High-speed Railway最新文献

{"title":"Research on fault time prediction method for high speed rail BTM unit based on multi method interactive validation","authors":"Limin Fu ,&nbsp;Junqiang Gou ,&nbsp;Chao Sun ,&nbsp;Hanrui Li ,&nbsp;Wei Liu","doi":"10.1016/j.hspr.2024.07.001","DOIUrl":"10.1016/j.hspr.2024.07.001","url":null,"abstract":"<div><div>The Balise Transmission Module (BTM) unit of the on-board train control system is a crucial component. Due to its unique installation position and complex environment, this unit has a higher fault rate within the on-board train control system. To conduct fault prediction for the BTM unit based on actual fault data, this study proposes a prediction method combining reliability statistics and machine learning, and achieves the fusion of prediction results from different dimensions through multi-method interactive validation. Firstly, a method for predicting equipment fault time targeting batch equipment is introduced. This method utilizes reliability statistics to construct a model of the remaining faultless operating time distribution considering uncertainty, thereby predicting the remaining faultless operating probability of the BTM unit. Secondly, considering the complexity of the BTM unit’s fault mechanism, the small sample size of fault cases, and the potential presence of multiple fault features in fault text records, an individual-oriented fault prediction method based on Bayesian-optimized Gradient Boosting Regression Tree (Bayes-GBRT) is proposed. This method achieves better prediction results compared to linear regression algorithms and random forest regression algorithms, with an average absolute error of only 0.224 years for predicting the fault time of this type of equipment. Finally, a multi-method interactive validation approach is proposed, enabling the fusion and validation of multi-dimensional results. The results indicate that the predicted fault time and the actual fault time conform to a log-normal distribution, and the parameter estimation results are basically consistent, verifying the accuracy and effectiveness of the prediction results. The above research findings can provide technical support for the maintenance and modification of BTM units, effectively reducing maintenance costs and ensuring the safe operation of high-speed railway, thus having practical engineering value for preventive maintenance.</div></div>","PeriodicalId":100607,"journal":{"name":"High-speed Railway","volume":"2 3","pages":"Pages 164-171"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142318915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial-intelligent-powered safety and efficiency improvement for integrated railway systems","authors":"Jun Liu, Gehui Liu, Yu Wang, Wanqiu Zhang","doi":"10.1016/j.hspr.2024.06.006","DOIUrl":"https://doi.org/10.1016/j.hspr.2024.06.006","url":null,"abstract":"","PeriodicalId":100607,"journal":{"name":"High-speed Railway","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141705455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal allocation method of electric/air braking force of high-speed train considering axle load transfer","authors":"Feng Guo,&nbsp;Jing He","doi":"10.1016/j.hspr.2024.04.004","DOIUrl":"https://doi.org/10.1016/j.hspr.2024.04.004","url":null,"abstract":"<div><p>Reasonable distribution of braking force is a factor for a smooth, safe, and comfortable braking of trains. A dynamic optimal allocation strategy of electric-air braking force is proposed in this paper to solve the problem of the lack of consideration of adhesion difference of train wheelsets in the existing high-speed train electric-air braking force optimal allocation strategies. In this method, the braking strategy gives priority to the use of electric braking force. The force model of a single train in the braking process is analyzed to calculate the change of adhesion between the wheel and rail of each wheelset after axle load transfer, and then the adhesion of the train is estimated in real time. Next, with the goal of maximizing the total adhesion utilization ratio of trailer/motor vehicles, a linear programming distribution function is constructed. The proportional coefficient of adhesion utilization ratio of each train and the application upper limit of braking force in the function is updated according to the change time point of wheelset adhesion. Finally, the braking force is dynamically allocated. The simulation results of Matlab/Simulink show that the proposed algorithm not only uses the different adhesion limits of each trailer to reduce the total amount of braking force undertaken by the motor vehicle, but also considers the adhesion difference of each wheelset. The strategy can effectively reduce the risk and time of motor vehicles during the braking process and improve the stability of the train braking.