科创中国

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.

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.

报告1例变形综合征.患者男,42岁,具有偏侧肥大、巨趾、脊柱侧凸、线状表皮痣、淋巴管瘤等变形综合征的表现.文中对该病进行文献回顾性总结及对最新诊断标准进行讨论.

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.

目的 探讨后尿道血管瘤的诊断和治疗.方法 回顾分析我院自2009年1月至2011年9月收治的后尿道血管瘤患者共6例.对其临床表现、诊断方法及治疗效果进行总结随访.结果 所有患者临床典型表现为性交后血尿或血精,内窥镜下检查证实为尿道血管瘤样病变,行经尿道血管瘤电切术.术后病理诊断为海绵状血管瘤.术后症状消失,随访9个月至3年,未见复发.结论 后尿道血管瘤的诊断主要依靠内窥镜检查和病理学检查,治疗以内窥镜下电切或电灼为主,效果确切.

目的探讨子宫输卯管造影术(HSG)在诊治宫腔粘连(IUA)中的价值.方法回顾性分析本院2007年3月~2011年4月经HSG诊断为宫腔粘连的200例患者的临床资料.结果经HSG诊断,宫腔完全性粘连22例(11.0%),中央型粘连34例(17.0%),周围型粘连69例(34.5%),混合性粘连75例(37.5%).经官腔镜检查,HSG与宫腔镜诊断符合率为91.0%,误诊率为9.0%.结论HSG可以确定粘连的部位和范围、程度,且操作简单、方便,患者痛苦较少,是诊断宫腔粘连常规、可靠的检查手段.

目的 分析肝小静脉闭塞病的临床特点、影像表现和诊治经验.方法 回顾性分析2005年1月~2011年1月我院收治的5例肝小静脉闭塞病患者的临床资料.结果 根据临床及病理学资料,将肝小静脉闭塞病分为急性期(1例)、亚急性期(1例)和慢性期(3例).CT平扫检查均发现肝脏肿大,肝实质密度降低.彩色B超检查均发现肝静脉变细,血流变缓;4例患者存在腹水.行门-体分流术3例,其中好转2例,死亡1例.行内科保守治疗2例,其中1例治愈,1例好转.结论 肝小静脉闭塞病临床表现以肝脏肿大和腹水为特征.影像学检查对肝小静脉闭塞病诊断有重要价值.急性期患者宜采取内科保守治疗,若出现门脉高压症状时,应行门-体分流术治疗.

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.