Abstract
Early detection of timber damage is essential for the safety of timber structures. In recent decades, wave-based approaches have shown great potential for structural damage assessment. Current damage assessment accuracy based on sensing signals in the time domain is highly affected by the varied boundary conditions and environmental factors in practical applications. In this research, a novel piezoceramic-based sensing technology combined with a visual domain network was developed to quantitatively evaluate timber damage conditions. Numerical and experimental studies reveal the stress wave propagation properties in different cases of timber crack depths. Through the spectrogram visualization process, all sensing signals in the time domain were transferred to images which contain both time and frequency features of signals collected from different crack conditions. A deep neural network (DNN) was adopted for image training, testing, and classification. The classification results show high efficiency and accuracy for identifying crack conditions for timber structures. The proposed technology can be further integrated with a fielding sensing system to provide real-time monitoring of timber damage in field applications.
Highlights
Timber structures have been increasingly utilized in building construction due to their excellent seismic performance and environmental friendliness, which mean flexible building function, especially with the improvement of engineering wood products (Cao et al, 2019; Chen et al, 2020; Sun et al, 2020)
A reliable crack detection technology for extensive in-service and newly constructed timber structures is of great importance to ensure the safety of timber structures
The proposed approach consists of three major steps, as detailed in Figure 1: 1) data pre-processing by conducting joint time–frequency analysis; 2) data augmentation for expanding the dataset and simulating environmental uncertainties in operation; and 3) deep neural network (DNN) training for crack depth classification
Summary
Timber structures have been increasingly utilized in building construction due to their excellent seismic performance and environmental friendliness, which mean flexible building function, especially with the improvement of engineering wood products (Cao et al, 2019; Chen et al, 2020; Sun et al, 2020). Wood cracking is an inevitable issue for timber structures because of the variation of temperature and humidity (Li et al, 2013; Dietsch and Winter 2018). Existing approaches for timber cracks detection mainly include resistance drilling measurement and scanning image technique (Wei et al, 2011; Brites et al, 2012; Tannert et al, 2014; Kloiber et al, 2015; Zhang et al, 2015; Mol et al, 2020). Drilling measurement is a conventional method to assess the internal condition of timber members (Mol et al, 2020). This method is semidestructive, and the results are highly affected by the test personnel.
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