</p></div>","PeriodicalId":100607,"journal":{"name":"High-speed Railway","volume":"2 2","pages":"Pages 77-84"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949867824000308/pdfft?md5=f893352645e3b14ecb17ccb28774ec7e&pid=1-s2.0-S2949867824000308-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141434697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Thermal stress simulation analysis of aerospace optical fibers and connectors and related extensions to high-speed railway area","authors":"Feng Zhou ,&nbsp;Siyuan Yu ,&nbsp;Zeren Gao ,&nbsp;Jie Kan ,&nbsp;Hao Xu ,&nbsp;Mengjie Liu","doi":"10.1016/j.hspr.2024.04.001","DOIUrl":"10.1016/j.hspr.2024.04.001","url":null,"abstract":"<div><p>Aerospace optical cables and fiber-optic connectors have numerous advantages (e.g., low loss, wide transmission frequency band, large capacity, light weight, and excellent resistance to electromagnetic interference). They can achieve optical communication interconnections and high-speed bidirectional data transmission between optical terminals and photodetectors in space, ensuring the stability and reliability of data transmission during spacecraft operations in orbit. They have become essential components in high-speed networking and optically interconnected communications for spacecrafts. Thermal stress simulation analysis is important for evaluating the temperature stress concentration phenomenon resulting from temperature fluctuations, temperature gradients, and other factors in aerospace optical cables and connectors under the combined effects of extreme temperatures and vacuum environments. Considering this, advanced optical communication technology has been widely used in high-speed railway communication networks to transmit safe, stable and reliable signals, as high-speed railway optical communication in special areas with extreme climates, such as cold and high-temperature regions, requires high-reliability optical cables and connectors. Therefore, based on the finite element method, comprehensive comparisons were made between the thermal distributions of aerospace optical cables and J599III fiber optic connectors under different conditions, providing a theoretical basis for evaluating the performance of aerospace optical cables and connectors in space environments and meanwhile building a technical foundation for potential optical communication applications in the field of high-speed railways.</p></div>","PeriodicalId":100607,"journal":{"name":"High-speed Railway","volume":"2 2","pages":"Pages 122-132"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949867824000278/pdfft?md5=a292d1a3b4bed47d3e32d39d4b8e8492&pid=1-s2.0-S2949867824000278-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140786695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of plasma spraying process on microstructure and mechanical properties of Cr2AlC/410 composite coatings","authors":"Yihu Ma ,&nbsp;Chaosheng Ma ,&nbsp;Guozheng Ma ,&nbsp;Wenbo Yu","doi":"10.1016/j.hspr.2024.05.001","DOIUrl":"10.1016/j.hspr.2024.05.001","url":null,"abstract":"<div><p>To investigate the influences of Cr₂AlC mass fraction and supersonic plasma spraying process on the microstructure and mechanical properties of Cr₂AlC reinforced 410 stainless steel composite coatings, the coatings containing different mass fractions of Cr₂AlC were prepared and investigated. The composite coating exhibited low porosity and high adhesion strength. The addition of Cr₂AlC significantly enhanced the hardness of the composite coatings through particle strengthening. However, when the mass fraction of Cr₂AlC was 20%, the aggregation of Cr₂AlC resulted in a strong decrease in the coating preparation efficiency, as well as a decline in adhesion strength. In the supersonic plasma spraying process, the Ar flow rate mainly influenced the flight velocity of the particles, while the H₂ flow rate and the current mainly affected the temperature of the plasma torch. Consequently, all of them influenced the melting degree of particles and the quality of the coating. The lowest porosity and the highest hardness and adhesion strength could be obtained when the Ar flow rate is 125 L/min, the H₂ flow rate is 25 L/min, and the current is 385 A.</p></div>","PeriodicalId":100607,"journal":{"name":"High-speed Railway","volume":"2 2","pages":"Pages 110-115"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S294986782400031X/pdfft?md5=0c04b09275b2d6798cf1da8d525b24c0&pid=1-s2.0-S294986782400031X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141042246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Temperature field calculation of rail flash welding","authors":"Rui Xu ,&nbsp;Min Zhang ,&nbsp;Zhenkun Gao ,&nbsp;Guo Zhao ,&nbsp;Wei Ding ,&nbsp;Shouming Wang ,&nbsp;Peng Zhang ,&nbsp;Xiang Liu ,&nbsp;Jingjing Li","doi":"10.1016/j.hspr.2024.03.001","DOIUrl":"10.1016/j.hspr.2024.03.001","url":null,"abstract":"<div><p>The forging stage of rail flash welding has a decisive influence on joint strength, and the study of the