Suppression of Railway Catenary Galloping Based on Structural Parameters' Optimization.

Railway catenary galloping, induced by aerodynamic instability, poses a significant threat by disrupting the electric current connection through sliding contact with the contact wire. This disruption leads to prolonged rail service interruptions and damage to the catenary's suspension components. This paper delves into the exploration of optimizing the catenary system's structure to alleviate galloping responses, addressing crucial parameters such as span length, stagger dropper distribution, and tension levels. Employing a finite element model, the study conducts simulations to analyze the dynamic response of catenary galloping, manipulating structural parameters within specified ranges. To ensure accurate and comprehensive exploration, the Sobol sequence is utilized to generate low-discrepancy, quasi-random, and super-uniform distribution sequences for the high-dimensional parameter inputs. Subsequent to the simulation phase, a genetic algorithm based on neural networks is employed to identify optimal parameter settings for suppressing catenary galloping, taking into account various constraints. The results gleaned from this investigation affirm that adjusting structural parameters can effectively diminish the galloping amplitude of the railway catenary. The most impactful strategy involves augmenting tension and reducing span length. Moreover, even when tension and span length are fixed, adjusting other parameters demonstrates efficacy in reducing galloping amplitudes. The adjustment of messenger-wire tension, dropper distribution, and stagger can achieve a 22.69% reduction in the maximum vertical galloping amplitude. Notably, maintaining a moderate stagger value and a short steady arm-dropper distance is recommended to achieve the minimum galloping amplitude. This research contributes valuable insights into the optimization of railway catenary systems, offering practical solutions to mitigate galloping-related challenges and enhance overall system reliability.

Modelling and Analysis of Expansion Joints' Effect on Dynamic Performance of Railway Rigid Overhead System.

This study focuses on developing a comprehensive model of a rigid overhead system, which includes essential components such as the suspension structure, positioning clamp, and expansion joint. The modelling approach utilizes finite element theory and beam elements to accurately represent the displacement, stiffness, and mass characteristics of the system. The models also incorporate the suspension structure and positioning line clamp, which play crucial roles in suspending and positioning the busbar. Various suspension structures and positioning line clamps are evaluated based on their dynamic characteristics. The expansion joint, responsible for connecting different anchor sections of the rigid overhead system, undergoes a detailed analysis. Different assembly scenarios, including ideal and deflected assembly conditions, are considered. To simulate the dynamic behaviour of the expansion joint, additional beams are introduced into the system model. The primary finding of the analysis is that the maximum stresses observed in the constructed expansion joint model, under different temperature conditions and normal/deflected assembly conditions, remain within the permissible stress limits of the material. This indicates a high level of safety. However, certain areas exhibit stress concentration, particularly at the sliding block B and sliding rod A positions. This stress concentration is primarily attributed to the unique assembly form of the expansion joint. To improve stress distribution and enhance service reliability, the analysis suggests optimizing the installation deflection angle and geometric design of the expansion joint. Furthermore, the concentrated mass at the expansion joint significantly impacts the current collection quality of the pantograph-overhead system. Mitigating this negative impact can be achieved by reducing the mass of the expansion joint.

A Siamese Network-Based Non-Contact Measurement Method for Railway Catenary Uplift Trained in a Free Vibration Test.

The vibration of the catenary that is initiated by the passing pantograph has a direct influence on the pantograph-catenary contact performance. Monitoring the dynamic uplift of the catenary can help inspectors to evaluate the railway operation conditions and investigate the mechanism of pantograph-catenary interaction further. In this paper, a non-contact measurement method based on the deep leaning method is proposed to monitor the real-time vibration of the catenary. The field test for the catenary free vibration is designed to validate the method's performance. The measurement method is developed based on the fully convolutional Siamese neural network, and the contact wire is taken as the tracking target. To reduce the recognition errors caused by the changes in the shape and grayscale of the moving contact wire in images, the class-agnostic binary segmentation mask is adopted. A developed down-sampling block is used in the neural network to reduce the image feature loss, which effectively enhances the recognition effect for the catenary vibration under variable lighting conditions. To validate the performance of the proposed measurement method, a series of field tests of catenary free vibration were conducted under various lighting conditions and different excitations, and the recognition results were compared with traditional target tracking methods. The results show that the proposed method performs well for catenary vibration identification in the field test. Additionally, the uplift data extracted from the identified images agree with the numerical results, and also help to further investigate the wave propagation and damping characteristics in the catenary structure.