論文ID: 15.20180200
Moisture sensors have been widely implemented in agricultural and forestry applications, but they can not obtain satisfied sensing performance without calibration. This letter presents an integrated moisture and temperature sensor with a model based linearization for eliminating the temperature-dependent nonlinearity. The temperature related nonlinear model is built by analyzing the relationship between the real moistures and the pairs of measured moistures and temperatures. The least squares algorithm is applied to estimate the coefficients of the obtained nonlinear model. The proposed linearization system has the advantage of wide suitability and applicability, and its performance is validated by experimental results.
