Near Stochiometric LiNbO3 Crystal: the Piezoelectric Features and the Shear Horizontal Guided Wave Transducer for Structural Health Monitoring up to 650 °C.

The application of shear horizontal (SH) guided wave transducers in high-temperature structural health monitoring (SHM) is a topic of significant interest across various industrial engineering sectors. In this study, we utilized the novelty piezoelectric crystal of near stoichiometric lithium niobate (NSLN), which exhibited a robust piezoelectric response (d15 = 77.6 pC/N@room temperature). Next, the pure thickness shear vibration mode d15' through size optimization was designed. It was demonstrated that the NSLN-based ultrasonic guided wave transducers utilizing the optimum d15' mode were proficient in transmitting and receiving pure fundamental SH wave (SH0 wave) along two orthogonal main directions (0° and 90°) over a wide frequency range (100-350 kHz), exhibiting strong response to the SH0 wave. Under the driving voltage of 100 V, the signal voltages of the NSLN-based transducer were found to be on the order of 200.3 and 11.8 mV at room temperature and high temperature of 650 °C, respectively. Moreover, the NSLN-based SH0 transducer showcased its better defect localization ability, and the signal-to-noise ratio (SNR) sensitivity of NSLN-based transducer was evaluated to be 16.1 dB at high temperature of 650 °C. To sum up, the ultrasonic wave transducer based on NSLN crystal demonstrated higher potential applications for in situ SHM under elevated temperatures.

Concrete Defect Localization Based on Multilevel Convolutional Neural Networks.

Concrete structures frequently manifest diverse defects throughout their manufacturing and usage processes due to factors such as design, construction, environmental conditions and distress mechanisms. In this paper, a multilevel convolutional neural network (CNN) combined with array ultrasonic testing (AUT) is proposed for identifying the locations of hole defects in concrete structures. By refining the detection area layer by layer, AUT is used to collect ultrasonic signals containing hole defect information, and the original echo signal is input to CNN for the classification of hole locations. The advantage of the proposed method is that the corresponding defect location information can be obtained directly from the input ultrasonic signal without manual discrimination. It effectively addresses the issue of traditional methods being insufficiently accurate when dealing with complex structures or hidden defects. The analysis process is as follows. First, COMSOL-Multiphysics finite element software is utilized to simulate the AUT detection process and generate a large amount of ultrasonic echo data. Next, the extracted signal data are trained and learned using the proposed multilevel CNN approach to achieve progressive localization of internal structural defects. Afterwards, a comparative analysis is conducted between the proposed multilevel CNN method and traditional CNN approaches. The results show that the defect localization accuracy of the proposed multilevel CNN approach improved from 85.38% to 95.27% compared to traditional CNN methods. Furthermore, the computation time required for this process is reduced, indicating that the method not only achieves higher recognition precision but also operates with greater efficiency. Finally, a simple experimental verification is conducted; the results show that this method has strong robustness in recognizing noisy ultrasonic signals, provides effective solutions, and can be used as a reference for future defect detection.

A defect localization method based on self-sensing and orthogonal matching pursuit.

In conventional structural health monitoring (SHM), a sensor array enables to localize a potential defect by using at least three lead zirconate titanate (PZT) patches. To reduce the vast number of patches needed for large-scaled structure, this paper presents an extremely sparse sensor array with only one single PZT patch, which could actuate and sense simultaneously. Firstly, a half-bridge circuit, referred as a self-sensing circuit is developed with a capacitor connected with the PZT patch, and the capacitance parameter and self-sensing performance are studied subsequently. Then, an orthogonal matching pursuit (OMP)-based sparse decomposition and dispersion removal algorithm is proposed to separate and reconstruct wave packets which are acutely overlapped. Subsequently, a matching strategy is proposed to determine the matching relationship between wave packets and wave paths. Finally, the ellipse-type imaging approach is employed to image the defect location. Two cases: one and two defects respectively are implemented to verify its efficacy. Experimental results illustrate that the proposed self-sensing unit and signal process method could erase the adverse effect of sensor-actuator interval and dispersion characteristic to the localization resolution and accuracy.

Ellipse of uncertainty based algorithm for quantitative evaluation of defect localization using Lamb waves.

