To solve the problem that it is difficult to calculate the availability analysis of the existing private cloud safety computer platform, this paper proposes an executable availability analysis method of the private cloud safety computer platform based on Markov process. Firstly, according to the characteristics of private cloud safety computer platform, the executor is divided into three states: running, hot standby and cold standby. Secondly, the dynamic migration Markov model of private cloud safety computer platform is established. Then the equations based on Markov process are solved. Finally, the availability analysis model of private cloud safety computer platform based on Markov process is used to analyze the factors affecting the availability of the platform. Experimental results show that increasing the number of hot spare actuators can improve platform availability.
{"title":"Availability analysis of private cloud safety computer platform based on markov process","authors":"Limin Fu, Jiakun Wen","doi":"10.1093/tse/tdad004","DOIUrl":"https://doi.org/10.1093/tse/tdad004","url":null,"abstract":"\u0000 To solve the problem that it is difficult to calculate the availability analysis of the existing private cloud safety computer platform, this paper proposes an executable availability analysis method of the private cloud safety computer platform based on Markov process. Firstly, according to the characteristics of private cloud safety computer platform, the executor is divided into three states: running, hot standby and cold standby. Secondly, the dynamic migration Markov model of private cloud safety computer platform is established. Then the equations based on Markov process are solved. Finally, the availability analysis model of private cloud safety computer platform based on Markov process is used to analyze the factors affecting the availability of the platform. Experimental results show that increasing the number of hot spare actuators can improve platform availability.","PeriodicalId":52804,"journal":{"name":"Transportation Safety and Environment","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49577968","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}
Because of its large capacity, high efficiency, and energy savings, the subway has gradually become the primary mode of transportation for citizens. A high density of passengers exists within a large-passenger-flow subway station, and the number of casualties and injuries during a fire emergency is substantial. In this paper, Pathfinder software and on-site measured data of Pingzhou station in Shenzhen were utilized to simulate a fire emergency evacuation in a large-passenger-flow subway station. The Required Safe Egress Time (RSET), number of passengers, and flow rates of stairs and escalators were analysed for three fire evacuation scenarios: train fire, platform fire, and hall fire. The evacuation time of the train fire, which was 1173 s, was the longest, and 3621 occupants needed to evacuate when the train was fully loaded. Occupants could not complete the evacuation within 6 mins in all three fire evacuation scenarios, which does not meet the currently standards requirements and codes. By changing the number of passengers and the number of stairs for evacuation, the flow rate capacity and evacuation time were explored, which have reference values for safety management and emergency evacuation plan optimization during peak hours of subway operation.
{"title":"Simulation of Fire emergency evacuation in a large-passenger-flow subway station based on the on-site measured data of shenzhen metro","authors":"Hua Chen, Chenyang Zhang, Jieyu Zhang, Ya Shu, Xinjian Qi, Chaozhe Jiang","doi":"10.1093/tse/tdad006","DOIUrl":"https://doi.org/10.1093/tse/tdad006","url":null,"abstract":"\u0000 Because of its large capacity, high efficiency, and energy savings, the subway has gradually become the primary mode of transportation for citizens. A high density of passengers exists within a large-passenger-flow subway station, and the number of casualties and injuries during a fire emergency is substantial. In this paper, Pathfinder software and on-site measured data of Pingzhou station in Shenzhen were utilized to simulate a fire emergency evacuation in a large-passenger-flow subway station. The Required Safe Egress Time (RSET), number of passengers, and flow rates of stairs and escalators were analysed for three fire evacuation scenarios: train fire, platform fire, and hall fire. The evacuation time of the train fire, which was 1173 s, was the longest, and 3621 occupants needed to evacuate when the train was fully loaded. Occupants could not complete the evacuation within 6 mins in all three fire evacuation scenarios, which does not meet the currently standards requirements and codes. By changing the number of passengers and the number of stairs for evacuation, the flow rate capacity and evacuation time were explored, which have reference values for safety management and emergency evacuation plan optimization during peak hours of subway operation.","PeriodicalId":52804,"journal":{"name":"Transportation Safety and Environment","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49372288","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}
In order to deal with the uncertainties caused by different operation conditions and unknown actuator failures of high-speed trains, an adaptive failures compensation control scheme is designed based on the piecewise model. A piecewise constant model is introduced to describe the variable system parameters caused by the variable operation environments, and a multiple-particle piecewise model of high-speed trains, with unknown actuator failures is then established. An adaptive failure compensation controller is developed for the multiple-particle piecewise constant model, by using a direct model reference adaptive control method. Such an adaptive controller can not only compensate the uncertainties from unknown actuator failures, but also effectively deal with the uncertainties caused by different operating conditions. Finally, a CRH380A type high-speed train model is taken as the controlled object for the simulation study. The simulation results show that the proposed controller ensures the desired system performance in the presence of unknown actuator failures and uncertain operation conditions.
