Search Results (329)

Composite engine fan blades are critical aircraft engine components, and their failure can compromise the safe and reliable operation of the entire aircraft. To enhance aircraft availability and safety within a condition-based maintenance framework, effective methods are needed to identify damage and monitor the blades’ condition throughout manufacturing and operation. This paper presents a unique experimental framework for real-time monitoring of composite engine blades utilizing state-of-the-art structural health monitoring (SHM) technologies, discussing the associated benefits and challenges. A case study is conducted on a representative Foreign Object Damage (FOD) panel, a substructure of a LEAP (Leading Edge Aviation Propulsion) engine fan blade, which is a curved, 3D-woven Carbon Fiber Reinforced Polymer (CFRP) panel with a secondary bonded steel leading edge. The loading scheme involves incrementally increasing, cyclic 4-point bending (loading–unloading) to induce controlled damage growth, simulating in-operation conditions and allowing evaluation of flexural properties before and after degradation. External damage, simulating foreign object impact common during flight, is introduced using a drop tower apparatus either before or during testing. The panel’s condition is monitored in-situ and in real time by two types of SHM sensors: screen-printed piezoelectric sensors for guided ultrasonic wave propagation studies and surface-bonded Fiber Bragg Grating (FBG) strain sensors. Experiments are conducted until panel collapse, and degradation is quantified by the reduction in initial stiffness, derived from the experimental load-displacement curves. This paper aims to demonstrate this unique experimental setup and the resulting SHM data, highlighting both the potential and challenges of this SHM framework for monitoring complex composite structures, while an attempt is made at correlating SHM data with structural degradation. Full article

As a critical supporting component in geotechnical engineering structures such as bridges, tunnels, and highways, the anchorage quality of bolts directly impacts their structural safety. The ultrasonic guided wave method is a popular method for the non-destructive testing of anchorage quality. However, noise from complex field environments, modal mixing caused by anchoring interface reflections, and dispersion effects make it challenging to directly extract defect features from guided wave signals in the time or frequency domains. To address these challenges, this study proposes a solution based on the combination of the guided wave time–frequency spectrum and the gated attention residual network (GA-ResNet). The GA-ResNet introduces a gating mechanism to balance spatial attention and channel attention, and it is used for anchoring model type recognition. Experiments were conducted on four types of anchorage models, and the time–frequency spectrum was selected to be the input feature. The results demonstrate that the GA-ResNet can effectively predict the anchorage bolt defect type and prevent potential safety accidents. Full article

Productive and healthy soils are essential in agriculture and other economic uses of land which depend on plant growth, and are under increasing pressure globally. The physical properties of soil, its porosity and pore structure, also have a significant impact on a wide range of environmental factors, such as surface water runoff and greenhouse gas exchange. Methods exist for evaluating soil porosity that are applied in a laboratory environment or by inserting sensors into soil in the field. However, such methods do not readily sample adequately in space or time and are labour-intensive. The purpose of the current study is to investigate the potential for estimation of soil porosity and pore size using the strength of reflection of audio pulses from natural soil surfaces. Estimation of porous material properties using acoustic reflections is well established. But because of the complex, viscous interactions between sound waves and pore structures, these methods are generally restricted to transmissions at low audio frequencies or at ultrasonic frequencies. In contrast, this study presents a novel design for an integrated broad band sensing system, which is compact, inexpensive, and which is capable of rapid, non-contact, and in situ sampling of a soil structure from a small, moving, farm vehicle. The new system is shown to have the capability of obtaining soil parameter estimates at sampling distances of less than 1 m and with accuracies of around 1%. In describing this novel design, special care is taken to consider the challenges presented by real agriculture soils. These challenges include the pasture, through which the sound must penetrate without significant losses, and soil roughness, which can potentially scatter sound away from the specular reflection path. The key to this new integrated acoustic design is an extension of an existing theory for acoustic interactions with porous materials and rigorous testing of assumptions via simulations. A configuration is suggested and tested, comprising seven audio frequencies and three angles of incidence. It is concluded that a practical, new operational tool of similar design should be readily manufactured. This tool would be inexpensive, compact, low-power, and non-intrusive to either the soil or the surrounding environment. Audio processing can be conducted within the scope of, say, mobile phones. The practical application is to be able to easily map regions of an agricultural space in some detail and to use that to guide land treatment and mitigation. Full article

