Novel Processing Algorithm to Improve Detectability of Disbonds in Adhesive Dissimilar Material Joints

Abstract

Adhesively bonded dissimilar materials have attracted high interest in the aerospace and automotive industries due to their ability to provide superior structural characteristics and reduce the weight for energy savings. This work focuses on the improvement of disbond-type defect detectability using the immersion pulse-echo ultrasonic technique and an advanced post-processing algorithm. Despite the extensive work done for investigation, it is still challenging to locate such defects in dissimilar material joints due to the large differences in the properties of metals and composites as well as the multi-layered structure of the component. The objective of this work is to improve the detectability of defects in adhesively bonded aluminum and carbon fiber-reinforced plastic (CFRP) by the development of an advanced post-processing algorithm. It was determined that an analysis of multiple reflections has a high potential to improve detectability according to results received by inspection simulations and the evaluation of boundary characteristics. The impact of a highly influential parameter such as the sample curvature can be eliminated by the alignment of arrival time of signals reflected from the sample. The processing algorithm for the improvement of disbond detectability was developed based on time alignment followed by selection of the time intervals with a significant amplitude change of the signals reflected from defective and defect-free areas and shows significant improvement of disbond detectability.

Probabilistic ultrasound C-scan imaging of barely visible impact damage in CFRP laminates

“…ℱ −1 (•) denotes the inverse discrete Fourier transform operator, and * symbolizes complex conjugation. Following the cross-correlation operation, a dynamic time gating approach is employed to compensate for possible curved geometry and/or non-horizontality of the sample [17,53]. In other words, the signals 𝑠̅ (𝑡) are aligned in time dimension by putting a threshold on all signals at 60% of their maximum amplitude in order to align the signals at their FWE.…”

Ultrasonic Features for Evaluation of Adhesive Joints: A Comparative Study of Interface Defects

“…The development trends and main demands in the automotive and aerospace industries are the reduction in fuel consumption and carbon dioxide emissions as well as the maintenance of high safety for environmental and human health at the same time [ 1 , 2 , 3 ]. Adhesive bonding is an attractive joining technology that meets the above-listed requirements due to characteristics such as high strength-to-weight ratio, a uniform distribution of loads between joined parts and a decrease in the weight of a structure due to the exclusion of all metal bolts and rivets [ 2 , 4 , 5 ]. Other advantageous characteristics of adhesively bonded joints are the ability to join similar and dissimilar materials, vibroacoustic damping properties, high fatigue life, impact resistance, residual strength, sealing capabilities and cost effectiveness.…”

“…To detect defects in such multi-layered adhesively bonded structures is a challenging task. Despite all the advantages that adhesive bondings have, the application of this technology in the aerospace industry is still limited due to a lack of knowledge on the reliability of the non-destructive testing (NDT) techniques [ 2 , 7 ].…”

“…Various configurations of ultrasonic methods based on the measurement of the difference in amplitude of reflected signals from defective and non-defective interfaces have been used to detect interface defects [ 12 , 13 , 14 , 15 , 16 ]. In addition, the following ultrasonic features, which characterize the signal response, were extracted to evaluate the adhesive quality: phase shift [ 12 ], ratio coefficients of peak-to-peak amplitudes [ 2 ], the decibel drop between ultrasonic pulses [ 17 , 18 ], maximum correlation between pulse response and excitation signals to obtain time reversal signals of Lamb waves [ 19 ], mean value, root mean square, standard deviation, skewness, kurtosis and crest factor, as well as modal frequency, modal mode and damping [ 20 ]. A number of works have been carried out using numerical evaluations and modeling to study the feasibility of different NDT methods [ 2 , 7 , 21 , 22 ].…”

“…In addition, the following ultrasonic features, which characterize the signal response, were extracted to evaluate the adhesive quality: phase shift [ 12 ], ratio coefficients of peak-to-peak amplitudes [ 2 ], the decibel drop between ultrasonic pulses [ 17 , 18 ], maximum correlation between pulse response and excitation signals to obtain time reversal signals of Lamb waves [ 19 ], mean value, root mean square, standard deviation, skewness, kurtosis and crest factor, as well as modal frequency, modal mode and damping [ 20 ]. A number of works have been carried out using numerical evaluations and modeling to study the feasibility of different NDT methods [ 2 , 7 , 21 , 22 ]. Advanced post-processing algorithms of the collected data have been developed to provide C-scan images of the interface defects in multilayer structures, improve detection quality or extract features from the signal responses [ 2 , 3 , 16 , 19 , 20 , 23 ].…”