{"title":"Piecewise model based adaptive compensation control for high-speed trains with unknown actuator failures","authors":"Chang Tan, Junhui Zhang, Hui Yang, Leilei Zhang","doi":"10.1093/tse/tdad003","DOIUrl":"https://doi.org/10.1093/tse/tdad003","url":null,"abstract":"\u0000 In order to deal with the uncertainties caused by different operation conditions and unknown actuator failures of high-speed trains, an adaptive failures compensation control scheme is designed based on the piecewise model. A piecewise constant model is introduced to describe the variable system parameters caused by the variable operation environments, and a multiple-particle piecewise model of high-speed trains, with unknown actuator failures is then established. An adaptive failure compensation controller is developed for the multiple-particle piecewise constant model, by using a direct model reference adaptive control method. Such an adaptive controller can not only compensate the uncertainties from unknown actuator failures, but also effectively deal with the uncertainties caused by different operating conditions. Finally, a CRH380A type high-speed train model is taken as the controlled object for the simulation study. The simulation results show that the proposed controller ensures the desired system performance in the presence of unknown actuator failures and uncertain operation conditions.","PeriodicalId":52804,"journal":{"name":"Transportation Safety and Environment","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48752359","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}
In order to deal with the problems of insufficient or excessive maintenance in current maintenance activities of China transit train, this paper develops a novel multi-component system maintenance optimization approach based on an opportunistic correlation model. Based on the minimal reliability and failure rate change rule of each train component, the novel proposed maintenance optimization benefits from an improved opportunistic maintenance model with system structure correlation, fault correlation and reliability correlation under imperfect maintenance. Then, different maintenance modes can be determined by a proposed maintenance factor under the different condition of components. Specifically, the reliability threshold of each component is also considered to optimize the maintenance cost by the system reliability and operational availability of the train. Furthermore, as the mentioned problem belongs to the NP-Hard optimization problems, a modified PSO with the improvement of inertia weight is proposed to cope with the optimization problem. Based on a specific case under the practical recorded failure data, the analysis shows that the proposed model and approach can effectively cut the maintenance cost.
{"title":"Multi-component system maintenance optimization of rail transit train based on opportunistic correlations","authors":"Jisheng Dai, Rongjun Ding, Yong Fu, Yong Qin","doi":"10.1093/tse/tdad005","DOIUrl":"https://doi.org/10.1093/tse/tdad005","url":null,"abstract":"\u0000 In order to deal with the problems of insufficient or excessive maintenance in current maintenance activities of China transit train, this paper develops a novel multi-component system maintenance optimization approach based on an opportunistic correlation model. Based on the minimal reliability and failure rate change rule of each train component, the novel proposed maintenance optimization benefits from an improved opportunistic maintenance model with system structure correlation, fault correlation and reliability correlation under imperfect maintenance. Then, different maintenance modes can be determined by a proposed maintenance factor under the different condition of components. Specifically, the reliability threshold of each component is also considered to optimize the maintenance cost by the system reliability and operational availability of the train. Furthermore, as the mentioned problem belongs to the NP-Hard optimization problems, a modified PSO with the improvement of inertia weight is proposed to cope with the optimization problem. Based on a specific case under the practical recorded failure data, the analysis shows that the proposed model and approach can effectively cut the maintenance cost.","PeriodicalId":52804,"journal":{"name":"Transportation Safety and Environment","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42939124","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}
Juan Li, F. Guo, Yanning Zhou, Wenchen Yang, Dingan Ni
Traffic accident severity prediction is essential for dynamic traffic safety management. To explore the factors influencing the severity of traffic accidents on mountain freeways and to predict the severity of traffic accidents, four models based on machine learning algorithms are constructed using support vector machine (SVM), decision tree classifier (DTC), Ada_SVM and Ada_DTC. In addition, random forest (RF) is used to calculate the importance degree of variables, and accident severity influences with high importance levels form the RF dataset. The results show that rainfall intensity, collision type, number of vehicles involved in the accident and road section type are important variables influencing accident severity. The RF feature selection method improves the classification performance of four machine learning algorithms, resulting in 9.3%, 5.5%, 7.2% and 3.6% improvement in prediction accuracy for SVM, DTC, Ada_SVM and Ada_DTC, respectively. The combination of Ada_SVM integrated algorithm and RF feature selection method has the best prediction performance, and it achieves 78.9% and 88.4% prediction precision and accuracy, respectively.
