Pub Date : 2024-02-17DOI: 10.1177/09544097241234380
Ling Wang, Qiuyu Zang, Kehua Zhang, Lintong Wu
Being a crucial component of railway tracks, monitoring the health condition of fasteners stands as a critical aspect within the realm of railroad track management, ensuring the normal passage of trains. However, traditional track fastener detection methods mainly use artificial checks, giving rise to challenges encompassing reduced efficiency, safety hazards, and poor detection accuracy. Consequently, we introduce an innovative model for the detection of track fastener defects, termed YOLOv5-CGBD. In this study, we first imbue the backbone network with the CBAM attention mechanism, which elevates the network’s emphasis on pertinent feature extraction within defective regions. Subsequently, we replace the standard convolutional blocks in the neck network with the GSConv convolutional module, achieving a delicate balance between the model’s accuracy and computational speed. Augmenting our model’s capacities for efficient feature map fusion and reorganization across diverse scales, we integrate the weighted bidirectional feature pyramid network (BiFPN). Ultimately, we manipulate a lightweight decoupled head structure, which improves both detection precision and model robustness. Concurrently, to enhance the model’s performance, a data augmentation strategy is employed. The experimental findings testify to the YOLOv5-CGBD model’s ability to conduct real-time detection, with mAP0.5 scores of 0.971 and 0.747 for mAP0.5:0.95, surpassing those of the original YOLOv5 model by 2.2% and 4.1%, respectively. Furthermore, we undertake a comparative assessment, contrasting the proposed methodology with alternative approaches. The experimental outcomes manifest that the YOLOv5-CGBD model exhibits the most exceptional comprehensive detection performance while concurrently maintaining a high processing speed.
{"title":"A rail fastener defect detection algorithm based on improved YOLOv5","authors":"Ling Wang, Qiuyu Zang, Kehua Zhang, Lintong Wu","doi":"10.1177/09544097241234380","DOIUrl":"https://doi.org/10.1177/09544097241234380","url":null,"abstract":"Being a crucial component of railway tracks, monitoring the health condition of fasteners stands as a critical aspect within the realm of railroad track management, ensuring the normal passage of trains. However, traditional track fastener detection methods mainly use artificial checks, giving rise to challenges encompassing reduced efficiency, safety hazards, and poor detection accuracy. Consequently, we introduce an innovative model for the detection of track fastener defects, termed YOLOv5-CGBD. In this study, we first imbue the backbone network with the CBAM attention mechanism, which elevates the network’s emphasis on pertinent feature extraction within defective regions. Subsequently, we replace the standard convolutional blocks in the neck network with the GSConv convolutional module, achieving a delicate balance between the model’s accuracy and computational speed. Augmenting our model’s capacities for efficient feature map fusion and reorganization across diverse scales, we integrate the weighted bidirectional feature pyramid network (BiFPN). Ultimately, we manipulate a lightweight decoupled head structure, which improves both detection precision and model robustness. Concurrently, to enhance the model’s performance, a data augmentation strategy is employed. The experimental findings testify to the YOLOv5-CGBD model’s ability to conduct real-time detection, with mAP0.5 scores of 0.971 and 0.747 for mAP0.5:0.95, surpassing those of the original YOLOv5 model by 2.2% and 4.1%, respectively. Furthermore, we undertake a comparative assessment, contrasting the proposed methodology with alternative approaches. The experimental outcomes manifest that the YOLOv5-CGBD model exhibits the most exceptional comprehensive detection performance while concurrently maintaining a high processing speed.","PeriodicalId":54567,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part F-Journal of Rail and Rapid Transit","volume":"145 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139949507","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}
Pub Date : 2024-02-16DOI: 10.1177/09544097241234094
Junhua Xiao, Yingqi Bai, Chengjie Song, Siqi Sun, Xiaozhou Liu
