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A Review of Localised Time-Frequency Features Classification Associated to Fatigue Data Analysis
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Abstract
The paper presents a review of the rational to perform the localised time-frequency fatigue damage feature classifications, which can be categorised as an alternative approach for fatigue life prediction that is relatively new in this research field. It is a good need to have a study in fatigue feature classification that lead to the formation of a new guideline and enable a design to the same reference level as well as high reliability towards the maximum usage. Consequently, this review paper emphasis on the concentration for performing the localised time-frequency feature classification approach as a scientific and engineering knowledge advancement in about fatigue of material and structures. Hence, related approaches to be said as the subject contents, i.e. fatigue life prediction models, signal processing approaches, the implementation of segmentation and clustering methods towards fatigue data, as well as data classification that lead for pattern recognition technique. It is known from the literature about the selection of the appropriate approaches which were often based on the analyst’s experience and preferences. By predicting the structure fatigue life, which needs only several variable and will automatically calculate, classify and optimise the severity of fatigue damage through the significant mathematical and experimental findings, leading to cost and time saving.
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