{"title":"Predicting the severity of traffic accidents on mountain freeways with dynamic traffic and weather data","authors":"Juan Li, F. Guo, Yanning Zhou, Wenchen Yang, Dingan Ni","doi":"10.1093/tse/tdad001","DOIUrl":"https://doi.org/10.1093/tse/tdad001","url":null,"abstract":"\u0000 Traffic accident severity prediction is essential for dynamic traffic safety management. To explore the factors influencing the severity of traffic accidents on mountain freeways and to predict the severity of traffic accidents, four models based on machine learning algorithms are constructed using support vector machine (SVM), decision tree classifier (DTC), Ada_SVM and Ada_DTC. In addition, random forest (RF) is used to calculate the importance degree of variables, and accident severity influences with high importance levels form the RF dataset. The results show that rainfall intensity, collision type, number of vehicles involved in the accident and road section type are important variables influencing accident severity. The RF feature selection method improves the classification performance of four machine learning algorithms, resulting in 9.3%, 5.5%, 7.2% and 3.6% improvement in prediction accuracy for SVM, DTC, Ada_SVM and Ada_DTC, respectively. The combination of Ada_SVM integrated algorithm and RF feature selection method has the best prediction performance, and it achieves 78.9% and 88.4% prediction precision and accuracy, respectively.","PeriodicalId":52804,"journal":{"name":"Transportation Safety and Environment","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43895381","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 study aims to develop a reliable safety evaluation model for diverging vehicles and investigates the impact of the surrounding traffic environment on freeway diverging risks. High-resolution trajectory data from three sites in the Netherlands (Delft, Ter-Heide, and Zonzeel) were employed for the risk analysis. Linear regression (LR), Support vector machine (SVM), Random Forest (RF), Extreme randomize trees (ET), Adaptive boosting (Adaboost), Extreme gradient boosting (XGboost), and Multilayer perceptron (MLP), were developed for safety evaluation. The result showed that MLP outperforms the other models for diverging risk prediction over all the indicators, conflict thresholds, and locations. Pairwise matrix, Shapely addictive explanation (SHAP), and Linear regression algorithms were further adopted to interpret the influence of the surrounding environment. It indicates that an increase in traffic density, subject vehicle lateral speed, the distance of subject vehicle from ramp nose, and subject vehicle length would increase the diverging risk. At the same time, an increase in leading vehicle speed and space headway would decrease diverging risk. Finally, spatial analysis was also conducted to explore the stability of identified traffic features regarding the impact on the diverging risk across the sites.
