Initiation Life Prediction Method for Defective Materials

Saggar, Maroua; Nasr, Anouar; Bouraoui, Chokri

doi:10.1007/978-3-030-24247-3_3

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…Therefore, it is difficult to accurately determine the number of cycles for the crack initiation. In general, the fatigue life of a component is influenced by some external factors such as temperature and surface finish 1,2,5,6 …”

Section: Introductionmentioning

confidence: 99%

“…In general, the fatigue life of a component is influenced by some external factors such as temperature and surface finish. 1,2,5,6 It is well known that the last stage of the manufacturing process is the surface finishing, and it determines the surface topography of a machined part. The surface finishing is known as a fingerprint of the manufacturing process because it plays a major role in lubricant retention, sealing, wear resistance, friction, and fatigue.…”

Section: Introductionmentioning

confidence: 99%

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Feature selection of surface topography parameters for fatigue‐damage detection using Pearson correlation method and neural network analysis

Alqahtani

Ray

2023

Fatigue Fract Eng Mat Struct

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The global objective of this study was to investigate the best features of the surface topography for fatigue‐damage detection and classification. The presence of the stress concentration in valleys of the surface topography causes a grain slip and a crack initiation at the surface of the machined structure and finally leads to fatigue failures. Therefore, the surface topography has a major influence on the fatigue strength of the machined structure. An optical confocal measurement system (Alicona) was applied to measure six surface topography parameters. In this paper, feature selection using the Pearson correlation method was adopted to select the best surface textures that provide best the neural network (NN) model performance. The NN model is capable of detecting and classifying the damage with an accuracy of up to ∼ 94.4%.

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Section: Introductionmentioning

confidence: 99%