Yunting Zheng, Shaohua Chen, Zhiyong Tan, Yongkui Sun
A new fault diagnosis method is proposed to effectively extract the fault features of the sound signal of typical faults of ZDJ9 railway point machines. A multi-entropy feature extraction method is proposed by combing multi-scale permutation entropy and wavelet packet entropy. Firstly, empirical mode decomposition is performed on sound signals to obtain modal components with different time scales. Then, multi-scale permutation entropy is extracted from these components. Meanwhile, the wavelet packet entropy of the sound signals of these sensitive nodes is obtained by analyzing the reconstructed signals of the last layer nodes. Since the multi-scale arrangement entropy and the wavelet packet entropy can distinguish the subtle features of the signal, the subtle features of the original signal can be obtained as the feature vector of the ZDJ9 railway point machine in different states. To reduce the redundant information among the high-dimensional features, ReliefF is utilized. Finally, support vector machine (SVM) is used to judge the fault type of ZDJ9 railway point machine.
{"title":"Research on fault diagnosis of railway point machine based on multi-entropy and support vector machine","authors":"Yunting Zheng, Shaohua Chen, Zhiyong Tan, Yongkui Sun","doi":"10.1093/tse/tdac071","DOIUrl":"https://doi.org/10.1093/tse/tdac071","url":null,"abstract":"\u0000 A new fault diagnosis method is proposed to effectively extract the fault features of the sound signal of typical faults of ZDJ9 railway point machines. A multi-entropy feature extraction method is proposed by combing multi-scale permutation entropy and wavelet packet entropy. Firstly, empirical mode decomposition is performed on sound signals to obtain modal components with different time scales. Then, multi-scale permutation entropy is extracted from these components. Meanwhile, the wavelet packet entropy of the sound signals of these sensitive nodes is obtained by analyzing the reconstructed signals of the last layer nodes. Since the multi-scale arrangement entropy and the wavelet packet entropy can distinguish the subtle features of the signal, the subtle features of the original signal can be obtained as the feature vector of the ZDJ9 railway point machine in different states. To reduce the redundant information among the high-dimensional features, ReliefF is utilized. Finally, support vector machine (SVM) is used to judge the fault type of ZDJ9 railway point machine.","PeriodicalId":52804,"journal":{"name":"Transportation Safety and Environment","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41879334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yongkui Sun, Yuan Cao, Haitao Liu, Weifeng Yang, Shuai Su
Condition monitoring of railway point machines is important for train operation safety and effectiveness. Referring to the fields of mechanical equipment fault detection, this paper proposes a fault detection and identification strategy of railway point machines via vibration signals. Comprehensive feature distilling approach by combining variational mode decomposition (VMD) energy entropy, time- and frequency-domain statistical features is presented, which is more effective than single kind of features. The optimal set of features was selected with ReliefF, which help improve the diagnosis accuracy. Support vector machine (SVM) which is suitable for small sample is adopted to realize diagnosis. The diagnosis accuracy of the proposed method reaches 100%, and its effectiveness is verified by experiment comparisons. In this paper, vibration signals are creatively adopted for fault diagnosis of railway point machines. The presented method can help guide field maintenance stuff and also provide reference for fault diagnosis of other equipment.
