PSI - Issue 78

Florence More et al. / Procedia Structural Integrity 78 (2026) 944–951

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specimens revealed that impedance signals are highly responsive to both the size and location of simulated damage, with sensitivity decreasing as the distance from the sensor increased. The Root Means Square Deviation (RMSD) index provided a robust quantitative measure of damage severity, although the practical limitations of sensor placement and timber’s anisotropic nature call for further validation at larger scales. The pictorial representation of the sensors like accelerometers and electrical moisture sensors are shown in Fig. 2.

Fig. 2. (a) Accelerometers; (b) and (c) Electrical moisture sensors The evolution of SHM for heritage timber also includes the development of real-time alert systems. Wang et al. 2020 implemented a multi-sensor SHM network in the Feiyun Wood Pavilion, integrating strain, inclination and environmental data with statistical models to establish dynamic early warning thresholds. Their tiered alert system, calibrated using normal distribution and extreme value theory, proved effective in anticipating abnormal structural behaviours, offering a proactive framework for conservation intervention. Expanding on this initiative, Wang et al. 2022 introduced a BIM-integrated SHM platform that merges monitoring data with a parametric digital model of the Feiyun Pavilion. This system enabled the visualization of strain, temperature, humidity and wind data, while a dual indicator warning approach, based on absolute strain levels and their rate of change, significantly enhanced the precision of risk detection. The study demonstrated how BIM and SHM integration facilitates data traceability, improves communication among stakeholders and promotes intelligent heritage management strategies. The study conducted by Uwizeyimana et al. 2020 investigates the effectiveness of embedded surface-type resistive sensors for real-time MC monitoring in glulam timber structures, aiming to enhance durability by detecting moisture-induced damage early. Using douglas fir specimens, the research evaluates key parameters influencing sensor performance, including electrode size, placement, temperature effects and mechanical impact. Results revealed that smaller electrodes (10 mm) provided more accurate resistance readings and sensor placement away from specimen edges affected current flow, necessitating calibration. A temperature-compensated calibration model was developed for reliable MC estimation under varying environmental conditions. The findings support the system’s viab ility for long term field deployment in timber structures, with future work focused on wireless integration and in-service validation. The adhesive side of each patch facilitated a proper connection between the electrode and the wood. Electrodes were installed at points along the glulam beam where moisture content was expected to be higher (towards the ends) and where it was likely to be lower (near the centre). Amaddeo et al. 2025 evaluated the dynamic behavior of a six-story lightweight timber frame building under varying environmental conditions through a combination of periodic and continuous ambient vibration monitoring and finite element (FE) modeling. Using advanced Operational Modal Analysis (OMA) techniques, Enhanced Frequency Domain Decomposition (EFDD) and Stochastic Subspace Identification (SSI), the study aimed to identify key modal parameters such as natural frequencies, damping ratios and modal shapes. Periodic measurements over 18 months and permanent monitoring over 4 months revealed that environmental factors like temperature, relative humidity (RH) of air and moisture content of timber significantly influence the building's dynamic response. Aloisio et al. 2025 presents the first long-term continuous dynamic monitoring of a fully cross-laminated timber eight-story building in Ås, Norway, aiming to investigate how environmental factors, particularly temperature, wood moisture content and snow depth, influence the building's modal properties. Using a rooftop monitoring system with accelerometers and weather sensors, along with embedded MC sensors, the researchers tracked three primary vibration modes and found that the first two natural frequencies positively correlated with both temperature and MC, while snow accumulation significantly reduced the fundamental frequency due to increased mass. Uwizeyimana et al. 2022 develop and validate a method for monitoring strain within glulam timber elements used in bridge construction, particularly under the influence of moisture variation due to environmental exposure. To achieve this, the researchers designed an