科创中国

依据故障树分析法(VIA)原理,对城市轨道交通车辆维修的安全故障因素进行了分析.城市轨道交通车辆维修的工艺过程存在着安全"风险累积"效应;维修后车辆的营运过程存在着"风险扩散"效应.在分析目前城市轨道交通车辆维修面临挑战的基础上,提出了风险应急和风险控制的相应对策.

Multi-way principal component analysis(MPCA)has received considerable attention and been widely used in process monitoring.A traditional MPCA algorithm unfolds multiple batches of historical data into a two-dimensional matrix and cut the matrix along the time axis to form subspaces.However,low efficiency of subspaces and difficult fault isolation are the common disadvantages for the principal component model.This paper presents a new subspace construction method based on kernel density estimation function that can effectively reduce the storage amount of the subspace information.The MPCA model and the knowledge base are built based on the new subspace.Then,fault detection and isolation with the squared prediction error(SPE)statistic and the Hotelling(T2)statistic are also realized in process monitoring.When a fault occurs,fault isolation based on the SPE statistic is achieved by residual contribution analysis of different variables.For fault isolation of subspace based on the T2 statistic,the relationship between the statistic indicator and state variables is constructed,and the constraint conditions are presented to check the validity of fault isolation.Then,to improve the robustness of fault isolation to unexpected disturbances,the statistic method is adopted to set the relation between single subspace and multiple subspaces to increase the corrective rate of fault isolation.Finally fault detection and isolation based on the improved MPCA is used to monitor the automatic shift control system(ASCS)to prove the correctness and effectiveness of the algorithm.The research proposes a new subspace construction method to reduce the required storage capacity and to prove the robustness of the principal component model,and sets the relationship between the state variables and fault detection indicators for fault isolation.

The intermittent connection(IC)of the field-bus in networked manufacturing systems is a common but hard troubleshooting network problem,which may result in system level failures or safety issues.However,there is no online IC location identification method available to detect and locate the position of the problem.To tackle this problem,a novel model based online fault location identification method for localized IC problem is proposed.First,the error event patterns are identified and classified according to different node sources in each error frame.Then generalized zero inflated Poisson process(GZIP)model for each node is established by using time stamped error event sequence.Finally,the location of the IC fault is determined by testing whether the parameters of the fitted stochastic model is statistically significant or not using the confident intervals of the estimated parameters.To illustrate the proposed method,case studies are conducted on a 3-node controller area network(CAN)test-bed,in which IC induced faults are imposed on a network drop cable using computer controlled on-off switches.The experimental results show the parameters of the GZIP model for the problematic node are statistically significant(larger than 0),and the patterns of the confident intervals of the estimated parameters are directly linked to the problematic node,which agrees with the experimental setup.The proposed online IC location identification method can successfully identify the location of the drop cable on which IC faults occurs on the CAN network.

Forming limit curves(FLCs) are commonly used for evaluating the formability of sheet metals. However, it is difficult to obtain the FLCs with desirable accuracy by experiments due to that the friction effects are non-negligible under warm/hot stamping conditions. To investigate the experimental errors, experiments for obtaining the FLCs of the AA5754 are conducted at 250℃. Then, FE models are created and validated on the basis of experimental results. A number of FE simulations are carried out for FLC test-pieces and punches with different geometry configurations and varying friction coefficients between the test-piece and the punch. The errors for all the test conditions are predicted and analyzed. Particular attention of error analysis is paid to two special cases, namely, the biaxial FLC test and the uniaxial FLC test. The failure location and the variation of the error with respect to the friction coefficient are studied as well. The results obtained from the FLC tests and the above analyses show that, for the biaxial tension state, the friction coefficient should be controlled within 0.15 to avoid significant shifting of the necking location away from the center of the punch; for the uniaxial tension state, the friction coefficient should be controlled within 0.1 to guarantee the validity of the data collected from FLC tests. The conclusions summarized are beneficial for obtaining accurate FLCs under warm/hot stamping conditions.

Nondestructive techniques for appraising gas metal arc welding(GMAW) faults plays a very important role in on-line quality controllability and prediction of the GMAW process. On-line welding quality controllability and prediction have several disadvantages such as high cost, low efficiency, complication and greatly being affected by the environment. An enhanced, efficient evaluation technique for evaluating welding faults based on Mahalanobis distance(MD) and normal distribution is presented. In addition, a new piece of equipment, designated the weld quality tester(WQT), is developed based on the proposed evaluation technique. MD is superior to other multidimensional distances such as Euclidean distance because the covariance matrix used for calculating MD takes into account correlations in the data and scaling. The values of MD obtained from welding current and arc voltage are assumed to follow a normal distribution. The normal distribution has two parameters: the mean ? and standard deviation of the data. In the proposed evaluation technique used by the WQT, values of MD located in the range from zero to ?+3? are regarded as "good". Two experiments which involve changing the flow of shielding gas and smearing paint on the surface of the substrate are conducted in order to verify the sensitivity of the proposed evaluation technique and the feasibility of using WQT. The experimental results demonstrate the usefulness of the WQT for evaluating welding quality. The proposed technique can be applied to implement the on-line welding quality controllability and prediction, which is of great importance to design some novel equipment for weld quality detection.