Heavy rainfall has posed a great challenge to the service performance of high-speed rail (HSR) substructure, resulting in a reduction in the ride quality and safety of high-speed trains. To carry out proper repair work for the substructure, it is imperative to realize efficient identification of precipitation-induced subgrade defects. To this end, this paper aims to extract the features of typical precipitation-induced subgrade defects from the multiple track inspection data to provide a basis for defect identification. Firstly, the geotechnical site investigation including Ground Penetrating Radar (GPR) detection, moisture content test, and dynamic cone penetration (DCP) test of a typical defective spot is performed to determine the condition of the subgrade after heavy rainfall; then, the analysis methods of track inspection data are introduced; finally, the track geometry data and carbody acceleration data of four typical defective sections are analyzed, and the time-domain, frequency-domain and discrete wavelet transform (DWT)-based features which are highly correlated with the precipitation-induced subgrade defects are extracted. The results show that the feature indexes extracted from track surface irregularity and carbody vertical acceleration increase significantly after heavy rainfall; the long wavelength components (8 m and above) of both track irregularity and carbody vibration are more sensitive to the subgrade defects, which is reflected by the sharp increase of the DWT-based features at some levels corresponding to long wavelength ranges. The results of defect feature extraction based on the track inspection data agree well with the geotechnical site investigation results, which demonstrate the feasibility of utilizing multiple track inspection data to identify the typical precipitation-induced subgrade defects.
{"title":"Feature analysis of precipitation-induced subgrade defects on a high-speed rail ballasted track using multiple track inspection data: A case study","authors":"Junhua Xiao, Yingqi Bai, Chengjie Song, Siqi Sun, Xiaozhou Liu","doi":"10.1177/09544097241234094","DOIUrl":"https://doi.org/10.1177/09544097241234094","url":null,"abstract":"Heavy rainfall has posed a great challenge to the service performance of high-speed rail (HSR) substructure, resulting in a reduction in the ride quality and safety of high-speed trains. To carry out proper repair work for the substructure, it is imperative to realize efficient identification of precipitation-induced subgrade defects. To this end, this paper aims to extract the features of typical precipitation-induced subgrade defects from the multiple track inspection data to provide a basis for defect identification. Firstly, the geotechnical site investigation including Ground Penetrating Radar (GPR) detection, moisture content test, and dynamic cone penetration (DCP) test of a typical defective spot is performed to determine the condition of the subgrade after heavy rainfall; then, the analysis methods of track inspection data are introduced; finally, the track geometry data and carbody acceleration data of four typical defective sections are analyzed, and the time-domain, frequency-domain and discrete wavelet transform (DWT)-based features which are highly correlated with the precipitation-induced subgrade defects are extracted. The results show that the feature indexes extracted from track surface irregularity and carbody vertical acceleration increase significantly after heavy rainfall; the long wavelength components (8 m and above) of both track irregularity and carbody vibration are more sensitive to the subgrade defects, which is reflected by the sharp increase of the DWT-based features at some levels corresponding to long wavelength ranges. The results of defect feature extraction based on the track inspection data agree well with the geotechnical site investigation results, which demonstrate the feasibility of utilizing multiple track inspection data to identify the typical precipitation-induced subgrade defects.","PeriodicalId":54567,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part F-Journal of Rail and Rapid Transit","volume":"145 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139949444","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}
Pub Date : 2023-11-07DOI: 10.1177/09544097231213895
Tao Wen, Yaoyao Zhang, Zhiqiang Long
In order to meet the strict requirements of the reliability and safety of the commercial operation of the maglev train, it is necessary to carry out the control performance evaluation of the suspension system. However, at present, variance is often used as the evaluation index of control system. This method cannot get accurate performance evaluation results when the system is affected by non-Gaussian disturbance. Therefore, aiming at the non-Gaussian control performance evaluation of maglev train suspension system, a control performance evaluation method of maglev train suspension system based on minimum entropy is proposed in this paper. In view of the non-Gaussian characteristics in the operation data of maglev train suspension system, this paper introduces the feedback invariant entropy of non-Gaussian system, and then realizes the evaluation and analysis of the control performance of maglev train suspension system based on the minimum entropy criterion. Finally, combined with the evaluation and analysis of the operation data of Changsha medium and low-speed maglev train, this paper verifies the effectiveness and accuracy of the proposed performance evaluation method for the control performance evaluation of maglev train suspension system.
