Adaptive H_(∞)Filtering Algorithm for Train Positioning Based on Prior Combination Constraints

To solve the problem of data fusion for prior information such as track information and train status in train positioning,an adaptive H∞filtering algorithm with combination constraint is proposed,which fuses prior information with other sensor information in the form of constraints.Firstly,the train precise track constraint method of the train is proposed,and the plane position constraint and train motion state constraints are analysed.A model for combining prior information with constraints is established.Then an adaptive H∞filter with combination constraints is derived based on the adaptive adjustment method of the robustness factor.Finally,the positioning effect of the proposed algorithm is simulated and analysed under the conditions of a straight track and a curved track.The results show that the positioning accuracy of the algorithm with constrained filtering is significantly better than that of the algorithm without constrained filtering and that the algorithm with constrained filtering can achieve better performance when combined with track and condition information,which can significantly reduce the train positioning error.The effectiveness of the proposed algorithm is verified.

Enhancing train position perception through Al-driven multi-source information fusion

This paper addresses the challenge of accurately and timely determining the position of a train,with specific consideration given to the integration of the global navigation satellite system(GNSS)and inertial navigation system(INS).To overcome the increasing errors in the INS during interruptions in GNSS signals,as well as the uncertainty associated with process and measurement noise,a deep learning-based method for train positioning is proposed.This method combines convolutional neural networks(CNN),long short-term memory(LSTM),and the invariant extended Kalman filter(IEKF)to enhance the perception of train positions.It effectively handles GNSS signal interruptions and mitigates the impact of noise.Experimental evaluation and comparisons with existing approaches are provided to illustrate the effectiveness and robustness of the proposed method.

Research on train integrated positioning based on grey neural network

Train positioning is the key to ensure the transportation and efficient operation of the railway.Due to the low accuracy and the poor real-time of the train positioning,a train positioning system based on global navigation satellite system/inertial measurement unit/odometer(GNSS/IMU/ODO)combination framework and a train integrated positioning method based on grey neural network are put forward.A data updating method based on the established grey prediction model of train positioning is put forward,which uses the accumulation and summary of the grey theory for the rough prediction of the data.The purpose of the method is to reduce the noise of the original data.Moreover,the radial basis function(RBF)neural network is introduced to correct residual sequence of the grey prediction model.Compared with the single model calibration,this method can make full use of the advantages of each model,thus getting a high positioning accuracy in the case of small samples and poor information.Experiments show that the method has good real-time performance and high accuracy,and has certain application value.

Integrity assurance of GNSS-based train integrated positioning system

This paper presents a novel Autonomous Integrity Monitoring and Assurance （AIMA） scheme for integrity assurance of the GNSS-based train integrated positioning system. In this scheme, integrity assurance strategies are combined with a three-stage hierarchical architecture, considering the coupling effects among sensor collection, sensor fusion and matching decision level in train integrated positioning. In sensor collecting stage, the AIMA scheme deals with sensor faults and failures with a PCA-based fault detection, diagnosis and isolation approach. In multi-sensor fusion stage, a novel cubature point H0o filter is presented to enhance the fault tolerance capability, and a hybrid approach is applied to indicating and monitoring the protection level of position estimation, concerning both the estimating covariance and measurement slopes. In map matching stage, hypothesis testing with specific test statistic is carried out to determine effectiveness of positioning results. Position calculation will be invalid with an alarm triggered if the specific integrity criterion is not satisfied in any stage. Since independent solutions are applied in AIMA, integrity assurance is closely coupled with information processing in train integrated positioning. Numerical results of the three cases correspond to the hierarchical architecture with field data and simulations are presented to illustrate features and applicability of the proposed AIMA scheme and specific solutions.

