Urban Rail Transit最新文献

Running rails are the return conductors of the traction current in DC subway systems, which should be insulated from the earth. Due to the large length of the line, as well as the humidity and metal dust in the tunnel, grounding fault of the running rails usually occurs, which will increase stray current (SC) leakage and endanger power supply safety. In this paper, a method of grounding fault diagnosis of running rails based on a multi-scale one-dimensional convolutional neural network (MS-1DCNN) is proposed. Firstly, a platform for the dynamic distribution of SC and rail potential (RP) with grounding faults existing in the running rails is established, which generates the dynamic RP data with various grounding faults. Secondly, a grounding fault diagnostic method of running rails based on MS-1DCNN is proposed, so as to realize the effective identification of ground fault types in subway systems. Thirdly, with the proposed diagnostic method, the datasets under two operating conditions of a single train and two trains are tested; a comparison test between MS-1DCNN and the 1D convolutional neural network (1DCNN) is carried out, and the effectiveness of the proposed method is verified. Results demonstrate that the proposed model can significantly improve the ground fault diagnostic accuracy of running rails. The dynamic RP simulation platform for trains established in this paper lays a theoretical foundation for the grounding fault research of running rail. Moreover, the deep learning method is proposed for the first time to diagnose the grounding fault of running rail, and the high diagnostic accuracy is obtained, which is of great significance for the safe and stable operation of the subway line.

To investigate the concrete damage of prefabricated steel spring floating slab tracks (SSFST), a three-slab prefabricated SSFST system was established using the ABAQUS finite element software. Full trainload conditions and fatigue load conditions of a train passage were successively applied to the system. Plastic damage and fatigue damage of the floating slab were simulated based on concrete damage plasticity theory and model code, respectively. For comparison, a simulation of the fatigue experiment was conducted. Parametric analyses of the concrete strength and isolator stiffness were also performed. The results show that the maximum positive and negative bending moments of the floating slab throughout the loading stage are close in value. The positive bending moment causes stress concentration on the top slab surface which leads to plastic damage and low-cycle fatigue damage, while the negative bending moment causes middle-level elastic tensile stress on the bottom slab surface which leads to high-cycle fatigue damage. Under experimental conditions, damage on the bottom surface is much more severe, while the upper part is undamaged. Improving the concrete strength can reduce both kinds of damage, while increasing the isolator stiffness can only mitigate the high-cycle fatigue damage. Accordingly, recommendations are provided for improving fatigue experiments and structural design of prefabricated floating slabs.This study can inform the design and maintenance of the prefabricated SSFST system, ultimately enhancing their safety and longevity.

To maximize the use of urban land, many cities have built buildings above metro depots. However, the low-frequency vibration caused by metro operation affects the lives of surrounding residents, which seriously restricts the further development of over-track buildings. To study this problem, Firstly, the vibration of the metro depot and surrounding sensitive areas are tested on a large actual metro depot in Southwest China, and the rail, sleeper/support column, bearing column, and cover plate are mainly tested. Then, considering nonlinear factors such as mechanical properties of building materials, soil layering characteristics, and artificial viscoelastic boundary, the numerical coupled model of the train-track-depot-building is established, and the simulation data are compared with the test data to verify the accuracy of the numerical model. Finally, the impact of metro operation on the over-track buildings is evaluated. Results show that for the over-track buildings concerned in this paper, the floor vibration near the rail is the strongest, the main vibration frequency of the office building is concentrated in 10–20 Hz, and the maximum Z vibration level (VL_zmax) of the office building is 52.02 dB. The main vibration frequency of the residential building is similar to that of the office building, and the superposition of floor vibration energy causes the vibration of the mid-span point to be larger than the vibration of the corner point and the side wall point. The vibration wave of lower floors mainly propagates through the bearing column, and the vibration of the parking garage is larger than other buildings. The research results can provide a reference for the vibration control and design of over-track buildings above the metro depot.

Accurate forecasting of airport light rail transit line (ALRTL) outbound passenger flow is critical to the optimal operations of both light rail and airport systems. Considering the nonlinearity, non-stationarity, uncertainty, and periodicity of outbound passenger flow in the ALRTL, we propose a combined forecasting model that integrates the Holt and Winters additive model (HWAM), empirical mode decomposition (EMD) and gated recurrent unit (GRU). Firstly, the edge effect of EMD will greatly affect the performance of the forecasting model. To overcome this, we extend the passenger flow by HWAM. After that, the decomposition method, EMD, can be applied to passenger flow, and several intrinsic mode function (IMF) components can be extracted. After extracting all the IMFs, the remaining part is referred to as the residual (Res) component. Then, a correlation test is performed on all the components, followed by their aggregation. Finally, the GRU is used to predict each of the aggregated components, and the prediction of aggregated components requires reconstruction. To verify the performance of the HWAM-EMD-GRU, we conducted a comparative study on the hourly passenger flow data for Beijing Daxing International Airport Express and set the autoregressive integrated moving average model, HWAM, Prophet, and GRU as the baseline. Predictions of the HWAM-EMD-GRU combined model demonstrated higher accuracy than baseline models, with a root mean square error of 83.52 (Prophet is 110.21) and mean absolute percentage error of 8.32% (Prophet is 12.48 %). The experimental result shows that the HWAM-EMD-GRU forecasting model offers more accurate predictions.

