Gear Contact Fatigue Research Articles

Fatigue reliability analysis methodology based on fatigue life and failure mechanism for carburized gear

Gears are one of the important components in mechanical products, and their fatigue reliability determines the safety performance of mechanical products. In this paper, the fatigue characteristics of carburized gears under different torque and constant rotational speed conditions are investigated by using a gear contact fatigue testing machine, and combined with the dynamic maximum contact stress distribution on the subsurface of the meshing gears, the very-high cycle fatigue P-S-N curves of carburized gears under a stress ratio of −1 is established. Local stress concentration in the surface or subsurface of carburized gears causes grain dislocation movement under the combined influence of maximum contact and residual stresses, and then causes dislocation pileup and transcrystalline rupture after being hindered by grain boundaries, ultimately leading to pitting and fatigue failure of gears. Based on the dislocation energy method and combined with the fatigue failure mechanism of gears, a life prediction model of gears with good prediction results is established by considering the interaction of factors such as dynamic load, grain size, initial crack length, residual stress, slip band length and width. A fatigue reliability analysis method of gears is established based on the life state equation of gears considering the life prediction model. Further analyses of the influence of rotational speed, grain size, residual stress, slip band width, slip band length and initial crack size on the fatigue life reliability index of the gears resulted in the conclusion that the fatigue reliability of the gears not only decreases with the increase of the above-mentioned parameters, but also shows decreasing trend with the increase of time. This is of significance for evaluating the fatigue reliability of gears under very-high cycle fatigue conditions.

Integrated analysis strategy for detecting gear contact fatigue before reaching failure interruption criterion

Identifying the occurrence of gear contact fatigue failure as early as possible is essential for condition-based maintenance (CBM). Vibration signals can be used to identify gear contact fatigue. However, the use of vibration signals can be challenging due to its complexity, compounded by lower levels of vibration during the initial stages of contact fatigue. The present study details a new algorithm that integrates stand-alone features to correlate the vibrational signal with early failure occurrence. The study aim is to identify the failure in the early stages, before reaching the ISO 6336-5 stopping criterion of 4% damaged area. A damage induction on the flank of helical gears is applied to simulate and characterize the failure occurrence. Damping characteristics with impact evaluation, Kurtosis analysis and the monitoring of the Gear Meshing Frequency are applied to characterize the failure signature. This strategy stands out by the integration of these stand-alone features and their behavior. The algorithm's capacity is verified through durability tests, promoting the natural evolution of this failure mode. Results show a success rate of above 80% at identifying the failure presence before the stopping criterion limit.

Gear contact fatigue prediction under mixed elastohydrodynamic lubrication with ellipsoidal asperity rough surface: Experimental and numerical investigation

A three-dimensional(3D) line-contact mixed lubrication model and contact fatigue life prediction model for gears are established, considering the elastoplastic contact of ellipsoidal asperities and their interactions. The localized lubrication states across the actual 3D rough surfaces are visually depicted. The direct asperity contact pressures calculation exhibits greater accuracy and universality. The proposed mixed lubrication model can be applied accurately and efficiently to heavy-load conditions. The synergistic mechanisms of multi-scale surface integrity parameters, such as surface morphology-lubrication coupling, hardness gradient, and residual stress, on gear contact fatigue has been revealed. The results reveal that surface roughness significantly affects the competitive failure mechanism between surface-initiated micropitting and subsurface-initiated macropitting. The increase in surface compressive residual stress is more sensitive to the enhancement of near-surface and subsurface fatigue lives, compared to the increase of peak residual stress and the depth of peak residual stress. The proposed physics-based gear contact fatigue life prediction model has been validated through gear contact fatigue experiments under various operating conditions. The maximum deviation between the predicted and experimental fatigue lives is within 10%. This paper presents theoretical methodologies and data-driven support for optimizing the design and manufacturing processes of gears, specifically focusing on enhancing anti-fatigue properties.

