Abstract
In order to investigate the variation of three‐dimensional metal surface topography during fatigue process, a three‐dimensional (3D) topography acquisition platform was built with an in situ tensile tester and a three‐dimensional profilometer. Q235 steel specimens were chosen as research objects, and the three‐dimensional surface topography information at various stages of fatigue damage was obtained. Through the characterization of three‐dimensional roughness, combined with surface height distribution and multifractal analysis, the variations of metal surface topography in the fatigue process were described. Results show that the arithmetic mean deviation of the surface (Sa), the width of the multifractal spectrum (Δα), and the mean value of surface height distribution (μ) and its standard deviation (δ) increase nonlinearly with the increase of fatigue cycles. The rate of fatigue damage is slow in the early stage and high in the middle and late stages. The surface height distribution amplitude (A) decreases with the increase of fatigue cycles, which indicates that the height data concentration decreases, and the metal surface becomes uneven. The Bayesian data fusion method was applied to establish a nonlinear mapping between the topography features and the damage, with the above five characteristic parameters (Sa, Δα, A, μ, and δ) as the data layer. Finally, a surface topography feature fusion method is proposed, and a case study is conducted to verify its applicability. The research results can provide reference for fatigue damage assessment.
Highlights
Metal surface topography is closely related to its fatigue strength and wear resistance, which affects the service life and reliability of components
By analyzing the data of 3D surface topography of the Q235 steel specimen during the fatigue damage process, it is found that the statistical characteristics of the above 3D topography, such as arithmetic mean deviation Sa, surface height distribution mean μ, and standard deviation δ. show obvious regular changes with the increase of fatigue cycles
In the process of low-cycle fatigue damage, significant plastic deformation will be generated during each cycle of loading, and its fatigue behavior can be related to plastic deformation and limited fatigue cycles. e fatigue damage process consists of three stages: microstructure evolution, crack initiation, and propagation, and the crack initiation life accounts for the majority of the total life. e low-cycle fatigue cracks preferentially nucleate in the persistent slip band (PSB) with the highest slip inhomogeneity and maximum strain localization. e slip produced by the PSB in the surface grains can be transferred in a large amount, and the phenomenon of Multifractal spectrum f (α)
Summary
Metal surface topography is closely related to its fatigue strength and wear resistance, which affects the service life and reliability of components. 2πσ the metal surface height in the fatigue process obeys the normal distribution, which is recorded as follows:. In equation (9), μ is the mathematical expectation (mean value) and the position parameter, which determines the location of the distribution, that is, the dominant numerical value of the surface height in the process of metal fatigue. In the Gaussian model, the mean and variance of fatigue damage states (i.e., cyclic loading cycles, corresponding to ci of equation (11)) are calculated, and the probability density function of normal distribution is obtained. According to the probability density function, the probability density value of continuous test data is calculated to obtain the prior probability. e posterior probability value corresponding to each fatigue damage state is obtained by substituting the probability density value into the posterior probability formula equation (14). e fatigue damage state corresponding to the maximum posterior probability value is the prediction result
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