A noncontact method to evaluate the acoustic nonlinearity of surface waves in a plastically deformed aluminum alloy is proposed. Line-arrayed laser beams modulated with slit masks were used for the generation of narrowband surface waves. A laser-ultrasonic detector using a two-wave mixing (TWM) approach was also employed to detect the surface waves. The specimens were deformed by a stroke-controlled tensile tester so as to generate various degrees of tensile deformation. The experimental results showed that the acoustic nonlinearity of the laser-generated surface waves increased according to the level of tensile deformation. This tendency was in good agreement with our previous results obtained using a contact piezoelectric (PZT)-transducer as the receiver. These results imply that our noncontact technique is suitable for the evaluation of acoustic nonlinearity and can be applied to practical damage assessment.National Research Foundation of Korea (NRF) - Korean Government (MEST

Anomaly detection (AD) is a crucial task in various industrial sectors where large amounts of data are generated from multiple sensors. Deep learning-based methods have made significant progress in AD, owing to big data and deep neural networks (DNN). Most methods for deep anomaly detection (DAD) utilize reconstruction error (i.e., the difference between the original and reconstructed values) as a measure of abnormality. However, AD performance can be improved by diversifying the source of anomaly score. To support this, we introduce the concept of anomaly source diversification and provide mathematical proofs to support this idea. In this regard, we propose a quantile autoencoder (QAE) with abnormality accumulation (AA) as a novel DAD approach that leverages data uncertainty and iteratively obtains reconstruction errors as additional sources. The anomaly score with QAE is derived from both the reconstruction error and the uncertainty term which is the range between the two quantiles. In addition, AA aggregates the errors obtained from the recursive reconstruction of the input, after which calculates the anomaly score based on the Mahalanobis distance. This process induces the score distributions of both the normal and abnormal samples farther apart by narrowing the width of the distributions, which contributes to the improvement of AD performance. The performance of the proposed QAE-AA was verified through the experiments on multi-variate sensor datasets in various domains; QAE-AA achieves 4-23% higher AUROC score on average compared to the other AD methodologies.

Nonlinear acoustic techniques are established tools for the characterization of micro-inhomogeneous materials with higher sensitivity, compared to linear ultrasonic techniques. In particular, the evaluation of material elastic quadratic nonlinearity via the detection of the second harmonic generation by acoustic waves is known to provide an assessment of the state variation of heat treated micro-structured materials. We report on the first application for non-destructive diagnostics of material thermal aging of finite-amplitude longitudinal acoustic pulses generated and detected by lasers. Finite-amplitude longitudinal pulses were launched in aluminum alloy samples by deposited liquid-suspended carbon particles layer irradiated by a nanosecond laser source. An out-of-plane displacement at the epicenter of the opposite sample surface was measured by an interferometer. This laser ultrasonic technique provided an opportunity to study the propagation in aluminum alloys of finite-amplitude acoustic pulses with a strain up to 5 × 10⁻³. The experiments revealed a signature of the hysteretic quadratic nonlinearity of micro-structured material manifested in an increase of the duration of detected acoustic pulses with an increase of their amplitude. The parameter of the hysteretic quadratic nonlinearity of the aluminum alloy (Al6061) was found to be of the order of 100 and to exhibit more than 50% variations in the process of the alloy thermal aging. By comparing the measured parameter of the hysteretic quadratic nonlinearity in aluminum alloys that were subjected to heat-treatment at 220 °C for different times (0 min, 20 min, 40 min, 1 h, 2 h, 10 h, 100 h, and 1000 h), with measurements of yield strength in same samples, it was established that the extrema in the dependence of the hysteretic nonlinearity and of the yield strength of this alloy on heat treatment time are correlated. This experimental observation provides the background for future research with the application goal of suggested nonlinear laser ultrasonic techniques for non-destructive evaluation of alloys’ strength and rigidity in the process of their heat treatment.