Monitoring Moisture Content and Mass Flow of Wood Chips Using Electrical Capacitance Tomography

Abstract

Woody biomass is currently sold on a wet basis, a system that works because moisture content of harvested trees normally uctuates within a narrow range and wood from multiple sources can be considered a uniform product. Wet wood, however, is not an optimal energy feedstock and various methods have been proposed to reduce moisture content in woody biomass prior to its sale. Once moisture content can vary outside its typical range, however, the use of wet weight as a basis for selling timber products becomes untenable. Promoting a robust bioenergy market will, therefore, require the development of reliable sensors for measuring moisture content of wood in the eld. A logical place at which to measure moisture content of woody biomass would be just prior to shipment for nal conversion. For biomass harvested from pine plantations prevalent in the US South, that would most likely be between the chipping and loading operations. To avoid handling the biomass an extra time, however, a moisture sensor should work accurately on a moving stream of chips as they exit a chipper and are blown into a van for hauling. This type of high-speed, non-contact moisture sensor suitable for application in a rough environment is not currently available. Our goal in this study was to develop a sensor for measuring moisture content of a rapidly moving stream of pine chips that was robust, non-contact in operation, reliable, and accurate. An 8-electrode electrical capacitance sensor was built for that purpose. The multiple electrode system was used to characterize the distribution of permittivity within the circular area (diameter = 16.5cm) enclosed by the sensor and surrounded by the electrodes (2.5x10 cm copper plates). The sensor was could be operated in two modes: a) static mode in which the cumulative permittivity between each combination of plates was the variable correlated with moisture (a bulk measurement), and b) a dynamic mode in which multiple sequential readings of electrode combinations was used to sample a stream of chips moving through the ii sensor enclosure, the result being a sequence of 2-D maps of permittivity. This method is referred to as electrical capacitance tomography (ECT). The objectives of the research presented in this dissertation were: 1. Validate the accuracy of the sensor in static mode in predicting moisture content of xed quantities of biomass, and investigate the sensor's limits of performance when subjected to variations in such confounding variables as quantity, location, and size of the material under test. 2. Develop the necessary hardware and software systems to perform dynamic (ECT) mode characterization of moving streams of biomass, and establish the accuracy of moisture content predictions. Static mode calibration of the sensor was carried out on wood chips having uniform moisture content. Tests were made on chips ranging in moisture content of from 4% to 140% (dry basis), and the results compared with the widely-accepted near infrared spectroscopy (NIR) method. For tests on individual wood chips (about 10 g each), the root mean squared errors of prediction (RMSEP) were 13.52% and 48.43% for NIR and ECT, respectively. In bulk measurements (multiple chips, 40-80 in number), RMSEPs were found to be 15.39% and 11.65% for the NIR and ECT methods, indicating the main di erence between the two methods: NIR predictions were independent of sample mass, the ECT estimates were not. Two additional measurement procedures were developed using the capacitance sensor, one using multiple excitation frequencies and the other assuming a xed sample mass based on volume, to remove its dependency on sample mass. The RMSEPs for the two methods were similar (13.0% and 10.9% for the xed volume and two-frequency methods, respectively) and also comparable to the previous methods when sample mass was known. It was concluded the capacitive approach was very comparable to NIR in its ability to accurately predict moisture content of biomass using either approach (unknown or known mass), and the capacitive sensor was superior in predicting moisture content of bulk materials. On quantities of wood iii near the detection limit of the capacitance sensor (about 10g), however, the NIR approach was preferable. Dynamic mode tests of the sensor were made in two steps, the rst involving simultane- ous independent measurement of mass ow using another sensor (plus moisture content from the sensor in capacitive mode), and the second using the sensor in ECT mode to estimate both total mass ow and moisture content simultaneously. In the rst tests, an impact mea- surement approach was used to estimate mass ow. In the second, the ECT tomographic mode was used to image the variation in permittivity of the owing stream of wood chips. The images also provided a means to estimate chip volume within the sensor, which, assum- ing uniform density, provided a mass value. The RMSEP of moisture content predictions using the impact and ECT mass ow estimation methods were 11.86% and 17.71%, respec- tively. It was concluded these tests proved the feasibility of using electrical capacitance tomography as a means of measuring moisture content of moving biomass streams. Further development of the techniques to increase the sampling rates above that achieved in these tests will be required to make the system practical.