In this paper, some recent piezoelectric wafer active sensors (PWAS) progress achieved in our laboratory for active materials and smart structures (LAMSS) at the University of South Carolina: http: //www.me.sc.edu/research/lamss/ group is presented. First, the characterization of the PWAS materials shows that no significant change in the microstructure after exposure to high temperature and nuclear radiation, and the PWAS transducer can be used in harsh environments for structural health monitoring (SHM) applications. Next, PWAS active sensing of various damage types in aluminum and composite structures are explored. PWAS transducers can successfully detect the simulated crack and corrosion damage in aluminum plates through the wavefield analysis, and the simulated delamination damage in composite plates through the damage imaging method. Finally, the novel use of PWAS transducers as acoustic emission (AE) sensors for in situ AE detection during fatigue crack growth is presented. The time of arrival of AE signals at multiple PWAS transducers confirms that the AE signals are originating from the crack, and that the amplitude decay due to geometric spreading is observed.

https://scholarcommons.sc.edu/cgi/viewcontent.cgi?article=1798&context=emec_facpub

Recent Advances in Piezoelectric Wafer Active Sensors for Structural Health Monitoring Applications

Imaging algorithms for visualization of defects play a significant role in Lamb wave–based research of nondestructive testing and structural health monitoring. In classical algorithms, the position...

An intelligent algorithm based on evolutionary strategy and clustering algorithm for Lamb wave defect location

FRF-based lamb wave phased array

Intelligent defect location algorithms based on the times-of-flight (ToFs) of Lamb waves are attractive for nondestructive testing (NDT) and structural health monitoring (SHM) of structures with large geometric sizes. Unlike the classical imaging algorithm based on projecting the amplitude information of scattering signals into a discrete spatial grid on the structure via their propagation characteristics, intelligent defect location algorithms are more efficient in specific applications. In our previous work, an intelligent algorithm for the location of defects in plates was proposed by considering the statistical, diversity, and fuzzy characteristics of the classical defect location algorithm. This approach can realize the efficient location of different defects under a suitable parameter selection. However, interfering components remain in the results, which decreases the detection resolution. Because the measurement uncertainty is directly related to the time, an optimized intelligent location algorithm is provided for the efficient defect location with Lamb waves and a sparse transducer array in this study. The defect position is identified with high resolution by analyzing the distribution of individuals. Several specific data and a fuzzy control parameter are introduced to the proposed algorithm. The K-means algorithm was adopted to realize the adaptive updating of individuals. The influence of parameter values on the detection results was analyzed. A combined analysis of the individuals was provided to ensure the detection robustness by eliminating the influence of fuzzy control parameters on the detection. Compared with the elliptic imaging algorithm, the intelligent defect location algorithm has higher location resolution and executes approximately 65 times faster.

Evolutionary Strategy-Based Location Algorithm for High-Resolution Lamb Wave Defect Detection With Sparse Array

Lamb waves are widely used in the structural health monitoring (SHM) for plate-like structures. In this paper, a new and flexible ultrasonic transducer with a high photo-acoustic conversion efficiency was proposed by using candle soot nanoparticles (CSNPs) and polydimethylsiloxane (PDMS). Experimental results demonstrate that the developed transducer can generate a longitudinal wave with a short duration of 0.28 μs under the illumination of a nanosecond laser pulse. The amplitude of the excited longitudinal wave is 10 times to that of the signal generated by the traditional laser ultrasound technique. Further, wedge shape transducers were developed to excite Lamb waves in a 1.5-mm thick aluminium substrate by the oblique incidence method. The specific A0 and S0 modes of the Lamb wave with the central frequency of 647 kHz were successfully excited in the aluminium plate. Based on the synthetic aperture focusing imaging technique, a delay-and-sum signal processing method was adopted for damage location in the plate by using the A0 mode Lamb. A 3.5-mm defect was well imaged and the results demonstrate that the developed flexible photo-acoustic transducer can be a good alternative method for the SHM.

