Axle Box Bearing Research Articles

Establishment of the thermo-mechanical coupling model of axle box bearings with track irregularity excitation and analysis of its temperature characteristics

Establishment of the thermo-mechanical coupling model of axle box bearings with track irregularity excitation and analysis of its temperature characteristics

A simulation data-driven semi-supervised framework based on MK-KNN graph and ESSGAT for bearing fault diagnosis

Current supervised intelligent fault diagnosis relies on abundant labeled data. However, collecting and labeling data are typically both expensive and time-consuming. Fault diagnosis with unlabeled data remains a significant challenge. To address this issue, a simulation data-driven semi-supervised framework based on multi-kernel K-nearest neighbor (MK-KNN) and edge self-supervised graph attention network (ESSGAT) is proposed. The novel MK-KNN establishes the neighborhood relationships between simulation data and real data. The developed multi-kernel function mitigates the risks of overfitting and underfitting, thereby enhancing the robustness of the simulation-real graphs. The designed ESSGAT employs two forms of self-supervised attention to predict the presence of edges, increasing the weights of crucial neighboring nodes in the MK-KNN graph. The performance of the proposed method is evaluated using a public bearing dataset and a self-constructed dataset of high-speed train axle box bearings. The results show that the proposed method achieves better diagnostic performance compared with other state-of-the-art graph construction methods and graph convolutional networks.

Dynamic responses of locomotive axle box bearings under varying operating conditions

Axle box bearings (ABBs) are a vital component of a railway locomotive, ensuring their reliable performance requires an in-depth understanding of their dynamic behaviour. This work theoretically derives a locomotive–track longitudinal–vertical coupled dynamics model that takes detailed dynamics of the ABBs into account. The model considers a number of complex interactions, such as non-linear contact and friction forces within the ABB, wheel–rail interactions, and track irregularities. The motions of ABB are coupled with the wheelset and bogie frame, allowing detailed investigation of the ABB dynamic behaviour during operation. The correctness of the proposed model is verified in both the time and frequency domains by comparing with field test. The dynamic characteristics of ABBs under varying operating conditions were comprehensively investigated. The results demonstrate that track irregularities have a non-negligible influence on the dynamic forces of the locomotive ABB. Furthermore, the axle load transfer occurs during loading conditions, which leads to significant differences in vertical and longitudinal dynamic interactions within the ABBs across wheelsets. It is clear that the operating conditions of the locomotive should be suitably considered in the dynamic assessment, operation, and maintenance of ABBs.

A High-Speed Train Axle Box Bearing Fault Diagnosis Method Based on Dimension Reduction Fusion and the Optimal Bandpass Filtering Demodulation Spectrum of Multi-Dimensional Signals

The operating state of axle box bearings is crucial to the safety of high-speed trains, and the vibration acceleration signal is a commonly used bearing-health-state monitoring signal. In order to extract hidden characteristic frequency information from the vibration acceleration signal of axle box bearings for fault diagnosis, a method for extracting the fault characteristic frequency based on principal component analysis (PCA) fusion and the optimal bandpass filtered denoising signal analytic energy operator (AEO) demodulation spectrum is proposed in this paper. PCA is used to measure the dimension reduction and fusion of three-direction vibration acceleration, reducing the interference of irrelevant noise components. A new type of multi-channel bandpass filter bank is constructed to obtain filtering signals in different frequency intervals. A new, improved average kurtosis index is used to select the optimal filtering signals for different channel filters in a bandpass filter bank. A dimensionless characteristic index characteristic frequency energy concentration coefficient (CFECC) is proposed for the first time to describe the energy prominence ability of characteristic frequency in the spectrum and can be used to determine the bearing fault type. The effectiveness and applicability of the proposed method are verified using the simulation signals and experimental signals of four fault bearing test cases. The results demonstrate the effectiveness of the proposed method for fault diagnosis and its advantages over other methods.