{"title":"Condition monitoring and fault diagnosis strategy of railway point machines using vibration signals","authors":"Yongkui Sun, Yuan Cao, Haitao Liu, Weifeng Yang, Shuai Su","doi":"10.1093/tse/tdac048","DOIUrl":"https://doi.org/10.1093/tse/tdac048","url":null,"abstract":"\u0000 Condition monitoring of railway point machines is important for train operation safety and effectiveness. Referring to the fields of mechanical equipment fault detection, this paper proposes a fault detection and identification strategy of railway point machines via vibration signals. Comprehensive feature distilling approach by combining variational mode decomposition (VMD) energy entropy, time- and frequency-domain statistical features is presented, which is more effective than single kind of features. The optimal set of features was selected with ReliefF, which help improve the diagnosis accuracy. Support vector machine (SVM) which is suitable for small sample is adopted to realize diagnosis. The diagnosis accuracy of the proposed method reaches 100%, and its effectiveness is verified by experiment comparisons. In this paper, vibration signals are creatively adopted for fault diagnosis of railway point machines. The presented method can help guide field maintenance stuff and also provide reference for fault diagnosis of other equipment.","PeriodicalId":52804,"journal":{"name":"Transportation Safety and Environment","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43951555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Simulation driven design method which use multiple optimization methods can effectively promote innovative structural design and reduce product development cycle. Meanwhile, the submodel technology which proceed more detailed simulation and optimization analysis can enormously improve the efficiency of modeling and solving. This study establishes a general workflow of structural optimization for stainless-steel metro bolster by combining the simulation driven design method and the submodel technology. In the submodel definition phase, the end underframe submodel which contains the bolster is obtained based on the whole car body FE model, and the effectiveness of the end underframe submodel is also proved. In the conceptual design phase, the topology path inside the bolster is obtained by topology method and the optimized structure of the inner ribs inside the bolster is determined according to manufacturing processes and design experiences. In the detailed design phase, the thicknesses of each part of the bolster are determined by size optimization. The simulation analyses indicate that the requirements of static strength and fatigue strength are fulfilled by the optimized bolster structure. Besides, the weight can be reduced by 11.18% and the weld length can be decreased by 17.79% compared with the original bolster structure, which means that not only the lightweight design goal is achieved, but also the welding quantity and manufacturing difficulty are greatly reduced. The results show the effectiveness of the simulation driven design method based on the submodel technology in the structural optimization for key parts of the rail transit vehicles.
{"title":"Structural optimization design of a bolster based on simulation driven design method","authors":"Xinkang Li, Fei Peng, Zeyun Yang, Yong Peng, Jiahao Zhou","doi":"10.1093/tse/tdac075","DOIUrl":"https://doi.org/10.1093/tse/tdac075","url":null,"abstract":"\u0000 Simulation driven design method which use multiple optimization methods can effectively promote innovative structural design and reduce product development cycle. Meanwhile, the submodel technology which proceed more detailed simulation and optimization analysis can enormously improve the efficiency of modeling and solving. This study establishes a general workflow of structural optimization for stainless-steel metro bolster by combining the simulation driven design method and the submodel technology. In the submodel definition phase, the end underframe submodel which contains the bolster is obtained based on the whole car body FE model, and the effectiveness of the end underframe submodel is also proved. In the conceptual design phase, the topology path inside the bolster is obtained by topology method and the optimized structure of the inner ribs inside the bolster is determined according to manufacturing processes and design experiences. In the detailed design phase, the thicknesses of each part of the bolster are determined by size optimization. The simulation analyses indicate that the requirements of static strength and fatigue strength are fulfilled by the optimized bolster structure. Besides, the weight can be reduced by 11.18% and the weld length can be decreased by 17.79% compared with the original bolster structure, which means that not only the lightweight design goal is achieved, but also the welding quantity and manufacturing difficulty are greatly reduced. The results show the effectiveness of the simulation driven design method based on the submodel technology in the structural optimization for key parts of the rail transit vehicles.","PeriodicalId":52804,"journal":{"name":"Transportation Safety and Environment","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41878693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper proposes a hybrid deep reinforcement learning framework for locomotive axle temperature by combining the wavelet packet decomposition (WPD), long short-term memory (LSTM), the gated recurrent unit (GRU) reinforcement learning, and generalized autoregressive conditional heteroskedasticity (GARCH) algorithms. The WPD is utilized to decompose the raw nonlinear series into subseries. Then the deep learning predictors LSTM and GRU are established to predict the future axle temperatures in each subseries. The Q-learning could generate optimal ensemble weights to integrate the predictors to finish the deterministic forecasting and GARCH is used to conduct the deterministic forecasting based on the deterministic forecasting residual. These parts of the hybrid ensemble structure contributed to optimal modeling accuracy and provided effective support in the real-time monitoring and fault diagnosis of transportation.