The traditional research methods of the notch frequency phenomenon are mainly discussed by experimental observation or the semi-analytical finite element method. In this paper, the notch frequency characteristics of ultrasonic guided waves are simulated by the general finite element method. Firstly, the theoretical dispersion curve of the longitudinal mode in the axially loaded rod is derived by the acoustic elasticity theory, and the finite element simulation is carried out by ABAQUS/Explicit 6.14 to simulate the wave propagation in the seven-wire steel strand. In order to verify the model, laboratory experiments are carried out on three types of prestressed steel strands with diameters of 12.7 mm, 15.2 mm, and 17.8 mm, respectively. Each specimen is gradually loaded from 50 kN to 110 kN in increments of 30 kN. At each loading level, the ultrasonic signal is obtained, and the corresponding notch frequency is extracted from the spectrum. The experimental results confirm the accuracy of the model, and the maximum deviation between the predicted notch frequency and the measured value is 3%. The results show that the proposed method provides a robust and non-destructive means for structural health monitoring in civil engineering applications, and has the potential to be more widely used in complex waveguide structures. Full article

Ultrasonic guided wave interdigital transducers realized with piezoelectric materials are of interest for structural health monitoring systems because of their capability of performing Lamb wave mode selection with respect to single-element transducers. Besides this advantage, the coverage of large areas with a minimum number of elements is an important challenge and the problem of efficient excitation with integrated electronics must be solved. This work proposes an electrical matching network topology made of L and C passive components that can be designed for the trade-off between electrical to mechanical conversion efficiency and bandwidth. The network circuit is analyzed considering the equivalent transducer impedance and the output impedance of the driving electronics. The design rules derived by the transfer function analysis are described and a case study for a piezopolymer IDT is presented. Finally, with the implementation of the integrated matching network with the connector of the IDT, the effect of cable capacitance is minimized. In conclusion this article is a contribution to the study of using IDT efficiently and in a versatile mode for different electronic front-ends that usually operate at low power supply voltage. Full article

In order to measure the depth profile of the heat-treated case-hardened layer of linear guides, this paper proposes a B-scan imaging and 3D visualization method for detecting the depth profile of the case-hardened layer of linear guides based on the ultrasonic transverse wave backscattering technology. Firstly, by analyzing the generation mechanism of ultrasonic transverse waves and their advantages in material detection, and combining the differences in metallographic structure and hardness properties between the case-hardened layer and the base material, an ultrasonic transverse wave backscattering model for the case-hardened layer of linear guides was established. Then, an ultrasonic transverse wave detection experiment for the GH20 linear guide was designed and carried out to obtain the A-scan signals of the case-hardened layer depth at different positions on the cross-section of the linear guide. Finally, the A-scan signals obtained from the detection were used to generate the B-scan image of the case-hardened layer depth profile, and the 3D visualization of the case-hardened layer of the linear guide was achieved using Python and VTK tools. The experimental results show that the error between the measurement results of ultrasonic transverse waves and those of the metallographic method is 0.063 mm, and the detection results are within the allowable error range. This research provides an efficient, intuitive, and reliable technical method for detecting the depth of the case-hardened layer of linear guides in the industrial field. Full article

Hydrogen is one of the future green energy sources that could resolve issues related to fossil fuels. The widespread use of hydrogen can be enabled by composite-overwrapped pressure vessels for storage. It offers advantages due to its low weight and improved mechanical performance. However, the safe storage of hydrogen requires continuous monitoring. Combining ultrasonic guided waves with interpretable machine learning provides a powerful tool for structural health monitoring. In this study, we developed a feature extraction approach based on a similarity method that enables interpretability in the proposed machine learning model for damage detection and localization in pressure vessels. Furthermore, a systematic optimization was performed to explore and tune the model’s parameters. This resulting model provides accurate damage localization and is capable of detecting and localizing damage on hydrogen pressure vessels with an average localization error of 2 cm and a classification accuracy of 96.5% when using quantized classification. In contrast, binarized classification yields a higher accuracy of 99.5%, but with a larger localization error of 6 cm. Full article

