Traditional phased array controllers are bulky and expensive meaning they cannot be used for SHM applications where equipment needs to be left in place for regular measurements to be made. Much of the size and cost associated with traditional array controllers arises due to the electronics architecture used for the transmission signals and receiver amplification. Removing these components is not possible when traditional excitation techniques are used. Similarly, high-voltage transmit signals are not easily switched, making channel multiplexing for the purpose of cost-reduction complicated. Conversely, coded excitation techniques can enable the construction of miniature, low-power acquisition systems that are light-weight and low-cost. This is possible due to the use of long-sequence based transmit signals that enable transmission energy to be spread over time, making low-voltage excitations capable of producing high-quality signals following appropriate processing. Furthermore, low voltage transmit signals are easily switched, which enables additional system simplification via multiplexing. Devices using this code-based architecture are therefore well suited to SHM as they can be installed in place on structures to monitor cracks online. A phased array monitoring system was built using an acquisition module designed around using coded excitation – a CA1-MUX32 from CodeAcq. This system uses <1V transmit amplitudes (in pulse-echo mode) and is of similar size to phased array probes themselves. The system was installed on a reference sample containing a notch of increasing depth and used to measure the notch size. Total Focusing Method images were acquired at regular intervals across the block. This paper presents the results of the experiments and compares the performance of the low-power coded excitation system to a standard phased array controller commonly used in lab conditions.

Ultrasonic techniques (UT) are a vital technique for detailed wind turbine blade composite inspection. However, in-situ inspection in maintenance is challenging using handheld tools. A development of a lightweight, inexpensive phased array ultrasonic, specifically tailored for wind turbine blade inspection, is presented in this work. The UT probe is based on a 3D-printed structural design to reduce the weight, as a drone used to transport it to the wind turbine blade for in-situ inspection. Further, to maximize coupling performance on Glass Fiber Reinforced Polymer (GFRP) and Carbon Fiber Reinforced Polymer (CFRP) composite surfaces, the study compares the performance of ultrasonic wave propagation in pure silicone as a wheel tyre material and a low-cost sandwich (silicone and cotton) wheel-tyre material with acoustic impedance values closely matched to that of water. 3D-printed parts were used in the design of the probe housing, inexpensive tyre, and wheel assembly to reduce weight, increase manoeuvrability, and lower manufacturing costs without sacrificing structural integrity or acoustic performance. Phased array ultrasonic testing was used for simulation validation in order to assess the suggested probe's imaging potential, fault detectability, and usefulness. The findings show the viability of a flexible, reasonably priced UT inspection tool that can be used to examine large-scale wind turbine blade composite structures. This instrument offers a practical method to collect inspection data, which can be integrated into a digital twin to inform future inspection and repair decisions for wind turbine blades in the field.

Metal-rubber layered structures are commonly used as barriers against acids and corrosive liquids in industrial vessels. The complex multi-layer nature of these structures—combining insulating and conductive materials with highly sound-attenuating layers and intermediate boundaries—makes assessing their barrier effectiveness challenging. This is a critical issue concerning structural integrity and safety. Specifically, the boundary between degraded rubber and corrosive liquid is diffuse rather than abrupt, resulting in a gradient of altered physicochemical properties rather than a different change in thickness.

A non-destructive, non-invasive ultrasonic strategy is proposed to monitor the acid-induced degradation of anti-corrosion rubber linings bonded to steel plates, measured from the metallic side. This strategy uses medium-frequency (1–5 MHz) pulse-echo ultrasound combined with time and frequency domain signal processing. These techniques aim to detect subtle signal variations caused by barrier degradation, distinguishing them from external fluctuations. This involves selective analysis of attenuation and Time of Flight (TOF) of echoes from key boundaries, signal comparison algorithms (SDC, Euclidean, Chebyshev, and Manhattan), and resonance analysis of the structural signal. For this purpose, time-domain analysis, FFT, and CWT techniques were used.

The study was conducted in two stages. First, individual barrier sections were studied to look for signal changes caused by controlled stepwise degradation of the lining. In the second stage, a comprehensive three-week continuous degradation experiment was carried out using an ALTAS cell (Figure 1) containing 98% sulfuric acid. This involved two different barriers and the simultaneous comparison of twelve ultrasonic configurations.

Results indicate that signal comparison algorithms and resonance analysis yield a high correlation between the physicochemical degradation of the barriers and specific ultrasonic signal parameters. Key parameters include resonance frequencies and their magnitudes, as well as numerical values derived from the comparison algorithms. In the continuous degradation experiment, the percentage changes obtained using the Euclidean and Manhattan algorithms exhibit a monotonically increasing trend, with a maximum ripple of 6–10%, depending on the lining, attributable to temperature fluctuations. The slope is steeper within the first 1–2 days, after which the trend gradually stabilises at a rate that also depends on the type of lining. Regarding resonance analysis, the changes in frequency values were approximately 9 kHz or 1.2% relative change, whilst amplitude variation was up to 20% for normalized non-principal resonance peaks and up to 60% in absolute terms. Frequency analysis results were observed to be predominantly monotonic.

These findings pave the way for continuous, non-destructive monitoring of barrier effectiveness against corrosive media in industrial settings, thereby enhancing the safety of critical facilities.

