Ultrasonic testing of adhesive bonds of thick composites with applications to wind turbine blades

Chakrapani, Sunil Kishore; Dayal, Vinay; Krafka, Ryan; Eldal, Aaron

doi:10.1063/1.4716366

Cited by 11 publications

(3 citation statements)

References 5 publications

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“…The Ultrasonic non-destructive testing (NDT) method is adept at detecting the bonding area and depth of a structure by analyzing the time gap between transmission and echo signals [153]. Chakrapani et al [154] conducted experiments utilizing the pulse-echo technique to scrutinize adhesive bonds within composite plates, which exhibited varying thickness ranging from 1.4 mm to 45.5 mm.…”

Section: E Ultrasonic Testingmentioning

confidence: 99%

Review on the Advancements in Wind Turbine Blade Inspection: Integrating Drone and Deep Learning Technologies for Enhanced Defect Detection

Memari,

Shakya,

Shekaramiz

et al. 2024

IEEE Access

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The increasing demand for wind power requires more frequent inspections to identify defects in the Wind Turbine Blades (WTBs). These defects, if not detected, can compromise the structural integrity and safety of wind turbines. As WTBs are crucial and costly components, they may suffer material degradation and fatigue failure, which affects their performance and safety. Thus, the urgency for efficient and regular monitoring to maintain their structural integrity is greater than ever. This review paper explores innovative methods in fatigue testing, damage detection, and structural reliability in WTBs, focusing on the use of recent inspection methods, including those that take advantage of drones. Drones are used to identify defects such as cracks, erosion, and coating irregularities using high-resolution imagery with the onboard cameras. Various investigators have developed novel data-driven approaches, incorporating machine learning and deep learning, to accurately identify these defects. Although deep learning-based image processing has been successful in other public infrastructure contexts, its application to wind turbine inspection from aerial images presents unique challenges. This paper also highlights the critical role of failure inspection in enhancing the operational integrity of WTBs, showcasing state-of-the-art deep learning techniques that are pivotal for identifying and analyzing failures in WTBs from images captured by drones. The paper provides insights into the latest developments in using drone imagery for blade defect detection, contrasting this method with traditional non-destructive techniques. This approach could significantly transform the wind energy industry by offering a more efficient, automated, and precise way of ensuring the structural health of wind turbines. Unlike previous studies that predominantly focus on isolated aspects such as inspection or fatigue, this review paper not only integrates the three major aspects of WTBs integrity in terms of aerial inspection, image processing using machine learning, and structural integrity of the blade but also undertakes an extensive examination of the prevailing methodologies in the field, pinpointing crucial gaps and challenges. It provides a detailed review of existing research, covering various areas including automated inspection, image processing techniques, fatigue analysis, and the reliability of wind turbines. This approach enriches the discourse by offering a multifaceted perspective on WTB maintenance, thereby advancing the understanding of operational integrity within the field of wind energy.

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Section: E Ultrasonic Testingmentioning

confidence: 99%

Review on the Advancements in Wind Turbine Blade Inspection: Integrating Drone and Deep Learning Technologies for Enhanced Defect Detection

Memari,

Shakya,

Shekaramiz

et al. 2024

IEEE Access

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show abstract

“…Currently, these mainly include applications related to the inspection of spot welds [10][11][12][13] and adhesive joints [13][14][15][16][17][18]. Due to the uncomplicated design of these joints and relatively easy access to the test surfaces, longitudinal wave, which is not transformed, is most commonly used.…”

Section: Ultrasonic Subsurface Wave Generation In Continuous Mediummentioning

confidence: 99%

Application of Immersion Ultrasonic Testing For Non-Contact Quality Evaluation of Magnetically Impelled Arc Butt Welded Drive Shafts of Motor Vehicles

KustroÅ¹,

Korzeniowski²,

Piwowarczyk³

et al. 2017

Adv Automob Eng

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The article presents contemporary ultrasonic methods that can be applied to evaluate the quality of transmission drive components of motor vehicles. The issues of non-destructive analysis of discontinuities in manufactured drive shafts, consisting currently of thin-walled tubes, were investigated in this study. The driveshaft elements were joined by using innovative method called Magnetically Impelled Arc Butt Welding (MIAB). For many years, a major challenge for engineers working with ultrasonic techniques was joining of thin-walled components (having thickness below 3 mm). In addition of this limitation, the problem of variable geometry of the weld flash on the weld perimeter was highlighted. To reduce the impact of mentioned factors the pseudo-surface waves (also known as lateral waves) have been applied in this study. In order to select optimal parameters of the ultrasonic beam propagation and to understand the physical-acoustic phenomena, the Finite Elements Method modelling was performed. The phenomena of wave transformation on medium boundary and reflections from artificial flaw have been analyzed by numerical modelling.The results of numerical analysis were confirmed by UT experimental research. The manufactured MIAB welded joints were tested with using in-house made experiment set-up. The selected configurations with various shapes and dimensions of samples, and various process parameters have been investigated. The results confirm the usefulness of pseudo-surface ultrasonic waves in UT quality evaluation of MIAB welded elements of drive shafts of motor vehicles.

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“…De Freitas et al [16] used acoustic emission to detect weak bonds by monitoring the de-bonding mechanisms in mode I loading using a double cantilever beam test. Various other researchers have used ultrasound to study adhesive bonds [17][18][19][20]. Korzeniowsk [21] for example used ultrasound to detect the shape and size of defects which were embedded in the adhesive bond.…”

mentioning

confidence: 99%

An experimental investigation on the effect of adhesive distribution on strength of bonded joints

et al. 2019

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Adhesive joints are widely used due to their higher strengths, lower weights, lesser expenses and ease of fabrication than other methods of joining. Hence, they are used extensively in aerospace and automobile industries. High quality bonds require the use of fixtures which are essential to ensure proper curing and to attain uniform thickness. Improper adhesive application and method of fixturing can cause irregularities in the distribution of the adhesive along the overlap which could affect the joint strength. This is especially critical for aerospace components as the replacement of parts can be costly and time consuming. This paper presents a nondestructive test (NDT) methodology to quantify the bonded joints where the adhesive does not completely cover the overlap area. Single lap adhesive joints with carbon fiber adherents were fabricated using a two-part epoxy based adhesive. The adhesive region was fabricated to have various shapes including elliptical and circular of different sizes and a joint with full coverage for comparison. Polytetrafluoroethylene (PTFE) cutouts were used to mask regions of adhesive to achieve the desired coverage pattern. After fabrication all samples were ultrasonically scanned with a 10 MHz spherically focused immersion transducer using pulse-echo ultrasonics to determine the actual as tested adhesive distribution shape. The scans were able to resolve the shape of adhesive distribution across the overlap region of 25.4 × 25.4 mm and were correlated with the actual adhesive distribution at the interface after lap shear tests. Lap shear tests were then performed on the samples fabricated and the samples were loaded to failure. It was found that the shape and the orientation of the adhesive shape relative to the loading direction had an effect on failure strength.

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Ultrasonic testing of adhesive bonds of thick composites with applications to wind turbine blades

Cited by 11 publications

References 5 publications

Review on the Advancements in Wind Turbine Blade Inspection: Integrating Drone and Deep Learning Technologies for Enhanced Defect Detection

Review on the Advancements in Wind Turbine Blade Inspection: Integrating Drone and Deep Learning Technologies for Enhanced Defect Detection

Application of Immersion Ultrasonic Testing For Non-Contact Quality Evaluation of Magnetically Impelled Arc Butt Welded Drive Shafts of Motor Vehicles

An experimental investigation on the effect of adhesive distribution on strength of bonded joints

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