• Proceedings of the KSME Conference
• /
• 2003.04a
• /
• pp.370-375
• /
• 2003

Optical fiber vibrations sensors (OFVSs) and extrinsic Fabry-Perot interferometer (EFPI) were used in damage monitoring of fiber-metal laminates(FML). The optical fiber vibration sensor and EFPI were applied in order to detect and evaluate the strain, damage and failure of FML. Damages in composites, such as matrix cracks, delamination and fiber breakage may occur as a result of excessive load, fatigue and low-velocity impacts. Tensile and indentation test was performed with the measurement of optical signal and acoustic emission (AE). The signals of the optical fiber vibration sensor due to damages were quantitatively evaluated by wavelet transform. It was found that damage information of comparable in quality to acoustic emission data could be obtained from the optical fiber vibration sensor signals.

• Proceedings of the Korean Society For Composite Materials Conference
• /
• 2003.04a
• /
• pp.42-45
• /
• 2003

Optical fiber vibrations sensors (OFVSs) and extrinsic Fabry-Perot interferometer (EFPI) were used in damage monitoring of fiber-metal laminates(FML). The optical fiber vibration sensor and EFPI were applied in order to detect and evaluate the strain, damage and failure of FML. Damages in composites, such as matrix cracks, delamination and fiber breakage may occur as a result of excessive load, fatigue and low-velocity impacts. Indentation test was performed with the measurement of optical signal and acoustic emission (AE). The signals of the optical fiber vibration sensor due to damages were quantitatively evaluated by wavelet transform. It was found that damage information of comparable in quality to acoustic emission data could be obtained from the optical fiber vibration sensor signals.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2002.10a
• /
• pp.345-350
• /
• 2002

In this study, researchers classifying the artificial flaws in semiconductor packages are performed by pattern recognition technology. For this purposes, image pattern recognition package including the user made software was developed and total procedure including ultrasonic image acquisition, equalization filtration, binary process, edge detection and classifier design is treated by Backpropagation Neural Network. Specially, it is compared with various weights of Backpropagation Neural Network and it is compared with threshold level of edge detection in preprocessing method fur entrance into Multi-Layer Perceptron(Backpropagation Neural network). Also, the pattern recognition techniques is applied to the classification problem of defects in semiconductor packages as normal, crack, delamination. According to this results, it is possible to acquire the recognition rate of 100% for Backpropagation Neural Network.

• Computational Structural Engineering
• /
• v.9 no.2
• /
• pp.173-182
• /
• 1996

The present study proposes a detection technique for delaminations in a laminated compoiste structure. the proposed technique optimizes the spatial distribution of harmonic excitation so as to magnify the difference in response between the delaminated and intact structures. The technique is evaluated by numerical simulation of two-layered aluminum beams. Effects of measurement and geometric noises are included in the analysis. A finite element model for a delaminated beam, based on the layer-wise laminated plate theory in conjunction with a step function to simulate ddelaminations, is used.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.10a
• /
• pp.721-726
• /
• 2005

In this study, researchers classifying the artificial flaws in semiconductor. packages are performed by pattern recognition technology. For this purposes, image pattern recognition package including the user made software was developed and total procedure including ultrasonic image acquisition, equalization filtration, binary process, edge detection and classifier design is treated by Backpropagation Neural Network. Specially, it is compared with various weights of Backpropagation Neural Network and it is compared with threshold level of edge detection in preprocessing method for entrance into Multi-Layer Perceptron(Backpropagation Neural network). Also, the pattern recognition techniques is applied to the classification problem of defects in semiconductor packages as normal, crack, delamination. According to this results, it is possible to acquire the recognition rate of 100% for Backpropagation Neural Network.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.29 no.4
• /
• pp.323-330
• /
• 2009

The objective of this research was to develop a practical integrated approach using extracted features from electrical resistance measurements and coupled electromechanical models of damage, for in-situ damage detection and sensing in carbon fiber reinforced plastic(CFRP) composites. To achieve this objective, we introduced specific known damage (in terms of type, size, and location) into CFRP laminates and established quantitative relationships with the electrical resistance measurements. For processing of numerous measurement data, an autonomous data acquisition system was devised. We also established a specimen preparation procedure and a method for electrode setup. Coupon and panel CFRP laminate specimens with several known damage were tested. Coupon specimens with various sizes of artificial delaminations obtained by inserting Teflon film were manufactured and the resistance was measured. The measurement results showed that increase of delamination size led to increase of resistance implying that it is possible to sense the existence and size of delamination. A quasi-isotropic panel was manufactured and electrical resistance was measured. Then three different sizes of holes were drilled at a chosen location. The panel was prepared using the established procedures with six electrode connections on each side making a total of twenty-four electrodes. Vertical, horizontal, and diagonal pairs of electrodes were chosen and the resistance was measured. The measurement results showed the possibility of the established measurement system for an in-situ damage detection method for CFRP composite structures.