Dynamic stress is one of the key indicators reflecting the fatigue characteristics of metro bogie frames. Considering the test costs, operation safety, and other factors, it is impossible to record all the dynamic stress data for the whole service period in the tracking test. Therefore, the overall stress spectrum is statistically deduced based on limited dynamic stress data samples, which can not only provide a basis for the fatigue reliability research of the bogie frame, but also save costs. In this paper, the typical fatigue control points in different areas of the frame with large equivalent stress are selected for research. The daily measured stress spectrum samples are obtained through the rainflow counting method, and the statistical stress spectrum is then compiled. Weibull distribution fitting of the stress spectrum is carried out to obtain the scale and shape parameter samples for different fatigue control parts. After sampling of the obtained parameter samples and conducting variance homogeneity tests as well as t-tests, the minimum sample size representing the overall distribution of the interval is obtained. Therefore, the shortest tracking test period reflecting the overall stress distribution of typical fatigue control parts can be obtained.

It is important to strengthen the research on urban rail transit (URT) existing line renovation strategies. In this paper, we investigate the optimization of bottlenecks that are less attractive but have strong travel demand in existing URT networks. A URT local line optimization model is constructed. The maximum passenger flow and minimum project cost are chosen as the optimization objective for the benefit of both passengers and operators, and several actual constraints are considered in the proposed model, such as the station interval. In order to obtain higher computational efficiency and accuracy, a passenger flow allocation method is embedded in a genetic algorithm with elitist preservation. Taking the local network of the Beijing URT as a case study, the calculation results show that the designed algorithm can quickly and effectively obtain the optimal solution, and the generated local line scheme is able not only to meet the regional travel demand, but also to optimize the connection relationship of the existing URT network. This study can provide a reference method for increasing the attraction of URT and optimization of existing URT networks.

In dual traction power supply systems, the overhead catenary system operates in different power supply modes. It passes across the AC section, DC section, and a neutral part, which influences the features and properties of the feedback current and aggregates its effects on stray current and rail potential. This research paper presents an integrated model of an AC and DC traction power system (TPS), along with a unified chain equivalent circuit model, the ground wire through the AC section, and the insulation joints fixed in the AC–DC neutral section under different operating positions. To make a unified impedance and admittance matrix for traction network, a virtual conductor wire has been added in the DC section to make the balance order of the TPS. The influence of reflex system configuration on rail potential, stray current, and distribution of rail potential at AC and DC stations has also been calculated. The simulation results demonstrate that establishing the insulation joints in the AC–DC section and using ground wires in the AC part can significantly decrease the stray current and rail potential.

With the evolution of people's consumption habits and the rapid growth of urban logistics, the number of trucks and delivery frequency has increased significantly, exacerbating urban traffic congestion and environmental pollution. Consequently, there is an urgent need to improve the current inefficient and highly polluted distribution mode. Currently, in most cities in China, the metro passenger flow is insufficient, and the capacity is excessive during off-peak hours, resulting in underutilized carriage capacity. The integration of surface and underground transport resources can effectively address these issues and facilitate complementary advantages and win–win cooperation between express companies and metro enterprises. This study proposes an innovative problem of split demand route planning in the cooperative distribution system involving express companies and subways. A cooperative distribution model is developed to minimize the total cost, and solved by the Cuckoo Search algorithm to obtain the optimized solution. The model is applied to the urban rail transit network in Changchun, and the results demonstrate that it is effective in reducing truck mileage and distribution costs. Compared to the single delivery pattern by trucks, the cooperative distribution approach proves to be more cost-effective and environmentally friendly.

The express/local mode of municipal rail transit provides passengers with multiple alternatives to achieve more efficient and superior travel, in contrast to the conventional all-stop operation mode. However, the various route choices (including direct express trains, direct local trains, or transfers) covering different passenger groups pose a significant challenge to passenger flow assignment. To understand route choice behavior, it is crucial to measure the passenger heterogeneity (variability in individual and trip attributes) in order to propose targeted solutions for operation schemes and service planning. This paper proposes a hybrid model by integrating structural equation modeling and the mixed logit model under express/local mode to estimate the impact of passenger heterogeneity on route choice. An empirical study with revealed preference and stated preference surveys carried out in Shanghai revealed how individual and trip attributes quantitatively impact the sensitivity of factors in route choice. The results show that age and trip purpose are more significant factors. Compared to the control group, the probability of express trains is reduced by 10.22% for the elderly and by 11.36% for non-commuters. Our findings can provide support for more reasonable operation schemes and more targeted services.

The cascading propagation and evolution of metro operation failures can significantly impact the safety of metro operation. To overcome this challenge, this study pre-processes a massive amount of metro operation log data through noise reduction. Moreover, a professional terminology dictionary is constructed along with a custom stop-word dictionary to segment the preprocessed data. Subsequently, the AFP-tree algorithm is employed to mine the segmented log data and identify key hazards. A weighted urban rail transit network is established, considering the effective path time cost, and the shortest travel OD path. To simulate the dynamic evolution of the failure chain propagation, a model based on disaster propagation theory is constructed. Taking the Shanghai Metro line as a case, multiple simulation scenarios are established with 25 key hazards as triggering points, and the number of cascade failure stations affected under different scenarios is outputted. The results indicate that the fault stations caused by the large passenger flow are the largest. Meanwhile, the number of stations affected by the door clamp is the smallest. The scale of fault stations reaches a maximum value in 16–20 min. Through case analysis, a positive correlation is found when the self-recovery factor is between 14 and 18, and the number of fault stations shows a significant increasing trend. The research results can provide decision-making support and theoretical guidance for rail transit operation safety management enterprises.