Non-destructive evaluation (NDE) and structural health monitoring (SHM) play a critical role in ensuring the safety, reliability, and longevity of engineering structures and materials. Among the various NDE techniques, ultrasonic methods are widely regarded as the most effective for damage detection and material characterization due to their high sensitivity and versatility. However, conventional ultrasonic approaches face challenges in analyzing complex signals, limiting their accuracy and efficiency in certain applications. The advent of machine learning (ML) has revolutionized ultrasonic data analysis by utilizing advanced data mining and pattern recognition capabilities to decode intricate signal patterns. This review provides a comprehensive overview of ML techniques applied to ultrasonic-based damage detection and material characterization, including key processes such as data preprocessing and feature engineering. Emphasis is placed on case studies and real-world applications, highlighting ML’s role in defect detection, localization, and material property assessment. Additionally, the paper addresses critical challenges, limitations, and future directions, offering insights into the transformative potential of ML in ultrasonic NDE and SHM.

Guided waves propagating in nonlinear media, featuring second harmonic generation, represent a promising avenue for early-stage damage detection due to their high sensitivity and long-range propagation capabilities. However, nonlinear ultrasonic measurements are hindered by nonlinearities induced by the experimental system, necessitating careful calibrations that have restricted their application to laboratory settings. While several phononic crystal and metamaterial designs have been devised to enhance nonlinear-based ultrasonic testing, most are tailored for suppressing second harmonics within a frequency range of 100–300 kHz, primarily utilizing low-frequency excitation. In this paper, we propose a metallic ring-shaped metafilter designed to explore high-order bandgaps. To fully understand the bandgap characteristics, we begin by analyzing mode shapes, providing insights into the underlying wave mechanics. The efficacy of the designed filter is subsequently assessed through 3D time step elastodynamic simulations. In addition, this study underscores the significance of parameters such as the number of rings employed in the filter, signal duration, and bandgap width in optimizing its performance. Furthermore, the observed mode conversion phenomena from S0 to A0 guided wave modes underscore the filter’s capacity to influence guided wave propagation. The defect localization technique, based on the time difference of arrival of second-order wave modes, accurately predicts the defect location with an error margin of less than 0.2%. The present investigation showcases advancements in the sensitivity of nonlinear-based guided wave testing for characterizing microstructural changes, promising substantial potential for detecting incipient damage in practical structural health monitoring applications.

This article presents an analysis of torsional wave propagation in phononic crystal-based metamaterials. Such structures hold great promise as tools for wave manipulation. The unit cell of the presented structure was meticulously examined to obtain dispersion curves, revealing the presence of bandgaps and negative group velocities. The calculations of effective material parameters, based on eigenfrequencies, are presented to substantiate the existence of the bandgap and the negative value of group velocity. Time-domain simulations were conducted at various frequencies to analyze the wave behavior. In the case of negative group velocity, the wave inside the metamaterial propagates in the same direction as the incident wave. To verify the existence of negative velocity, a 2D Fast Fourier Transform (FFT) was performed, and the results from the 2D FFT data analysis align perfectly with the eigenfrequency analysis.

The results of a study on the geometric shape of the damper on the efficiency of the ultrasonic piezoelectric transducer are presented. In particular, a damper in the form of a truncated cone is considered, the generatrix of which has an inclination angle α relative to the diameter of the piezoceramic plate. The shape of the damper in the form of a truncated cone is chosen based on the a priori assumption that this helps to increase the path of the wave in the damper material due to numerous reflections in it. A criterion for the efficiency of damper operation is proposed. The optimal (from the point of view of the damper efficiency) value of the angle α was determined theoretically and experimentally. The technology of its production is described. Satisfactory agreement between the results of theoretical and experimental studies was noted.

In modern days, low-frequency vibration is still challenging to suppress due to its high vibrational energy. A typical suppression method is to increase the object’s mass to reduce the amplitude of the vibration, but such a way is unsuitable in many cases. Membrane dampers can potentially eliminate the limitation and offer lightweight and compact damper. The idea is to decrease the stiffness and add additional mass to increase the dissipation of the vibration energy. For that, the membrane and an extra mass made of silicone rubber were used for the damper. Finite element eigenfrequency simulation showed the transformation of each mode to the damper mode, where the tube displacement was zero. Also, it showed the bandgap between modes in the frequency range from 106 Hz to 158 Hz. The experimental verification of clamped from both ends of the tube showed the predicted bandgap and absence of the resonance peak of the bare tube. Overall, the membrane damper showed good efficiency in extremely low frequencies and seems promising for vibration suppression.