{"title":"Study on levitation control performance assessment of maglev train based on minimum entropy","authors":"Tao Wen, Yaoyao Zhang, Zhiqiang Long","doi":"10.1177/09544097231213895","DOIUrl":"https://doi.org/10.1177/09544097231213895","url":null,"abstract":"In order to meet the strict requirements of the reliability and safety of the commercial operation of the maglev train, it is necessary to carry out the control performance evaluation of the suspension system. However, at present, variance is often used as the evaluation index of control system. This method cannot get accurate performance evaluation results when the system is affected by non-Gaussian disturbance. Therefore, aiming at the non-Gaussian control performance evaluation of maglev train suspension system, a control performance evaluation method of maglev train suspension system based on minimum entropy is proposed in this paper. In view of the non-Gaussian characteristics in the operation data of maglev train suspension system, this paper introduces the feedback invariant entropy of non-Gaussian system, and then realizes the evaluation and analysis of the control performance of maglev train suspension system based on the minimum entropy criterion. Finally, combined with the evaluation and analysis of the operation data of Changsha medium and low-speed maglev train, this paper verifies the effectiveness and accuracy of the proposed performance evaluation method for the control performance evaluation of maglev train suspension system.","PeriodicalId":54567,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part F-Journal of Rail and Rapid Transit","volume":"190 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135479772","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}
Pub Date : 2023-11-04DOI: 10.1177/09544097231195656
Susanne Reetz, Thorsten Neumann, Gerrit Schrijver, Arnout van den Berg, Douwe Buursma
To meet the increasing demands for availability at reasonable cost, operators and maintainers of railway point machines are constantly looking for innovative techniques for switch condition monitoring and prediction. This includes automated fault root cause diagnosis based on measurement data (such as motor current curves) and other information. However, large, comprehensive sets of labeled data suitable for standard machine learning are not yet available. Existing data-driven approaches focus only on the differentiation of a few major fault categories at the level of the measurement data (i.e., the “fault symptoms”). There is great potential in hybrid models that use expert knowledge in combination with multiple sources of information to automatically identify failure causes at a much more detailed level. This paper discusses a Bayesian network diagnostic model for determining the root causes of faults in point machines, based on expert knowledge and few labeled data examples from the Netherlands. Human-interpretable current curve features and other information sources (e.g., past maintenance actions) are used as evidence. The result of the model is a ranking of the most likely failure causes with associated probabilities in terms of fuzzy multi-label classification, which is directly aimed at providing decision support to maintenance engineers. The validity and limitations of the model are demonstrated by a scenario-based evaluation and a brief analysis using information theoretic measures. We present the information sources used, the detailed development process and the analysis methodology. This article is intended to be a guide to developing similar models for various complex technical assets.
