Predicting moisture content of chipped pine samples with a multi-electrode capacitance sensor

Abstract

Woody biomass is currently sold on a weight basis, practical moisture sensors are essential for fair sales, especially in energy markets. To address this need, an 8-electrode electrical capacitance tomography (ECT) sensor was built and tested for predicting moisture content of wood chips and compared with the near infrared spectroscopy (NIR) method. The goal was to find an optimal means of measuring moisture content of woody biomass in the form of chips in two situations: individual chips and bulk samples. Tests were made on chips ranging in moisture content from 4% to 140% (d.b.). Results indicated that NIR had better performance in measuring moisture of single wood chips, while ECT was more accurate and rapid in bulk moisture determination. Knowledge of the mass of wood chips under test was required in the ECT moisture prediction model, unlike in the case of NIR. Both methods had the capability to measure moisture content of biomass while in motion. From a practical standpoint, however, only a portion of the material flowing past a near-infrared sensor could be practically scanned and the sub-sampled biomass would have to be representative of the entire population to be accurate. The ECT sensor, on the other hand, could likely be designed to scan the entirety of a large quantity of moving material and provide an accurate bulk average moisture content. Compared to a single paired-plate capacitance sensor, the ECT system also provided images, through its tomography function, that displayed permittivity distribution variability throughout bulk biomass samples.