{"title":"A hybrid ensemble deep reinforcement learning model for locomotive axle temperature using the deterministic and probabilistic strategy","authors":"Guangxi Yan, Hui Liu, Chengqing Yu, Chengming Yu, Ye Li, Zhu Duan","doi":"10.1093/tse/tdac055","DOIUrl":"https://doi.org/10.1093/tse/tdac055","url":null,"abstract":"\u0000 This paper proposes a hybrid deep reinforcement learning framework for locomotive axle temperature by combining the wavelet packet decomposition (WPD), long short-term memory (LSTM), the gated recurrent unit (GRU) reinforcement learning, and generalized autoregressive conditional heteroskedasticity (GARCH) algorithms. The WPD is utilized to decompose the raw nonlinear series into subseries. Then the deep learning predictors LSTM and GRU are established to predict the future axle temperatures in each subseries. The Q-learning could generate optimal ensemble weights to integrate the predictors to finish the deterministic forecasting and GARCH is used to conduct the deterministic forecasting based on the deterministic forecasting residual. These parts of the hybrid ensemble structure contributed to optimal modeling accuracy and provided effective support in the real-time monitoring and fault diagnosis of transportation.","PeriodicalId":52804,"journal":{"name":"Transportation Safety and Environment","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42007364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhenhao Zhang, Zhenpeng Zhao, Jun Xiong, Fuming Wang, Yi Zeng, Bingfang Zhao, Lu Ke
Analysis of the dynamic response of a complex nonlinear system is always a difficult problem. By using Volterra functional series to describe a nonlinear system, its response analysis can be similar to using Fourier/Laplace transform and linear transfer function method to analyze a linear system's response. In this paper, a dynamic response analysis method for nonlinear systems based on Volterra series is developed. Firstly, the recursive formula of the least square method is established to solve the Volterra kernel function vector, and the corresponding MATLAB program is compiled. Then, the Volterra kernel vector corresponding to the nonlinear response of a structure under seismic excitation is identified, and the accuracy and applicability of using the kernel vector to predict the response of a nonlinear structure are analyzed. The results show that the Volterra kernel function identified by the derived recursive formula can accurately describe the nonlinear response characteristics of a structure under an excitation. For a general nonlinear system, the first three order Volterra kernel function can relatively accurately express its nonlinear response characteristics. In addition, the obtained Volterra kernel function can be used to accurately predict the nonlinear response of a structure under the similar type of dynamic load.
{"title":"An approach of dynamic response analysis of nonlinear structures based on least square Volterra kernel function identification","authors":"Zhenhao Zhang, Zhenpeng Zhao, Jun Xiong, Fuming Wang, Yi Zeng, Bingfang Zhao, Lu Ke","doi":"10.1093/tse/tdac046","DOIUrl":"https://doi.org/10.1093/tse/tdac046","url":null,"abstract":"\u0000 Analysis of the dynamic response of a complex nonlinear system is always a difficult problem. By using Volterra functional series to describe a nonlinear system, its response analysis can be similar to using Fourier/Laplace transform and linear transfer function method to analyze a linear system's response. In this paper, a dynamic response analysis method for nonlinear systems based on Volterra series is developed. Firstly, the recursive formula of the least square method is established to solve the Volterra kernel function vector, and the corresponding MATLAB program is compiled. Then, the Volterra kernel vector corresponding to the nonlinear response of a structure under seismic excitation is identified, and the accuracy and applicability of using the kernel vector to predict the response of a nonlinear structure are analyzed. The results show that the Volterra kernel function identified by the derived recursive formula can accurately describe the nonlinear response characteristics of a structure under an excitation. For a general nonlinear system, the first three order Volterra kernel function can relatively accurately express its nonlinear response characteristics. In addition, the obtained Volterra kernel function can be used to accurately predict the nonlinear response of a structure under the similar type of dynamic load.","PeriodicalId":52804,"journal":{"name":"Transportation Safety and Environment","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47120327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the increasing computing demand of train operation control system, the application of cloud computing technology to train control system safety computer platform has become a research hotspot in recent years. How to improve the safety and availability of private cloud safety computer is the key problem to apply cloud computing to train operation control system. Because the cloud computing platform is in an open network environment, it faces many security loopholes and malicious network attacks. Therefore, it is necessary to change the existing safety computer platform structure to improve the attack resistance of the private cloud safety computer platform, thereby enhancing its safety and reliability. Firstly, a private cloud safety computer platform architecture based on dynamic heterogeneous redundant(DHR) structure is proposed, and a dynamic migration mechanism for heterogeneous executives is designed in this paper. Then, a generalized stochastic Petri net (GSPN) model of a private cloud safety computer platform based on DHR is established, and its steady-state probability is solved by using its isomorphism with the continuous-time Markov model (CTMC). To analyze the impact of different system structures and executive migration mechanisms on the system's anti-attack performance. Finally, through the experimental verification, the system structure proposed in this paper can improve the anti-attack of the private cloud safety computer platform, thereby improving its safety and reliability.