{"title":"Expert system based fault diagnosis for railway point machines","authors":"Susanne Reetz, Thorsten Neumann, Gerrit Schrijver, Arnout van den Berg, Douwe Buursma","doi":"10.1177/09544097231195656","DOIUrl":"https://doi.org/10.1177/09544097231195656","url":null,"abstract":"To meet the increasing demands for availability at reasonable cost, operators and maintainers of railway point machines are constantly looking for innovative techniques for switch condition monitoring and prediction. This includes automated fault root cause diagnosis based on measurement data (such as motor current curves) and other information. However, large, comprehensive sets of labeled data suitable for standard machine learning are not yet available. Existing data-driven approaches focus only on the differentiation of a few major fault categories at the level of the measurement data (i.e., the “fault symptoms”). There is great potential in hybrid models that use expert knowledge in combination with multiple sources of information to automatically identify failure causes at a much more detailed level. This paper discusses a Bayesian network diagnostic model for determining the root causes of faults in point machines, based on expert knowledge and few labeled data examples from the Netherlands. Human-interpretable current curve features and other information sources (e.g., past maintenance actions) are used as evidence. The result of the model is a ranking of the most likely failure causes with associated probabilities in terms of fuzzy multi-label classification, which is directly aimed at providing decision support to maintenance engineers. The validity and limitations of the model are demonstrated by a scenario-based evaluation and a brief analysis using information theoretic measures. We present the information sources used, the detailed development process and the analysis methodology. This article is intended to be a guide to developing similar models for various complex technical assets.","PeriodicalId":54567,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part F-Journal of Rail and Rapid Transit","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135774499","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}
Pub Date : 2023-11-02DOI: 10.1177/09544097231194679
Jun Wang, Zhao-Hui Lu, Xuan-Yi Zhang, Yan-Gang Zhao
The interface damage is considered to be one of the main diseases of China Railway Track System (CRTS) Ⅱ slab ballastless track, which will affect the long-term performance of the track structure and safety operation of high-speed trains. This study aims to reveal the interface damage mechanism between the track slab and the cement asphalt (CA) mortar layer of CRTS Ⅱ slab ballastless track, under different combinations of temperature actions and initial gap damage. A three-dimensional finite element model of CRTS Ⅱ slab ballastless track was established, in which a cohesive constitutive model was incorporated to simulate the interaction behavior of the interface. The interface damage evolution under different temperature actions and initial gap damage was analyzed. The analysis results show that: (1) Overall temperature has a more obvious effect on interface damage compared with temperature gradient, and the greater the overall temperature drops, the lower the decrease of interface damage will be; (2) When initial gap damage occur at the slab end, the growth rate of interface damage under temperature gradient is greater than that under overall temperature; The interface will begin to delaminate when the overall temperature drop reaches −50°C and the gap length becomes greater than one fastener spacing; and (3) When initial gap damage occur at the slab edge, the influence of overall temperature on interface damage is greater than that of temperature gradient; The interface gap damage reaches level II (according to TG/GW 115-2012) at the slab edge under the combination of −50°C and −50°C/m, while the slab center interface is unlikely to be damaged under negative temperature.
{"title":"Interface behaviour analysis of China railway track system Ⅱ slab ballastless track under temperature action and initial gap damage","authors":"Jun Wang, Zhao-Hui Lu, Xuan-Yi Zhang, Yan-Gang Zhao","doi":"10.1177/09544097231194679","DOIUrl":"https://doi.org/10.1177/09544097231194679","url":null,"abstract":"The interface damage is considered to be one of the main diseases of China Railway Track System (CRTS) Ⅱ slab ballastless track, which will affect the long-term performance of the track structure and safety operation of high-speed trains. This study aims to reveal the interface damage mechanism between the track slab and the cement asphalt (CA) mortar layer of CRTS Ⅱ slab ballastless track, under different combinations of temperature actions and initial gap damage. A three-dimensional finite element model of CRTS Ⅱ slab ballastless track was established, in which a cohesive constitutive model was incorporated to simulate the interaction behavior of the interface. The interface damage evolution under different temperature actions and initial gap damage was analyzed. The analysis results show that: (1) Overall temperature has a more obvious effect on interface damage compared with temperature gradient, and the greater the overall temperature drops, the lower the decrease of interface damage will be; (2) When initial gap damage occur at the slab end, the growth rate of interface damage under temperature gradient is greater than that under overall temperature; The interface will begin to delaminate when the overall temperature drop reaches −50°C and the gap length becomes greater than one fastener spacing; and (3) When initial gap damage occur at the slab edge, the influence of overall temperature on interface damage is greater than that of temperature gradient; The interface gap damage reaches level II (according to TG/GW 115-2012) at the slab edge under the combination of −50°C and −50°C/m, while the slab center interface is unlikely to be damaged under negative temperature.","PeriodicalId":54567,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part F-Journal of Rail and Rapid Transit","volume":"131 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135933054","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}
