Wear Model Research Articles

Nonlinear dynamic characteristics of mechatronics integrated planetary gears considering wear and temperature effects

The electromechanical planetary gear system has high work efficiency and long service life, but factors such as heat, wear, and electrical signals can affect the transmission performance of electromechanical planetary gears. This article comprehensively considers factors such as temperature, tooth surface wear, lubrication, current and voltage, damping ratio, etc. Based on the principle of thermal deformation, Archard wear model, and equivalent circuit principle, a dynamic model of electromechanical planetary gears is established. The existing literature has not comprehensively analyzed the effects of temperature, wear, and electrical signal changes on the nonlinear characteristics of electromechanical planetary gear systems. The results show that when the motor current is between 7 A and 18 A and the voltage is lower than the rated voltage, the system is in a stable state; as the temperature rises, the system tends to stabilize; the gear wear exceeds 30 μm, and the bifurcation characteristics of the system are more pronounced.

Friction and wear properties of wide-velocity range high-energy plasma sprayed CuSn–NiCr solid self-lubricating coatings under heavy load

As one of important copper-based solid self-lubricating coatings, the low wear resistance of Cu–Sn coatings greatly limits its application in some heavy-duty cases. In the present work, two types of CuSn–NiCr composite powders designed by electroless plating (E-CN) and mechanical mixing (M − CN) methods, respectively. The friction and wear properties of wide-velocity range high-energy plasma sprayed CuSn–NiCr coatings were studied. The results suggested that, the fracture toughness of E-CN and M − CN coatings increased by 1.38 times and 1.55 times compared with as-sprayed Cu–Sn coatings, and the wear rate decreased by 29 % and 50 % correspondingly. Due to the tribofilm formation and micro-pores storage effect, the M − CN coating with 10 wt% addition ratio of Ni–Cr phase exhibited the lowest friction coefficient and the smallest wear rate. With the increase of Ni–Cr phase, the wear mechanism was transformed from adhesive to abrasive, and accompanied by fatigue step-shaped spallation. Friction and wear model of the CuSn–NiCr coatings was divided into rapid, stable and declining stages.

Simulation of fretting wear in steel wires under variable coefficient of friction and variable wear coefficient

In this paper, the fretting wear behaviour of steel wires working in coal mining technology is studied numerically. In past studies, the fretting process of steel wires was carried out numerically considering that the coefficient of friction (COF) and wear coefficient (WC) are constant parameters. However, it has been noticed experimentally that COF increases up to a certain number of fretting cycles and then becomes constant, i.e. a steady-state stage, depending on the loading conditions. This increase in COF during the fretting process is also known as the running-up stage. The fretting wear model is modified to evaluate the influence of the varying coefficient of friction (VCOF), which is associated with the variable wear coefficient (VWC), so the influence of VWC is also considered. The subroutine UMESHMOTION used to implement the wear law is also modified to study the effect of VCOF and VWC. Therefore, in this study, the numerical results of a three-dimensional finite element (FE) model are compared, with analytical results of contact area and contact stresses, and with experimental results of peak wear depth. After validating the FE model, the wear scar, the increasing wear depth, wear volume, and the decreasing contact stress with increasing fretting cycles are determined numerically considering VCOF and VWC using cycle jump approach. The energy dissipation effect of frictional force and fretting amplitude is also studied for varying interaction properties of fretting wear models. The numerical simulations are performed by considering both elastic and plastic material properties to analyse the influence of varying interaction properties on fretting wear models at the running-up stage. The results indicate that the VWC model exhibits comparable impacts on both the elastic and plastic models. The results also show that the VWC fretting wear model leads to higher wear scar, wear volume, and wear depth values at the running-up stage as well as at the steady state stage, which are close to the experimental data.

An improved energy wear model of three-dimensional ball-plane contact structure and its fretting wear dynamic behaviors study

This paper proposes a method that combines the finite element method with an improved energy wear model to establish a three-dimensional (3D) ball-plane contact structures fretting wear model. The correctness of the model was verified by Hertz contact theory and fretting wear experiments. Then, the fretting wear dynamic behaviors of 3D ball-plane contact structures were investigated in detail. The results show that when the contact structure is in the partial slip regime (PSR), the cross-sectional wear scar profile changes from the “W” shape to the “U” shape along the fretting direction. When the contact structure is in the gross slip regime (GSR), the cross-sectional wear scar profile always maintains a “U” shape along the fretting direction. In addition, it was also found in the study that when the contact structure is at GSR under a low normal load or PSR under a high normal load, it will help reduce wear. This study can provide significant theoretical guidance for reducing and protecting fretting wear in contact structures.

