Effect of wheel structure on friction-induced wheel polygonal wear of high-speed train

According to a large amount of the test data, the mid and high frequency vibrations of high-speed bogies are very notable, especially in the 565~616 Hz range, which are just the passing frequencies corresponding to the 22nd to 24th polygonal wear of the wheel. In order to investigate the main cause of wheel higher-order polygon formation, a 3D flexible model of a Chinese high-speed train bogie is developed using the explicit finite element method. The results show that the couple vibration of bogie and wheelset may lead to the high-order wears of wheel. In order to reduce the coupled resonance of the wheelset and the bogie frame, the effects of the stiffness and damping of the primary suspensions, wheelset axle radius, and bogie frame strength on the vibration transmissibility are discussed carefully. The numerical results show that the resonance peaks in high frequency range can be reduced by reducing the stiffness of axle box rotary arm joint, reducing the wheelset axle radius or strengthening the bogie frame location. The related results may provide a reference for structure improvement of the existing bogies and structure design of the new high-speed bogies.

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Experimental analysis of the mechanism of high-order polygonal wear of wheels of a high-speed train

Journal of Zhejiang University SCIENCE A ◽

10.1631/jzus.a1600741 ◽

2017 ◽

Vol 18 (8) ◽

pp. 579-592 ◽

Cited By ~ 25

Author(s):

Yue Wu ◽

Xing Du ◽

He-ji Zhang ◽

Ze-feng Wen ◽

Xue-song Jin

Keyword(s):

Experimental Analysis ◽

High Speed ◽

High Order ◽

High Speed Train ◽

Polygonal Wear

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Dynamic Responses of Gear Transmission System of High-Speed Train Due to Wheel Polygonal Wear

Lecture Notes in Mechanical Engineering - Advances in Dynamics of Vehicles on Roads and Tracks ◽

10.1007/978-3-030-38077-9_96 ◽

2020 ◽

pp. 827-833

Author(s):

Zhonghui Yin ◽

Jiye Zhang

Keyword(s):

High Speed ◽

Transmission System ◽

Gear Transmission ◽

Dynamic Responses ◽

High Speed Train ◽

Gear Transmission System ◽

Polygonal Wear

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Vibration and Stress Response of High-Speed Train Gearboxes under Different Excitations

Applied Sciences ◽

10.3390/app12020712 ◽

2022 ◽

Vol 12 (2) ◽

pp. 712

Author(s):

Wangang Zhu ◽

Wei Sun ◽

Hao Wu

Keyword(s):

High Speed ◽

Dynamic Stress ◽

Coupling Model ◽

Transmission Model ◽

Railway Vehicle ◽

Time Varying ◽

High Speed Train ◽

Dynamic Stresses ◽

Vibration Data ◽

Polygonal Wear

The vibration data of the gearbox on a high-speed train was measured, and the vibration characteristics were analyzed in this paper. The dynamic stress of the gearbox under the internal and external excitation was examined by a railway vehicle dynamic model with a flexible gearbox and a flexible wheelset. The ideal 20th polygonal wear was considered, and dynamic stresses of the gearbox under different polygonal wear amplitudes were calculated. The gear transmission model was established to study the dynamic stress of the gearbox under the influence of the time-varying stiffness of the gear meshing. Based on the rigid–flexible coupling model, and considering the influence of wheel polygonization, gear meshing time-varying stiffness, and wheelset elastic deformation, the dynamic stress of the gearbox was investigated with consideration of the measured polygonal wear and measured rail excitation. The results show that the dynamic stress of the gearbox is dominated by the wheel polygonization. Moreover, not only the wheel polygonization excites the resonance of the gearbox, but also the flexible deformation of the wheelset leads to the deformation of the gearbox, which also increases the dynamic stress of the gearbox. Within the resonant bandwidth of the frequency, the amplitude of the dynamic stresses in the gearbox will increase considerably compared with the normal case.

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A data-driven approach for the health prognosis of high-speed train wheels

Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability ◽

10.1177/1748006x20929158 ◽

2020 ◽

Vol 234 (6) ◽

pp. 735-747 ◽

Cited By ~ 2

Author(s):

Zhexiang Chi ◽

Taotao Zhou ◽

Simin Huang ◽

Yan-Fu Li

Keyword(s):

High Speed ◽

Failure Modes ◽

Sampling Technique ◽

Bayesian Optimization ◽

Data Driven ◽

Support Vector ◽

High Speed Train ◽

Mixed Features ◽

Data Driven Approach ◽

Polygonal Wear

Polygonal wear is one of the most critical failure modes of high-speed train wheels that would significantly compromise the safety and reliability of high-speed train operation. However, the mechanism underpinning wheel polygon is complex and still not fully understood, which makes it challenging to track its evolution of the polygonal wheel. The large amount of data gathered through regular inspection and maintenance of Chinese high-speed trains provides a promising way to tackle this challenge with data-driven methods. This article proposes a data-driven approach to predict the degree of the polygonal wear, assess the reliability of individual wheels and the health index of all wheels of a high-speed train for maintenance priority ranking. The synthetic minority over-sampling technique—nominal continuous is adopted to augment the maintenance dataset of imbalanced and mixed features. The autoencoder is used to learn abstract features to represent the original datasets, which are then fed into a support vector machine classifier. The approach is coherently optimized by tuning the model hyper-parameters based on Bayesian optimization. The effectiveness of our proposed approach is demonstrated by the wheel maintenance data obtained from the year 2016 to 2017. The results can also be used to support practical maintenance priority allocation.

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