Analysis of the dynamic contact behaviour of high-speed train transmission gear excited by wheel defects

Studies on wheel flatness and polygonal wear have demonstrated that wheel defects cause severe impact forces at the wheel–rail interfaces. This study investigated the dynamic contact mechanical behaviour of high–speed train transmission gears when subjected to wheel defects. First, a train-track coupling dynamics model was established, considering the localized contact characteristics of transmission gears. This model was developed using the slice method and the Hertz contact model, exploring the spatial coupling effects between the gear contact interface and the train–track interface. Subsequently, the dynamic model was employed to extract essential contact mechanical parameters of the transmission gear under the influence of wheel defects, including gear meshing load, gear contact stress, and sliding velocity. Furthermore, an analysis was conducted to uncover and elucidate the mechanism by which wheel flatness and polygonal wear impact the dynamic contact behaviour of the transmission gear. This study underscores the importance of considering wheel defects when assessing the contact fatigue and wear performance of high-speed train transmission gears.

Analysis of rolling contact and tooth root bending fatigue in a new high-strength steel: Experiments and micromechanical modelling

To find materials that meet the future requirements of increasing load density in wind turbine gear structures, the commonly used reference material, 18CrNiMo7-6, and another high-strength steel were analysed. Their fatigue properties were studied through rolling contact fatigue (RCF) and gear tooth root bending fatigue (TRBF) tests. The reference steel exhibited better fatigue performance under RCF conditions compared to the new steel; however, it was outperformed by the new steel under TRBF conditions. This study aims to understand gear contact fatigue at the microscopic level, moving beyond the macroscopic focus that dominates current research literature. To establish the causal link between the varied fatigue performance observed in these materials, we proposed a multiscale modelling workflow based on crystal plasticity. This crystal plasticity framework is combined with the fatigue indicator parameter (FIP) to explore the fatigue resistance of materials subjected to RCF and TRBF conditions. Emphasis has been placed on the role of retained austenite (RA) in fatigue performance. Utilizing representative elementary volumes (REVs) generated based on statistically representative crystallographic features and measured size distribution of RA, we examined the effects of various RA levels on fatigue resistance. Our findings reveals that the fatigue damage accumulation is significantly influenced by the level of RA. Different fatigue damage accumulation behaviours were observed under RCF and TRBF conditions. These insights offer new perspectives on RA’s role in fatigue resistance and highlight its complex influence under varied loading conditions.

Calculation of transmission gears for deep contact endurance

The types of contact fatigue of machine transmission gears are considered. It is shown that the main criterion for the workability of gear wheels of transmissions of tractors and heavy-duty vehicles is the deep contact fatigue of the tooth surfaces. It is established that the calculation of the strength of gears according to GOST 21354—87 gives significant errors, which lead to significant uncertainty in the calculation. A calculation of the life of gears is proposed, taking into account the fatigue resistance of the tooth material and based on the dependence of the limit of deep contact endurance on the hardness and structure of the hardened layer. An example of calculating the life of a gear is considered, comparing the results with bench test data. Keywords:gear, transmission, contact fatigue, pitting, deep contact spalling, calculation, life sprud.47@mail.ru, sand_work@mail.ru, valcoalex5@gmail.com

Numerical modeling and experimental investigation on fatigue failure and contact fatigue life forecasting for 8620H gear

Surface integrity parameters exert an enormous function on contact fatigue performance of gears. In this paper, a gear contact fatigue life prediction model that incorporates surface integrity parameters is proposed. The micropitting and pitting damage of failed gears are quantitatively analyzed through micro-characterization techniques. A three-dimensional contact analysis of rough surface is performed to simulate the morphology evolution during gear running-in. And the coupling effect of residual stress and rough morphology on the contact stress field and fatigue life is analyzed. Finally, residual stress optimization design is carried out based on the failed gear. Gears subjected to shot peening are designed and gear contact fatigue tests under various working conditions are performed. The research results indicate that the plastic deformation at the asperities level in the running-in process mainly occurs during the initial loading. The fatigue life significantly increases by improving the residual stress distribution on the tooth surface through shot peening process. The maximum relative error between predicted fatigue life and measured fatigue life is less than 20%, which effectively verifies the accuracy of the proposed model. The technique presented in this study could provide theoretical basis and data support for the anti-fatigue design and manufacturing of gears.