Ensuring the safety of civil structures is vital in preventing disasters affecting people, economy, and environment.

Active Structural Health Monitoring (SHM) based on ultrasonic waves helps to achieve this, but its signals can be distorted by environmental and operating conditions (EOCs), causing false damage detections. To address this, many studies have focused on environmental effects (especially temperature) compensation using data-driven and physics-based methods. Among these, the time-stretching method is a common physics-based approach method.

Time-stretching has however a fundamental limitation: it inherently distorts the waveform shape and changes its frequency spectrum. This frequency distortion alters the shape of individual wave packets even when temperature variations are uniform and the medium is homogeneous [1]. Consequently, damage detection methods that rely on waveform similarity metrics (e.g., correlation coefficient) are affected, potentially leading to false alarms or reduced damage sensitivity.

While time-stretching is generally used in Lamb wave propagation in thin panels for temperature compensation, this research focuses on concrete monitoring using embedded transducers, where wave propagation is three-dimensional and the material is highly heterogeneous. In such conditions, temperature variations and scattering effects make compensation more complex. The aim is to assess how much the conventional time-stretching method can be improved to handle these challenges.

To achieve this goal, two methods are proposed to enhance waveform preservation while maintaining temperature compensation. The first approach is based on frequency correction as proposed by Croxford et al. [1], where the reference wave packet shape should be known and all the wave packets in the signal should have the same shape, which is not often realistic. The second approach introduces a two-parameter optimisation combining time-shift and time-stretch operations. Time-shifting simply translates the entire waveform along the time axis without modifying its shape or frequency content. Optimising both parameters simultaneously reduces the amount of stretching required, thereby minimising waveform distortion.

Both methods are evaluated first on analytically generated signals, and then on real pitch-catch measurements performed in air using identical piezoelectric transducers for the emitter and the receiver. These transducers have been developed at ULB-BATir and are intended to be embedded in concrete for SHM using ultrasonic waves. The tests were performed in a climatic chamber over a temperature range of 0°C to 40°C, with relative humidity held constant at 60%. To further assess the robustness of the compensation, an obstacle was introduced between the emitter and receiver to modify the waveform, and check if the obstacle can be detected under changing temperature conditions.

The results show that both methods performed better than conventional time-stretching, showing higher signal correlation and improved waveform preservation. They maintained waveform fidelity across temperature variations, making ultrasonic SHM more accurate and reliable. Future work will apply these approaches to concrete structures with heterogeneous and non-uniform temperature conditions.

References:

1. Croxford, A.J., Moll, J., Wilcox, P.D. and Michaels, J.E., 2010. Efficient temperature compensation strategies for guided wave structural health monitoring. Ultrasonics, 50(4-5), pp.517-528.

The precise characterization of internal defects such as their type, size, and shape is vital for assessing the structural integrity of safety-critical components like those in gas/oil pipeline and aero-engines. However, existing ultrasonic imaging techniques (e.g., tomography, total focusing method or reverse time migration) are resolution-limited which is typically greater than half wavelength, resulting in blurred images that lack crucial subwavelength details. Conventional full waveform inversion (FWI) tends to fail for defects with strong scattering behavior because of the significant mismatch between simulated and measured signals.

To address this challenge, we propose a geometrical full waveform inversion (GFWI) method that enables deep subwavelength reconstruction of single or multiple complex defect geometries based on phased array measurements. Our approach leverages high-fidelity finite element (FE) modeling to capture full scattering physics, specifically incorporating the effects of multiple scattering and evanescent waves. By integrating derived 2D/3D boundary gradient with level set function, GFWI iteratively guides defect evolution toward the true solution, automatically exploiting scattering mechanisms to resolve micron features. The computational efficiency of forward FE model is drastically enhanced by a GPU-accelerated software, greatly accelerating the inversion process.

The efficacy of the proposed method is demonstrated through several numerical examples, which successfully reconstruct 2D and 3D defects with complex deep-subwavelength details, including voids, cracks, and surface corrosion that are representative of those encountered in practical scenarios. Furthermore, experimental validation using MHz-range ultrasonic frequencies confirms the ability to reconstruct defect shapes with an error of less than 100 micrometers. By significantly advancing the capabilities of defect imaging and inversion, this level set-based GFWI method provides a more reliable safety-risk evaluations for engineering components.

In asset-intensive industries like Oil&Gas and Power Generation, ensuring the integrity and reliability of the infrastructure is paramount. Traditional inspection methods, based on periodic assessments, are limited to provide enough data into asset health, leading to unanticipated failures and costly maintenance interventions. This paper explores some approaches to asset integrity management, transitioning from inspection datas to real time monitoring by putting in the critical localization the right sensor.

Focusing on corrosion management, we highlight the advantages of real-time monitoring with Wireless Ultrasonic sensor, over traditional spot inspections. By enabling continuous data collection and trend analysis, the asset-owner enhances predictive maintenance strategies, reduces operational risks, and optimizes maintenance planning. The shift from periodic inspections to continuous monitoring not only improves decision-making but also extends asset life, reduces downtime, and enhances safety.

Through case studies and analysis, we demonstrate how our customers transform corrosion monitoring from a reactive to a proactive process, aligning with industry 4.0 principles and digitalization trends. This approach ensures a more efficient, cost-effective, and resilient asset integrity management framework for industrial operators.