手法复位及压膜正位器治疗青少年急性不可复盘前移位的疗效观察

目的:评价手法复位联合运动疗法及压膜正位器对青少年急性不可复盘前移位的短期疗效。方法:选取15例张口受限(病程在4个月内),且经MRI证实颞下颌关节盘不可复性前移的患者。对患者关节周围肌肉进行按摩放松,随后进行关节盘手法复位,复位后2周内对患者进行下颌运动轨迹训练、关节稳定性训练和关节盘复位训练,白天自我维持下颌姿势位,夜间配戴压膜正位器,以保持良好的盘-髁关系。分别在治疗前、治疗后评价患者的最大主动开口度和疼痛视觉类比评分(visual analogue score,VAS),复位即刻、3、6个月MRI复查盘-髁关系。结果:经过2周治疗,患者开口度明显改善,疼痛明显缓解。复位即刻、3、6个月,最大开口度均>40 mm,VAS评分均小于1。复位后半年MRI结果显示,9例为正常盘-髁关系,5例为可复性关节盘前移,1例为不可复性关节盘前移。结论:关节盘手法复位联合运动治疗及压膜正位器,可以恢复急性盘前移位患者开口度,缓解疼痛,对维持正常盘-髁关系有一定疗效。

Text retrieval algorithm that decreases confusion

To overcome the problem that the confusion between texts limits the precision in text re- trieval, a new text retrieval algorithm that decrease confusion （DCTR） is proposed. The algorithm constructs the searching template to represent the user＇ s searching intention through positive and negative training. By using the prior probabilities in the template, the supported probability and anti- supported probability of each text in the text library can be estimated for discrimination. The search- ing result can be ranked according to similarities between retrieved texts and the template. The com- plexity of DCTR is close to term frequency and mversed document frequency （TF-IDF）. Its distin- guishing ability to confusable texts could be advanced and the performance of the result would be im- proved with increasing of training times.

Propagation Mechanisms of Incident Tsunami Wave in Jiangsu Coastal Area,Caused by Eastern Japan Earthquake on March 11,2011

At 13：46 on March 11, 2011（Beijing time）, an earthquake of Mw=9.0 occurred in Japan. By comparing the tsunami data from Guanhekou marine station with other tsunami wave observation gathered from southeast coastal area of China, it was evident that, only in Guanhekou, the position of the maximum wave height appeared in the middle part rather than in the front of the tsunami wave train. A numerical model of tsunami propagation based on 2-D nonlinear shallow water equations was built to study the impact range and main causes of the special tsunami waveform discovered in Jiangsu coastal area. The results showed that nearly three-quarters of the Jiangsu coastal area, mainly comprised the part north of the radial sand ridges, reached its maximum tsunami wave height in the middle part of the wave train. The main cause of the special waveform was the special underwater topography condition of the Yellow Sea and the East China Sea area, which influenced the tsunami propagation and waveform significantly. Although land boundary reflection brought an effect on the position of the maximum wave height to a certain extent, as the limits of the incident waveform and distances between the observation points and shore, it was not the dominant influence factor of the special waveform. Coriolis force＇s impact on the tsunami waves was so weak that it was not the main cause for the special phenomenon in Jiangsu coastal area. The study reminds us that the most destructive wave might not appear in the first one in tsunami wave train.

基于变位机的多功能机器人实训台的自动控制

实现机器人实训设备功能的多样化,对于职业院校节约设备采购成本,扩大学生实训广度意义重大。从多功能机器人实训台的搭建入手,分析了多功能机器人实训台的控制要求,用实验法确定了IO信号和地址分配,PLC与机器人采用总线通讯,设计了控制程序。结合PLC梯形图和机器人Rapid程序,介绍了装配功能的实现原理。结果表明,变位机应用到机器人实训台,配以程序控制,能满足一机多用的实训需求。

浅谈气动薄膜控制阀与电/气阀门定位器调校实训台的设计

介绍了气动薄膜控制阀的结构、性能参数及工作原理,并针对电/气阀门定位器性能及工作原理进行了研究,设计研发了专用于定位器调校的实训台架,重点介绍了实训台架的气路、控制电路及组态信号输出部分的设计及组态调校原理,为实训平台开发提供新的思路。