The fasteners employed in the railway tracks are susceptible to defects arising from their intricate composition.Foreign objects are frequently observed on the track bed in an open environment.These two types of defec...The fasteners employed in the railway tracks are susceptible to defects arising from their intricate composition.Foreign objects are frequently observed on the track bed in an open environment.These two types of defects pose potential threats to high-speed trains,thus necessitating timely and accurate track inspection.The majority of extant automatic inspection methods are predicated on the utilization of single visible light data,and the efficacy of the algorithmic processes is influenced by complex environments.Furthermore,due to the single information dimension,the detection accuracy of defects in similar,occluded,and small object categories is low.To address the aforementioned issues,this paper proposes a track defect detectionmethod based on dynamicmulti-modal fusion and challenging object enhanced perception.First,in light of the variances in the representation dimensions ofmultimodal information,this paper proposes a dynamic weighted multi-modal feature fusion module.The fused multi-modal features are assigned weights,and thenmultiplied with the extracted single-modal features atmultiple levels,achieving adaptive adjustment of the response degree of fusion features.Second,a novel stepwise multi-scale convolution feature aggregation module is proposed for challenging objects.The proposed method employs depth separable convolution and cross-scale aggregation operations of different receptive fields to enhance feature extraction and reuse,thereby reducing the degree of progressive loss of effective information.The experimental results demonstrate the efficacy of the proposed method in comparison to eight established methods,encompassing both single-modal and multi-modal methods,as evidenced by the extensive findings within the constructed RGBD dataset.展开更多
As an important component of load transfer,various fatigue damages occur in the track as the rail service life and train traffic increase gradually,such as rail corrugation,rail joint damage,uneven thermite welds,rail ...As an important component of load transfer,various fatigue damages occur in the track as the rail service life and train traffic increase gradually,such as rail corrugation,rail joint damage,uneven thermite welds,rail squats fas-tener defects,etc.Real-time recognition of track defects plays a vital role in ensuring the safe and stable operation of rail transit.In this paper,an intelligent and innovative method is proposed to detect the track defects by using axle-box vibration acceleration and deep learning network,and the coexistence of the above-mentioned typical track defects in the track system is considered.Firstly,the dynamic relationship between the track defects(using the example of the fastening defects)and the axle-box vibration acceleration(ABVA)is investigated using the dynamic vehicle-track model.Then,a simulation model for the coupled dynamics of the vehicle and track with different track defects is established,and the wavelet power spectrum(WPS)analysis is performed for the vibra-tion acceleration signals of the axle box to extract the characteristic response.Lastly,using wavelet spectrum photos as input,an automatic detection technique based on the deep convolution neural network(DCNN)is sug-gested to realize the real-time intelligent detection and identification of various track problems.Thefindings demonstrate that the suggested approach achieves a 96.72%classification accuracy.展开更多
Speckle tracking imaging （STI） was employed to investigate the effect of right ventricular （RV） volume and pressure overload on left ventricular （LV） rotation and twist in 35 patients with atrial septal defect ...Speckle tracking imaging （STI） was employed to investigate the effect of right ventricular （RV） volume and pressure overload on left ventricular （LV） rotation and twist in 35 patients with atrial septal defect （ASD）, 18 of which with pulmonary hypertension, and 21 healthy subjects serving as controls. The peak rotations of 6 segments at the basal and apical short-axises and the average peak rotation and interval time of the 6 segments in the opposite direction during early systolic phase were measured respectively. LV twist versus time profile was drawn and the peak twist and time to peak twist were calculated. LV ejection fraction （EF） was measured by Biplane Simpson. Compared to ASD patients without pulmonary hypertension and healthy subjects, the peak rotations of posterior, inferior and postsept walls at the basal level were lower （P〈0.05）, and the average counterclockwise peak rotation of 6 segments at the basal level during early systolic phase was higher （P〈0.05）, and the average interval time was delayed （P〈0.05）. LV peak twist was also lower （P〈0.05）, and had a significant negative correlation with pulmonary arterial systolic pressure （r=-0.57, P=0.001）. No significant differences were found in LVEF among the three groups. It was suggested that although RV volume overload due to ASD has no significant effects on LV rotation and twist, LV peak twist is lower in ASD patients with pulmonary hypertension. Thus LV twist may serve as a new indicator of the presence of pulmonary hypertension in ASD patients.展开更多