Measurement deviation of time of flight (ToF) is inevitable in nondestructive testing based on the sparse array and ultrasonic Lamb waves. It affects the influence zone of temporal-spatial mapping trajectories (TSMTs) of signal parameters in the imaging zone, and further limits the quantitative evaluation of defect localization. In the paper, the ellipse of uncertainty (EOU) of TSMTs was derived from multiple parameters, including the group velocity, ToFs and their measurement deviations, distances between actuators and receivers. Then, an EOU-based algorithm was developed for quantitative evaluation of defect localization. The defects were localized by searching the individual scatterers at the intersection of multiple TSMTs. Based on the eccentricity of the uncertainty ellipse, a fuzzy scaling factor was introduced. It was combined with a fuzzy control parameter to tune the influence zone of TSMTs. Based on the acoustic reciprocity theorem and the fuzzy control parameter, the ToFs of scattering waves were fused to establish the one-to-one relation between individual scatterers and inspection pairs. Experimental results showed that the EOU-based algorithm can reduce the interferences of EOU in the detection; and the quantitative evaluation of defect localization was realized by analyzing the distribution of individuals and their ToF difference to inspection pairs.

Strategies for guided acoustic wave inspection using mobile robots.

Continuous non-destructive monitoring of large-scale structures is extremely challenging with traditional manual inspections. In this paper, we explore possible strategies that a collection of inspection robots could adopt to address this challenge. We envision the continuous inspection of a plate performed by multiple robots or a single robot that combines measurements from multiple locations. The robots use guided ultrasonic waves to interrogate a localized region for defects such as cracking or corrosion. In the detection stage, the receiver operating characteristic defines a detection zone in which a defect is thought to be present. In the localization stage, further measurements are made to locate the defect within this zone to a certain accuracy. We then address the question of what additional measurements are needed to achieve a given level of performance in the presence of uncertainty in robot locations? We explore this problem with Monte Carlo simulations that reveal the compromise between number of robots and performance in terms of defect location accuracy. In an experimental validation example on an aluminium plate, we show that six measurements arranged in a pentagon with a central measurement point leads to localization errors of similar magnitude to the uncertainty in sensor location.

A baseline-free approach of locating defect based on mode conversion and the reciprocity principle of Lamb waves.

Guided wave (GW) plays an important role in nondestructive testing and structural health monitoring. In the general Lamb wave inspection, difference between the baselines and the measured signals are used for structural damage evaluation. However, the baselines are unavoidably influenced by operational and environmental conditions leads to an increased error during inspection. To deal with this issue, this paper presents a base-line free method based on the mode conversion and reciprocity principle of Lamb wave. Once the defect is asymmetrical with respect to the transducer pair (two identical piezoelectric transducers used as actuator and receiver respectively), the elastic wave path length of the converted mode will be different, resulting in failing of the reciprocity principle. By processing the signals received by the transducer pair and extracting the time parameters of the wave packets in mode conversion signals, the defect can be localized. Results from the signals generated by numerical simulation are presented to verify the feasibility of the method, and the effectiveness of the proposed baseline-free method is demonstrated with experimental results.

A new multichannel time reversal focusing method for circumferential Lamb waves and its applications for defect detection in thick-walled pipe with large-diameter.

This paper proposes a new multichannel time reversal focusing (MTRF) method for circumferential Lamb waves which is based on modified time reversal algorithm and applies this method for detecting different kinds of defects in thick-walled pipe with large-diameter. The principle of time reversal of circumferential Lamb waves in pipe is presented along with the influence from multiple guided wave modes and propagation paths. Experimental study is carried out in a thick-walled and large-diameter pipe with three artificial defects, namely two axial notches on its inner and outer surface respectively, and a corrosion-like defect on its outer surface. By using the proposed MTRF method, the multichannel signals focus at the defects, leading to the amplitude improvement of the defect scattered signal. Besides, another energy focus arises in the direct signal due to the partial compensation of dispersion and multimode of circumferential Lamb waves, alongside the multichannel focusing, during MTRF process. By taking the direct focus as a time base, accurate defect localization is implemented. Secondly, a new phenomenon is exhibited in this paper that defect scattered wave packet appears just before the right boundary of truncation window after time reversal, and to which two feasible explanations are given. Moreover, this phenomenon can be used as the theoretical basis in the determination of defect scattered waves in time reversal response signal. At last, in order to detect defects without prior knowing their exact position, a large-range truncation window is used in the proposed method. As a result, the experimental operation of MTRF method is simplified and defect detection and localization are well accomplished.