%, 58%, and 72% in latitude, longitude, and height directions, respectively and reduces the 2D and 3D errors by about 80% compared with the predicted part of the IGS ultra-rapid clock corrections.

“机车行车安全与设备”课程岗位能力数字化培养研究

针对教学内容和岗位实际脱节、岗位能力培养的实施步骤和方法不够完善和思政育人路径不够全面等铁路机务岗位能力培养过程中面临的实际问题,依托铁道机车运用与维护专业核心课程“机车行车安全与设备”,提出了相应的三方面六种解决方法,形成了理实一体的行动导向模式和育训并举的实践训练模式,旨在通过数字化教学改革提升铁路机务岗位能力的培养实效。

电机车运输监控系统在煤矿中的应用

主要研究了电机车运输监控系统在煤矿中的应用。分析了电机车运输监控系统的组成、原理、功能,以及在煤矿运输过程中的实际应用效果。通过对电机车运输监控系统的优势和局限性进行分析,结合实际案例,探讨了该系统在提高煤矿运输效率和安全性方面的表现,以及与其他运输监控系统的整合。

An Underwater Robot Inspection Anomaly Localization Feedback System Based on Sonar Technology

This article introduces an underwater robot inspection anomaly localization feedback system comprising a real-time water surface tracking,detection,and positioning system located on the water surface,while the underwater robot inspection anomaly feedback system is housed within the underwater robot.The system facilitates the issuance of corresponding mechanical responses based on the water surface’s real-time tracking,detection,and positioning,enabling recognition and feedback of anomaly information.Through sonar technology,the underwater robot inspection anomaly feedback system monitors the underwater robot in real-time,triggering responsive actions upon encountering anomalies.The real-time tracking,detection,and positioning system from the water surface identifies abnormal conditions of underwater robots based on changes in sonar images,subsequently notifying personnel for necessary intervention.

A real-time detection and positioning method for small and weak targets using a 1D morphology-based approach in 2D images

A small and weak target detection method is proposed in this work that outperforms all other methods in terms of real-time capability.It is the first time that two-dimensional(2D)images are processed using only one-dimensional1D structuring elements in a morphology-based approach,enabling the real-time hardware implementation of the whole image processing method.A parallel image readout and processing structure is introduced to achieve an ultra-low latency time on the order of nanoseconds,and a hyper-frame resolution in the time domain can be achieved by combining the row-by-row structure and the electrical rolling shutter technique.Experimental results suggest that the expected target can be successfully detected under various interferences with an accuracy of 0.1 pixels(1σ)under the worst sky night test condition and that a centroiding precision of better than 0.03 pixels(1σ)can be reached for static tests.The real-time detection method with high robustness and accuracy is attractive for application to all types of real-time small target detection systems,such as medical imaging,infrared surveillance,and target measurement and tracking,where an ultra-high processing speed is required.

Effect of High Positive Acceleration(+Gz) Environment on Dental Implant Osseointegration:A Preliminary Animal Study

Objective To observe the effect of high positive acceleration(+Gz) environment on dental implant osseointegration in a rabbit model and to investigate its mechanism.Methods Forty-eight New Zealand white rabbits were randomly divided into 6 groups. The rabbit’s mandibular incisors were extracted and 1 implant was placed in each socket immediately. After 1 week of rest, the rabbits were exposed to a high +Gz environment, 3 times a week. The rabbits were sacrificed at 3 weeks(2 weeks +Gz exposure), 5 weeks(4 weeks +Gz exposure), and 12 weeks(4 weeks +Gz exposure and 7 weeks normal environment) after surgery, respectively. Specimens were harvested for micro-CT scanning, histological analysis, and real-time polymerase chain reaction examination.Results Compared with those in the control group, the mRNA expression levels of bone morphogenetic protein-2(BMP-2), osteopontin(OPN), and transforming growth factor-β1(TGF-β1)were significantly lower(P < 0.05), while the mRNA expression level of receptor activator of nuclear factor κB ligand(RANKL) and the RANKL/osteoprotegerin(OPG) ratio were significantly higher(P < 0.05)at 3 weeks;values of bone volume fraction, trabecular number, bone-implant contact(BIC), and TGF-β1 and OPG mRNA expression levels were significantly lower(P < 0.05), and the value of trabecular separation, RANKL mRNA expression level and RANKL/OPG ratio were significantly higher(P < 0.05) at 5 weeks;and the value of BIC was still significantly lower(P < 0.05) at 12 weeks in the experimental group.Conclusion Early exposure to the high +Gz environment after implant surgery might have an adverse effect on osseointegration, and its mechanism could be related to the inhibition of osteoblast activity and promotion of osteoclast activity.

Low-cost experimental application of real-time kinematic positioning for increasing the benefits in cereal crops

Traditional agriculture is facing several challenges worldwide such as increased population growth,rapid forestry and urbanization,resource scarcity,climate change,environmental pollution,competition among different markets.Hence,farmers need to improve productivity in order to maintain the output level.This study attempted to evaluate the benefits of using Real-Time Kinematic(RTK)positioning in precision agriculture through a series of real measurements carried out when farming cereals.All farming management actions involved in the cereal crop process(raise fallow,plow,sow,fertilize,mow,and harvest)have been done using an automatic guidance system that has reduced costs.A reduction of 20%has been quantified in the fuel,the amount of fertilizer,the labor costs and the hours of work.Consequently,the environmental impact has been also reduced.An inexpensive system consisting of a reference base station near the field and a mobile unit mounted on the test vehicle has been installed in order to increase the benefits in cereal crops.Global Navigation Satellite System(GNSS)systems including Global Positioning System(GPS),GLONASS,Galileo and Beidou have been used in the analysis.This research serves as a practical guide to implementing a low-cost guidance system to achieve best management practice.

