Abstract
PREDICTION OF FIBER BREAKAGE AND MATRIX CRACKING IN POLYMERIC COMPOSITES UNDER LOW-CYCLE FATIGUE REGIMES BY FUZZY AND WAVELET CLUSTERING OF ACOUSTIC EMISSION SIGNALS
Highlights
Today, for the engineering industry, the demand for materials that are highly efficient is considered important and the need for advanced materials and the production processes is felt
Analysis Methods In this research, the fast Fourier transform (FFT), the wavelet packet transforms, and fuzzy clustering methods were used to investigate the condition of structures by the acoustic emission signal processing and to determine the structural health monitoring (SHM) or the damage detection
Fast Fourier Transform (FFT) For the signal frequency analysis, one of the analysis methods is discrete Fourier transform (DFT), in which the fast Fourier transform is a method to reduce the amount of computations
Summary
For the engineering industry, the demand for materials that are highly efficient is considered important and the need for advanced materials and the production processes is felt. Perhaps the most important requirements are the use of high-performance materials, low weight and relatively low price. Among these materials are composites that are widely used in the industry. Various defects occur in composite structures that require constant monitoring and the prevention of any damage. Due to the small size of the primary defects and the impossibility of the visual inspection, nondestructive tests (NDT) are used to detect and identify these defects [1,2,3,4,5]. NDT methods such as; radiography, ultrasonic testing, and penetrant testing are used traditionally for identifying defects, each one having advantages and disadvantages, making it more or less appropriate for a given application [6,7,8,9,10]
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