Capacitance-Based Tomography of Fiberboards and Wood

In industry today, there is a need for designing modem instruments for quantitative and qualitative inspection of wood, wood-based materials and finished products. Development of technologies using electric fields requires a profound knowledge of the dielectric properties of wood. One of the promising techniques is the Electrical Capacitance Tomography (ECT). Constructing a capacitive tomographic profile of wood and fiberboards has several applications in industry and agriculture. In this study a technique based on multifrequency square- wave pulse signal is being used to probe the sample. The output signal is amplified, filtered and used to build property surface profiles for different local lumber samples. Analysis of the effect of different stimulating frequency on the overall contour shape of different samples is compared and the appropriate frequency is singled out. Details on how this technique can be utilized to develop a capacitive sensor are also explained. Two capacitive sensors were designed with different dimensions for the sensing plate. The capacitive output of the sensors can be related to the different properties of the material under test (MUT). In this study, the sensors were tested for moisture content, thickness variations and local defects present in the sample material. Both sensors were tested on local lumber samples and fiberboards. Contour plots were obtained for the output of the system, which represent the gradient changes in the wood moisture content as the probe moves across the material under test. The sensor with the smaller dimension probe proved to be superior in resolving the details of the sample and distinguishing the knots and defects of the sample. The larger probe is more accurate in determining the bulk moisture of the samples and more sensitive to thickness variations. The measurement accuracy of the moisture content percentage and thickness variation is about f 2.88% and +_ 0.035 cm respectively. Even though the proposed sensors offer less accuracy than expensive LRC laboratory analyzers and limited in frequency selection and voltage input to MUT, nonetheless they are inexpensive to make, lighter in weight and can be easily implemented in -site or online processing.

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