{"title":"Research on anti-attack of private cloud safety computer based on Markov-Percopy dynamic heterogeneous redundancy structure","authors":"Jiakun Wen, Zhen Liu, H. Ding","doi":"10.1093/tse/tdac069","DOIUrl":"https://doi.org/10.1093/tse/tdac069","url":null,"abstract":"\u0000 With the increasing computing demand of train operation control system, the application of cloud computing technology to train control system safety computer platform has become a research hotspot in recent years. How to improve the safety and availability of private cloud safety computer is the key problem to apply cloud computing to train operation control system. Because the cloud computing platform is in an open network environment, it faces many security loopholes and malicious network attacks. Therefore, it is necessary to change the existing safety computer platform structure to improve the attack resistance of the private cloud safety computer platform, thereby enhancing its safety and reliability. Firstly, a private cloud safety computer platform architecture based on dynamic heterogeneous redundant(DHR) structure is proposed, and a dynamic migration mechanism for heterogeneous executives is designed in this paper. Then, a generalized stochastic Petri net (GSPN) model of a private cloud safety computer platform based on DHR is established, and its steady-state probability is solved by using its isomorphism with the continuous-time Markov model (CTMC). To analyze the impact of different system structures and executive migration mechanisms on the system's anti-attack performance. Finally, through the experimental verification, the system structure proposed in this paper can improve the anti-attack of the private cloud safety computer platform, thereby improving its safety and reliability.","PeriodicalId":52804,"journal":{"name":"Transportation Safety and Environment","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42241424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As an important transportation infrastructure and transportation backbone in China, high-speed rail (HSR) plays a critical role in promoting the development of green and low-carbon transportation. Calculating the CO2 emissions reduction performance of HSR will be conducive to promote the CO2 emissions reduction work of the railway. Based on the Dalkic HSR CO2 emissions reduction performance model, by adjusting HSR CO2 emission factor (CEFHSR), annual times of departures (T) and other parameters, this study develops China HSR CO2 emissions reduction performance model. Taking the Beijing-Shanghai HSR as the research object, this study conducts a questionnaire survey to explore the substitution effect and demand effect of HSR on different transportation modes, collects data such as passenger volume, average electricity use, and annual times of departures of Beijing-Shanghai HSR in 2019, and calculates the CO2 emissions reduction performance of the Beijing-Shanghai HSR. This study has two main results: (1) Build China HSR CO2 emissions reduction performance model based on substitution effect and demand effect. (2) In 2019, the CO2 emissions of Beijing-Shanghai HSR is 2898 233.62t, the CO2 emissions reduction performance of Beijing-Shanghai HSR is 17 999 482.8t, the annual CO2 emissions of Beijing-Shanghai line in ‘No HSR’ case is as 7.2 times as in " HSR" case, and PKT of HSR is 10.2 g/pkm. Based on the research results, this study proposes three CO2 emissions reduction policy suggestions. This study would be helpful for further HSR CO2 emissions reduction research and departments related to railway transportation management to make CO2 emissions reduction policies.