Pub Date : 2023-10-28DOI: 10.1177/09544097231209483
Ben White, Roger Lewis, David Fletcher, Tim Harrison, Peter Hubbard, Christopher Ward
Friction forces (often referred to as adhesion or traction forces) at the wheel/rail interface can vary dramatically due to changing environmental and contact conditions. The causes of this variance are partially documented, but it is not fully understood. Friction forces affect wheel and rail wear, traction energy usage, vehicle dynamics and safety through braking performance. A range of different portable railhead tribometers are used in the field to measure friction, but until recently have been limited in their performance, being unable to measure low friction situations or have made use of an unrealistic contact geometry. Recent developments have improved this situation but there is currently a lack of published field data which is required for validation, benchmarking and comparison between other studies and test rigs, as well as for input to multi-body dynamics simulations of railway vehicles. Friction studies in general are often undertaken for a specific period of time or under closely controlled conditions which makes it difficult to understand the true range of conditions occurring in the wheel/rail contact. In this paper an extensive dataset of railhead measurements is presented, using two types of measuring devices and three railhead conditions throughout a 4-week test period. Confidence in tribometer results was gained by comparing between established laboratory friction test rigs and methodologies. The results provide an insight into the friction variance and transient conditions that would occur on the railhead during operational use.
{"title":"Rail-wheel friction quantification and its variability under lab and field trial conditions","authors":"Ben White, Roger Lewis, David Fletcher, Tim Harrison, Peter Hubbard, Christopher Ward","doi":"10.1177/09544097231209483","DOIUrl":"https://doi.org/10.1177/09544097231209483","url":null,"abstract":"Friction forces (often referred to as adhesion or traction forces) at the wheel/rail interface can vary dramatically due to changing environmental and contact conditions. The causes of this variance are partially documented, but it is not fully understood. Friction forces affect wheel and rail wear, traction energy usage, vehicle dynamics and safety through braking performance. A range of different portable railhead tribometers are used in the field to measure friction, but until recently have been limited in their performance, being unable to measure low friction situations or have made use of an unrealistic contact geometry. Recent developments have improved this situation but there is currently a lack of published field data which is required for validation, benchmarking and comparison between other studies and test rigs, as well as for input to multi-body dynamics simulations of railway vehicles. Friction studies in general are often undertaken for a specific period of time or under closely controlled conditions which makes it difficult to understand the true range of conditions occurring in the wheel/rail contact. In this paper an extensive dataset of railhead measurements is presented, using two types of measuring devices and three railhead conditions throughout a 4-week test period. Confidence in tribometer results was gained by comparing between established laboratory friction test rigs and methodologies. The results provide an insight into the friction variance and transient conditions that would occur on the railhead during operational use.","PeriodicalId":54567,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part F-Journal of Rail and Rapid Transit","volume":"14 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136233570","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}
Pub Date : 2023-10-18DOI: 10.1177/09544097231208334
Jiawei Wang, David Thompson, Giacomo Squicciarini
The dynamic behaviour of railway track plays an important role in the generation of rolling noise as well as the development of rail corrugation. A semi-analytical model is presented that includes vertical, lateral and axial dynamics and takes account of the discrete supports provided by the sleepers. The rail is represented by a semi-analytical beam model that includes vertical and lateral bending, extension and torsion, with warping and shear-centre eccentricity. A receptance-coupling method is used to couple the rails, through damped springs that represent the rail pads, with a finite number of flexible sleepers that are in turn supported on an elastic foundation. The model also accounts for the coupling between the two rails through the sleepers. Results are presented in terms of the point mobilities in different directions, including the vertical-lateral cross mobility, as well as the track decay rates, and the results are validated by comparison with measurements. The inclusion of torsion and warping is shown to have a significant effect on the lateral rail mobility, leading to better agreement with the measured results. The response on one rail due to excitation on the other rail is also explored and the results agree well with the measurements. It is found that the coupling between the two rails has only a limited effect on the resultant track response.
