The repetitive transient impulses are typical symptoms of rolling bearing faults. The indicator of second-order cyclostationarity (ICS2) based blind deconvolution (CYCBD) maximizing the cyclostationary behavior of the excitation source proves to be an effective method for enhancing the periodic cyclostationarity component caused by bearing defect. However, the deviation of the fault characteristic frequenc–a common phenomenon easily caused by roller creep or measurement systems, etc., can lead to the collapse of this method in practical applications. Additionally, this method is prone to induce the generation of pseudo-cyclostationary components under the guidance of an inappropriate cyclic frequency. Thus, this work proposes a candidate fault frequencies (CFFs) based blind deconvolution, abbreviated as CFFsBD, for fault feature enhancement of bearings. This idea comes from the concept of CFFs–a collection of frequencies most likely to be associated with bearing fault, that can be identified by mining the local time-frequency features of the signal to be analyzed. A new indicator constructed by using CFFs to replace the cycle frequencies in ICS2 is utilized as the criterion to guide the solution of the deconvolution filter. This new indicator is a generalized version of ICS2, and thus CYCBD can be considered a special case of the proposed CFFsBD. The performance of the CFFsBD is demonstrated by the analysis of simulated and experimental signals of faulty bearings. The results highlight the robustness and stability of the proposed CFFsBD in extracting fault-induced cyclostationary symptoms.

The Pantograph-Catenary System (PCS) is a critical component of railway vehicles, and its performance directly affects current collection quality. The arc rate serves as an essential measurement indicator for monitoring PCS state. However, in complex railway environments—where arc sizes and shapes can vary significantly and are further influenced by factors such as reflected light, glare, and adverse weather—traditional arc detection methods are easily affected by unstable current collection and power fluctuations, resulting in increased false detection rates and reduced measurement accuracy. Deep learning methods, while promising, also face limitations when dealing with such diverse arc morphologies and strong external interference. To address these challenges, this paper proposes a Multi-Modal Imitation Learning-based Arc Detection Network (MILADNet). First, the measurement system fuses infrared and visible-light image features to enhance arc feature extraction in scenarios with strong glare or reflective interference, thereby mitigating false alarms caused by relying on a single sensor. Second, to overcome the lack of information on small arcs, an online imitation learning framework is introduced to improve the system’s detection sensitivity for small arcs. Finally, to address data bias arising from uneven arc distributions, an unsupervised transferable representation learning method is employed to reduce dependence on labeled data and enhance model generalization. Experimental results show that MILADNet exhibits outstanding detection performance for arcs of various sizes and in complex environments, demonstrating both high efficiency and accuracy during measurement and data processing. Beyond improving the precision and reliability of arc detection, this method offers a novel solution for the instrumentation and measurement field and shows significant potential for condition monitoring and anomaly detection in railway systems.

A complete track-vehicle-pantograph-catenary (TVPC) coupling dynamics model is presented and several elaborate simulation cases are set to analyse the effect of vehicle body vibration on the pantograph-catenary system (PACS). The catenary is described by a finite-element model while the pantograph, vehicle and track are described by a multi-body model. In addition, different track irregularities are introduced to mimic real track conditions. Through Pearson correlation coefficient and spectrum analysis, the key kinematics parameters are identified, which influence both roof vibration and current collection quality. Frequency response of the TVPC shows that the forces between wheel and rail caused by track irregularities are transmitted to the bogie frame and vehicle body through primary and secondary suspension system, and finally to the PACS. Applying a series of excitation to the pantograph base frame and simulating the interaction between the PACS, the mechanism that the vehicle roof vibration affecting the PACS interaction is verified. Specifically, characteristic frequencies of the vertical displacement of the roof, which are related to the antiresonance and anti-phaseresponse of the pantograph, together with their corresponding amplitudes can be utilised to assess the influence of the body vibration caused by track irregularity on the current collection quality of PACS.

In order to investigate the damping characteristics of railway-overhead-wire systems, we propose herein an approach based on the continuous wavelet transform (CWT) and two existing formulas concerning Rayleigh damping coefficients (RDCs). In the proposed process, the displacement histories of a real catenary are first obtained by using a set of noncontact photogrammetric devices, following which an exclusive catenary damping ratio related to the first dominant modal component in the catenary response is identified through a complex Morlet CWT. Thereafter, iterative finite-element analysis is conducted to find the optimal RDCs, which involves using two related formulas and the similarity between the catenary displacements obtained by simulation and experimentation. The results of our study demonstrate that this combined approach is constructive, especially for structures with closely spaced modes, such as catenaries. For the case studied herein, the catenary modal damping ratio at 1.19 Hz is approximately 1%, and the mass and stiffness proportional Rayleigh damping coefficients are approximately 0.02845 and 0.00274, respectively.

To study the railway overhead wire's flexural wave motion that significantly affects the quality of current collection between pantograph and catenary, dynamic responses of a real catenary excited by different excitations are measured and analyzed by using a set of noncontact photogrammetric devices together with the finite-element simulation. Based on the measured and simulated results, the wave motion along the contact wire is investigated and some findings have been obtained. First, it is the first two dominant modal components in the catenary displacement responses that induce a beat phenomenon, and this beat phenomenon is increasingly obvious near the registration arm. Moreover, with the simulated displacement contour, catenary local vibration characteristics affected by the travelling wave can be clearly interpreted. Furthermore, the wave group velocity of contact wire in catenary is determined and verified to be approximately 139.18 m/s; in addition, treating the contact wire in the overhead wire system as an ideal string or a tensioned Euler beam will overestimate the corresponding group velocity with a relative error by about 13.21%.

Ice coating on overhead contact system (OCS) will affect the sliding of pantograph, and arc discharge phenomena will occur between pantograph and catenary, which will threaten the normal operation of train. This paper presents a comprehensive model to analyze the dynamics of icing on pantograph-catenary (PAC) system. The finite element model (FEM) is used for building the catenary, the pantograph is modeled as lumped-mass model, and the ice section of the cable is fan-shaped. The increased density method, uniform load method, and combinatorial material method of icing are used to analyze the icing problem of PAC system. The similarities and differences between the three simulation methods are compared. The influence of the ice thickness on the current collection quality between the pantograph and catenary at the different operating speeds calculated by the three methods is basically the same, which fully illustrates the effectiveness of the simulated ice coating method. In comparison, the combinatorial material method is a more reasonable method for calculating the icing of catenary systems. The research also shows that the influence of icing on the current collection quality of PAC system is different when the train runs at different speeds. Specifically, as the speed of trains increases, the effect of ice thickness on the current collection quality of the PAC system is becoming increasingly apparent.