Comprehensive surface integrity evaluation during early stages of gear contact fatigue

The study aims to evaluate the microstructural sensitive aspects of contact fatigue crack initiation and its evolution during the gear lifetime. Tests were performed to evaluate different stages in the evolution curve of gear contact fatigue. The magnetic Barkhausen noise (MBN) technique was used to characterize variations in the magnetic response in gears during the incipient gear contact fatigue mechanisms initiation. For a complete comprehension of the surface degradation, residual stresses, microstructure, and microhardness were explored. A substantial increase in the MBN signal is identified before the fatigue failure occurs, indicating the occurrence of microstructural alterations that change the magnetic properties. The early stages of contact fatigue are accompanied by a surface softening in the near-surface region, up to approximately 40 µm depth. These phenomena were also followed by a less compressive residual stress region at 20 µm depth. A lower influence of microstrains on the diffractogram can be observed by the full width at half maximum parameter (FWHM), indicating a higher amount of dislocation annihilation during the appearance of the initial stages of the contact fatigue mechanism. The study concludes by proposing a comprehensive approach to understand the mechanisms behind the early stages of gear contact fatigue and how the MBN signal can be used to detect fatigue damage.

Research on the fretting contact fatigue strength of interference fit in high speed rail traction motor shafts

Fretting wear and gear contact fatigue belong to adhesive wear. They have similar causes, failure mechanisms, and failure appearance. Drawing inspiration from the gear contact fatigue strength theory, this article creatively proposes a calculation method for the fretting contact fatigue strength. The safety factor of fretting fatigue is calculated to be 0.34. Due to the singularity of the contact point at the edge of the oil groove, the mesh size near this point needs to be sufficiently fine to 0.025 mm. The contact pressure at the edge contact point of the oil groove is calculated by finite element method (FEM) to be 1034 MPa, which is 6.8 times the Lame theoretical value of 152 MPa. The stress concentration is very severe. The fretting contact fatigue strength at the edge of the oil groove is severely insufficient. The friction torque of the interference connection is calculated to be 3.1 times the overload torque of the motor. The fundamental cause of fretting wear is excessive interference and unreasonable design.

A comprehensive evaluation of DLC coating on gear bending fatigue, contact fatigue, and scuffing performance

Modern advanced equipment demands higher reliability and longer service life, imposing increasingly stringent requirements on loading capacity of gears. Diamond-like carbon (DLC) coating significantly improves the friction and wear performance, which has potential to be applied to gears to enhance their loading capacity. In this study, a comprehensive evaluation of the DLC coating treatment on the loading capacity of 18CrNiMo7-6 gears was conducted. The surface morphology, hardness gradient, residual stress, and material microstructure of the DLC coated gears have been characterized. Additionally, bending fatigue, contact fatigue, and scuffing tests on the gears were performed, which took more than 1000 h. The results demonstrate that DLC coating significantly enhances surface microhardness, reaching up to 2000 HV, and surface residual compressive stress shows an increase of approximately 200 MPa. The DLC treated gear contact fatigue limits from 1570 MPa to 1770 MPa, and the scuffing limit temperature rises from 224.6 °C to 348.6 °C compared with grinding state. Although DLC coatings do not exhibit an improvement in gear bending fatigue strength, the composite treatment of shot peening combined with DLC coating still enhances its bending fatigue performance.

The effect of friction on surface crack initiation in rolling contact fatigue considering damage accumulation

AbstractSurface initiated rolling contact fatigue (RCF) of gears and rolling bearings can lead to premature failure in mechanical transmission systems. The orientation of surface crack initiation closely depends on surface tractive force, while the mechanism leading to this dependence is still obscure. In this work, a numerical model is proposed to investigate the effect of friction on surface crack initiation in RCF. An inhomogeneous contact solver based on semi‐analytical method (SAM) is developed by combining the damaged‐coupled constitutive relation and the Eshelby's equivalent inclusion method. The damage accumulation and concurrent degradation of material properties are modeled with continuum damage mechanics (CDM). The effect of surface tractive force on the orientation of surface crack initiation is simulated and analyzed. Results indicate that the progressive evolution of damage under the cyclic loading is accompanied by the stress variation around the damaged area. The damaged area increases, and the crack initiation life decreases with an increasing coefficient of friction.

