This study aims to analyze the development direction of track geometry inspection equipment for high-speed comprehensive inspection train in China.

The development of track geometry inspection equipment for high-speed comprehensive inspection train in China in the past 20 years can be divided into 3 stages. Track geometry inspection equipment 1.0 is the stage of analog signal. At the stage 1.0, the first priority is to meet the China's railways basic needs of pre-operation joint debugging, safety assessment and daily dynamic inspection, maintenance and repair after operation. Track geometry inspection equipment 2.0 is the stage of digital signal. At the stage 2.0, it is important to improve stability and reliability of track geometry inspection equipment by upgrading the hardware sensors and improving software architecture. Track geometry inspection equipment 3.0 is the stage of lightweight. At the stage 3.0, miniaturization, low power consumption, self-running and green economy are co-developing on demand.

The ability of track geometry inspection equipment for high-speed comprehensive inspection train will be expanded. The dynamic inspection of track stiffness changes will be studied under loaded and unloaded conditions in response to the track local settlement, track plate detachment and cushion plate failure. The dynamic measurement method of rail surface slope and vertical curve radius will be proposed, to reveal the changes in railway profile parameters of high-speed railways and the relationship between railway profile, track irregularity and subsidence of subgrade and bridges. The 200 m cut-off wavelength of track regularity will be researched to adapt to the operating speed of 400 km/h.

The research can provide new connotations and requirements of track geometry inspection equipment for high-speed comprehensive inspection train in the new railway stage.

The wavelet neural network (WNN) has the drawbacks of slow convergence speed and easy falling into local optima in data prediction. Although the artificial bee colony (ABC) algorithm has strong global optimization ability and fast convergence speed, it also has the drawbacks of slow speed while finding the optimal solution and weak optimization ability in the later stage.

This article uses an ABC algorithm to optimize the WNN and establishes an ABC-WNN analysis model. Based on the example of the Jinan Yuhan underground tunnel project, the deformation of the surrounding rock of the double-arch tunnel crossing the fault fracture zone is predicted and analyzed, and the analysis results are compared with the actual detection amount.

The comparison results show that the predicted values of the ABC-WNN model have a high degree of fitting with the actual engineering data, with a maximum relative error of only 4.73%. On this basis, the results show that the statistical features of ABC-WNN are the lowest, with the errors at 0.566 and 0.573, compared with the single back propagation (BP) neural network model and WNN model. Therefore, it can be derived that the ABC-WNN model has higher prediction accuracy, better computational stability and faster convergence speed for deformation.

This article uses firstly the ABC-WNN for the deformation analysis of double-arch tunnels. This attempt laid the foundation for artificial intelligence prediction in deformation analysis of multi-arch tunnels and small clearance tunnels. It can provide a new and effective way for deformation prediction in similar projects.

This paper analyzes the application of digital twin technology in the field of intelligent operation and maintenance of high-speed railway infrastructure from the perspective of top-level design.

This paper provides a comprehensive overview of the definition, connotations, characteristics and key technologies of digital twin technology. It also conducts a thorough analysis of the current state of digital twin applications, with a particular focus on the overall requirements for intelligent operation and maintenance of high-speed railway infrastructure. Using the Jinan Yellow River Bridge on the Beijing-Shanghai high-speed railway as a case study, the paper details the construction process of the twin system from the perspectives of system architecture, theoretical definition, model construction and platform design.

Digital twin technology can play an important role in the whole life cycle management, fault prediction and condition monitoring in the field of high-speed rail operation and maintenance. Digital twin technology is of great significance to improve the intelligent level of high-speed railway operation and management.

This paper systematically summarizes the main components of digital twin railway. The general framework of the digital twin bridge is given, and its application in the field of intelligent operation and maintenance is prospected.

Safety management is a key point and poses a challenge in joint testing. To detect and address potential accidents' hidden dangers early, this paper conducts research on the safety control technology for high-speed railway joint tests by incorporating the concept of hazardous events.

Aiming at ensuring the safety of high-speed railway combined inspections and trials, this paper starts from the dual prevention mechanism. It introduces the concept of threatening events, defines them and analyzes the differences between threatening events and railway accidents. The paper also proposes a cause model for threatening events in high-speed railway combined inspections and trials, based on three types of hazard sources. Furthermore, it conducts research on the control strategies for these threatening events.

The research on safety control technology for high-speed railway combined operation and testing, based on the analysis of threatened events, offers a new perspective for safety management in these operations. It also provides theoretical and practical support for the transition from passive prevention to active risk pre-control, which holds significant theoretical and practical value.