A novel wear prediction method and wear characteristic analysis of piston/cylinder pair in axial piston pump

The wear of the piston/cylinder pair in the axial piston pump is a significant factor that adversely affects pump performance. To conduct a thorough investigation into the wear characteristics of the piston/cylinder pair, a dynamic model based on the equivalent load method is established. Then, a novel wear prediction method for the piston/cylinder pair is proposed by integrating the Archard wear model. The validity of the proposed method is confirmed through experimental verification. The results demonstrate that specific circumferential areas of the cylinder bore exhibit severe wear, and the distribution of these areas remains relatively stable over time. At the swash plate side, the most severe wear area along the circumference direction is concentrated in the range of approximately 200°–320°, which means the area that deviates from the extreme position in the radial direction of the pitch circle by a specific angle, with the deviation direction being opposite to the rotational speed. Conversely, at the valve plate side, the most severely worn circumferential area is situated in the range of about 0°–120°, which is opposite to the area at the swash plate side. The proposed wear prediction method offers improved computational efficiency, providing valuable support for analyzing the wear characteristics and failure mechanisms of piston pumps.

Discrimination of wear performance based on surface roughness parameters arithmetic mean height (Sa) and skewness (Ssk)

Enhancing interfacial contact bearing performance typically involves minimizing the roughness parameter Sa (arithmetic mean height). Yet, exceedingly low Sa incur steep increases in processing costs, indicating that Sa-centric optimization strategies may not be universally suitable for interface performance control. Roughness parameters skewness (Ssk) and kurtosis (Sku) exert a pronounced influence on component contact wear performance. Accordingly, investigating the correlation between Ssk, Sku, and wear performance holds significant promise for enhancing wear resistance. A finite element wear calculation model for rough-surface abrasive wear employing elastic-plastic contact mechanics and the Jump-in-Cycle method. Cylindrical roller dry sliding experiments validate the model's reliability. Integrating this model, a method is proposed for wear performance discrimination based on Sa and Ssk at different loads. It enables the identification of critical roughness parameter values for improved surface wear resistance. The calculated wear model aligns with experiment trends, with predicted surface textures mirroring observed wear surface characteristics. Critical Sa and Ssk diverge under distinct loads. The study underscores the importance of moving beyond the exclusive pursuit of exceptionally low Sa and Ssk. It provides a foundation for reducing workpiece processing costs while optimizing wear performance.

Investigation of curve minimum radius in heavy-haul railway to improve wheel wear evolution and wheel-rail contact geometry

To determine the minimum and reasonable radius of horizontal curve for reducing wheel wear in heavy-haul railway design, a HXD locomotive with the wheel arrangement of C0-C0 is taken as the research object. Both the corresponding locomotive dynamic model and wheel wear model are established. Based on the measured wear data in a specific line, the simulation model is verified with the prediction error of wheel wear depth below 0.5 mm in general. The wheel wear evolution rules in 400∼1000m radius curves are studied and compared. The results indicate that, the wheel wear is large and sensitive to curve radius within 400∼600 m. The larger radius curve will be helpful to reduce wheel flange contact and wheel wear. For curve radius increasing from 600m to 1000m, the wheel average wear reduces slowly. Especially for curve radius below around 740 m, the wheel flange wear will be predominant. For radius above 740m, the wheel tread wear becomes the main wear form and the wheel flange wear can be reduced significantly. The increase of curve radius will also improve the wheel-rail equivalent conicity. If the minimum curve radius is set as 800m, the equivalent conicity difference between new wheelset and 1st ∼ 3rd worn wheelset can be kept below 21%, 52% and 9% respectively. In this case, the equivalent conicity is closest to the initial state and reaches a steady state, which will not change significantly with the radius further increasing. Viewed from the aspects of reducing wheel wear, avoiding wheel flange contact and keeping conicity stable simultaneously, the minimum radius of horizontal curve should be limited to 800 m. The research results validate the minimum curve radius suggested in Code for Design of Heavy-haul Railway in China, and provide a scientific explanation for the determination of this value.