https://iopscience.iop.org/article/10.1088/1361-665X/ab85e0/pdf

A flexible laser ultrasound transducer for Lamb wave-based structural health monitoring

Lamb waves defect detection technique is suitable to detect long-range defects and multi-defects in plates because of its attractive properties such as multi-modes, low attenuation, and multi-defect sensitivity. As the laser beams have the tiny size and noncontact property, in this paper a full non-contact laser-based Lamb waves phased array inspection technique was proposed for defect detection in an aluminum plate. A Q-switched Nd: YAG pulse laser generating Lamb waves and a continuous laser inspection system was used to inspect the out-of-plane displacements. The laser-generated Lamb waves have the broadband property and low temporal resolution that are not suitable for defects detection directly. So the continuous wavelet transform was used to extract narrowband signals from laser-generated Lamb wave and a linear mapping algorithm was adopted to compensate for the dispersion of the extracted narrowband signals. Two experiments were carried out to verify the applicability and effectiveness of the developed full non-contact laser-based Lamb waves phased array inspection technique. Two compact phased array imaging algorithms, the total focusing method and the sign coherence factor algorithm, were adopted to image the defects with processed signals. The experimental results accurately located the positions of the defects.

Full non-contact laser-based Lamb waves phased array inspection of aluminum plate

Lamb waves have been widely studied in structural integrity evaluation during the past decades with their low-attenuation and multi-defects sensitive nature. The performance of the evaluation has close relationship with the vibration property and the frequency of Lamb waves signals. Influenced by the nature of Lamb waves and the environment, the received signals may be difficult to interpret that limits the performance of the detection. So pure Lamb waves mode emitting and high-resolution signals acquisition play important roles in Lamb waves structural integrity evaluation. In this chapter, the basic theory of Lamb waves nature and some environment factors that should be considered in structural integrity evaluation are introduced. Three kinds of typical transduces used for specific Lamb waves mode emitting and sensing are briefly introduced. Then the development of techniques to improve the interpretability of signals are discussed, including the waveform modulation techniques, multi-scale analysis techniques and the temperature effect compensation techniques are summarized.

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Application and Challenges of Signal Processing Techniques for Lamb Waves Structural Integrity Evaluation: Part A-Lamb Waves Signals Emitting and Optimization Techniques

The wavefield of Lamb waves is yielded by the feature of plate-like structures. And many defects imaging techniques and intelligent recognition algorithms have been developed for defects location, sizing and recognition through analyzing the parameters of received Lamb waves signals including the arrival time, attenuation, amplitude and phase, etc. In this chapter, we give a briefly review about the defects imaging techniques and the intelligent recognition algorithms. Considering the available parameters of Lamb waves signals and the setting of detection/monitoring systems, we roughly divide the defect location and sizing techniques into four categories, including the sparse array imaging techniques, the tomography techniques, the compact array techniques, and full wavefield imaging techniques. The principle of them is introduced. Meanwhile, the intelligent recognition techniques based on various of intelligent recognition algorithms that have been widely used to analyze Lamb waves signals in the research of defect recognition are reviewed, including the support vector machine, Bayesian methodology, and the neural networks.

Application and Challenges of Signal Processing Techniques for Lamb Waves Structural Integrity Evaluation: Part B-Defects Imaging and Recognition Techniques

Honglei Chen

Papers

An intelligent algorithm based on evolutionary strategy and clustering algorithm for Lamb wave defect location

Evolutionary Strategy-Based Location Algorithm for High-Resolution Lamb Wave Defect Detection With Sparse Array

Full non-contact laser-based Lamb waves phased array inspection of aluminum plate

Application and Challenges of Signal Processing Techniques for Lamb Waves Structural Integrity Evaluation: Part A-Lamb Waves Signals Emitting and Optimization Techniques

Application and Challenges of Signal Processing Techniques for Lamb Waves Structural Integrity Evaluation: Part B-Defects Imaging and Recognition Techniques