A dynamics simulation-assisted transfer learning method for track condition diagnosis in urban rail transits

Track defects are gradually emerging with the development of urban rail transits. However, there is rare research implemented to diagnose track conditions in real time. Although some intelligent data-driven methods seem to have the potential to achieve the track condition diagnosis, it’s hard to acquire sufficient labeled data in actual applications. This study proposes a dynamics simulation-assisted transfer learning (TL) method for label-scarce track condition diagnosis. Firstly, a dynamics model of axle-box bearings considering the service environment is established. Based on this model, a large amount of axle-box vibration signals corresponding to healthy/defective track conditions is simulated. Wavelet transform is performed for these signals to characterize their time-frequency energy distribution modes in the format of time-frequency maps, which are considered source-domain data. Similarly, the time-frequency maps of the collected signals during vehicle operation are served as the target-domain data. Subsequently, a sub-domain alignment TL network is constructed to map the data from the source and target domain into a deep feature space. In this network, unlabeled target-domain data are classified to obtain their pseudo labels. Finally, Wasserstein distance measure and multiple domain discriminators are employed to achieve label alignment between two domains for each corresponding category. A feature centroid-driven loss function is applied to further reduce the intra-class variations, ultimately realizing accurate knowledge transfer from simulated signals to collected signals. A two-level sliding window algorithm is designed to detect abnormal axle-box vibration signal parts which are then diagnosed through the well-trained network. The proposed method is validated through a transfer diagnosis experiment using simulated signals and collected signals. This study provides a promising solution to diagnose different track conditions, which is of great significance for ensuring running safety in urban rail transits.

ВЛИЯНИЕ ВИБРАЦИИ НА ИЗНОС БУКСОВОГО ПОДШИПНИКА

The study objective is to determine the effect of vibration on the wear of the parts of a rolling axle box bearing. The tasks of the study are to obtain dependences of the speed and wear intensity of bearing elements depending on time, to determine the most unfavorable factors affecting the bearing, to evaluate methods for increasing wear resistance and vibration resistance of parts of a rolling axle box bearing. The bearing is tested on 1K62 screw-cutting lathe under the action and without the action of axial vibration. Wear is calculated for the treadmill using a mass method, by stopping tests and measuring mass loss (with an accuracy of 1g). The friction path of the roller to determine the wear intensity is calculated analytically. The scientific novelty of the work consists in confirming the hypothesis about the adverse effect of vibration on wear and suggesting methods and ways to increase the vibration resistance of rolling axle box bearing parts. The results of the tests and calculations are presented as graphs showing the effect of vibration on the axle box bearing parts in the form of a wear curve, which has a nonlinear dependence on the test time, as well as a wear curve for tests without vibration. The main factors influencing the fretting wear of rolling axle bearings are determined, methods for increasing their vibration resistance and wear resistance are proposed.

Research on a Fault Feature Extraction Method for an Electric Multiple Unit Axle-Box Bearing Based on a Resonance-Based Sparse Signal Decomposition and Variational Mode Decomposition Method Based on the Sparrow Search Algorithm.

In light of the issue that the vibration signal from an axle-box bearing collected during the operation of an electric multiple unit (EMU) is seriously polluted by background noise, which leads to difficulty in identifying fault characteristic frequency, this paper proposes a resonance-based sparse signal decomposition (RSSD) and variational mode decomposition (VMD) method based on sparrow search algorithm (SSA) optimization to extract the fault characteristic frequency of the bearing. Firstly, the RSSD method is utilized to decompose the signal based on the obtained optimal combination of quality factors, resulting in the optimal low-resonance component with periodic fault information. Then, the VMD method is performed on this low-resonance component. The parameter combinations for both methods are optimized utilizing the SSA method. Subsequently, envelope demodulation is applied to the intrinsic mode function (IMF) with maximum kurtosis, and fault diagnosis is achieved by comparing it with the theoretical fault characteristic frequency. Finally, experimental validation and comparison are conducted by utilizing simulated signals and example signals. The results demonstrate that the proposed method extracts more obvious periodic fault impact components. It effectively filters out the interference of complex noise and reduces the blindness of setting weights on parameters due to human experience, indicating excellent adaptability and robustness.

Measured dynamic load distribution within the in situ axlebox bearing of high-speed trains under polygonal wheel–rail excitation

The dynamic load distribution within in-service axlebox bearings of high-speed trains is crucial for the fatigue reliability assessment and forward design of axlebox bearings. This paper presents an in situ measurement of the dynamic load distribution in the four rows of two axlebox bearings on a bogie wheelset of a high-speed train under polygonal wheel–rail excitation. The measurement employed an improved strain-based method to measure the dynamic radial load distribution of roller bearings. The four rows of two axlebox bearings on a wheelset exhibited different ranges of loaded zones and different means of distributed loads. Besides, the mean value and standard deviation of measured roller–raceway contact loads showed non-monotonic variations with the frequency of wheel–rail excitation. The fatigue life of the four bearing rows under polygonal wheel–rail excitation was quantitatively predicted by compiling the measured roller–raceway contact load spectra of the most loaded position and considering the load spectra as input.

