• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.7
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• pp.51-59
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• 2004

An experimental procedure to identify failure modes of impact damage using sensor signals and to analyze their general features is examined. A series of low-velocity impact tests from low energy to damage-induced high energy were performed on the instrumented drop weight impact tester to monitor the stress wave signals due to failure modes such as matrix cracking, delamination, and fiber breakage. The wavelet transform(WT) and Short Time Fourier Transform(STFT) are used to decompose the piezoelectric sensor signals in this study. The extent of the damage in each case was examined by means of a conventional ultrasonic C-scan. The PVDF sensor signals are shown to carry important information regarding the nature of the impact process that can be extracted from the careful signal processing and analysis.

• Smart Structures and Systems
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• v.25 no.3
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• pp.369-384
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• 2020

A wavefield sparse reconstruction technique based on compressed sensing is developed in this work to dramatically reduce the number of measurements. Firstly, a severely underdetermined representation of guided wavefield at a snapshot is established in the spatial domain. Secondly, an optimal compressed sensing model of guided wavefield sparse reconstruction is established based on l₁-norm penalty, where a suite of discrete cosine functions is selected as the dictionary to promote the sparsity. The regular, random and jittered undersampling schemes are compared and selected as the undersampling matrix of compressed sensing. Thirdly, a gradient projection method is employed to solve the compressed sensing model of wavefield sparse reconstruction from highly incomplete measurements. Finally, experiments with different excitation frequencies are conducted on an aluminum plate to verify the effectiveness of the proposed sparse reconstruction method, where a scanning laser Doppler vibrometer as the true benchmark is used to measure the original wavefield in a given inspection region. Experiments demonstrate that the missing wavefield data can be accurately reconstructed from less than 12% of the original measurements; The reconstruction accuracy of the jittered undersampling scheme is slightly higher than that of the random undersampling scheme in high probability, but the regular undersampling scheme fails to reconstruct the wavefield image; A quantified mapping relationship between the sparsity ratio and the recovery error over a special interval is established with respect to statistical modeling and analysis.

• Composites Research
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• v.28 no.4
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• pp.155-161
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• 2015

A composite structure was fabricated with embedded impact detection capabilities for applications in Structural Health Monitoring (SHM). By embedding sensor functionality in the composite, the structure can successfully perform impact localization in real time. Smart resin, composed of $Pb(Ni_{1/3}Nb_{2/3})O_3-Pb(Zr,\;Ti)O_2$ (PNN-PZT) powder and epoxy resin with 1:30 wt%, was used instead of conventional epoxy resin in order to activate the sensor function in the composite structure. The embedded impact sensor in the composite was fabricated using Hand Lay-up and Vacuum Assisted Resin Transfer Molding(VARTM) methods to inject the smart resin into the glass-fiber fabric. The electrodes were fabricated using silver paste on both the upper and bottom sides of the specimen, then poling treatment was conducted to activate the sensor function using a high voltage amplifier at 4 kV/mm for 30 min at room temperature. The composite's piezoelectric sensitivity was measured to be 35.13 mV/N by comparing the impact force signals from an impact hammer with the corresponding output voltage from the sensor. Because impact sensor functionality was successfully embedded in the composite structure, various applications of this technique in the SHM industry are anticipated. In particular, impact localization on large-scale composite structures with complex geometries is feasible using this composite embedded impact sensor.