A hybrid physics-based and data-driven method for gear contact fatigue life prediction

A hybrid physics-based and data-driven method is proposed for gear contact fatigue life prediction. The parameters influencing the fatigue life are determined by the physics-based model. A deep belief network (DBN) model is developed to reveal the relationships between these parameters and fatigue life. A variational autoencoder (VAE) model is presented to expand the size of the training dataset. The proposed method is verified by a gear contact fatigue test, and the predictions are all within a factor of 1.5 scatter band of the experimental results. This work provides an effective method for life prediction with small sample sets.

Effect of manganese phosphate conversion coating with different crystal sizes on fatigue life of 20MnCrS5 steel helical gears

Fatigue pitting is the main failure form of automatic transmission gear at present. In this paper, the contact stress of the tooth surface under different coefficients of friction is calculated by the finite element method. The contact fatigue test and transmission performance were carried out on the 20MnCrS5 helical gears after carburizing with different thicknesses of manganese phosphate conversion coating by a special gear test bench. And the influence of the solid lubricating coating on gear contact fatigue performance was deeply discussed. The results show that the contact fatigue life of the gear treated by manganese phosphate conversion coating is improved by more than 100 %, and the manganese phosphate coated gear with a thickness of 12 µm has a higher fatigue life.

Interaction Between Gear Surface Wear and Contact Fatigue

Abstract A methodology is proposed to study the interplay between tooth wear and contact fatigue under elastohydrodynamic lubrication condition. The modeling methodology includes the influence of contact fatigue on wear and the influence of wear on contact fatigue. First, the changes in film pressure and film thickness of oil at each meshing point caused by contact fatigue are introduced according to the surface wear model, and the change of wear model is analyzed to study the effect of contact fatigue on wear. Then, according to the elastohydrodynamic lubrication theory, the change in film pressure affected by tooth surface wear is analyzed to study the effect of wear on contact fatigue. Finally, the influence of lubrication conditions on the interplay between tooth surface wear and contact fatigue is analyzed. In addition, an experimental fatigue study is performed and introduced into the model predictions to improve the accuracy of the proposed methodology.

Vibration and control optimization of pressure reducer based on genetic algorithm

Abstract A research challenge of vibration and control optimization of pressurized reducer is solved in this article; a method based on genetic algorithm (GA) is proposed to optimize the vibration and control of reducer. Considering the bending strength of helical gear root and tooth surface contact fatigue strength as constraints, the improved GA is used to solve it, and the optimal parameter combination is obtained. The size of center distance is reduced by 9.59% compared with that before. Based on the optimized results, the vibration becomes weaker with the increase of the load at the output end of the reducer, and its maximum value is only 1/8 of that when the load is 550 N. The experimental results show the optimized surface load distribution of driving gear teeth. The maximum normal load per unit length of the optimized output stage driving gear surface is 521.321 N/mm, which is significantly lower than the 662.455 N/mm before optimization. At the same time, the tooth surface load is evenly distributed. The larger tooth surface load is mainly distributed in the middle of the tooth surface with strong bearing capacity, which effectively solves the problem of unbalanced load before optimization and improves the bearing capacity of gear transmission. It is proved that GA can effectively realize the vibration and control optimization of pressurized reducer.

Gear contact fatigue life prediction based on transfer learning

The gear contact fatigue test is characterised by extraordinarily high costs and a long period of testing. A transfer learning algorithm was applied to develop a gear contact fatigue life prediction strategy to fully use other low-cost fatigue test data, such as twin-disc test data. The twin-disc contact fatigue test data were incorporated into the neural network model to explore the combined effects of surface integrity and stress level on fatigue life, which was further transferred for gear contact fatigue life prediction. The results indicate that this method enables an effective gear fatigue life prediction under minor gear sample conditions. With a small sample amount of 7, the prediction error in the fatigue life of the model with transfer learning is 46.33%, while the typical back-propagation neural network (BPNN) model without transfer learning is 101.66%. To control life prediction error to within 50%, the model without transfer learning requires at least 17 gear samples, while the transfer model calls for only 7 gear samples. The proposed data transfer learning framework can be used to predict the gear contact fatigue S-N curve under minor sample conditions and is straightforwardly applied to extended applications.