Study on the vibration characteristics of double-row tapered roller bearings for high-speed rail axle box

PurposeThe purpose of this paper is to establish a dynamic model considering the actual operating conditions of the train and to study the dynamic performance and vibration characteristics of axle box bearings under different operating conditions.Design/methodology/approachIn this paper, based on the internal contact characteristics of double-row tapered roller bearings, a dynamic model considering the actual operating conditions of the train is established. The correctness of the model is verified by the vibration test of the bearing. Comparative analysis was conducted on the effects of axial force, radial force and rotational speed on the angular velocity of the cage, slip rate and vibration acceleration level of the inner ring.FindingsAs the force increases, the slip rate of the cages on both sides decreases, and the vibration acceleration level of the inner ring increases. With the increase of rotational speed, the cage slip rate of the axle box bearing increases and the vibration acceleration level of the inner ring increases.Originality/valueA dynamic model is established considering the actual operating conditions, and the dynamic performance and vibration characteristics of the axle box bearing under different operating conditions are analyzed by numerical method. The research content can provide reference for the parameter design of high-speed railway bearings.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2024-0085/

Influence of temperature on dynamic contact characteristics of oil-jet lubricated rolling bearings

The temperature variation alters the contact state of each component during the operating process of oil-jet lubricated rolling bearings, which directly affects the dynamic performance of the bearing. However, previous studies on the dynamics of oil-jet lubricated rolling bearings do not comprehensively consider the influence of temperature factors. In addition, the impact of the temperature on the dynamic contact characteristics of the bearing is rarely investigated. To fill these gaps, this study develops a finite element model based on the mechanism of heat generation and transfer of the bearing to simulate the bearing temperature field and obtain the temperature of various components. On this basis, a dynamic model of an oil-jet lubricated axle box bearing is established to explore the influence of the radial clearance, internal temperature of the axle box and lubricating oil temperature on the contact force between the race and the rolling body by considering the influence of temperatures on the thermal deformation, lubricating oil parameters and equivalent stiffness. It was found that the influence of the temperature on bearings is primarily manifested in the elastic modulus, lubricating oil viscosity, oil film thickness, equivalent stiffness and thermal deformation. The contact force between the rolling body and the race increases significantly when the lubricating oil temperature is high, which may result in bearing pitting failure. These analysis results can provide a theoretical foundation for bearing parameter design and life research.

Detection method for contact stress distribution of tapered roller bearings

The axle box of high-speed train adopts double row tapered roller bearings as transmission parts, and the reliability of bearings directly affects the safety of train operation. Tapered roller bearings can withstand axial and radial loads, their service life being closely related to the distribution of contact stress. The test object is the axle box bearing of high-speed train. According to bearing’s structural characteristics, based on the digital speckle correlation method (DSCM) and machine vision, the contact stress distribution detection devices for rollers and complete sets of bearings are developed respectively and an effective detection method is proposed. The contact stress data of the bearing which has reached the service life and the new bearing under the condition of no lubrication and grease lubrication are collected and normalized. Through the geometric relationship, based on the measured data of the selected detection points, the normal and tangential contact stress distribution of the roller and raceway under different contact conditions is obtained by data fitting. The test can be used as an evaluation basis for the effectiveness of bearing modification and provide reference for bearing design.

A hybrid ICEEMDAN and OMEDA-based vibrodiagnosis method for the bearing of rolling stock

Purpose. To develop a hybrid method based on ICEEMDAN and OMEDA for high-fidelity detection of the diagnostic features of the technical condition of roller bearing. Methodology. Due to digital signal processing the search was made of the informative components on the broadband spectra, envelope spectra, squared envelope spectra. The usage of the methods of mathematical statistics for the selection of informative IMFs as a result of iterative calculate procedures. The introduction of blind deconvolution method with a proper objective function for the enhancement of impulse fault features. Findings. The use of traditional spectral methods provided an incomplete list of diagnostic features of bearing roller damage. The empirical mode decomposition (EMD) method and its minor versions provide the series of intrinsic mode functions (IMFs). On the broadband vibration spectra of the selected low-frequency IMFs, diagnostic features were not detected in a sufficient number. Further research focused on the development of a hybrid method that takes into account the demodulation procedure of the high-frequency components of those IMFs that were selected according to the complex evaluation index. The Fast Kurtogram technique determined an informative frequency band of 7.2–7.5 kHz for demodulation and construction of the squared envelope spectra, where harmonics of the roller spin frequency and some side bands with a width equal to the separator rotation frequency appeared. The use of OMEDA caused the reduction of residual noise on the squared envelope spectra and bilateral sidebands to appear around all harmonics of the roller spin frequency. Originality. For the first time, the whole list of the diagnostic features of roller faults of the axle-box bearing was identified using the developed hybrid method, which involves steps of noise reduction for enhancing a physical meaning of a proper frequency components, associated with faults. The usage of the optimal minimum entropy deconvolution adjusted method helped to eliminate noise and provide all diagnostic features of the technical condition on the squared envelope spectrum. Practical value. The results of the study help to control the quality of repair of the axle-box rolling bearings on the test rig at the workshop of the freight railway car depot.