Research on Prediction Methods for Eccentric Wear of the Slipper Pair in Axial Piston Pumps and Lubrication Performance Analysis

Abstract The axial piston pump (APP) is the core power component of hydraulic systems. Its friction pair wear can cause the degradation of piston pump performance until the function is completely lost or the service life is terminated. The slipper pair, prone to wear failure, is selected as the research object in this paper. The prediction method for the eccentric wear of the slipper pair is established, and the gradual change rules of the performance with wear accumulation are explored. The micro-surface rough peak contact and the stress state of the slipper pair are analyzed, and the mixed lubrication model of the slipper pair is established based on the elastohydrodynamic lubrication (EHL) model of the slipper pair. Grid discretization of a sealing belt of the slipper pair is carried out based on two-body abrasive wear and Archard adhesive wear models to improve the prediction method for eccentric wear of the slipper pair. The effectiveness of the proposed method is verified by a surface morphology analysis of the worn slipper. The results showed that the wear depth and wear width of the outer edge of the slipper bottom surface are positively correlated with the oil discharge pressure and the inclination angle of the swashplate, and negatively correlated with the rotational speed and the dynamic oil viscosity. The outer edge of the slipper is wedged after eccentric wear, and the hydrodynamic effect of the lubricating oil film of the slipper pair is enhanced. Hence, proper wear can improve the lubrication performance of the slipper pair.

Design of experiments integrated with neural networks for optimization and predictive modelling of electrode wear of novel Ti-6Al-4V-SiCp composites during die sinking electric discharge machining

Die Sink Electric Discharge Machining is a widely used manufacturing process for shaping hard and electrically conductive materials. This study investigates the effects of various electrode materials such as, Ti-6Al-4V-SiCp, Brass and Copper on the machining performance of AISI 316 l Stainless Steel workpieces using EDM. The methodology involved optimizing parameters such as Electrode Material, Discharge Current, Gap Voltage, Spark Gap, Pulse-on Time, and Pulse-off Time. From the extensive experimantation it was observed that the combination of Ti-6Al-4V-SiCp electrode material, 8Amp Discharge Current, 90 V Gap Voltage, 75 μm Spark Gap, 100 μs Pulse-on Time and 15 μs Pulse-off Time has resulted in lowest electrode eear rate, higher machining time, and low electrode surface roughness ratio. Ti-6Al-4V-SiCp electrodes possess higher hardness and electrical conductivity compared to Brass and Copper Electrodes leading to higher wear resistance against repeated thermal shocks during electric discharge machining operation. Feed Forward Artificial Neural Network is successfully applied to predict the output characteristics of the experimentation with high accuracy of 98.3% (Electrode Wear Rate), 94.6% (Machining Time) and 93.8% (Electrode Surface Roughness Ratio). Further, microstructure analysis concludes that lowest wear is observed in Ti-6Al-4V-SiCp electrodes compared to Brass and Copper electrodes.

Physics based models for characterization of machining performance – A critical review

This paper presents a comprehensive review of the concept of machinability by considering the dynamic, tribological, and thermo-mechanical interactions encountered at the tool-chip-machined surface interfaces. The paper provides a demonstration of the capabilities and gaps of the physics-based models for the characterization of the machining performance and the prediction of machinability of difficult-to-cut materials, including additively manufactured (AM) materials, nanocrystalline (NC) materials, fibre reinforced polymers (FRP), metal matrix composites reinforced with ceramic hard particles (MMC), and ceramic matrix composites (CMC). The utilization of efficient computation methods for accurate prediction of force, torque, power consumption, cutting temperature, deflection errors, vibration amplitudes, chatter stability, and thermomechanical interactions in the tool-workpiece system is discussed. The development of thermally-activated dissolution-diffusion wear models to describe the chemical reactions at the tool-chip-workpiece contact interfaces is also presented. These predictions are critical for identifying multi-objectives optimal machining conditions. The integration of predictive machining models within the framework of digital twins in cyber-physical spaces, for in-process monitoring and adaptive control, is demonstrated. Future research for developing new models that can characterize the machinability of AM and NC materials, by considering the effects of varying material microstructure and anisotropy, is presented for conventional and micro-machining operations.

Effect of rotation of abrasives on material removal in chemical mechanical polishing using a proposed three-body model: Molecular dynamics simulation

A three-body wear model, comprising a soft polyurethane pad, silica abrasive, and crystalline silicon substrate, was established to analyze the impact of abrasive rotation on material removal process during chemical mechanical polishing (CMP) through molecular dynamics simulation. The results revealed that abrasive rotation would reduce the local temperature in the contact area between the abrasive and the substrate due to the cooling effect, thereby enhancing the surface quality of the substrate and decreasing the material removal volume (MRV). However, another effect of abrasive rotation, termed the "hedgehog effect", resulting in an increase in MRV. Through the trade-off between the cooling effect and the porcupine effect, the abrasive rotation can not only improve surface quality but also increase the MRV.