• Journal of Institute of Control, Robotics and Systems
• /
• v.13 no.11
• /
• pp.1060-1066
• /
• 2007

When a high-energy ultrasound propagates through a solid body that contains a crack or a delamination, the two faces of the defect do not ordinarily vibrate in unison, and dissipative phenomena such as friction, rubbing and clapping between the faces will convert some of the vibrational energy to heat. By combining this heating effect with infrared imaging, one can detect a subsurface defect in material efficiently. In this paper a detection of the welding defect of thin SUS 304 plates using the UIR (ultrasonic infrared imaging) technology is described. A low frequency (20kHz) ultrasonic transducer was used to infuse the welded thin SUS 304 plates with a short pulse of sound for 280ms. The ultrasonic source has a maximum power of 2kW. The surface temperature of the area under inspection is imaged by a thermal infrared camera that is coupled to a fast frame grabber in a computer. The hot spots, which are a small area around the defect tip and heated up highly, are observed. From the sequence of the thermosonic images, the location of defective or inhomogeneous regions in the welded thin SUS 304 plates can be detected easily.

• Structural Monitoring and Maintenance
• /
• v.4 no.1
• /
• pp.1-15
• /
• 2017

Installation of sensors networks for continuous in-service monitoring of structures and their efficiency conditions is a current research trend of paramount interest. On-line monitoring systems could be strategically useful for road infrastructures, which are expected to perform efficiently and be self-diagnostic, also in emergency scenarios. This work researches damage detection in composite concrete-steel structures that are typical for highway overpasses and bridges. The techniques herein proposed assume that typical damage in the deck occurs in form of delamination and cracking, and that it affects the peak power spectral density of dynamic curvature. The investigation is performed by combining results of measurements collected by long-gauge fiber optic strain sensors installed on monitored structure and a statistic approach. A finite element model has been also prepared and validated for deepening peculiar aspects of the investigation and the availability of the method. The proposed method for real time applications is able to detect a documented unusual behavior (e.g., damage or deterioration) through long-gauge fiber optic strain sensors measurements and a probabilistic study of the dynamic curvature power spectral density.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.41 no.5
• /
• pp.401-407
• /
• 2017

This paper describes wavenumber filtering for damage detection using single-frequency standing wave excitation and laser scanning sensing. An embedded piezoelectric sensor generates ultrasonic standing waves, and the responses are measured using a laser Doppler vibrometer and mirror tilting device. After scanning, newly developed damage detection techniques based on wavenumber filtering are applied to the full standing wave field. To demonstrate the performance of the proposed techniques, several experiments were performed on composite plates with delamination and aluminum plates with corrosion damage. The results demonstrated that the developed techniques could be applied to various structures to localize the damage, with the potential to improve the damage detection capability at a high interrogation speed.

• Composites Research
• /
• v.34 no.5
• /
• pp.317-322
• /
• 2021

When a complex load such as torsion, low-speed impact, or fatigue load is applied, the properties in the thickness direction are weakened through microcracks inside the material due to the nature of the laminated composite material, and delamination occurs. To prevent the interlaminar delamination, various three-dimensional reinforcement methods such as Z-pinning and stitching, and structural health monitoring techniques that detect the microcrack of structures in real time have been continuously studied. In this paper, the single-lap joints with I-fiber stitching process were manufactured by a co-curing method and their strengths and failure detection capability were evaluated. AE and electric resistance method were used for detection of crack and failure signal and electric circuit for signal analysis was manufactured, and failure signal was analyzed during the tensile test of a single-lap joint. From the experiment, the strength of the single lap joint reinforced by I-fiber stitching process was improved by about 44.6% compared to the co-cured single lap joint without reinforcement. In addition, as the single-lap joint reinforced by I-fiber stitching process can detect failure in both the electrical resistance method and the AE method, it has been proven to be an effective structure for failure monitoring as well as strength improvement.