Vibration analysis of the axle bearings considering the combined errors for a high-speed train

Liu, Jing; Li, Xinbin; Yu, Wennian

doi:10.1177/1464419320917235

Cited by 12 publications

(8 citation statements)

References 49 publications

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“…Meanwhile, the simulated time interval between impulse C1 and C2, D1 and D2 are approximately 6.1 ms, equaling to 1/f BPFI . The time interval between D1 and C2 is approximately 4.6 ms, and the time difference relationship given by Igarashi et al 5 for ball bearing with two defects on inner raceway are shown in equations (30) and (31),…”

Section: Defects On Inner Raceway Surfacementioning

confidence: 92%

“…Liu et al. 31 conducted an improved analytical model for a high-speed train considering the axle bearings with combined roundness and waviness errors. The ADAMS model 32 could be used to simulate complex bearing defects.…”

Section: Introductionmentioning

confidence: 99%

“…Lynagh et al 30 presented a dynamic model which incorporated surface waviness and offsized balls, principal and sidebands frequency were listed and analyzed. Liu et al 31 conducted an improved analytical model for a high-speed train considering the axle bearings with combined roundness and waviness errors. The ADAMS model 32 could be used to simulate complex bearing defects.…”

Section: Introductionmentioning

confidence: 99%

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A 4-DOF dynamic model for ball bearing with multiple defects on raceways

Gao

Yan

Liu

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part K:

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Localized defects in ball bearing components would cause additional vibration and it is imperative to reveal the vibration mechanism. The relationship between fault characteristic frequency (fBPFI and fBPFO) and multiple defect parameters of ball bearing were given in this paper. Considering elastohydrodynamic lubrication (EHL), radial clearance, time-varying displacement and excitation force generated from multiple defects, a 4 degree-of-freedom (DOF) dynamic model for ball bearing with multiple defects on inner or outer raceway was established, and the model has been verified by experiments. Vibration signals of ball bearing with different defects parameters were simulated, the effects of the angle between two defects ( θIAD and θOAD), the number of defects ( NDI and NDO) and the location of defects on outer raceway on dynamic response were studied. Comparing simulated signals with experimental results, it is shown that more impulses of acceleration signals are generated by multiple defects than that by single defect, meanwhile time delay due to two defects on raceways could also be found, fault characteristic frequency and their harmonics frequencies appeared in the envelope spectrums. Harmonics frequencies of fBPFI are modulated mainly by 2 fs instead of fs in frequency domain for multiple defects on inner raceway. The amplitudes of fBPFO and fBPFI change as Fourier curve when θOAD and θIAD varied within a certain range, and a series of Fourier function are given to describe the mathematic relationship.

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Section: Defects On Inner Raceway Surfacementioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A 4-DOF dynamic model for ball bearing with multiple defects on raceways

Gao

Yan

Liu

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part K:

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show abstract

“…Track geometry degradation can have a negative impact on passenger comfort and safety. Moreover, the track geometry degradation can significantly affect the working performance, and noise, vibration, and harshness characteristics of the whole train system [5]. Therefore, effective track maintenance is essential to prevent these negative effects.…”

Section: Introductionmentioning

confidence: 99%

Analysis and prediction of railway track longitudinal level using multiple machine learning methods

Han,

Liao,

Wang

et al. 2023

Meas. Sci. Technol.

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With the fast development of computer science, many prediction models based on machine learning methods have been used in the railway industry, which can better predict the random characteristics in track degradation, plan maintenance activities, and eventually meet the requirement of railway transportation. However, the applicability and generality of these models are unclear and the comparative analysis of these models on the random railway track is rare, which makes it hard for railway engineers to choose the most suitable prediction models in practice. In this paper, the track longitudinal level of a section of a railway which measured monthly by Rail Infrastructure Alignment Acquisition system (RILA) for 1.5 years in the Netherlands has been analysed using multiple mathematical methods. After that, three machine learning-based prediction models were developed to predict the future development of the track longitudinal level, using Support Vector Machine (SVM), Grey Model (GM) and Deep Neural Network (DNN). The prediction performance of different prediction models is compared and discussed. Recommendations for choosing prediction models and further development are provided.

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“…Dipen and Patel [12] established a dynamic model to study the vibration responses of ball bearings with obvious raceway waviness. Liu et al [13,14] introduced a displacement excitation model to study the coupling errors including the waviness and roundness of both raceways and balls. The effects of the order and amplitudes of the coupling errors on the vibrations of ball bearings were studied.…”

Section: Introductionmentioning

confidence: 99%

A Study on the Modeling Method of Cage Slip and Its Effects on the Vibration Response of Rolling-Element Bearing

Luo

Chen

et al. 2022

Energies

Self Cite

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Rolling-element bearings play vital roles in the dynamic vibration performance of the whole machinery. Hence, accurate modeling and assessment of the rolling-element bearing are beneficial for the well understanding of the vibration response of rolling-element bearing. However, cage slip is usually ignored in the traditional rolling-element bearing modeling methods, which has a direct influence on the rotating speed and friction force of the rolling elements. To settle the modeling problem of rolling-element bearing with cage slip, in this study, a nonlinear dynamic model with multiple degrees of freedom of the roller bearing is established. The cage slip, the motion of each roller, nonlinear contact, damping, and friction are taken into consideration. With the proposed method, a nonlinear traction model is presented to describe the friction forces induced by cage slip. Furthermore, both the friction force acting on rolling elements and the effects of cage slip on the vibration response are investigated based on the established model. Some comparisons between the proposed modeling method with cage slip and the classical method without cage slip are made. The results show that the friction force applied to the balls increases with the cage slip, friction coefficient, rotational speed, and radial load. A slight cage slip could be beneficial for reducing the vibration energy of rolling-element bearing; however, it will result in more friction loss and impact components.

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Vibration analysis of the axle bearings considering the combined errors for a high-speed train

Cited by 12 publications

References 49 publications

A 4-DOF dynamic model for ball bearing with multiple defects on raceways

A 4-DOF dynamic model for ball bearing with multiple defects on raceways

Analysis and prediction of railway track longitudinal level using multiple machine learning methods

A Study on the Modeling Method of Cage Slip and Its Effects on the Vibration Response of Rolling-Element Bearing

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