{"title":"A semi-analytical model of a discretely supported railway track","authors":"Jiawei Wang, David Thompson, Giacomo Squicciarini","doi":"10.1177/09544097231208334","DOIUrl":"https://doi.org/10.1177/09544097231208334","url":null,"abstract":"The dynamic behaviour of railway track plays an important role in the generation of rolling noise as well as the development of rail corrugation. A semi-analytical model is presented that includes vertical, lateral and axial dynamics and takes account of the discrete supports provided by the sleepers. The rail is represented by a semi-analytical beam model that includes vertical and lateral bending, extension and torsion, with warping and shear-centre eccentricity. A receptance-coupling method is used to couple the rails, through damped springs that represent the rail pads, with a finite number of flexible sleepers that are in turn supported on an elastic foundation. The model also accounts for the coupling between the two rails through the sleepers. Results are presented in terms of the point mobilities in different directions, including the vertical-lateral cross mobility, as well as the track decay rates, and the results are validated by comparison with measurements. The inclusion of torsion and warping is shown to have a significant effect on the lateral rail mobility, leading to better agreement with the measured results. The response on one rail due to excitation on the other rail is also explored and the results agree well with the measurements. It is found that the coupling between the two rails has only a limited effect on the resultant track response.","PeriodicalId":54567,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part F-Journal of Rail and Rapid Transit","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135825241","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}
Pub Date : 2023-10-14DOI: 10.1177/09544097231206216
Heng Zhang, Liang Ling, Wanming Zhai, Kaiyun Wang
The running safety of trains subjected to strong crosswinds has become a major concern for the high-speed railways passing through complicated mountain areas. This paper reports an active secondary suspension system to improve the operation stability and running safety of high-speed trains under strong crosswind. The goal of the active suspension system is to regulate the lateral, yaw, and roll motion attitudes of high-speed train carbody, in which a controller is designed by combining with a disturbance observer and the sliding mode control method. To further verify the proposed active suspension strategy, a crosswind-vehicle-track coupled dynamics model is established, where the unsteady aerodynamic loads and random track irregularity excitations are considered. The results show that the proposed active suspension system has the efficient potential to regulate the carbody motion attitudes and enhance the anti-rolling performance of high-speed trains. In comparison to a quasi-static control strategy of active suspension, the use of the proposed active suspension system has led to a significant reduction in both wheel-load reduction ratios and derailment risks of high-speed trains.
{"title":"An active suspension system for enhancing running safety of high-speed trains under strong crosswind","authors":"Heng Zhang, Liang Ling, Wanming Zhai, Kaiyun Wang","doi":"10.1177/09544097231206216","DOIUrl":"https://doi.org/10.1177/09544097231206216","url":null,"abstract":"The running safety of trains subjected to strong crosswinds has become a major concern for the high-speed railways passing through complicated mountain areas. This paper reports an active secondary suspension system to improve the operation stability and running safety of high-speed trains under strong crosswind. The goal of the active suspension system is to regulate the lateral, yaw, and roll motion attitudes of high-speed train carbody, in which a controller is designed by combining with a disturbance observer and the sliding mode control method. To further verify the proposed active suspension strategy, a crosswind-vehicle-track coupled dynamics model is established, where the unsteady aerodynamic loads and random track irregularity excitations are considered. The results show that the proposed active suspension system has the efficient potential to regulate the carbody motion attitudes and enhance the anti-rolling performance of high-speed trains. In comparison to a quasi-static control strategy of active suspension, the use of the proposed active suspension system has led to a significant reduction in both wheel-load reduction ratios and derailment risks of high-speed trains.","PeriodicalId":54567,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part F-Journal of Rail and Rapid Transit","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135804327","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}
Dynamic characteristics and reliability of elastomeric pads are dominant components in the design methodology to satisfy the performance parameters under dynamic operations. The fatigue life of rubber pads fitted with elastomeric pads mainly depends upon elastomers; natural rubber, chloroprene, nitrile butadiene, silicon compounds, etc., additives, accelerators, activators, fillers, anti-degradants, and manufacturing processes. The performance of the elastomeric pad is evaluated based on service operation, simulation, and laboratory testing. New and failed elastomeric (EM) pads have been examined in the Indian Rubber Manufacturer’s Research Association IRMRA laboratory for detailed failure analysis of existing EM pads. Further, chemical and physical properties are also evaluated in M&C (Metallurgical and Chemical) and Testing Directorate of Research Designs and Standards Organization (RDSO), labs respectively. The fatigue life of the EM pad is estimated based on the results extracted from the Finite Element (FE) analysis of the EM pad. An attempt is made to modify the design of the EM pad by considering the results of detailed field trials, lab testing, and FE analysis. The modified design satisfies the dynamic characteristic during FE (Structural and Thermal) analysis and lab testing.
