Synthetic Aperture Imaging of Contact Acoustic Nonlinearity at Closed Interfaces

Ultrasonic imaging has been widely used as an intuitive recognition method for the detection of defects [1]. To enhance the resolution in ultrasound imaging, various kinds of techniques have been developed. Synthetic aperture focusing technique (SAFT) is one of effective post-processing techniques for the resolution improvement. Many studies have shown that SAFT has high resolution as well as high signal to noise ratio for identifying the characteristics of defects accurately [2]. However, most of the imaging techniques based on linear characteristics of ultrasound could underestimate the size of flaws. In particular, the defects in initial state so called micro cracks or closed interfaces are very difficult to be visualized. In order to visualize these micro defects, it is necessary to adopt novel imaging technique using nonlinear ultrasonic characteristics such as contact acoustic nonlinearity (CAN) effect. This study proposed a nonlinear SAFT based on CAN effect and verified its effectiveness. The experiments with array probe for imaging closed interfaces were carried out. The pressure of the interfaces was increased by a hydraulic press, which resulted in the change of the contact state at the interfaces from open interfaces to closed interfaces. When a fundamental ultrasonic wave is incident at closed interfaces, the CAN effect leads the harmonic generation [3]. The proposed synthetic aperture imaging based on CAN effect was applied to visualize the closed interfaces with respect to the change of the contact interface condition. The results showed that SAFT based on CAN effect was effective for the detection of closed interface. This supports that synthetic aperture imaging techniques based on acoustic nonlinearity had advantages for the diagnosis of structural integrity

SleePyCo: Automatic Sleep Scoring with Feature Pyramid and Contrastive Learning

Automatic sleep scoring is essential for the diagnosis and treatment of sleep disorders and enables longitudinal sleep tracking in home environments. Conventionally, learning-based automatic sleep scoring on single-channel electroencephalogram (EEG) is actively studied because obtaining multi-channel signals during sleep is difficult. However, learning representation from raw EEG signals is challenging owing to the following issues: 1) sleep-related EEG patterns occur on different temporal and frequency scales and 2) sleep stages share similar EEG patterns. To address these issues, we propose a deep learning framework named SleePyCo that incorporates 1) a feature pyramid and 2) supervised contrastive learning for automatic sleep scoring. For the feature pyramid, we propose a backbone network named SleePyCo-backbone to consider multiple feature sequences on different temporal and frequency scales. Supervised contrastive learning allows the network to extract class discriminative features by minimizing the distance between intra-class features and simultaneously maximizing that between inter-class features. Comparative analyses on four public datasets demonstrate that SleePyCo consistently outperforms existing frameworks based on single-channel EEG. Extensive ablation experiments show that SleePyCo exhibits enhanced overall performance, with significant improvements in discrimination between the N1 and rapid eye movement (REM) stages.Comment: 14 pages, 3 figures, 8 table

In-Line Ultrasonic Monitoring for Sediments Stuck on Inner Wall of a Polyvinyl Chloride Pipe

This research verified the applicability and effectiveness of the ultrasonic monitoring of sediments stuck on the inner wall of polyvinyl chloride (PVC) pipes. For identifying the transmittance of acoustic energy and the speed of sound in the PVC material, the pulse-echo ultrasonic testing was conducted for PVC sheets of different thicknesses. To simulate the solidified sediment, the hot melt adhesive (HMA) was covered on the inner wall of the PVC pipe in different heights. From the experiment, the speeds of sound in the PVC and the HMA materials were obtained as about 2258 and 2000 m/s, respectively. The thickness of the materials was calculated through the signal processing such as taking the absolute value and low pass filtering, the echo detection, and the measurement of the time of flight. The errors between actual and measured thicknesses of PVC sheets were below 5%. In the case of the substance stuck on the inner wall, the errors were below 2.5%. Since the pulse-echo ultrasonic inspection is available on the outer surface and its measurement accuracy was over 95%, it can be an efficient and effective in-service structural health monitoring for the sediment on the wall of PVC pipes

Nondestructive Evaluation of Thermal Aging in Al6061 Alloy by Measuring Acoustic Nonlinearity of Laser-Generated Surface Acoustic Waves