Formation of nuclear tracks in solids has been described as a thermal spike as well as a Coulomb explo- sion spike.Here,formation of nuclear tracks is described as a compound spike including partial roles of both ther...Formation of nuclear tracks in solids has been described as a thermal spike as well as a Coulomb explo- sion spike.Here,formation of nuclear tracks is described as a compound spike including partial roles of both thermal and Coulomb explosion spikes in track formation.Fractional roles of both spikes depend on atomic and electronic structure of a track detector and deposited energy density in the track detector by the incident charged particle.Be- havior of the cylindrical zone along the path of the incident particle is described mathematically in terms of bulk and individual atomic flow or movement.Defect structure of the latent nuclear tracks is described and conditions of con- tinuity and discontinuity of latent tracks are evaluated and discussed.This paper includes mathematical description, analysis and evaluation of the nuclear track formation issue in the light of published experimental and theoretical re- sults,which are useful for users of nuclear track detection technique and researchers involved in ion beam induced materials modification and ions implantation in semiconductors.展开更多
The feasibility of monitoring the dipped rail joint defects has been theoretically investigated by simulating a locomotive-mounted acceleration system negoti- ating several types of dipped rail defects. Initially, a c...The feasibility of monitoring the dipped rail joint defects has been theoretically investigated by simulating a locomotive-mounted acceleration system negoti- ating several types of dipped rail defects. Initially, a comprehensive locomotive-track model was developed using the multi-body dynamics approach. In this model, the locomotive car-body, bogie frames, wheelsets and driving motors are considered as rigid bodies; track modelling was also taken into account. A quantitative relationship between the characteristics （peak-peak values） of the axle box accelerations and the rail defects was determined through simulations. Therefore, the proposed approach, which combines defect analysis and comparisons with theoretical results, will enhance the ability for long-term monitoring and assessment of track systems and provides more informed preventative track maintenance strategies.展开更多
基金funded by Beijing Natural Science Foundation,grant number L241078.
文摘The fasteners employed in the railway tracks are susceptible to defects arising from their intricate composition.Foreign objects are frequently observed on the track bed in an open environment.These two types of defects pose potential threats to high-speed trains,thus necessitating timely and accurate track inspection.The majority of extant automatic inspection methods are predicated on the utilization of single visible light data,and the efficacy of the algorithmic processes is influenced by complex environments.Furthermore,due to the single information dimension,the detection accuracy of defects in similar,occluded,and small object categories is low.To address the aforementioned issues,this paper proposes a track defect detectionmethod based on dynamicmulti-modal fusion and challenging object enhanced perception.First,in light of the variances in the representation dimensions ofmultimodal information,this paper proposes a dynamic weighted multi-modal feature fusion module.The fused multi-modal features are assigned weights,and thenmultiplied with the extracted single-modal features atmultiple levels,achieving adaptive adjustment of the response degree of fusion features.Second,a novel stepwise multi-scale convolution feature aggregation module is proposed for challenging objects.The proposed method employs depth separable convolution and cross-scale aggregation operations of different receptive fields to enhance feature extraction and reuse,thereby reducing the degree of progressive loss of effective information.The experimental results demonstrate the efficacy of the proposed method in comparison to eight established methods,encompassing both single-modal and multi-modal methods,as evidenced by the extensive findings within the constructed RGBD dataset.
基金supported by the Doctoral Fund Project(Grant No.X22003Z).