Modern aerospace engineering places increasing emphasis on materials that combine low weight with high mechanical performance. Fiber metal laminates (FMLs), which merge metal layers with fiber-reinforced composites, meet this demand by delivering improved fatigue resistance, impact tolerance, and environmental durability, often surpassing the performance of their constituents in demanding applications. Despite these advantages, inspecting such thin, layered structures remains a significant challenge, particularly when they are difficult or impossible to access. As with any new invention, they always come with challenges. This study examines the effectiveness of the fundamental anti-symmetric Lamb wave mode (A0) in detecting weak interfacial defects within Carall laminates, a type of hybrid fiber metal laminate (FML). Delamination detectability is analyzed in terms of strong wave dispersion observed downstream of the delaminated sublayer, within a region characterized by acoustic distortion. A three-dimensional finite element (FE) model is developed to simulate mode trapping and full-wavefield local displacement. The approach is validated by reproducing experimental results reported in prior studies, including the author’s own work. Results demonstrate that the A0 mode is sensitive to delamination; however, its lateral resolution depends on local position, ply orientation, and dispersion characteristics. Accurately resolving the depth and extent of delamination remains challenging due to the redistribution of peak amplitude in the frequency domain, likely caused by interference effects in the acoustically sensitive delaminated zone. Additionally, angular scattering analysis reveals a complex wave behavior, with most of the energy concentrated along the centerline, despite transmission losses at the metal-composite interfaces in the Carall laminate. The wave interaction with the leading and trailing edges of the delaminations is strongly influenced by the complex wave interference phenomenon and acoustic mismatched regions, leading to an increase in dispersion at the sublayers. Analytical dispersion calculations clarify how wave behavior influences the detectability and resolution of delaminations, though this resolution is constrained, being most effective for weak interfaces located closer to the surface. This study offers critical insights into how the fundamental anti-symmetric Lamb wave mode (A0) interacts with delaminations in highly attenuative, multilayered environments. It also highlights the challenges in resolving the spatial extent of damage in the long-wavelength limit. The findings support the practical application of A0 Lamb waves for structural health assessment of hybrid composites, enabling defect detection at inaccessible depths. Full article

The integrity of bolted components primarily relies on the quality of interfacial contact, which is achieved by maintaining prescribed bolt torque levels. However, challenges arise from corrosion-induced bolt head damage, potentially compromising the bolt preload, and quantifying such effects remains unanswered. Many studies often compare bolt corrosion’s effects to bolt loosening as both affect the interfacial contact stresses to some extent. This technical study aimed to investigate whether a correlation exists between the impact of bolt head damage and the different levels of bolt torque. Guided wave ultrasonic testing (UT) was implemented for this investigation. Laboratory experiments were conducted to monitor the transmission of ultrasonic signals across the bolted interface first during the bolt-tightening process. Once the highest bolt torque was achieved, the process was repeated for a simplified corrosion scenario, simulated by artificially damaging the bolt head in a controlled manner. The analysis focused on studying the transmission of signal energy for both scenarios. The findings revealed different trends for the signal energy transmission during bolt tightening, which are subjective to the inspection frequency. On the contrary, even at an advanced level of bolt head damage corresponding to 16% mass loss, no clear or monotonic trend was observed in the total transmitted energy. While the total energy remained relatively stable across all inspection frequencies, distinct waveform changes, such as energy redistribution and the emergence of additional wave packets, were observed. The findings emphasize the need for more advanced waveform-based analysis techniques to detect and interpret subtle changes caused by bolt degradation. Full article

