Multi-sensor data fusion and parallel factor analysis reveals kinetics of wood weathering

Understanding mechanisms of materials deterioration during service life is fundamental for their confident use in the building sector. This work presents analysis of time series of data related to wood weathering acquired at three scales (molecular, microscopic, macroscopic) with different sensors. By using several complementary techniques, the material description is precise and complete; however, the data provided by multiple equipment are often not directly comparable due to different resolution, sensitivity and/or data format. This paper presents an alternative approach for multi-sensor data fusion and modelling of the deterioration processes by means of PARAFAC model. Time series data generated within this research were arranged in a data cube of dimensions samples × sensors × measuring time. The original protocol for data fusion as well as novel meta parameters, such as cumulative nested biplot, was proposed and tested. It was possible to successfully differentiate weathering trends of diverse materials on the basis of the NIR spectra and selected surface appearance indicators. A unique advantage for such visualization of the PARAFAC model output is the possibility of straightforward comparison of the degradation kinetics and deterioration trends simultaneously for all tested materials

Performance of modified wood in service - multi-sensor data fusion and its multi-way analysis

Recent developments in the field of electronic sensors and analytics provide new opportunity for accurate characterization of materials often based on portable and non-destructive methods. By using several complementary techniques, the material description is precise and complete. The data provided by multiple equipment, however, are often not directly comparable due to different resolution, sensitivity and/or data format. The complexity related to the data fusion step and its further interpretation often leads to not complete exploitation of the available data. This paper presents a multi-block approach used for merging experimental data collected by measurement of modified wood in service. Characterization of samples appearance (colour and gloss) is merged with spectral data that decodes information regarding chemical composition. Alternative approaches for data fusion on the low-, mid- and high-levels are introduced, discussed and confronted with the standard approach (single sensor data interpretation). Finally, the trial to analyse the data with multi-way method is presented and interpreted

Assessment of the chemical change in heat treated pine wood by near infrared spectroscopy

Fourier-transform near-infrared spectroscopy (FT-NIR) was used as none-destructive method to determinate changes in the chemical structure of heat-treated wood. For this purpose, pine sapwood (Pinus sylvestris L.) was treated at different temperatures (from 100 °C to 240 °C) and for three durations(1, 3 or 5 hours). The effects of chemical changes on the FT-NIR spectra are linked to absorbance changes of functional groups (–OH, –CH, –CO and –CH2) of lignin, hemicelluloses and cellulose. Gradual degradation of amorphous portion of cellulose was caused by high temperature, while crystalline and semi-crystalline portions of cellulose seem to be less affected by the thermal treatment. The effect of various intensities of heat treatment on chemical changes of wood polymers varied depending on temperature and duration. Presentation of spectra in the form of the xylograms shows clear tendency of degradation kinetic. Evaluation of thermal stability of selected wood component and/or comparison of the influence of modification process parameters can be carried out

A Method for Accelerated Natural Weathering of Wood Subsurface and Its Multilevel Characterization

The function of altering weathering factors and degradation mechanisms are essential for understanding the weathering process of materials. The goal of this work was to develop a method for the acceleration of natural weathering and to investigate the molecular, microstructure and macrostructure degradation of wood caused by the process. Tests were performed in the whole month of July, which, according to previous research, is considered as the most severe for weathering of wood micro-sections. Sample appearance was evaluated by colour measurement. Scanning electron microscopy was used for evaluation of the structural integrity and changes in the microstructure of wood morphological components. Changes on the molecular level were assessed by means of FT-IR spectroscopy. Observation of the effects of weathering allowed a better understanding of the degradation process. Typical structural damage, such as cracks on bordered pits and cross-field pits, and, as a consequence, their erosion, revealed the sequence of the degradation process. It was confirmed that earlywood was more susceptible to damage than latewood. Even if the weathering test was conducted for a relatively short time (28 days) the ultra-thin wood samples changed noticeably. The progress of alteration was similar as usually noticed for wood surfaces, but occurred at shorter exposure times. The estimated acceleration factor was ×3, compare to the natural weathering kinetics of wood. The research methodology presented can be used for the determination of the weather dose-response models essential to estimate the future service life performance of timber elements

Development of a Sensorized Timber Processor Head Prototype – Part 1: Sensors Description and Hardware Integration

Forest operations are in constant development to provide increasingly higher standards of economic and environmental sustainability. The latest innovation trends are concentrated in the generation, storage and management of data related to the harvesting process, timber products and logistics operations. Current technologies provide productivity and position, but only physical parameters are made available for timber products. The possibility of providing a comprehensive quality evaluation of roundwood early in the supply chain and linking the information to each log provides a new tool for optimization of the whole forest-timber supply chain. Current in-field methods for grading logs are based on visual rating scales, which are subjective, operator-dependent and time-consuming. As an alternative, a sensorized processor head was developed, featuring the following sensors: near infrared (NIR) spectrometer and hyperspectral cameras to identify surface defects, stress wave and time of flight sensors to estimate timber density, hydraulic flow sensor to estimate cross-cutting resistance and delimbing sensors to estimate branches number and approximate position. The prototype also deployed an RFID UHF system, which allowed the identification of the incoming tree and individually marked each log, relating the quality parameters recorded to the physical item and tracing it along the supply chain. The tested sensors were installed and designed to be independent, nevertheless, their integrated use provides a comprehensive evaluation of timber quality. This paper presents the technical solutions adopted, the main hindrances found and some preliminary results of the operative prototype as tested in laboratory and in forest operational conditions