Fracture mechanisms in rails with mechanically and thermomechanically-induced white etching layers under three-point bending

Nguyen, Ba Hieu; Al-Juboori, Ali; Zhu, Hong Tao; Gazder, Azdiar A.; Li, Huijun; Tieu, Kiet

doi:10.1016/j.engfailanal.2021.105813

Cited by 7 publications

(2 citation statements)

References 50 publications

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“…According to the method of three-point bending [26], several rail specimens were machined from the rail (material: U71Mn). The dimensions of the specimens were 230 × 43 × 20 mm 3 as shown in figure 2(a).…”

Section: Experimental Conditionsmentioning

confidence: 99%

Rail crack defect recognition based on a multi-feature fusion algorithm using electromagnetic acoustic emission technique

Chang

Zhang

Song

et al. 2023

Meas. Sci. Technol.

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Multi-feature fusion has been widely used to enhance recognition accuracy for different health stages of rail, which may lead to high-dimensionality and information redundancy of signal. In addition, conventional supervised methods require plenty of labeled samples with class information, which can lead to significant time and economic costs. In order to improve the effectiveness of the electromagnetic acoustic emission (EMAE) technique in rail crack defect recognition, a novel method including multi-feature fusion based on weakly supervised learning and recognition threshold construction, is proposed in this paper. First, a mechanism contains of multi-feature extraction and feature selection, is developed to fully reflect the information of different health stages of rail and avoid interference caused by the ineffective features. Then, the effective features and a novel weakly unsupervised label are input into the self-normalizing convolutional neural network and long short-term memory (SCNN-LSTM) model to construct the rail health indicator (RHI). Finally, the recognition threshold is calculated by the characteristics of RHI, to achieve crack recognition automatically. Furthermore, the experimental results under different working conditions demonstrate that the proposed method achieves higher recognition performance than other existing methods in rail crack defect recognition.

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Section: Experimental Conditionsmentioning

confidence: 99%

Rail crack defect recognition based on a multi-feature fusion algorithm using electromagnetic acoustic emission technique

Chang

Zhang

Song

et al. 2023

Meas. Sci. Technol.

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“…Most of these studies are concentrated on pearlite railways. Generally, the WEL mainly consists of ultra-fine martensite [1][2][3], fine grains of ferrite [2,4] or severe plastic deformation pearlite [5], and some retained austenite. Li [6] pointed out that the BEL may be a new microstructure on rail surfaces under real working conditions, and the features and formation of the BEL have not been studied clearly.…”

Section: Introductionmentioning

confidence: 99%

Formation Mechanisms and Crack Propagation Behaviors of White Etching Layers and Brown Etching Layers on Raceways of Failure Bearings

Zhang,

Wu,

Zhang

et al. 2024

Lubricants

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White etching layers (WELs) and brown etching layers (BELs), formed on the upper layer of bearing raceways generally lead to surface crack initiation and propagation and significantly affect the stable operation of precision bearings. In this study, the microstructure features of WELs and BELs from two failure bearings have been characterized and analyzed. The BEL mainly consists of quenched martensite with higher hardness values. The bainite simultaneously exists at the boundary of the BEL/matrix. Owing to the relative roll and slip, temperature increases and rapid decreases are the main formation mechanisms of the BEL in this study (thermal-induced effect). The WEL can be only found on one sample, and elongated and coarse grains are found in this region. It can be speculated that the WEL may originate from the surface region temperature increasing again and then slowly decreasing. Cracks can initiate at the boundaries of the WEL/BEL/matrix. The crack propagation behaviors are significantly affected by the properties of the WEL and BEL microstructure. It is difficult for the cracks to propagate from a softer WEL into a harder BEL. Thus, the depth of cracks in the WEL is shallower. However, because of the brittle nature of quenched martensite in the BEL, cracks can easily propagate downward under contact stress. Thus, the depth of cracks can exceed 100 μm easily. The formation mechanisms of the WEL/BEL and crack propagation behaviors have been further proved and discussed in this study.

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Modeling and optimization of flexural properties of FDM-processed PET-G specimens using RSM and GWO algorithm

Fountas

Papantoniou

Kechagias

et al. 2022

Engineering Failure Analysis

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Fracture mechanisms in rails with mechanically and thermomechanically-induced white etching layers under three-point bending

Cited by 7 publications

References 50 publications

Rail crack defect recognition based on a multi-feature fusion algorithm using electromagnetic acoustic emission technique

Rail crack defect recognition based on a multi-feature fusion algorithm using electromagnetic acoustic emission technique

Formation Mechanisms and Crack Propagation Behaviors of White Etching Layers and Brown Etching Layers on Raceways of Failure Bearings

Modeling and optimization of flexural properties of FDM-processed PET-G specimens using RSM and GWO algorithm

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