Influence of main operating conditions on contact wire wear of rigid catenary lines

A validated overhead conductor rail and a well-known wear model have been programmed to perform closer-to-reality simulations. Reliable wear rate estimates for two configurations of overhead conductor rails and three models of pantographs at different speeds and supply currents have been obtained. Results show that wear decreases with increasing speed at high currents and when the distances between supports are uniform. In addition, the use of different types of pantographs in the same facility has a positive effect in terms of wear reduction. Consequently, an adequate selection of the operating conditions contributes to reducing the wear rate.

Influence of flange deflection wear and the economy-oriented reversing control policy

In this paper, we describe the phenomenon of deflection wear of the wheel flange and analyze the causes according to actual line conditions, and the influence of deflection wear of wheel flange is analyzed from the perspective of safety and economy of trains by combining dynamic modeling and simulation. The degree of deflection wear of wheel flange is divided into different grades. Based on the reliability-cost function, the influence of economy is quantified and introduced into the analysis of deflection wear as an index. We establish an economic model of flange deflection wear and cutting amount of reprofiling (FDW-CA). Based on the deflection wear prediction model and FDW-CA model, we model the economy-oriented reversing control policy. To verify the feasibility and validity of the control policy. The measured data before and after the reversing policy are analyzed. The results indicate that the cutting amount of wheelset is reduced from 11.2 to 6.6 mm on average for single reprofiling, and the saving is more than 40%. The reversing control policy can reduce the cutting amount of wheelset, reduce the limit probability of wheelset, extend the life of the wheelset, and reduce the operation and maintenance cost of the wheelset, and further provide basis for wheelset spare planning.

Machine Tool Wear Prediction Technology Based on Multi-Sensor Information Fusion.

The intelligent monitoring of cutting tools used in the manufacturing industry is steadily becoming more convenient. To accurately predict the state of tools and tool breakages, this study proposes a tool wear prediction technique based on multi-sensor information fusion. First, the vibrational, current, and cutting force signals transmitted during the machining process were collected, and the features were extracted. Next, the Kalman filtering algorithm was used for feature fusion, and a predictive model for tool wear was constructed by combining the ResNet and long short-term memory (LSTM) models (called ResNet-LSTM). Experimental data for thin-walled parts obtained under various machining conditions were utilized to monitor the changes in tool conditions. A comparison between the ResNet and LSTM tool wear prediction models indicated that the proposed ResNet-LSTM model significantly improved the prediction accuracy compared to the individual LSTM and ResNet models. Moreover, ResNet-LSTM exhibited adaptive noise reduction capabilities at the front end of the network for signal feature extraction, thereby enhancing the signal feature extraction capability. The ResNet-LSTM model yielded an average prediction error of 0.0085 mm and a tool wear prediction accuracy of 98.25%. These results validate the feasibility of the tool wear prediction method proposed in this study.

Multi-objective optimisation of a metro wheel profile to reduce wheel flange wear and RCF considering the distribution density of wheel−rail contact points

In this study, the problem of severe wheel flange wear and tread rolling contact fatigue (RCF) of metro wheels with two wheel profiles, i.e. the LM-30 profile and the DIN5573-30 profile, is investigated. The contact characteristics of the two profiles are compared to analyse the causes of wheel flange wear and RCF. Indices combining the density distribution of contact points are proposed to evaluate the wheel flange wear and RCF. The optimisation region of the wheel profile is defined by eight arc parameters, which is derived from the tangency of the arcs. A back-propagation neural network is constructed as a surrogate model for the design variables and the objective function. Four intelligent optimisation algorithms are compared and used to solve the optimisation problem. The vehicle—track dynamic model and the wheel wear and RCF prediction model are used to verify the performance of the optimised profile. The results show that the critical speed of the optimised profile is between that of the LM profile and that of the DIN5573 profile, and the curving performance of the optimised profile is significantly improved. At the same time, the optimised wheel profile can reduce wheel flange wear and tread RCF.

A Computational Model for Analysing the Dry Rolling/Sliding Wear Behaviour of Polymer Gears Made of POM.

