Multivariate analysis of multi-sensor data for assessment of timber structures: Principles and applications

The proper timber structure assessment is of great importance to assure safe service of buildings as well as to preserve cultural heritage objects for future generations. However, due to peculiar anatomic structure of wood, anisotropy and heterogeneity, its characterization is a problematic task. Several methods are used nowadays for improving existing structure assessment routines, including also continuous monitoring of the structure performance. Current trend for using multiple sensors simultaneously is more favorable than a single sensor approach due to superior representation of the real-world cases. Moreover, the availability of novel statistical tools to handle many variables concurrently is another motivation for rapid changes within the field of measurement technology. It is important, therefore, to assure proper pre-processing of the signals from sensors, appropriate data fusion and optimal data analysis. The integrated use of non-destructive testing methodologies and data handling techniques to assess, monitor and predict properties of wood within structures and buildings is briefly described in this work. Examples for successful applications of the different data analysis techniques on the assessment and monitoring of civil engineering constitutions are reported.Multi-sensor approach may be a very attractive alternative to the conventional assessment and can provide supplementary data to be considered when inspector decision is made. It is assumed that, after additional developments, such methodologies can serve as assisting tools for non-destructive assessment of the wooden structures, service life prediction of structural elements and to support selection of optimal conservation process.