文摘As an important component of load transfer,various fatigue damages occur in the track as the rail service life and train traffic increase gradually,such as rail corrugation,rail joint damage,uneven thermite welds,rail squats fas-tener defects,etc.Real-time recognition of track defects plays a vital role in ensuring the safe and stable operation of rail transit.In this paper,an intelligent and innovative method is proposed to detect the track defects by using axle-box vibration acceleration and deep learning network,and the coexistence of the above-mentioned typical track defects in the track system is considered.Firstly,the dynamic relationship between the track defects(using the example of the fastening defects)and the axle-box vibration acceleration(ABVA)is investigated using the dynamic vehicle-track model.Then,a simulation model for the coupled dynamics of the vehicle and track with different track defects is established,and the wavelet power spectrum(WPS)analysis is performed for the vibra-tion acceleration signals of the axle box to extract the characteristic response.Lastly,using wavelet spectrum photos as input,an automatic detection technique based on the deep convolution neural network(DCNN)is sug-gested to realize the real-time intelligent detection and identification of various track problems.Thefindings demonstrate that the suggested approach achieves a 96.72%classification accuracy.
文摘Speckle tracking imaging （STI） was employed to investigate the effect of right ventricular （RV） volume and pressure overload on left ventricular （LV） rotation and twist in 35 patients with atrial septal defect （ASD）, 18 of which with pulmonary hypertension, and 21 healthy subjects serving as controls. The peak rotations of 6 segments at the basal and apical short-axises and the average peak rotation and interval time of the 6 segments in the opposite direction during early systolic phase were measured respectively. LV twist versus time profile was drawn and the peak twist and time to peak twist were calculated. LV ejection fraction （EF） was measured by Biplane Simpson. Compared to ASD patients without pulmonary hypertension and healthy subjects, the peak rotations of posterior, inferior and postsept walls at the basal level were lower （P〈0.05）, and the average counterclockwise peak rotation of 6 segments at the basal level during early systolic phase was higher （P〈0.05）, and the average interval time was delayed （P〈0.05）. LV peak twist was also lower （P〈0.05）, and had a significant negative correlation with pulmonary arterial systolic pressure （r=-0.57, P=0.001）. No significant differences were found in LVEF among the three groups. It was suggested that although RV volume overload due to ASD has no significant effects on LV rotation and twist, LV peak twist is lower in ASD patients with pulmonary hypertension. Thus LV twist may serve as a new indicator of the presence of pulmonary hypertension in ASD patients.
文摘Formation of nuclear tracks in solids has been described as a thermal spike as well as a Coulomb explo- sion spike.Here,formation of nuclear tracks is described as a compound spike including partial roles of both thermal and Coulomb explosion spikes in track formation.Fractional roles of both spikes depend on atomic and electronic structure of a track detector and deposited energy density in the track detector by the incident charged particle.Be- havior of the cylindrical zone along the path of the incident particle is described mathematically in terms of bulk and individual atomic flow or movement.Defect structure of the latent nuclear tracks is described and conditions of con- tinuity and discontinuity of latent tracks are evaluated and discussed.This paper includes mathematical description, analysis and evaluation of the nuclear track formation issue in the light of published experimental and theoretical re- sults,which are useful for users of nuclear track detection technique and researchers involved in ion beam induced materials modification and ions implantation in semiconductors.
基金the support of the Centre for Railway Engineering, Central Queensland Universitythe support from State Key Laboratory of Traction Power, Southwest Jiaotong University in the Open Projects: TPL1504, ‘Study on heavy haul train and coupler system dynamics’
文摘The feasibility of monitoring the dipped rail joint defects has been theoretically investigated by simulating a locomotive-mounted acceleration system negoti- ating several types of dipped rail defects. Initially, a comprehensive locomotive-track model was developed using the multi-body dynamics approach. In this model, the locomotive car-body, bogie frames, wheelsets and driving motors are considered as rigid bodies; track modelling was also taken into account. A quantitative relationship between the characteristics （peak-peak values） of the axle box accelerations and the rail defects was determined through simulations. Therefore, the proposed approach, which combines defect analysis and comparisons with theoretical results, will enhance the ability for long-term monitoring and assessment of track systems and provides more informed preventative track maintenance strategies.
