Inspection of Aboveground Pipeline Using Vibration Responses

One of methods for detecting cracks and estimating their growth in materials such as composites is the acoustic emission technique. The detection of damages, cracks and their growth in industrial composite structures, under static and dynamic loads, has a significant importance, in order to prevent any damages and increase the reliability. Therefore, achieving required technical knowledge in this field, can be helpful in repairing and the maintenance of the part in industries. The prediction of the damage in polymeric composites under static loads has been already investigated by researchers; however, under cyclic loadings, researches about this behavior are still rare. In this study, by acoustic emission sensors and analyzing experimental data, the damage, including matrix cracking, the fiber breakage and other damages (debonding, fiber pull-out and delamination) during dynamic loading was investigated. At the first stage, standard specimens were made by the pure resin epoxy and the pure carbon fiber, subjected to monotonic tensile loading and then, the frequency of the failure was extracted. Then, composite specimens were loaded in the low-cycle fatigue regime. Mechanical test results and acoustic emission data were analyzed by fuzzy C-Means and wavelet transform methods and then compared to each other to find the percentage of failures in first, mid- and last cycles by the differentiation of failure types. Results clearly indicated that the acoustic emission approach is useful and an effective tool for identifying and detecting damages in polymeric composites.

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“…By continuing to categorize data in pairs and using Relation (7), the computational order is reduced to 2 [26].…”

Section: Ifmentioning

confidence: 99%

Prediction of fiber breakage and matrix cracking in polymeric composites under low-cycle fatigue regimes by fuzzy and wavelet clustering of acoustic emission signals

Esfarjani

Azadi

Alizadeh

et al. 2021

Preprint

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show abstract

“…By continuing to categorize data in pairs and using Relation (7), the computational order is reduced to…”

Section: Fast Fourier Transform (Fft)mentioning

confidence: 99%

“…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].…”

Section: Introductionmentioning

confidence: 99%

Prediction of Fiber Breakage and Matrix Cracking in Polymeric Composites Under Low-Cycle Fatigue Regimes by Fuzzy and Wavelet Clustering of Acoustic Emission Signals

Esfarjani

Azadi

Alizadeh

et al. 2021

Comp Mech Comput Appl Int J

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One of methods for detecting cracks and estimating their growth in materials such as composites is the acoustic emission technique. The detection of damages, cracks and their growth in industrial composite structures, under static and dynamic loads, has a significant importance, in order to prevent any damages and increase the reliability. Therefore, achieving required technical knowledge in this field, can be helpful in repairing and the maintenance of the part in industries. The prediction of the damage in polymeric composites under static loads has been already investigated by researchers; however, under cyclic loadings, researches about this behavior are still rare. In this study, by acoustic emission sensors and analyzing experimental data, the damage, including matrix cracking, the fiber breakage and other damages (debonding, fiber pull-out and delamination) during dynamic loading was investigated. At the first stage, standard specimens were made by the pure resin epoxy and the pure carbon fiber, subjected to monotonic tensile loading and then, the frequency of the failure was extracted. Then, composite specimens were loaded in the low-cycle fatigue regime.Mechanical test results and acoustic emission data were analyzed by fuzzy C-Means and wavelet transform methods and then compared to each other to find the percentage of failures in first, mid-and last cycles by the differentiation of failure types. Results clearly indicated that the acoustic emission approach is useful and an effective tool for identifying and detecting damages in polymeric composites.

show abstract

“…Nowadays, NDT methods are very important in the industry. Many standards and technical instructions use NDT methods for a wide range of equipment and devices such as; storage tanks, pressure tanks, pressure pipes, metal structures of tall buildings, bridges, etc., have been considered mandatory [5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Application of Acoustic Emission to Detect Damage in Composites Materials

Mohammadi Esfarjani

2024

Fiber-Reinforced Composites - Recent Advances, New Perspectives and Applications

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In today’s modern world, the use of composite in the construction of various equipment and parts due to many advantages such as; weight reduction, design durability, flexibility, etc., is increasing. Damages may occur unintentionally in composite materials, either during the manufacturing process or during the normal lifetime of the part. Structural health monitoring (SHM) of composite structures is an industry requirement. The acoustic emission method can be used as an effective nondestructive testing (NDT) method to continuously monitor the development of damages in composites. In this chapter of the book, it has been prepared with the aim of application of AE to detect damage in composites. For this purpose, the literature done in the field of SHM of composite structures using the AE method is reviewed. The content of this chapter shows the importance of using the AE method for SHM of composite structures.

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Inspection of Aboveground Pipeline Using Vibration Responses

Cited by 6 publications

References 9 publications

Prediction of fiber breakage and matrix cracking in polymeric composites under low-cycle fatigue regimes by fuzzy and wavelet clustering of acoustic emission signals

Prediction of fiber breakage and matrix cracking in polymeric composites under low-cycle fatigue regimes by fuzzy and wavelet clustering of acoustic emission signals

Prediction of Fiber Breakage and Matrix Cracking in Polymeric Composites Under Low-Cycle Fatigue Regimes by Fuzzy and Wavelet Clustering of Acoustic Emission Signals

Application of Acoustic Emission to Detect Damage in Composites Materials

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