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A method that permits the determination of moisture content in biofuel in a fast and representative way is under development. The method uses radio frequency waves within the range of 310 MHz to 800 MHz and measures the reflection coefficient in samples with volume of about 0.1 m 3 . The influence of sample temperature in the measurements is shown in this study. Two biofuel types were used, with moisture content varying between 31% and 63% and temperature varying between 1ºC and 63ºC. The data was evaluated with multivariate data analysis. Results show that it is not possible to identify the sample temperature as a principal component in a principal component analysis and partial least squares regression shows no correlation between temperature and the radio frequency data. For the frequency interval and the temperature range studied, it was not possible to detect any influence of sample temperature on moisture content prediction with the radio frequency method.

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The aim of the research described in this paper is to measure moisture content in biomass fuel with radio frequency spectroscopy. The advantage with this method is that radio waves penetrate large samples, and thereby gives an average moisture content representing the whole sample. The method is fast and is a small scale version of what can be applied in the future on-line for biomass fuel arriving in containers to the power plants. The moisture content is determined with a sensor that measure attenuation and phase shift for a frequency spectrum from 310 MHz to 900 MHz. The measurements are performed on sawdust with moisture contents normally occurring in power plants (from 34 to 65%). Multivariate data analysis is used for evaluation of the dielectric spectra from samples with known moisture content. Our results show that it is possible to measure moisture content in sawdust using radio frequency spectroscopy. A partial least square model is built on samples from sawdust. The moisture content varied between 34 and 60%. A standard error for the cross validation of 0.99% and a correlation factor of 0.99 was received. It is known that dielectric properties are also influenced by bulk density and temperature. Tests show that the influence of the bulk density is of greater importance. Further calibration measurements have to be performed to be able to make reliable measurements on the different bio fuels used at power plants.