{"title":"Analyzing freeway diverging risks using high-resolution trajectory data based on conflict prediction models","authors":"Ye Li, S. Dalhatu, Chen Yuan","doi":"10.1093/tse/tdad002","DOIUrl":"https://doi.org/10.1093/tse/tdad002","url":null,"abstract":"\u0000 This study aims to develop a reliable safety evaluation model for diverging vehicles and investigates the impact of the surrounding traffic environment on freeway diverging risks. High-resolution trajectory data from three sites in the Netherlands (Delft, Ter-Heide, and Zonzeel) were employed for the risk analysis. Linear regression (LR), Support vector machine (SVM), Random Forest (RF), Extreme randomize trees (ET), Adaptive boosting (Adaboost), Extreme gradient boosting (XGboost), and Multilayer perceptron (MLP), were developed for safety evaluation. The result showed that MLP outperforms the other models for diverging risk prediction over all the indicators, conflict thresholds, and locations. Pairwise matrix, Shapely addictive explanation (SHAP), and Linear regression algorithms were further adopted to interpret the influence of the surrounding environment. It indicates that an increase in traffic density, subject vehicle lateral speed, the distance of subject vehicle from ramp nose, and subject vehicle length would increase the diverging risk. At the same time, an increase in leading vehicle speed and space headway would decrease diverging risk. Finally, spatial analysis was also conducted to explore the stability of identified traffic features regarding the impact on the diverging risk across the sites.","PeriodicalId":52804,"journal":{"name":"Transportation Safety and Environment","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43181425","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}
The paper proposes a model of mandatory lane-changing behaviour based on a non-cooperative game in a traditional environment and analyses its applicability in a connected environment. In order to solve the problem of traffic safety and traffic congestion caused by mandatory lane-changing on urban roads, this paper applies the non-cooperative game theory to describe the game behaviour of the two parties, the lane-changing vehicle and the vehicle behind the target lane, in the connected and traditional environments respectively, and constructs the model considering the safety gain, speed gain and lane-changing gain to obtain a game model and the Nash equilibrium solution. The model is calibrated and tested using NGSIM data, and the results of the study show that the model has a good performance for the decision behaviour of lane-changing vehicles and lag vehicles for mandatory lane-changing behaviour on urban roads.
{"title":"Mandatory lane-changing modelling based on a game theoretic approach in traditional and connected environments","authors":"G. Cheng, Qiuyue Sun, Y. Bie","doi":"10.1093/tse/tdac035","DOIUrl":"https://doi.org/10.1093/tse/tdac035","url":null,"abstract":"\u0000 The paper proposes a model of mandatory lane-changing behaviour based on a non-cooperative game in a traditional environment and analyses its applicability in a connected environment. In order to solve the problem of traffic safety and traffic congestion caused by mandatory lane-changing on urban roads, this paper applies the non-cooperative game theory to describe the game behaviour of the two parties, the lane-changing vehicle and the vehicle behind the target lane, in the connected and traditional environments respectively, and constructs the model considering the safety gain, speed gain and lane-changing gain to obtain a game model and the Nash equilibrium solution. The model is calibrated and tested using NGSIM data, and the results of the study show that the model has a good performance for the decision behaviour of lane-changing vehicles and lag vehicles for mandatory lane-changing behaviour on urban roads.","PeriodicalId":52804,"journal":{"name":"Transportation Safety and Environment","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48200120","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}
By considering a mandatory lane changing as a collision avoidance measure, this paper presented the corresponding lane change decision making and trajectory planning algorithm under emergency scenario. Different from the traditional algorithm in which lane change decision making and trajectory planning are separated, the lane change decision making and trajectory making are coupled in proposed algorithm and the related parameters are dynamically adjusted in whole process. In addition to lane change collision avoidance feasibility analysis, lane change time instance and duration time is obtained by solving the constrained convex quadratic optimization program. By taking lane change time instance and duration time as inputs, the algorithm then proceeded to propose a kinematic model based high-order polynomial lane change trajectory. By giving the simulation result compassion with the related algorithm, it is proved that the proposed algorithm has a good robustness and high efficiency.