Vibration-Based Detection of Axlebox Bearing Considering Inner and Outer Ring Raceway Defects

The occurrence of an axlebox bearing ring raceway defect is an inevitable and commonly observed phenomenon in railway wheels. It not only leads to surface damage but also poses the potential threat of further damage and degradation, thereby increasing the risks associated with running safety and maintenance costs. Hence, it becomes imperative to detect raceway defects at an early stage to mitigate safety hazards and reduce maintenance efforts. In this study, the focus lies in investigating the effectiveness of vibration-based detection techniques for identifying raceway defects in high-speed train axlebox bearing systems. To achieve this, a dynamic model that accurately represents the coupling dynamics between the vehicle and the track is developed. This model incorporates various dynamic factors, such as traction transmission, gear transmission, and track geometry irregularities. By using the comprehensive dynamic model, the dynamic responses of the axlebox can be accurately calculated. The proposed methodology primarily revolves around analysing the vertical vibrations of the axlebox caused by raceway defects in both the time and frequency domains. Additionally, an envelope analysis using a developed band-pass filter is also employed. The results obtained from this study clearly demonstrate the successful detection of raceway defects in a more realistic vehicle model, thereby providing an efficient approach for the detection of axlebox bearing raceway defects. Consequently, this research contributes significantly to the field of high-speed train systems and paves the way for enhanced safety and maintenance practices.

Vibration characteristics of defective axle box bearings in high-speed trains under track irregularity excitation

Track irregularity is a type of excitation source for the wheel-rail system, and it is also the major cause of vibration and wheel-rail forces on the axle box bearings of vehicles, and it is commonly found on in-service lines. Therefore, this paper mainly focuses on the dynamic characteristics of high-speed train axle box bearings under track irregularity. Firstly, a nonlinear system containing a faulty double-row tapered roller bearings is established, the obtained equations of motion are solved numerically using the Runge–Kutta and comparing it with the varying compliance vibration frequency and fault characteristic frequency obtained by formula, the comparison results verify the effectiveness of the model. Then, the track irregularity is coupled to the above bearing system, the model is also verified by using the rolling and vibrating test rig of single wheelset. Secondly, the eigenvalue of covariance matrix is introduced as an index to analyze the influence trend of different fault sizes, loads, and inner rotational speeds on the axial trajectory. Finally, the influence trend of track irregularity on the stability of vertical acceleration is analyzed by simulating different operating conditions.

Dynamics modeling of urban rail vehicle axle-box bearings with roller defect considering time-varying impact

Accurately simulating the vibration response of the axle-box bearing with a localized defect on the roller can guide the proposal of several health condition estimation methods. However, there is still a lack of discussion and analysis on the detailed motion process of the roller defect passing through the inner/outer race. For filling this gap, a roller defect model considering time-varying impact is proposed and applied to the vehicle–track coupling system considering axle-box bearings. In addition to the Hertz contact force due to the relative displacement between the roller and race, time-varying impact excitation is designed according to the law of the conservation of energy. At first, an onsite test and an experimental test are implemented to validate the accuracy of the roller defect model and the vehicle–track coupling model, respectively. Then, the effect of the roller defect on the vibration characteristics of the components in the vehicle system is investigated. Finally, the influence of the defect size and vehicle speed on the vibration response of the axle-box bearing is studied, and the change rule of the time-varying impact is also researched with the defect size. Besides, the axle-box vibration response is simulated under variable vehicle speeds, and order tracking technique is applied to analyze the simulated result.

