摘要 :
Image detection based on machine learning and deep learning currently has a good application prospect for railway fault diagnosis,with good performance in feature extraction and the accuracy of image localization and good classifi...
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Image detection based on machine learning and deep learning currently has a good application prospect for railway fault diagnosis,with good performance in feature extraction and the accuracy of image localization and good classification results.To improve the speed of locating small target objects of fasteners,the YOLOv5 framework model with faster algorithm speed is selected.To improve the classification accuracy of fasteners,YOLOv5-based heavy-duty railway rail fastener detection is proposed.The anchor size is modified on the original basis to improve the attention to small targets of fasteners.The CBAM(Convolutional Block Attention Module)module and TPH(Transformer Prediction Head)module are introduced to improve the speed and accuracy issues.The rail fasteners are divided into 6 categories.Experiment comparisons show that before the improvement,the MAP@0.5 value of all categories are close to the peak of 0.989 after the epoch of 150,and the F1 score approaches 1 with confidence in the interval(0.2,0.95).The improved mAP@0.5 value approached the highest value of 0.991 after the epoch of 75,and the F1 score approached 1 with confidence in the interval(0.01,0.95).The experiment results indicate that the improved YOLOv5 model proposed in this paper is more suitable for the task of detecting rail fasteners.
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摘要 :
A ballastless slab track,which is commonly used in the track structures of heavy-haul railway tunnels,was analysed based on field measurement data of the Fuyingzi Tunnel on the Zhangtang Railway.In accordance with the measured dat...
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A ballastless slab track,which is commonly used in the track structures of heavy-haul railway tunnels,was analysed based on field measurement data of the Fuyingzi Tunnel on the Zhangtang Railway.In accordance with the measured data,the dynamic load thresholds and distributions on the surface and bottom of the ballastless slab track were investigated.A fatigue damage analysis of the ballastless slab track was performed based on the dynamic load time–history curve.The results show that the ballastless slab track can accomplish train load attenuation and reduce the dynamic load from heavy-haul trains by 47.22%from the surface to the bottom.In addition,the distribution at the bottom of the ballastless slab track exhibited a triangular shape,and the dynamic load threshold at the line centre accounted for 78.67%of that at the track position.Meanwhile,the distribution at the surface was saddle-shaped;the dynamic load threshold at the track position accounted for 79.55%of that at the line centre position.The fatigue damage of the ballastless slab track was analysed effectively by combining the measured data and the linear fatigue damage theory.Moreover,the accuracy of the calculation results was verified based on the measured dynamic stress of the ballastless slab track structure.The dynamic action of the train load led to more-concentrated damage to the track bed,and the damage occurred earlier than that in the ordinary line.The axle load was the primary influencing factor of the track bed fatigue damage,and the damage mainly occurred in the track position.These results provide a theoretical basis for performing stress analysis and designing parameters for ballastless slab tracks in heavy-haul railway tunnels.
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摘要 :
In order to address the issues of complex system structure and variable selection difficulty for the current heavy haul railway line status evaluation system, a three-category and three-layer heavy-haul line status evaluation vari...
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In order to address the issues of complex system structure and variable selection difficulty for the current heavy haul railway line status evaluation system, a three-category and three-layer heavy-haul line status evaluation variable set construction and reduction optimization method is proposed. Firstly, the status of heavy haul railway line is analyzed, and an initial set of evaluation variables affecting the line status is constructed. Then, based on the association rule and the principal component analysis method, key variables are extracted from the initial variable set to establish the evaluation system. Finally, this method is verified with actual data of a line. The results show that the service performance of heavy haul railway line can still be evaluated accurately when the evaluation variables are reduced by 60% in the proposed method.
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摘要 :
This study investigated the degradation mechanism of the surrounding rock of a heavy-haul railway under a water-rich condition,based on the construction of the Taihangshan tunnel for the Wari Railway,a heavy-haul railway that used...
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This study investigated the degradation mechanism of the surrounding rock of a heavy-haul railway under a water-rich condition,based on the construction of the Taihangshan tunnel for the Wari Railway,a heavy-haul railway that used standard construction practices for axle loads of 30 t.Remote monitoring demonstrated that the coupling effect between the dynamic load of a heavy-haul train and the groundwater leads to the deterioration and hollowing of the surrounding rock.This study clarified the void evolution process and deterioration mechanism of the basement rock under the comprehensive influence of the groundwater–train dynamic load using a refined discrete element numerical simulation.The results revealed that the groundwater was the primary influencing factor in the deterioration of the lower part of the heavy-haul railway tunnel.Rock particles were gradually lost under the effects of long-term erosion due to groundwater and heavy-haul trains,which inevitably damaged the basement rock after the construction was completed.Based on this observation,the critical conditions for the deterioration and attenuation law of the physical parameters of the basement rock were obtained.The results of this study can provide ideas and serve as a reference for the forecasting and disaster treatment of basement rock damage in heavy-haul railway tunnels.
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摘要 :
Purpose-In order to develop high-strength,high-toughness and high-wear-resistance rails suitable for the development and application of heavy-haul railways.Design/methodology/approach-Based on the trial production of 60 kg·m^(−1...
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Purpose-In order to develop high-strength,high-toughness and high-wear-resistance rails suitable for the development and application of heavy-haul railways.Design/methodology/approach-Based on the trial production of 60 kg·m^(−1) bainite rails,the Zeiss inverted optical microscope,transmission electron microscope and static hydraulic universal tester were used to test the microstructure and property of rail base metal and welded joints.Meanwhile,a trial laying of rails,wing rails of frogs and switch rails for turnouts was performed to systematically analyze their strength,toughness and wear resistance.Findings-The results show that the base metal of 60 kg·m^(−1) bainite rail is of a uniform microstructure,with a carbide-free bainite matrix,a few of stable residual austenite and M/A islands,and it features high hardness,good wear resistance and good strength-toughness balance.The welded joint is of a uniform microstructure and has good properties.Originality/value-A bainite rail,laid in a curve section of heavy-haul railway is able to serve for 48 months with a gross traffic tonnage of nearly 600 million tons,whose service life is more than one time longer than that of pearlite rail;the service life of the wing rail of frog and the switch rail for turnout with 60 kg·m^(−1) bainite rails is 3-4 times longer than that with U75V rails,and no serious damage occurs.The bainite rails also have strong peeling and spalling resistance.
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