Applying Global Positioning System Real-Time Kinematic Technology to Collection and Analysis of Rowing Information

To obtain higher accuracy of information concerning boat motion, the use of global positioning system (GPS) real-time kinematic (RTK) technology was investigated. Through RTK technology, a measurement precision of the ±1 cm range can be achieved. The research equipment included a GPS receiver and a personal digital assistant as a data control and processing unit. Real-time GPS data was captured and processed to acquire various parameters, including the boat track, velocity curve, stroke rate, and stroke distance. Using this data, the quantitative information related to rowing training can be achieved. The results are helpful for analyzing the biomechanical parameters of rowing techniques and for evaluating training efficiency.

朔黄铁路2万吨组合列车编组方式探究及优化

由于朔黄铁路2万吨列车牵引质量大、编组长,在运行时不可避免地会由于制动、缓解或地形影响而产生较大的纵向冲动,目前在实际运用中多以优化操纵方式来减小车钩力,但该方式受操纵连续性的影响较大,且优化幅度有限。从列车编组方式的角度出发,探究如何减小车钩力及改善列车综合性能。在不改变现行2万吨列车牵引质量、机车车辆数量的基础上,更改从控机车位置并探究其对列车制动性能、纵向冲动和缓解时再充风能力的影响,为改进2万吨列车编组方式提供数据支撑和理论依据。

矿用电机车精确定位及导航系统关键技术研究

针对井下电机车的定位技术仅能实现目标的区段定位,无法实时获取行驶电机车精确位置的问题,采用无线及有线通信结合、定位基站和速度传感器互相配合为技术路线设计了一种矿用电机车精确定位及导航系统。该系统可对电机车具体位置、运动轨迹及分布情况等进行实时监测,有效提高定位精度,并建立了一种信号灯自适应控制策略及模型,实现井下电机车运输安全感知全覆盖。

煤矿井下机车运输智能监控调度系统关键技术研究

井下机车运输作为目前井下运输主要发展方向,受特定道路环境限制影响,仍缺乏有效的机车运输监控及调度系统。针对上述问题,将数据通信与GIS等技术相融合,建立了网络、数据通信、GIS信息相统一的集成化井下机车运输综合监控及管理平台,可实现车辆跟踪定位、交通信号联动控制、超速报警、追尾报警等功能,为井下交通运输提供实时调度与智能支持,并可为矿井环境、人员、设备等安全监测提供扩展应用,实现矿山灾害预警和突发事件救助,使井下机车运输优势得以有效发挥。

非限制场景下铁路机车车号定位检测方法

针对传统铁路机车车号定位检测模型泛化性较低,不适用于多种检测应用场景等问题,提出一种适用于非限制场景、基于YOLO(You Only Look Once)v4-tiny模型的铁路机车车号定位检测方法。文章采用空洞卷积代替标准卷积,增大机车车号特征提取感受野,提升传统YOLOv4-tiny模型的检测精度;建立铁路机车车号数据集(RLND,Railway Locomotive Number Dataset),用于模型训练,并对模型的检测效果进行验证。验证结果表明,该方法对铁路机车车号的定位检测精度为99.44%,检测速度为50帧/s,能够应对非限制场景下的机车车号定位检测需求。

基于非视距误差抑制的矿井轨道机车定位方法研究

矿井轨道机车定位方法以超宽带(UWB)定位为主,但井下运输巷道环境复杂,非视距传播多发,对UWB定位精度的影响严重。目前针对非视距传播引起的定位误差研究存在算法复杂、实时定位差等问题。通过分析轨道机车定位特点,在基于信号到达时间(TOA)的UWB定位技术基础上,提出一种基于非视距误差抑制的矿井轨道机车定位方法。在轨道机车不同位置安装2个定位卡,采用射频识别技术准确划分定位卡与定位基站的相对位置关系,根据UWB定位信号在非视距传播条件下测距值比实际值大的情况,采用2个定位卡之间距离测算值与实际值差值的经验范围,推算出不同定位卡和定位基站位置关系下非视距传播条件的鉴别阈值,通过该鉴别阈值剔除由非视距路径传播定位信号的测距值,使用由视距路径传播定位信号的测距值进行定位计算,实现对非视距误差的抑制,从而提高矿井轨道机车平均定位精度。测试结果表明:使用基于非视距误差抑制的矿井轨道机车定位方法,在定位信号处于视距传播条件时,机车平均定位误差均在1m以内;在定位信号处于非视距传播条件时,大部分非视距误差得到了有效抑制,平均定位精度在1 m左右,轨道机车定位精度较常规基于TOA的UWB定位方法大幅度提升。

Application Research of an Intelligent Detection Algorithm for Vehicle Trajectory Route Deviation

In the vehicle trajectory application system, it is often necessary to detect whether the vehicle deviates from the specified route. Trajectory planning in the traditional route deviation detection is defined by the driver through the mobile phone navigation software, which plays a more auxiliary driving role. This paper presents a method of vehicle trajectory deviation detection. Firstly, the manager customizes the trajectory planning and then uses big data technologies to match the deviation between the trajectory planning and the vehicle trajectory. Finally, it achieves the supervisory function of the manager on the vehicle track route in real-time. The results show that this method could detect the vehicle trajectory deviation quickly and accurately, and has practical application value.