Dynamic analysis of axle box bearings on the high-speed train caused by wheel-rail excitation

To explore the impact of wheel-rail excitation on the dynamic performance of axle box bearings, a dynamic model of the high-speed train including axle box bearings is developed. Subsequently, the dynamic response characteristics of the axle box bearing are examined. The investigation focuses on the acceleration characteristics of bearing vibration under excitation of track irregularities and wheel flats. In addition, experiments on both normal and faulty bearings are conducted separately, and the correctness of the model and some conclusions are verified. According to the research, track irregularity is unfavorable for bearing fault detection based on resonance demodulation. Under the same speed conditions, the acceleration peak of bearing is inversely proportional to the length of the wheel flat and directly proportional to its depth. The paper will contribute to a deeper understanding of the dynamic performance of axle box bearings.

Laboratory robustness validation of a humidity sensor system for the condition monitoring of grease-lubricated components for railway applications

Abstract. The condition monitoring of the health status of lubricating greases used in axle box bearings can be realized by applying well-established electrical or optical measurement principles. Furthermore, some novel methods have been reported that make use of humidity sensors or of dielectric thermoscopy. One of the most important grease condition parameters is the water content of the lubricating grease, as water can degrade grease to the point that it is no longer able to provide suitable lubrication and can also damage the bearing due to corrosion and cavitation. In this study, a new approach for water detection in lubricated wagon components is presented that is based on commercially available humidity sensors. The core element of this sensor system is a robust humidity sensor mounted in the immediate atmosphere of the grease-lubricated wagon axle bearing. In the case of water intake, the humidity of the gaseous atmosphere above the grease increases and can be detected by the customized sensor concept Humidity Sensor in Axle Bearings (HSAB). As this sensor system has to be sufficiently robust, it must be able to withstand environmental impact factors. The most important of these factors are temperature, relative humidity, and mechanical load, like vibrations and shocks, depending on the relevant railway application. To mimic these field effects under controlled laboratory conditions, the “lab-to-field” approach was set up and employed. Of the utmost importance was the installation of a development environment for the sensors that enabled the transfer of laboratory results to the respective rail field application. As a result, the HSAB system shows promise with respect to enhancing the reliability of railway wagons and decreasing maintenance costs, thereby reducing the downtime of railway wagons significantly.

Research on the change in lubrication state and temperature control strategy of high-speed train axle box bearings using non-destructive testing

ABSTRACT The heat generation problem of axle box bearing during churning phase leads to abnormal temperature rise and temperature alarm, which affects the normal operation of high-speed train. Aiming at this problem, the temperature characteristics of bearing initial lubrication phase is studied, and the multi-speed grade cycle running schemes are used in tests to run multiple bearings for multiple times. The temperature data and friction data in tests are collected by using non-destructive testing method, and characteristic extraction is carried out. Under the premise of not destroying the internal structure and lubrication state of the bearing, the lubrication state inside the bearing is reflected by the change of the characteristic values. A 118 min scheme is proposed, and the bearing using this scheme to run on the test rig is used in the actual operation. The results show that the temperature of the bearing with running-in test is lower than that of the bearing without running-in test, which indicates the effectiveness of the proposed temperature control strategy.

An investigation on dynamic vibration characteristics of urban rail vehicle axle-box bearings in the presence of rail welds

The operation condition of axle-box bearings strongly affects the running safety of vehicles. However, the presence of rail welds can impact the wheel-rail interaction system, causing changes in the dynamic response of axle-box bearings and furtherly affecting their health condition. Despite this, there is still a lack of discussion and analysis on the effect of rail welds on dynamic characteristics of axle-box bearings. Therefore, a vehicle-track coupling dynamics model is developed. Besides the rigid vehicle model, flexible track model and wheel-rail contact model, the axle-box bearing model and flexible wheelset model are considered. Among them, the axle-box bearing model accounts for the motion of the roller and cage decentralized into multiple segments. Using modal superposition method, the flexible deformation of the wheelset is calculated and overlapped with its rigid displacement for the flexible wheelset model. The performance of the model is verified through theoretical analysis and field tests. It is crucial to consider the wheelset as flexible in the presence of rail welds and its effects are also researched. Moreover, the effect of the rail weld geometry on the wheel-rail separation is studied, and the consequence caused by rail welds on the bearing damage is discussed under different vehicle speeds.

Generalized Statistical Indicators-Guided Signal Blind Deconvolution for Fault Diagnosis of Railway Vehicle Axle-box Bearings

Generalized Statistical Indicators-Guided Signal Blind Deconvolution for Fault Diagnosis of Railway Vehicle Axle-box Bearings