Effect of machined surface texture on fretting crack nucleation under radial loading in conformal contact

Gu, Hairong; Li, Jiao; Pei, Yan; Liang, Jianhua; Qiu, Tianyang; Liu, Zhibing; Wang, Xibin

doi:10.1016/j.triboint.2020.106575

Cited by 19 publications

(20 citation statements)

References 39 publications

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“…It was also found that negatively skewed surfaces of smooth [ 76 ] and rough [ 77 ] discs led to a reduction in friction and to a decrease in wear under dry sliding conditions. Gu et al [ 78 ] found that the surface with positive skewness caused fretting crack nucleation. Chang and Jeng [ 75 ] found that skewness of —1 caused a decrease in the friction coefficient under boundary lubrication up to two times in comparison with the surface of Gaussian ordinate distribution.…”

Section: Height Parametersmentioning

confidence: 99%

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Functional Importance of Surface Texture Parameters

2021

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Areal 3D analysis of surface texture gives more opportunities than a study of 2D profiles. Surface topography evaluation, considered as 3D dimensional analysis in micro or nanoscales, plays an important role in many fields of science and life. Among many texture parameters, those connected with height are the most often used. However, there are many other parameters and functions that can provide additional important information regarding functional behaviour of surfaces in different applications. The knowledge about the functional importance of various surface properties is low. This review tries to fill this gap. Surface texture parameters are presented in various groups: height, spatial, hybrid, functional, feature, and others. Based on experiences of the present authors and literature review, the relationships among various surface parameters and functional properties are described. A proposal of a selection of parameters on the basis of their functional significations is provided. Considerations for future challenges are addressed.

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Section: Height Parametersmentioning

confidence: 99%

“…Chang and Jeng [ 75 ] found that skewness of —1 caused a decrease in the friction coefficient under boundary lubrication up to two times in comparison with the surface of Gaussian ordinate distribution. The tested surfaces [ 72 , 73 , 74 , 75 , 76 , 77 , 78 ] were not highly skewed.…”

Section: Height Parametersmentioning

confidence: 99%

Functional Importance of Surface Texture Parameters

2021

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“…To comply with the widely presented conformal contact situations and the previous works, 19,21,29 the pin‐hole contact case is employed. Since the contact zone length is about 10 mm 21 while the thickness of the specimen is 2.5 mm, and the direction of load is perpendicular to the thickness of the specimen, the fretting fatigue test apparatus (Figure 1A) was simplified as the two‐dimensional (2D) plane stress pin‐hole contact finite element model as shown in Figure 1C.…”

Section: Methodsmentioning

confidence: 99%

“…Gao et al 28 found that beneficial surface roughness and compressive residual stresses were considered to contribute to fatigue performance improvement. Gu et al 29 found that the higher surface skewness and kurtosis values tend to promote nucleation of fretting fatigue cracks, and the nucleation side of fretting fatigue crack is related to the angle between the direction of machining‐induced material flow and the tangential component of the contact force. However, the effect of the surface skewness and kurtosis on the fretting crack behaviors has not been quantitatively discussed.…”

Section: Introductionmentioning

confidence: 99%

Numerical simulation of the effect of surface microgeometry and residual stress on conformal contact fretting fatigue crack initiation behavior

Song

Pei

et al. 2023

Fatigue Fract Eng Mat Struct

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Conformal contact is a commonly presented contact form in assemblies. Nonproportional loading is the main characteristics of conformal contact, which leads to prominent difficulty in revealing fretting crack behavior. In this paper, a finite element prediction model for Ti-6Al-4V pin-hole contact fretting fatigue crack initiation was developed, which simultaneously considered the effect of fretting wear, surface roughness, surface skewness, surface kurtosis, and residual stress. The results show that phase differences of stress component, change in direction of principal stress, and high stress gradient are the main reasons for the initiation of fretting fatigue under conformal contact condition. The model based on the Fatemi-Socie (FS) parameter successfully predicted the location, orientation, and fatigue life of crack initiation, which agrees well with the experimental results. Additionally, machining-induced residual stress can effectively inhibit mode I crack initiation at valleys. Moreover, ignoring the surface microgeometry characteristics reduces the prediction accuracy of the crack behavior.

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“…Surface roughness and tool wear are two of the most important in-process parameters, which are related to the machining accuracy and efficiency of the parts. As an important evaluation index of machined surface quality, surface roughness affects the working state of mechanical parts in the assembly [1], the fatigue strength, and creep life of the parts [2,3]. In addition, the machining precision, machining efficiency, and surface integrity will be affected by the tool wear conditions.…”

Section: Introductionmentioning

confidence: 99%

A Novel Multi-Task Learning Model with PSAE Network for Simultaneous Estimation of Surface Quality and Tool Wear in Milling of Nickel-Based Superalloy Haynes 230

Cheng

Jiao

Yan

et al. 2022

Sensors

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For data-driven intelligent manufacturing, many important in-process parameters should be estimated simultaneously to control the machining precision of the parts. However, as two of the most important in-process parameters, there is a lack of multi-task learning (MTL) model for simultaneous estimation of surface roughness and tool wear. To address the problem, a new MTL model with shared layers and two task-specific layers was proposed. A novel parallel-stacked auto-encoder (PSAE) network based on stacked denoising auto-encoder (SDAE) and stacked contractive auto-encoder (SCAE) was designed as the shared layers to learn deep features from cutting force signals. To enhance the performance of the MTL model, the scaled exponential linear unit (SELU) was introduced as the activation function of SDAE. Moreover, a dynamic weight averaging (DWA) strategy was implemented to dynamically adjust the learning rate of different tasks. Then, the time-domain features were extracted from raw cutting signals and low-frequency reconstructed wavelet packet coefficients. Frequency-domain features were extracted from the power spectrum obtained by the Fourier transform. After that, all features were combined as the input vectors of the proposed MTL model. Finally, surface roughness and tool wear were simultaneously predicted by the trained MTL model. To verify the superiority and effectiveness of the proposed MTL model, nickel-based superalloy Haynes 230 was machined under different cutting parameter combinations and tool wear levels. Some other intelligent algorithms were also implemented to predict surface roughness and tool wear. The results showed that compared with the support vector regression (SVR), kernel extreme learning machine (KELM), MTL with SDAE (MTL_SDAE), MTL with SCAE (MTL_SCAE), and single-task learning with PSAE (STL_PSAE), the estimation accuracy of surface roughness was improved by 30.82%, 16.67%, 14.06%, 26.17%, and 16.67%, respectively. Meanwhile, the prediction accuracy of tool wear was improved by 46.74%, 39.57%, 41.51%, 38.68%, and 39.57%, respectively. For practical engineering application, the dimensional deviation and surface quality of the machined parts can be controlled through the established MTL model.

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Effect of machined surface texture on fretting crack nucleation under radial loading in conformal contact

Cited by 19 publications

References 39 publications

Functional Importance of Surface Texture Parameters

Functional Importance of Surface Texture Parameters

Numerical simulation of the effect of surface microgeometry and residual stress on conformal contact fretting fatigue crack initiation behavior

A Novel Multi-Task Learning Model with PSAE Network for Simultaneous Estimation of Surface Quality and Tool Wear in Milling of Nickel-Based Superalloy Haynes 230

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