temperature distribution in the process has an important role in further improving joint strength. In this paper, three calculation methods for the temperature field are given. First, the finite element model of the temperature field before forging rail flash welding is established by using the transient heat module of Ansys software and verified by infrared temperature measurement. Second, the temperature distribution of different parts of the rail before flash welding is obtained by using infrared thermal imaging equipment. Third, Matlab software is used to calculate the temperature of the non-measured part. Finally, the temperature distribution function along the rail axis is fitted through the temperature measurement data. The temperature distribution before the top forging of the rail flash welding can be used to analyze the joint and heat-affected zone organization and properties effectively and to guide the parameter setting and industrial production.</p></div>","PeriodicalId":100607,"journal":{"name":"High-speed Railway","volume":"2 2","pages":"Pages 116-121"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949867824000266/pdfft?md5=1118256472e5fe74cd160397164ccad6&pid=1-s2.0-S2949867824000266-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140407068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A related degree-based frequent pattern mining algorithm for railway fault data","authors":"Jiaxu Guo ,&nbsp;Ding Ding ,&nbsp;Peihan Yang ,&nbsp;Qi Zou ,&nbsp;Yaping Huang","doi":"10.1016/j.hspr.2024.05.003","DOIUrl":"10.1016/j.hspr.2024.05.003","url":null,"abstract":"<div><p>It is of great significance to improve the efficiency of railway production and operation by realizing the fault knowledge association through the efficient data mining algorithm. However, high utility quantitative frequent pattern mining algorithms in the field of data mining still suffer from the problems of low time-memory performance and are not easy to scale up. In the context of such needs, we propose a related degree-based frequent pattern mining algorithm, named Related High Utility Quantitative Item set Mining (RHUQI-Miner), to enable the effective mining of railway fault data. The algorithm constructs the item-related degree structure of fault data and gives a pruning optimization strategy to find frequent patterns with higher related degrees, reducing redundancy and invalid frequent patterns. Subsequently, it uses the fixed pattern length strategy to modify the utility information of the item in the mining process so that the algorithm can control the length of the output frequent pattern according to the actual data situation and further improve the performance and practicability of the algorithm. The experimental results on the real fault dataset show that RHUQI-Miner can effectively reduce the time and memory consumption in the mining process, thus providing data support for differentiated and precise maintenance strategies.</p></div>","PeriodicalId":100607,"journal":{"name":"High-speed Railway","volume":"2 2","pages":"Pages 101-109"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949867824000333/pdfft?md5=7ddc6c2c1df15b6be817951e15c67c9e&pid=1-s2.0-S2949867824000333-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141031330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An improved YOLOv7 for the state identification of sliding chairs in railway turnout","authors":"Yuan Cao ,&nbsp;Zongbao Liu ,&nbsp;Feng Wang ,&nbsp;Shuai Su ,&nbsp;Yongkui Sun ,&nbsp;Wenkun Wang","doi":"10.1016/j.hspr.2024.04.002","DOIUrl":"10.1016/j.hspr.2024.04.002","url":null,"abstract":"<div><p>The sliding chairs are important components that support the switch rail conversion in the railway turnout. Due to the harsh environmental erosion and the attack from the wheel vibration, the failure rate of the sliding chairs accounts for up to 10% of the total failure number in turnout. However, there is little research carried out in the existing literature to diagnose the deterioration states of the sliding chairs. To fill out this gap, by utilizing the images containing the sliding chairs, we propose an improved You Only Look Once version 7 (YOLOv7) to identify the state of the sliding chairs. Specifically, to meet the challenge brought by the small inter-class differences among the sliding chair states, we first integrate the Convolutional Block Attention Module (CBAM) into the YOLOv7 backbone to screen the information conducive to state identification. Then, an extra detector for a small object is customized into the YOLOv7 network in order to detect the small-scale sliding chairs in images. Meanwhile, we revise the localization loss in the objective function as the Efficient Intersection over Union (EIoU) to optimize the design of the aspect ratio, which helps the localization of the sliding chairs. Next, to address the issue caused by the varying scales of the sliding chairs, we employ K-means++ to optimize the priori selection of the initial anchor boxes. Finally, based on the images collected from real-world turnouts, the proposed method is verified and the results show that our method outperforms the basic YOLOv7 in the state identification of the sliding chairs with 4% improvements in terms of both mean Average [email protected] ([email protected]) and F1-score.