{"title":"CO2 emissions reduction Performance of China's HSR based on substitution effect and demand effect","authors":"Liying Wang, Ping Yin, Shangqing Liu","doi":"10.1093/tse/tdac060","DOIUrl":"https://doi.org/10.1093/tse/tdac060","url":null,"abstract":"\u0000 As an important transportation infrastructure and transportation backbone in China, high-speed rail (HSR) plays a critical role in promoting the development of green and low-carbon transportation. Calculating the CO2 emissions reduction performance of HSR will be conducive to promote the CO2 emissions reduction work of the railway. Based on the Dalkic HSR CO2 emissions reduction performance model, by adjusting HSR CO2 emission factor (CEFHSR), annual times of departures (T) and other parameters, this study develops China HSR CO2 emissions reduction performance model. Taking the Beijing-Shanghai HSR as the research object, this study conducts a questionnaire survey to explore the substitution effect and demand effect of HSR on different transportation modes, collects data such as passenger volume, average electricity use, and annual times of departures of Beijing-Shanghai HSR in 2019, and calculates the CO2 emissions reduction performance of the Beijing-Shanghai HSR. This study has two main results: (1) Build China HSR CO2 emissions reduction performance model based on substitution effect and demand effect. (2) In 2019, the CO2 emissions of Beijing-Shanghai HSR is 2898 233.62t, the CO2 emissions reduction performance of Beijing-Shanghai HSR is 17 999 482.8t, the annual CO2 emissions of Beijing-Shanghai line in ‘No HSR’ case is as 7.2 times as in \" HSR\" case, and PKT of HSR is 10.2 g/pkm. Based on the research results, this study proposes three CO2 emissions reduction policy suggestions. This study would be helpful for further HSR CO2 emissions reduction research and departments related to railway transportation management to make CO2 emissions reduction policies.","PeriodicalId":52804,"journal":{"name":"Transportation Safety and Environment","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41600843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the rapid development of the shipping industry, the safety and comfort of ship transportation have been paid more and more attention, and the pitch and heave motion of ships are the most serious factors. In this paper, the longitudinal motion mathematical model of YuKun is established. By assigning the zero-pole to the left half-plane and using the properties of the symmetric matrix, the shaping weighting functions matrix is designed to stabilize the Multi-Input Multi-Output (MIMO) system of YuKun. Finally, a new concise robust controller is designed using the steady output of the shaped system. The simulation results show that under the control of the concise robust controller, the pitch angle and heave of YuKun decrease by 79.9% and 86.2%. Theoretical analysis and simulation results show that the concise robust controller has a good control effect on the longitudinal motion of YuKun, and is simple and easy to use, with clear engineering significance.
{"title":"Design of concise robust control for longitudinal motion of YuKun","authors":"Chenfei Liu, Pei Xiao, Xianku Zhang, Pengqi Wang, Jiafu Wang, Dinghuo Hu","doi":"10.1093/tse/tdac063","DOIUrl":"https://doi.org/10.1093/tse/tdac063","url":null,"abstract":"\u0000 With the rapid development of the shipping industry, the safety and comfort of ship transportation have been paid more and more attention, and the pitch and heave motion of ships are the most serious factors. In this paper, the longitudinal motion mathematical model of YuKun is established. By assigning the zero-pole to the left half-plane and using the properties of the symmetric matrix, the shaping weighting functions matrix is designed to stabilize the Multi-Input Multi-Output (MIMO) system of YuKun. Finally, a new concise robust controller is designed using the steady output of the shaped system. The simulation results show that under the control of the concise robust controller, the pitch angle and heave of YuKun decrease by 79.9% and 86.2%. Theoretical analysis and simulation results show that the concise robust controller has a good control effect on the longitudinal motion of YuKun, and is simple and easy to use, with clear engineering significance.","PeriodicalId":52804,"journal":{"name":"Transportation Safety and Environment","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43870012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhao Liu, Feng Liu, S. Yao, Da-wei Chen, Ming-zhi Yang
The length of the high-speed railway tunnel is an important factor affecting the transient pressure. When the tunnel length is the most unfavorable, the transient pressure changes in the tunnel and on the surface of the train are the most severe, which may affect the safe operation of the train or damage the structure in the tunnel. Based on the three-dimensional, compressible, unsteady N-S equation and finite volume method, this paper uses the CFD numerical simulation method to study the change and amplitude distribution of the transient pressure on the train surface and the tunnel when the high-speed train passes through the most unfavorable length tunnel. And a fast calculation method is proposed to save the cost of calculation, it has a great applicability of pressure amplitude. The results show that the pressure distribution in the tunnel and on the surface of the train is affected by the train speed, the length of the train and the position of the measuring point. The minimum negative peak value in the tunnel appears at the position where the superposition phenomenon is most severe, and the position will change with the speed of the train. There are two negative peak waveforms of the train surface pressure, and the first waveform is greatly affected by the train speed. It improves a reference for studying the strength requirement of the most unfavorable length tunnels and trains and ensures the safe operation of trains in tunnels of different lengths.