The innovation mainly includes the following three aspects: (1) Building on the traditional dual prevention mechanism, which includes risk hierarchical management and control as well as hidden danger investigation and management, a triple prevention mechanism is proposed. This new mechanism adds the management of threatening events as the third line of defense. The aim is to more comprehensively identify and address potential security risks, thereby enhancing the efficiency and effectiveness of security management. (2) In this paper, the definition of a railway threatening event is clarified, and the causative model of a high-speed railway threatening event based on three kinds of danger sources is proposed. (3) This paper puts forward the control strategy of the high-speed railway combined operation and trial, which includes five key links: identification, reporting, analysis, rectification and feedback, which provides a new perspective for the safety management of the high-speed railway combined operation and trial and has important theoretical and application value.

To facilitate technical managers and field workers to master and understand the provisions of Technical Management Regulations for Railway more accurately, so as to better serve the comprehensive revision of the Regulations, this paper carries out the research on the traceability and evolution of the provisions of the Regulations.

This paper studies and analyzes the evolution of the 11th edition of the Regulations by analyzing the relevance of clauses and summarizes the historical background of the development of calendar editions of the Regulations. The basic research on the traceability and evolution of the Regulations is carried out from four aspects: the continuity of the development of the Regulations, the authority of contents, the relevance of clauses and the richness of historical materials.

From the first edition of the Regulations issued by the former Ministry of Railways in 1950 to the 11th edition, there have been ten comprehensive revisions. There is a strong correlation and continuity between the calendar editions of the Regulations in terms of chapter structure and clauses. Studying the context of the terms of the Regulations is an important way to understand and master the current clauses of the Regulations.

Through the research on the traceability and evolution of the clauses of the Regulations, one is to explore the context of the development of railway technical equipment in China, the other is to clarify the historical background when the provisions were formulated and the third is to trace the development and evolution of the provisions. The revision of the Regulations is based on an accurate grasp of the context of the provisions, which can effectively judge the possible security risks caused by the revision of the provisions and avoid the possible risks in field implementation from the source.

The volume of passenger traffic at metro transfer stations serves as a pivotal metric for the orchestration of crowd flow management. Given the intricacies of crowd dynamics within these stations and the recurrent instances of substantial passenger influxes, a methodology predicated on stochastic processes and the principle of user equilibrium is introduced to facilitate real-time traffic flow estimation within transfer station streamlines.

The synthesis of stochastic process theory with streamline analysis engenders a probabilistic model of intra-station pedestrian traffic dynamics. Leveraging real-time passenger flow data procured from monitoring systems within the transfer station, a gradient descent optimization technique is employed to minimize the cost function, thereby deducing the dynamic distribution of categorized passenger flows. Subsequently, adhering to the tenets of user equilibrium, the Frank-Wolfe algorithm is implemented to allocate the intra-station categorized passenger flows across various streamlines, ascertaining the traffic volume for each.

Utilizing the Xiaozhai Station of the Xi'an Metro as a case study, the Anylogic simulation software is engaged to emulate the intra-station crowd dynamics, thereby substantiating the efficacy of the proposed passenger flow estimation model. The derived solutions are instrumental in formulating a crowd control strategy for Xiaozhai Station during the peak interval from 17:30 to 18:00 on a designated day, yielding crowd management interventions that offer insights for the orchestration of passenger flow and operational governance within metro stations.

The construction of an estimation methodology for the real-time streamline traffic flow augments the model's dataset, supplanting estimated values derived from surveys or historical datasets with real-time computed traffic data, thereby enhancing the precision and immediacy of crowd flow management within metro stations.

The safe operation of the metro power transformer directly relates to the safety and efficiency of the entire metro system. Through voiceprint technology, the sounds emitted by the transformer can be monitored in real-time, thereby achieving real-time monitoring of the transformer's operational status. However, the environment surrounding power transformers is filled with various interfering sounds that intertwine with both the normal operational voiceprints and faulty voiceprints of the transformer, severely impacting the accuracy and reliability of voiceprint identification. Therefore, effective preprocessing steps are required to identify and separate the sound signals of transformer operation, which is a prerequisite for subsequent analysis.

This paper proposes an Adaptive Threshold Repeating Pattern Extraction Technique (REPET) algorithm to separate and denoise the transformer operation sound signals. By analyzing the Short-Time Fourier Transform (STFT) amplitude spectrum, the algorithm identifies and utilizes the repeating periodic structures within the signal to automatically adjust the threshold, effectively distinguishing and extracting stable background signals from transient foreground events. The REPET algorithm first calculates the autocorrelation matrix of the signal to determine the repeating period, then constructs a repeating segment model. Through comparison with the amplitude spectrum of the original signal, repeating patterns are extracted and a soft time-frequency mask is generated.