The structures in high-temperature environments are prone to undergo hardening and embrittlement as a result of thermal aging; this can cause variations in their mechanical properties. Because these changes occur at the microstructural level, it is difficult to evaluate them through linear ultrasonic techniques. In this work, a surface acoustic wave (SAW) was used to measure and compare the acoustic nonlinearity and mechanical properties of Al6061 alloys heat-treated at 220 °C for different durations (0 min, 20 min, 40 min, 1 h, 2 h, 10 h, 100 h, 1000 h). The SAW was generated by a pulsed laser and then received by an interferometer. Moreover, the yield strength, ultimate strength, and elongation to failure were measured by tensile tests. The results demonstrate that the critical variations in the mechanical properties can be detected by monitoring the variation features in the acoustic nonlinearity. Transmission electron microscopy images were captured to observe the microstructural changes, which shows that the acoustic nonlinearity varied according to the change in the precipitation phase. This supports the acoustic nonlinearity measurement using the laser-generated SAW being an effective technique for the fully noncontact nondestructive evaluation of material degradations as well as changes in mechanical properties

Quantile Autoencoder With Abnormality Accumulation for Anomaly Detection of Multivariate Sensor Data

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

In-Line Ultrasonic Monitoring for Sediments Stuck on Inner Wall of a Polyvinyl Chloride Pipe

This research verified the applicability and effectiveness of the ultrasonic monitoring of sediments stuck on the inner wall of polyvinyl chloride (PVC) pipes. For identifying the transmittance of acoustic energy and the speed of sound in the PVC material, the pulse-echo ultrasonic testing was conducted for PVC sheets of different thicknesses. To simulate the solidified sediment, the hot melt adhesive (HMA) was covered on the inner wall of the PVC pipe in different heights. From the experiment, the speeds of sound in the PVC and the HMA materials were obtained as about 2258 and 2000 m/s, respectively. The thickness of the materials was calculated through the signal processing such as taking the absolute value and low pass filtering, the echo detection, and the measurement of the time of flight. The errors between actual and measured thicknesses of PVC sheets were below 5%. In the case of the substance stuck on the inner wall, the errors were below 2.5%. Since the pulse-echo ultrasonic inspection is available on the outer surface and its measurement accuracy was over 95%, it can be an efficient and effective in-service structural health monitoring for the sediment on the wall of PVC pipes

Synthetic Aperture Imaging of Contact Acoustic Nonlinearity at Closed Interfaces

Ultrasonic imaging has been widely used as an intuitive recognition method for the detection of defects [1]. To enhance the resolution in ultrasound imaging, various kinds of techniques have been developed. Synthetic aperture focusing technique (SAFT) is one of effective post-processing techniques for the resolution improvement. Many studies have shown that SAFT has high resolution as well as high signal to noise ratio for identifying the characteristics of defects accurately [2]. However, most of the imaging techniques based on linear characteristics of ultrasound could underestimate the size of flaws. In particular, the defects in initial state so called micro cracks or closed interfaces are very difficult to be visualized. In order to visualize these micro defects, it is necessary to adopt novel imaging technique using nonlinear ultrasonic characteristics such as contact acoustic nonlinearity (CAN) effect. This study proposed a nonlinear SAFT based on CAN effect and verified its effectiveness. The experiments with array probe for imaging closed interfaces were carried out. The pressure of the interfaces was increased by a hydraulic press, which resulted in the change of the contact state at the interfaces from open interfaces to closed interfaces. When a fundamental ultrasonic wave is incident at closed interfaces, the CAN effect leads the harmonic generation [3]. The proposed synthetic aperture imaging based on CAN effect was applied to visualize the closed interfaces with respect to the change of the contact interface condition. The results showed that SAFT based on CAN effect was effective for the detection of closed interface. This supports that synthetic aperture imaging techniques based on acoustic nonlinearity had advantages for the diagnosis of structural integrity.</p

Monitoring of Thermal Aging of Aluminum Alloy via Nonlinear Propagation of Acoustic Pulses Generated and Detected by Lasers

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 &#215; 10&#8722;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 &#176;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&#8217; strength and rigidity in the process of their heat treatment