Conference Agenda

Corrosion of reinforcing steel remains one of the leading causes of deterioration, loss of serviceability, and premature failure in reinforced concrete structures. Its impact is becoming increasingly critical as a large proportion of existing infrastructure approaches or exceeds its original design life, with many elements already exhibiting significant damage. Although numerous sensing technologies have been developed to improve the assessment and monitoring of corrosion processes, most systems are conceived for installation during construction, which greatly limits their applicability to existing structures—particularly those that have undergone repair interventions or incorporate sacrificial anodes. This limitation is especially critical today, given the growing number of structures being repaired and the frequent lack of reliable verification regarding the effectiveness of such interventions.

This work presents the adaptation and validation of a corrosion monitoring system originally designed for new construction and previously demonstrated to be reliable in real structures, including those produced with UHPFRC. The system is based on a robust and well-established electrochemical technique, whose reproducibility and stability have been verified in multiple field applications. Building on this validated foundation, the system has been re-engineered to allow non-intrusive installation in existing reinforced concrete elements, including those that have been repaired using sacrificial anodes.

The methodological programme focused on evaluating the system’s performance under conditions representative of real deterioration and repair scenarios. Several reinforced concrete slabs were fabricated and intentionally contaminated with chlorides to induce active corrosion. Subsequently, sacrificial anodes were installed following standard repair practice. The adapted monitoring system was then employed to assess both corrosion activity and the performance of the repair. Measurements included continuous corrosion rate monitoring, temporal evolution of electrochemical potentials, and assessment of current flows between protected and unprotected areas. In addition, the system was used to quantify the consumption behaviour of the sacrificial anodes, enabling the estimation of their effective service life. Special emphasis was placed on the system’s ability to detect localised corrosion processes, differentiate between galvanically protected and unprotected zones, and maintain signal stability despite heterogeneous moisture and chloride profiles.

The results demonstrate that the adapted system provides consistent, spatially resolved information on reinforcement corrosion and on the performance of sacrificial anodes throughout their service life. The device proved capable of identifying areas where protection may be insufficient and of tracking the depletion of anodes with a level of resolution not typically available in current monitoring approaches. These findings confirm that the system constitutes a practical and effective tool for post-repair assessment, offering robust data to support maintenance planning and long-term durability management. Given the increasing prevalence of corrosion-related problems in existing infrastructure, the availability of such a monitoring solution holds particular relevance for ensuring effective repairs, optimising intervention strategies, and extending the service life of the reinforced concrete stock.

The Electromechanical Impedance (EMI) method has been widely employed in several Structural Health Monitoring (SHM) applications. Its basic principle relies on a piezoelectric transducer (PZT) bonded to a host structure, operating simultaneously as both an actuator and a sensor. The transducer is excited over a wide frequency range to compute the EMI. Conventional EMI-based SHM systems sequentially apply this procedure to each PZT when multiple transducers are used. Here, a novel approach is proposed in which all PZT transducers, bonded to the structure, are excited simultaneously, whereas the EMI is individually computed for each sensor, a fundamental distinction from parallel excitation methods that measure only total impedance. Since a PZT transducer can be modelled as a transmission line, the EMI measured at a given transducer includes the effects of crosstalk between adjacent sensors. To assess the proposed method, a simulation study was conducted on OnScale software to model an aluminium plate measuring 200 × 40 × 2 mm instrumented with two PZT transducers. Structural changes were simulated by adding an iron mass, with dimensions of 12 × 4 × 5 mm, to the plate. The EMI was computed from each sensor using both methods. The results obtained indicate that the proposed method increases the sensitivity of the EMI response for damage detection when compared to the conventional sequential EMI approach, which may support the development of improved damage detection and localisation methods.

Fatigue in metallic materials leads to progressive degradation driven by a sequence of microstructural mechanisms occurring over the life cycle. While fracture is typically the most obvious and critical damage state, it only appears at the end of life. However, when no fracture is monitored a material’s degree of fatigue degradation becomes difficult to be quantified. During that period a variety of other mechanisms act in a consecutive way starting from dislocation movements, phase transformation and leading over to plastic deformation. Electromagnetic techniques such as eddy current testing (ECT) are an interesting option to be considered for monitoring ferromagnetic materials. The attraction is the complexity of these ECT signals and the question arises: What can be read out of those?

To address this question, fatigue experiments were conducted on structural steel S235 (ASTM A36) under strain-controlled constant-amplitude loading to determine what is generally known as an S-N curve. All tests were continuously monitored using a commercial ECT system. The signals recorded were processed in terms of the real and imaginary part and the resultant impedance and phase were determined as further parameters characterizing ECT. These were then plotted in a specific 3D format displaying loading over normalized life (in the sense of the traditional S-N curves) added by one of the forementioned ECT parameters as the third dimension. The resulting topography is shown as an example for ECT impedance in Fig. 1. Such a visualization allows the monitoring capability of the respective technique (here ECT impedance) to be discussed.

Beyond this visualization, two complementary statistical processing frameworks were employed to analyze the time-domain signal response recorded. First, statistical thresholding techniques—both linear and moving standard-deviation based—were applied to identify significant deviation points that might be correlated with transitions in the material state. Second, a weighted scoring method was introduced leveraging nine time- and frequency-domain features including slope, roughness, RMS, high/low frequency ratio, local variance, kurtosis, zero-crossing rate, envelope rate, and the acceleration of the second-order slope. Robust normalization schemes were incorporated to reduce noise sensitivity and enhance tracking stability. Initial findings have been analyzed regarding these statistical approaches to possibly highlight critical transitions during the fatigue life and exhibit sensitivity to early state changes. The weighted scoring approach in particular shows improved stability compared to single-parameter tracking, making it a possible candidate for future automation.

In the broader perspective, this work establishes a data-driven electromagnetic monitoring framework that with possible potential to support future machine learning-based damage classification even to be used in structural health monitoring. Ongoing work focuses on refining feature selection, enhancing thresholding robustness, and evaluating performance across multiple material grades and loading conditions.