A novel prediction approach of polymer gear contact fatigue based on a WGAN‐XGBoost model

AbstractPolymer gears have long been used on power transmissions with the fundamental durability data, including fatigue S‐N curves, yielding important data informing reliable and compact designs. This paper proposed a prediction method for polyformaldehyde (POM) gear fatigue life based on the innovative WGAN‐XGBoost algorithm. The findings generated herein revealed that the proposed method performs well in terms of prediction accuracy. The predicted fatigue lives, analyzed under different loading conditions, were within 1.5 times dispersion band compared with experimental results. Furthermore, based upon the enhanced fatigue dataset, a thermo‐mechanical coupled prediction formula for POM gear contact fatigue life was proposed. These findings offered a new approach for high‐power density design of polymer gears.

Progressive Downsampling Transformer With Convolution-Based Decoder and Its Application in Gear Pitting Measurement

In Transformer for semantic segmentation, patch embedding usually has only one convolutional layer with a large stride, leading to the decrease of feature extraction capability. Additionally, the complex decoder results in high computation cost. To address above-mentioned two issues, we put forward a progressive downsampling Transformer with convolution-based decoder (PDCDT), which is a simple, efficient yet powerful framework. Specifically, progressive downsampling layers for patch embedding are designed to refine the extracted features and reduce information loss at each stage of the hierarchical Transformer encoder. Meanwhile, a simple decoder based on a convolution (conv) module is proposed for aggregating the characteristic information from multiscale output layers of the encoder, and it can realize dimensional transformation and information interaction with fewer parameters than the decoders used in the existing Transformers. Extensive experiments show that PDCDT achieves competitive results on ADE20K (47.9% mIoU) and Cityscapes (82.6% mIoU). Finally, PDCDT is applied to gear pitting measurement in gear contact fatigue test, and the comparative results indicate that PDCDT can improve the accuracy of pitting detection.

Numerical and experimental research of helical gear contact stress considering the influence of friction

Helical gears are widely used in various mechanical transmissions. Thus, analysing gear contact stresses is crucial to improve the fatigue limit and life of gears. In this paper, the contact stress of helical gear is analyzed by finite element simulation and experimental verification. The effect of coefficient of friction on the contact stress of helical gears is analysed, with given coefficients of friction. The following conclusions can be drawn through simulation and test. 1) The contact stress increases with the coefficient of friction in the early stage of meshing. 2) The contact stress decreases with the increase in the coefficient of friction in the late stage of meshing. 3) The gear contact fatigue test shows that the location of fatigue pitting on the tooth surface is consistent with that of the simulated maximum stress point. The friction-reducing coating on the gear surface can decrease the coefficient of friction between the tooth surfaces and thus effectively improve the gear contact fatigue life.

U-shaped Vision Transformer and Its Application in Gear Pitting Measurement

Although convolutional neural networks (CNNs) have become the mainstream segmentation model, the locality of convolution makes them cannot well learn global and long-range semantic information. To further improve the performance of segmentation models, we propose u-shaped vision Transformer (UsViT), a model based on Transformer and convolution. Specifically, residual Transformer blocks are designed in the encoder of UsViT, which take advantages of residual network and Transformer backbone at the same time. What’s more, transpositions in each Transformer layer achieve the information interaction between spatial locations and feature channels, enhancing the capability of feature learning. In the decoder, for enhancing receptive filed, different dilation rates are introduced to each convolutional layer. In addition, residual connections are applied to make the information propagation smoother when training the model. We first verify the superiority of UsViT on Automatic Portrait Matting public dataset, which achieves 90.43% Acc、95.56% DSC and 94.66% IoU with relatively fewer parameters. Finally, UsViT is applied to gear pitting measurement in gear contact fatigue test, and the comparative results indicate that UsViT can improve the accuracy of pitting detection.