From the point of view of the intelligent operation and maintenance of high-speed train tracks, this paper examines the research status of high-speed train rail damage detection technology in the field of high-speed train track operation and maintenance detection in recent years, summarizes the damage detection methods for high-speed trains, and compares and analyzes different detection technologies and application research results. The analysis results show that the detection methods for high-speed train rail damage mainly focus on the research and application of non-destructive testing technology and methods, as well as testing platform equipment. Detection platforms and equipment include a new type of vortex meter, integrated track recording vehicles, laser rangefinders, thermal sensors, laser vision systems, LiDAR, new ultrasonic detectors, rail detection vehicles, rail detection robots, laser on-board rail detection systems, track recorders, self-moving trolleys, etc. The main research and application methods include electromagnetic detection, optical detection, ultrasonic guided wave detection, acoustic emission detection, ray detection, vortex detection, and vibration detection. In recent years, the most widely studied and applied methods have been rail detection based on LiDAR detection, ultrasonic detection, eddy current detection, and optical detection. The most important optical detection method is machine vision detection. Ultrasonic detection can detect internal damage of the rail. LiDAR detection can detect dirt around the rail and the surface, but the cost of this kind of equipment is very high. And the application cost is also very high. In the future, for high-speed railway rail damage detection, the damage standards must be followed first. In terms of rail geometric parameters, the domestic standard (TB 10754-2018) requires a gauge deviation of ±1 mm, a track direction deviation of 0.3 mm/10 m, and a height deviation of 0.5 mm/10 m, and some indicators are stricter than European standard EN-13848. In terms of damage detection, domestic flaw detection vehicles have achieved millimeter-level accuracy in crack detection in rail heads, rail waists, and other parts, with a damage detection rate of over 85%. The accuracy of identifying track components by the drone detection system is 93.6%, and the identification rate of potential safety hazards is 81.8%. There is a certain gap with international standards, and standards such as EN 13848 have stricter requirements for testing cycles and data storage, especially in quantifying damage detection requirements, real-time damage data, and safety, which will be the key research and development contents and directions in the future. Full article

The timely detection of delamination is essential for preventing catastrophic failures and extending the service life of carbon fiber-reinforced polymers (CFRP). Full wavefields in CFRP encapsulate extensive information on the interaction between guided waves and structural damage, making them a widely utilized tool for damage mapping. However, due to the multimodal and dispersive nature of guided waves, interpreting full wavefields remains a significant challenge. This study proposes an end-to-end delamination imaging approach based on UNet++ using 2D frequency domain spectra (FDS) derived from full wavefield data. The proposed method is validated through a self-constructed simulation dataset, experimental data collected using Scanning Laser Doppler Vibrometry, and a publicly available dataset created by Kudela and Ijjeh. The results on the simulated data show that UNet++, trained with multi-frequency FDS, can accurately predict the location, shape, and size of delamination while effectively handling frequency offsets and noise interference in the input FDS. Experimental results further indicate that the model, trained exclusively on simulated data, can be directly applied to real-world scenarios, delivering artifact-free delamination imaging. Full article

Compared to traditional temperature measurement methods, ultrasonic temperature measurement technology based on the principle of resonance offers advantages such as shorter section lengths, higher signal amplitude, and reduced signal attenuation. First, the type of sensor-sensitive element was determined, with a resonant design chosen to improve measurement performance; using magnetostrictive and resonant temperature measurement principles, the length, diameter, and resonator dimensions of the waveguide rod were designed, and a molybdenum–rhenium alloy (Mo-5%Re) material suitable for high-temperature environments was selected; COMSOL finite element simulation was used to simulate the propagation characteristics of acoustic signals in the waveguide rod, observing the distribution of sound pressure and energy attenuation, verifying the applicability of the model in high-temperature testing environments. Second, a resonant temperature sensor consistent with the simulation parameters was prepared using a molybdenum–rhenium alloy waveguide rod, and an ultrasonic resonant temperature-sensing system suitable for high-temperature environments up to 1800 °C was constructed using the molybdenum–rhenium alloy waveguide rod. The experiment used a tungsten–rhenium calibration furnace to perform static calibration of the sensor. The temperature range was set from room temperature to 1800 °C, with the temperature increased by 100 °C at a time, and it was maintained at each temperature point for 5 to 10 min to ensure thermal stability. This was conducted to verify the performance of the sensor and obtain the functional relationship between temperature and resonance frequency. Experimental results show that during the heating process, the average resonance frequency of the sensor decreased from 341.8 kHz to 310.37 kHz, with an average sensitivity of 17.66 Hz/°C. During the cooling process, the frequency increased from 309 kHz to 341.8 kHz, with an average sensitivity of 18.43 Hz/°C. After cooling to room temperature, the sensor’s resonant frequency returned to its initial value of 341.8 kHz, demonstrating excellent repeatability and thermal stability. This provides a reliable technical foundation for its application in actual high-temperature environments. Full article

