Wavelet scattering transformation for sub-surface damage detection and localization in PZT sensor.

Structural Health Monitoring (SHM) systems typically employ piezoelectric sensors for the monitoring of variations in structural members. However, subsurface deterioration or damage within the sensors can impair the system's overall reliability and precision. This drawback can be addressed using a suggested reference-free detection method and subsurface defect localization for Lead zirconate titanate (PZT) sensor defects, combining signal processing and machine-learning-based feature extraction techniques.

Autonomous defect estimation in aluminum plate and prognosis through stochastic process modeling.

The structural integrity and longevity of aluminum alloy components in lightweight engineering require accurate and efficient damage detection and prognosis methods. Traditional supervised machine learning (ML) techniques often face limitations due to dependency on large datasets, risk of overfitting, and high computational costs. To overcome these challenges, this study proposes an unsupervised learning framework that combines k-means clustering with a multi-phase gamma process to detect and model damage in aluminum plates.

Scanning acoustic microscopy for biomechanical characterization of reindeer antler using singular spectral analysis.

Scanning Acoustic Microscopy (SAM) has become a vital tool in materials science and biology, allowing for non-destructive and non-invasive analysis of biological specimens and bio-inspired materials. Its deep-penetrating imaging capabilities enable a broad range of applications. This study combines SAM with Singular Spectral Analysis (SSA) to enhance signal processing and extract key data, particularly acoustic impedance.

AutoSAFT: Autofocusing for extended depth of imaging in scanning acoustic microscopy.

In the scanning acoustic microscopy (SAM) imaging, it is essential to address the diminished lateral resolution in the out-of-focus region, as image quality correlates with the ultrasound propagation distance either above or below the focal plane. To focus the scanned image, a refocusing technique called synthetic aperture focusing technique (SAFT) is widely used, which improves the resolution by extending the depth of focus manually. In SAM, refocusing the image accurately is challenging without prior defocusing information.

Uncertainty analysis of Altantic salmon fish scale's acoustic impedance using 30 MHz C-Scan measurements.

Understanding the biomechanics of fish scales is crucial for their survival and adaptation. Ultrasonic C-scan measurements offer a promising tool for non-invasive characterization, however, existing literature lacks uncertainty analysis while evaluating acoustic impedance. This article presents an innovative integration of uncertainty into the analytical framework for estimating stochastic specific acoustic impedance of salmon fish scale through ultrasonic C-scans.