{"title":"A mandatory lane changing decision making and planning under emergency situation","authors":"Yang Liu, Cong-Ling Shi","doi":"10.1093/tse/tdac041","DOIUrl":"https://doi.org/10.1093/tse/tdac041","url":null,"abstract":"\u0000 By considering a mandatory lane changing as a collision avoidance measure, this paper presented the corresponding lane change decision making and trajectory planning algorithm under emergency scenario. Different from the traditional algorithm in which lane change decision making and trajectory planning are separated, the lane change decision making and trajectory making are coupled in proposed algorithm and the related parameters are dynamically adjusted in whole process. In addition to lane change collision avoidance feasibility analysis, lane change time instance and duration time is obtained by solving the constrained convex quadratic optimization program. By taking lane change time instance and duration time as inputs, the algorithm then proceeded to propose a kinematic model based high-order polynomial lane change trajectory. By giving the simulation result compassion with the related algorithm, it is proved that the proposed algorithm has a good robustness and high efficiency.","PeriodicalId":52804,"journal":{"name":"Transportation Safety and Environment","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42612223","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}
In order to ensure the safety and efficiency of section tracking operation of guided transport system, a safety headway control method of section tracking based on intersection conditions is proposed in this paper. Considering the difference of signal phase, the evaluation model of road conditions was established based on a fuzzy comprehensive evaluation method FAGT. Based on the artificial potential field method, the time-varying hybrid artificial potential field (TH-APF) method was proposed, and the tracking headway control algorithm was designed to realize the dynamic control of the tracking headway of the guide transport vehicle. The simulation results verified the effectiveness and applicability of the evaluation model of intersection road conditions, the tracking headway can be maintained at about 120s. The tracking headway control algorithm of guided transport vehicles can respond to the road conditions and avoid the local optimum of the artificial potential field method, thus improving the operating efficiency.
{"title":"Research on headway control of guided transport system based on intersections conditions evaluation","authors":"Xiao Yu, Yuan Cao, Yongkui Sun","doi":"10.1093/tse/tdac068","DOIUrl":"https://doi.org/10.1093/tse/tdac068","url":null,"abstract":"\u0000 In order to ensure the safety and efficiency of section tracking operation of guided transport system, a safety headway control method of section tracking based on intersection conditions is proposed in this paper. Considering the difference of signal phase, the evaluation model of road conditions was established based on a fuzzy comprehensive evaluation method FAGT. Based on the artificial potential field method, the time-varying hybrid artificial potential field (TH-APF) method was proposed, and the tracking headway control algorithm was designed to realize the dynamic control of the tracking headway of the guide transport vehicle. The simulation results verified the effectiveness and applicability of the evaluation model of intersection road conditions, the tracking headway can be maintained at about 120s. The tracking headway control algorithm of guided transport vehicles can respond to the road conditions and avoid the local optimum of the artificial potential field method, thus improving the operating efficiency.","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":"47560567","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}
Railway Point Machines (RPMs) condition monitoring has attracted engineers’ attention due to safe train operation and accident prevention. To realize the fast and accurate fault diagnosis of RPMs, this paper proposes a method based on entropy measurement and Broad Learning System (BLS). Firstly, the Modified Multi-scale Symbolic Dynamic Entropy (MMSDE) module extracts dynamic characteristics from the collected acoustic signals as entropy features. Then the Fuzzy BLS takes the above entropy features as input to complete model training. Fuzzy BLS introduces Takagi-Sugeno fuzzy system into BLS, which improves the model’s classification performance while considering computational speed. Experimental results indicate that the proposed method significantly reduces the running time while maintaining high accuracy.
{"title":"Modified Multi-Scale Symbolic Dynamic Entropy and Fuzzy Broad Learning-Based fast fault diagnosis of Railway Point Machines","authors":"Junqi Liu, Tao Wen, Guo Xie, Yuan Cao","doi":"10.1093/tse/tdac065","DOIUrl":"https://doi.org/10.1093/tse/tdac065","url":null,"abstract":"\u0000 Railway Point Machines (RPMs) condition monitoring has attracted engineers’ attention due to safe train operation and accident prevention. To realize the fast and accurate fault diagnosis of RPMs, this paper proposes a method based on entropy measurement and Broad Learning System (BLS). Firstly, the Modified Multi-scale Symbolic Dynamic Entropy (MMSDE) module extracts dynamic characteristics from the collected acoustic signals as entropy features. Then the Fuzzy BLS takes the above entropy features as input to complete model training. Fuzzy BLS introduces Takagi-Sugeno fuzzy system into BLS, which improves the model’s classification performance while considering computational speed. Experimental results indicate that the proposed method significantly reduces the running time while maintaining high accuracy.","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":"46647543","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：