After adaptive thresholding processing, the target signal is separated. Experiments conducted on mixed sounds to separate background sounds from foreground sounds using this algorithm and comparing the results with those obtained using the FastICA algorithm demonstrate that the Adaptive Threshold REPET method achieves good separation effects.

A REPET method with adaptive threshold is proposed, which adopts the dynamic threshold adjustment mechanism, adaptively calculates the threshold for blind source separation and improves the adaptability and robustness of the algorithm to the statistical characteristics of the signal. It also lays the foundation for transformer fault detection based on acoustic fingerprinting.

The purpose of this study is to address the deficiency in safety monitoring technology for 27.5 kV high-voltage cables within the railway traction power supply by analyzing the grounding methods employed in high-speed railways and developing an effective monitoring solution.

Through establishing a mathematical model of induced potential in the cable sheath and analyzing its influencing factors, the principle of grounding current monitoring is proposed. Furthermore, the accuracy of data collection and alarm function of the monitoring equipment were verified through laboratory simulation experiments. Finally, through practical application in the traction substation of the railway bureau on site, a large amount of data were collected to verify the stability and reliability of the monitoring system in actual environments.

The experimental results show that the designed monitoring system can effectively monitor the grounding current of high-voltage cables and respond promptly to changes in cable insulation status. The system performs excellently in terms of data collection accuracy, real-time performance and reliability of alarm functions. In addition, the on-site trial results further confirm the accuracy and reliability of the monitoring system in practical applications, providing strong technical support for the safe operation of high-speed railway traction power supply systems.

This study innovatively develops a 27.5kV high-voltage cable grounding current monitoring system, which provides a new technical means for evaluating the insulation status of cables by accurately measuring the grounding current. The design, experimental verification and application of this system in high-speed railway traction power supply systems have demonstrated significant academic value and practical significance, contributing innovative solutions to the field of railway power supply safety monitoring.

This study aimed to facilitate a rapid evaluation of track service status and vehicle ride comfort based on car body acceleration. Consequently, a low-cost, data-driven approach was proposed for analyzing speed-related acceleration limits in metro systems.

A portable sensing terminal was developed to realize easy and efficient detection of car body acceleration. Further, field measurements were performed on a 51.95-km metro line. Data from 272 metro sections were tested as a case study, and a quantile regression method was proposed to fit the control limits of the car body acceleration at different speeds using the measured data.

First, the frequency statistics of the measured data in the speed-acceleration dimension indicated that the car body acceleration was primarily concentrated within the constant speed stage, particularly at speeds of 15.4, 18.3, and 20.9 m/s. Second, resampling was performed according to the probability density distribution of car body acceleration for different speed domains to achieve data balance. Finally, combined with the traditional linear relationship between speed and acceleration, the statistical relationships between the speed and car body acceleration under different quantiles were determined. We concluded the lateral/vertical quantiles of 0.8989/0.9895, 0.9942/0.997, and 0.9998/0.993 as being excellent, good, and qualified control limits, respectively, for the lateral and vertical acceleration of the car body. In addition, regression lines for the speed-related acceleration limits at other quantiles (0.5, 0.75, 2s, and 3s) were obtained.

The proposed method is expected to serve as a reference for further studies on speed-related acceleration limits in rail transit systems.

This study aims to investigate the cause of high-order wheel polygonization in a plateau high-speed electric multiple unit (EMU) train.

A series of field tests were conducted to measure the vibration accelerations of the axle box and bogie when the wheels of the EMU train passed through tracks with normal rail roughness after re-profiling. Additionally, the dynamic characteristics of the track, wheelset and bogie were also measured. These measurements provided insights into the mechanisms that lead to wheel polygonization.

The results of the field tests indicate that wheel polygonal wear in the EMU train primarily exhibits 14-16 and 25-27 harmonic orders. The passing frequencies of wheel polygonization were approximately 283-323 Hz and 505-545 Hz, which closely match the dominated frequencies of axle box and bogie vibrations. These findings suggest that the fixed-frequency vibrations originate from the natural modes of the wheelset and bogie, which can be excited by wheel/rail irregularities.

The study provides novel insights into the mechanisms of high-order wheel polygonization in plateau high-speed EMU trains. Futher, the results indicate that operating the EMU train on mixed lines at variable speeds could potentially mitigate high-order polygonal wear, providing practical value for improving the safety, performance and maintenance efficiency of high-speed EMU trains.