This study presents a computational model to determine the wear behaviour of polymer gears. Using PrePoMax finite element numerical calculation software, a proposed computational model was built to predict dry rolling/sliding wear behaviour based on Archard's wear model. This allows the calculation of the wear depth in each loading cycle with constant mesh updating using the finite element method. The developed computational model has been evaluated on a spur gear pair, where the pinion made of POM was meshed with a support gear made of steel. The computational results obtained were compared with the analytical results according to the VDI 2736 guidelines. Based on this comparison, it was concluded that the proposed computational model could be used to simulate the wear behaviour of contacting mechanical elements like gears, bearings, etc. The main advantage of the model, if compared to the standardised procedure according to the VDI 2736 guidelines, is the geometry updating after a chosen number of loading cycles, which enables a more accurate prediction of wear behaviour under rolling/sliding loading conditions.

Wear evaluation of hard disk drive head based on a converter-like neural network

Hard disk drives (HDDs) are indispensable industrial products in modern information society, with their heads playing a critical role in read/write performance, which is directly affected by head wear. Head wear at nanoscale challenges the applicability of traditional macroscopic physical wear models, necessitating innovative solutions for accurate wear estimation. Data-driven methodologies have emerged as an effective paradigm, yet facing limitations when addressing the multiple phases of head wear degradation. Herein, building on insights into nanoscale wear and interface dynamics, we devised a "converter" module. Simultaneously, a physical constraint is incorporated into the network to guarantee the physical compliance consistency of wear outcomes. The effectiveness of this method is validated on real worn heads. An interpretive analysis is performed, involving the visualization of GRU module's hidden units and the quantification of feature’s activity contribution. Our investigations revealed that the converter results in a higher proportion of neurons becoming actively engaged and discriminative in wear evaluation, thereby enhancing the network's sensitivity to wear-related variations. Meanwhile, the trace ratios of scatter indicate that the converter improves the discriminability of the input data, thereby bolstering the network's capacity to differentiate between wear states.

Research on Cutting Edge form Factor of Milling Tool after Drag Finishing Preparation Based on Discrete Element Method

Cutting edge preparation is a precision machining process that improves the surface quality of cutting tools through the relative movement of abrasives and the tool. Research on removing materials in drag finishing can be greatly beneficial to tool manufacturing. This paper proposes the hypothesis that both abrasive wear and erosion wear act on the surface of milling tools and discusses the material removal models for abrasive wear and erosion wear. The influence of immersion depth, abrasive velocity, abrasive radius, and abrasive density on the material removal rate in two material removal forms is compared and validated by discrete element simulations. The results show that immersion depth has a greater impact on abrasive wear, while abrasive properties have a greater impact on erosion wear. The correlation between simulation results and theoretical models demonstrates the sensitivity of the two forms of wear on this surface to parameter change differences. Dragging finishing was conducted to verify the effectiveness of the simulation, and the effects of immersion depth, dragging velocity, and abrasive properties on the edge radius and form factor (K value) were studied.

Launching dynamics of terminal guidance projectile considering barrel erosion and mechanical wear

This paper simulates the launching dynamics of the Terminal-guidance projectile considering the barrel thermo-chemical erosion wear and mechanical wear. A thermochemical erosive material degradation model that considers the rise in friction temperature is first introduced. Moreover, the wear state of barrel rifling at different periods is calculated using the erosion wear model. A three-dimensional model of the worn barrel is established, and the coupled barrel– terminal-guidance projectile launch dynamics are simulated for different wear periods. Finally, the projectile's bore overload and attitude are analyzed to explore the effect of barrel wear on launch.

Wheel-rail contact wear analysis on curved lubricated track for heavy haul locomotive studies

The effect of lubrications on a curved track to heavy-haul wheel-rail contact wear is studied. To analyse wheel-rail contact wear damage due to existing high-adhesive AC locomotive, a methodology for investigation is proposed, and the locomotive models are required to run at 20 km/h under maximum traction efforts, and the simulations include a DC locomotive for comparison. An extended creep force model, which was developed by Polach and has been widely used for the wheel-rail contacts under dry and wet conditions with variable friction coefficients, is further extended to apply for the typical low-coefficient-friction modifier, oil, and grease lubricant conditions. The wear models from two pairs of wheel-rail materials are used to predict the wear rates, and the wear numbers Tγ are presented for discussions. The simulations show that the lubricants significantly reduce the wheel-rail contact wear.