The ultrasonic guided wave-based damage imaging methods are often limited in detection accuracy and resolution due to the dispersive characteristics of guided waves. Finding ways to extract more information from the guided wave field to improve imaging resolution has always been a hot topic in ultrasonic imaging. Based on the same set of guided wave field data obtained by numerical simulation and experiments, this paper compares the detection accuracy and resolution of the time-domain delay-and-sum (DAS) method, the frequency-domain DAS method, and the DORT-MUSIC method, which integrates time-reversal operator decomposition with multiple signal classification. The results show that, compared to the traditional time-domain imaging method, the frequency-domain method that incorporates dispersion relations exhibits significantly higher imaging accuracy. Additionally, the DORT-MUSIC method demonstrates a remarkable advantage in resolution, which can approach the diffraction limit. Related work in this paper provides a research basis for improving the imaging accuracy and resolution for ultrasonic guided waves in the practical application of structure damage detection. Full article

Lamb waves offer a series of desirable features for Structural Health Monitoring (SHM) applications, such as the ability to detect small defects, allowing to detect damage at early stages of its evolution. On the downside, their propagation through media with multiple geometrical features results in complicated patterns, which complicate the task of damage detection, thus hindering the realization of their full potential. This is exacerbated by the fact that numerical models for Lamb waves, which could aid in both the prediction and interpretation of such patterns, are computationally expensive. The present paper provides a flexible surrogate to rapidly evaluate the sensor response in scenarios where Lamb waves propagate in plates that include multiple features or defects. To this end, an offline–online ray tracing approach is combined with Frequency Response Functions (FRFs) and transmissibility functions. Each ray is thereby represented either by a parametrized FRFs, if the origin of the ray lies in the actuator, or by a parametrized transmissibility function, if the origin of the ray lies in a feature. By exploiting the mechanical properties of propagating waves, it is possible to minimize the number of training simulations needed for the surrogate, thus avoiding the repeated evaluation of large models. The efficiency of the surrogate is demonstrated numerically, through an example, including different types of features, in particular through holes and notches, which result in both reflection and conversion of incident waves. For most sensor locations, the surrogate achieves an error between 1% and 4%, while providing a computational speedup of three to four orders of magnitude. Full article

The inspection of corrosion and pitting-type defects is critical in the petrochemical, marine, and offshore industries. Guided wave inspection is widely used to detect these flaws and control operational costs. Higher order modes cluster (HOMC) guided waves, composed of higher-order Lamb wave modes, offer enhanced resolution compared to low-frequency guided waves. They exhibit minimal dispersion, reduced sensitivity to surface features such as T-joints, and retain most of their energy upon interacting with surface defects. This study employs two-dimensional finite element simulations to investigate the propagation and interaction of HOMC guided waves with defects in a T-joint and an aluminum plate. Both conventional fitting methods and machine learning (ML) models are used to estimate the depth of sharp defects reaching up to half the plate thickness. The results demonstrate that both approaches can utilize data from defects of one width to predict the depth of defects with a different width. The ML model outperforms the fitting method, achieving higher prediction accuracy while reducing dependence on expert knowledge. The developed method shows strong potential for characterizing sharp defects of varying widths, closely resembling real-world pitting corrosion scenarios. Full article