{"title":"Reliability analysis based on load spectrum: A structural improvement of Indian Railways three-piece freight bogie elastomeric pad","authors":"Sanjay Shukla, Manish Thaplyal, Abhishek Kumar Gautam, Satyam Kumar Mall","doi":"10.1177/09544097231204389","DOIUrl":"https://doi.org/10.1177/09544097231204389","url":null,"abstract":"Dynamic characteristics and reliability of elastomeric pads are dominant components in the design methodology to satisfy the performance parameters under dynamic operations. The fatigue life of rubber pads fitted with elastomeric pads mainly depends upon elastomers; natural rubber, chloroprene, nitrile butadiene, silicon compounds, etc., additives, accelerators, activators, fillers, anti-degradants, and manufacturing processes. The performance of the elastomeric pad is evaluated based on service operation, simulation, and laboratory testing. New and failed elastomeric (EM) pads have been examined in the Indian Rubber Manufacturer’s Research Association IRMRA laboratory for detailed failure analysis of existing EM pads. Further, chemical and physical properties are also evaluated in M&C (Metallurgical and Chemical) and Testing Directorate of Research Designs and Standards Organization (RDSO), labs respectively. The fatigue life of the EM pad is estimated based on the results extracted from the Finite Element (FE) analysis of the EM pad. An attempt is made to modify the design of the EM pad by considering the results of detailed field trials, lab testing, and FE analysis. The modified design satisfies the dynamic characteristic during FE (Structural and Thermal) analysis and lab testing.","PeriodicalId":54567,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part F-Journal of Rail and Rapid Transit","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134975321","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}
Pub Date : 2023-09-29DOI: 10.1177/09544097231203275
Kenza Soufiane, Allan M. Zarembski, Joseph W. Palese
Cross-ties represent a key infrastructure asset of the railroad industry. Recent research has shown that the cross-tie life is not only affected by the traditionally defined load and track design parameters but also by support condition, and in particular, support condition as represented by the condition of adjacent cross-ties. This paper builds upon the recent research and is focused on predicting a cross-tie’s future condition as a function of the changing condition of the surrounding cross-ties. As accurate cross-tie condition information becomes available from automated inspection systems, this data allows for the development of a theoretical framework for predicting cross-tie degradation and corresponding cross-tie life. This theoretical framework allows for the modeling of the interactions between adjacent cross-ties as a complex and dynamic system. Thus, the objective of this paper is to develop a model that uses theory guided machine learning framework as supported by well-defined railroad engineering relationships, such as the Beam on Elastic Foundation theory, to forecast the cross-tie condition as a function of its adjacent cross-ties and their corresponding degradation rates. The resulting model outperformed a more conventional traditional neural network model. The theory guided machine learning model showed very good correlation with actual data exhibiting an R 2 of 88.6% and an a 20 -index of 91% suggesting that the incorporation of domain knowledge into the machine learning model leads to demonstrably better cross-tie life prediction results.
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