</p></div>","PeriodicalId":100607,"journal":{"name":"High-speed Railway","volume":"2 2","pages":"Pages 71-76"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S294986782400028X/pdfft?md5=c34de2ade9026bad6418a20d3cc740e0&pid=1-s2.0-S294986782400028X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140779833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bearing fault diagnosis based on a multiple-constraint modal-invariant graph convolutional fusion network","authors":"Zhongmei Wang ,&nbsp;Pengxuan Nie ,&nbsp;Jianhua Liu ,&nbsp;Jing He ,&nbsp;Haibo Wu ,&nbsp;Pengfei Guo","doi":"10.1016/j.hspr.2024.04.003","DOIUrl":"10.1016/j.hspr.2024.04.003","url":null,"abstract":"<div><p>Multisensor data fusion method can improve the accuracy of bearing fault diagnosis, in order to address the problems of single-sensor data types and the insufficient exploration of redundancy and complementarity between different modal data in most existing multisensor data fusion methods for bearing fault diagnosis, a bearing fault diagnosis method based on a Multiple-Constraint Modal-Invariant Graph Convolutional Fusion Network (MCMI-GCFN) is proposed in this paper. Firstly, a Convolutional Autoencoder (CAE) and Squeeze-and-Excitation Block (SE block) are used to extract features of raw current and vibration signals. Secondly, the model introduces source domain classifiers and domain discriminators to capture modal invariance between different modal data based on domain adversarial training, making use of the redundancy and complementarity between multimodal data. Then, the spatial aggregation property of Graph Convolutional Neural Networks (GCN) is utilized to capture the dependency relationship between current and vibration modes with similar time step features for accurately fusing contextual semantic information. Finally, the validation is conducted on the public bearing damage current and vibration dataset from Paderborn University. The experimental results showed that the delivered fusion method achieved a bearing fault diagnosis accuracy of 99.6 %, which was about 9 %–11.4 % better than that with nonfusion methods.</p></div>","PeriodicalId":100607,"journal":{"name":"High-speed Railway","volume":"2 2","pages":"Pages 92-100"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949867824000291/pdfft?md5=77c0cb7bf500e84117361557c994ede3&pid=1-s2.0-S2949867824000291-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140768214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Train wheel-rail force collaborative calibration based on GNN-LSTM","authors":"Changfan Zhang ,&nbsp;Zihao Yu ,&nbsp;Lin Jia","doi":"10.1016/j.hspr.2024.05.002","DOIUrl":"10.1016/j.hspr.2024.05.002","url":null,"abstract":"<div><p>Accurate wheel-rail force data serves as the cornerstone for analyzing the wheel-rail relationship. However, achieving continuous and precise measurement of this force remains a significant challenge in the field. This article introduces a calibration algorithm for the wheel-rail force that leverages graph neural networks and long short-term memory networks. Initially, a comprehensive wheel-rail force detection system for trains was constructed, encompassing two key components: an instrumented wheelset and a ground wheel-rail force measuring system. Subsequently, utilizing this system, two distinct datasets were acquired from the track inspection vehicle: instrumented wheelset data and ground wheel-rail force data, a feedforward neural network was employed to calibrate the instrumented wheelset data, referencing the ground wheel-rail force data. Furthermore, ground wheel-rail force data for the locomotive was obtained for the corresponding road section. This data was then integrated with the calibrated instrumented wheelset data from the track inspection vehicle. Leveraging the GNN-LSTM network, the article establishes a mapping relationship model between the wheel-rail force of the track inspection vehicle and the locomotive wheel-rail force. This model facilitates continuous measurement of locomotive wheel-rail forces across three typical scenarios: straight sections, long and steep downhill sections, and small curve radius sections.</p></div>","PeriodicalId":100607,"journal":{"name":"High-speed Railway","volume":"2 2","pages":"Pages 85-91"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949867824000321/pdfft?md5=22fe4eda6bf192d5a6a4dc4d24ca2848&pid=1-s2.0-S2949867824000321-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141027047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}