{"title":"Research on numerical simulation of transient pressure for the high-speed train passing through the most unfavorable length tunnel","authors":"Zhao Liu, Feng Liu, S. Yao, Da-wei Chen, Ming-zhi Yang","doi":"10.1093/tse/tdac059","DOIUrl":"https://doi.org/10.1093/tse/tdac059","url":null,"abstract":"\u0000 The length of the high-speed railway tunnel is an important factor affecting the transient pressure. When the tunnel length is the most unfavorable, the transient pressure changes in the tunnel and on the surface of the train are the most severe, which may affect the safe operation of the train or damage the structure in the tunnel. Based on the three-dimensional, compressible, unsteady N-S equation and finite volume method, this paper uses the CFD numerical simulation method to study the change and amplitude distribution of the transient pressure on the train surface and the tunnel when the high-speed train passes through the most unfavorable length tunnel. And a fast calculation method is proposed to save the cost of calculation, it has a great applicability of pressure amplitude. The results show that the pressure distribution in the tunnel and on the surface of the train is affected by the train speed, the length of the train and the position of the measuring point. The minimum negative peak value in the tunnel appears at the position where the superposition phenomenon is most severe, and the position will change with the speed of the train. There are two negative peak waveforms of the train surface pressure, and the first waveform is greatly affected by the train speed. It improves a reference for studying the strength requirement of the most unfavorable length tunnels and trains and ensures the safe operation of trains in tunnels of different lengths.","PeriodicalId":52804,"journal":{"name":"Transportation Safety and Environment","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42475883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yaran Yang, Lian-chuan Ma, Tao Tang, H. Ding, Zhen Liu
With the development of railway construction in China, the computing demand of train control system is increasing day by day. The application of cloud computing technology to rail transit signal system has become a research hotspot in recent years. How to improve the safety and availability of the safety computer platform in cloud computing environment is the key problem to apply cloud computing to train operation control system. As the cloud platform is in an open network environment, facing many security vulnerabilities and malicious network attacks, so it is necessary to monitor the operation of computer programs through edge safety nodes. Firstly, this paper encrypts the logical monitoring method, and then proposes a secure computer defense model based on dynamic heterogeneous redundancy structure. Then continuous time Markov chain (CTMC) is used to quantitatively solve the stable probability of the system, and the influence of different logical monitoring methods on the anti-attack performance of the system is analyzed. Finally, the experiment proves that the dynamic heterogeneous redundancy structure composed of encryption logic monitoring can guarantee the safe and stable operation of the safety computer more effectively.
{"title":"Research on Logic Monitoring Method for Cloud Computing Based Safety Computer","authors":"Yaran Yang, Lian-chuan Ma, Tao Tang, H. Ding, Zhen Liu","doi":"10.1093/tse/tdac052","DOIUrl":"https://doi.org/10.1093/tse/tdac052","url":null,"abstract":"\u0000 With the development of railway construction in China, the computing demand of train control system is increasing day by day. The application of cloud computing technology to rail transit signal system has become a research hotspot in recent years. How to improve the safety and availability of the safety computer platform in cloud computing environment is the key problem to apply cloud computing to train operation control system. As the cloud platform is in an open network environment, facing many security vulnerabilities and malicious network attacks, so it is necessary to monitor the operation of computer programs through edge safety nodes. Firstly, this paper encrypts the logical monitoring method, and then proposes a secure computer defense model based on dynamic heterogeneous redundancy structure. Then continuous time Markov chain (CTMC) is used to quantitatively solve the stable probability of the system, and the influence of different logical monitoring methods on the anti-attack performance of the system is analyzed. Finally, the experiment proves that the dynamic heterogeneous redundancy structure composed of encryption logic monitoring can guarantee the safe and stable operation of the safety computer more effectively.","PeriodicalId":52804,"journal":{"name":"Transportation Safety and Environment","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45194102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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