图像特征点匹配算法是增强现实几何一致性技术中的核心算法,目前图像特征点匹配算法耗时较大,准确性较差.提出了一种基于距离约束的改进SURF(Speeded-up Robust Features)算法:在特征点检测阶段,动态构建高斯金字塔图层,提高特征点提取的实时性和准确性;特征点的优化处理,避免提取到的图像特征点出现聚集现象.在特征点匹配阶段,对提取到的特征点构建KD-tree树索引,提高特征匹配的实时性和准确性.实验表明,改进的SURF算法有效地解决了目前方法存在特征提取时间相对较长,特征点匹配误差较大的缺点.

Fault diagnosis of various systems on rolling stock has drawn the attention of many researchers.However,obtaining an optimized sensor set of these systems,which is a prerequisite for fault diagnosis,remains a major challenge.Available literature suggests that the configuration of sensors in these systems is presently dependent on the knowledge and engineering experiences of designers,which may lead to insufficient or redundant development of various sensors.In this paper,the optimization of sensor sets is addressed by using the signed digraph(SDG)method.The method is modified for use in braking systems by the introduction of an effect-function method to replace the traditional quantitative methods.Two criteria are adopted to evaluate the capability of the sensor sets,namely,observability and resolution.The sensors configuration method of braking system is proposed.It consists of generating bipartite graphs from SDG models and then solving the set cover problem using a greedy algorithm.To demonstrate the improvement,the sensor configuration of the HP2008 braking system is investigated and fault diagnosis on a test bench is performed.The test results show that SDG algorithm can improve single-fault resolution from 6 faults to 10 faults,and with additional four brake cylinder pressure(BCP)sensors it can cover up to 67 double faults which were not considered by traditional fault diagnosis system.SDG methods are suitable for reducing redundant sensors and that the sensor sets thereby obtained are capable of detecting typical faults,such as the failure of a release valve.This study investigates the formal extension of the SDG method to the sensor configuration of braking system,as well as the adaptation supported by the effect-function method.

Existing biped robots mainly fall into two categories: robots with left and right feet and robots with upper and lower feet. The load carrying capability of a biped robot is quite limited since the two feet of a walking robot supports the robot alternatively during walking. To improve the load carrying capability, a novel biped walking robot is proposed based on a 2-UPU+2-UU parallel mechanism. The biped walking robot is composed of two identical platforms(feet) and four limbs, including two UPU(universal-prismatic-universal serial chain) limbs and two UU limbs. To enhance its terrain adaptability like articulated vehicles, the two feet of the biped walking robot are designed as two vehicles in detail. The conditions that the geometric parameters of the feet must satisfy are discussed. The degrees-of-freedom of the mechanism is analyzed by using screw theory. Gait analysis, kinematic analysis and stability analysis of the mechanism are carried out to verify the structural design parameters. The simulation results validate the feasibility of walking on rugged terrain. Experiments with a physical prototype show that the novel biped walking robot can walk stably on smooth terrain. Due to its unique feet design and high stiffness, the biped walking robot may adapt to rugged terrain and is suitable for load-carrying.

The classical natural coordinate modeling method which removes the Euler angles and Euler parameters from the governing equations is particularly suitable for the sensitivity analysis and optimization of multibody systems. However, the formulation has so many principles in choosing the generalized coordinates that it hinders the implementation of modeling automation. A first order direct sensitivity analysis approach to multibody systems formulated with novel natural coordinates is presented. Firstly, a new selection method for natural coordinate is developed. The method introduces 12 coordinates to describe the position and orientation of a spatial object. On the basis of the proposed natural coordinates, rigid constraint conditions, the basic constraint elements as well as the initial conditions for the governing equations are derived. Considering the characteristics of the governing equations, the newly proposed generalized-α integration method is used and the corresponding algorithm flowchart is discussed. The objective function, the detailed analysis process of first order direct sensitivity analysis and related solving strategy are provided based on the previous modeling system. Finally, in order to verify the validity and accuracy of the method presented, the sensitivity analysis of a planar spinner-slider mechanism and a spatial crank-slider mechanism are conducted. The test results agree well with that of the finite difference method, and the maximum absolute deviation of the results is less than 3%. The proposed approach is not only convenient for automatic modeling, but also helpful for the reduction of the complexity of sensitivity analysis, which provides a practical and effective way to obtain sensitivity for the optimization problems of multibody systems.

针对互联网中常见的VoIP应用类型,重点从分类特征的选取出发,提出了一种基于C4.5决策树算法的VoIP流量识别方法,并分别利用模拟数据和真实网络数据对其进行了测试.结果表明,该方法识别准确率高,对含有不同协议种类VoIP的网络数据具有较强的适应能力