Moving least squares-based multi-functional sensing technique for estimating viscosity and density of ternary solution

In the osmotic dehydration process of food, on-line estimation of concentrations of two components in ternary solution with NaCl and sucrose was performed based on multi-functional sensing technique. Moving Least Squares were adopted in approximation procedure to estimate the viscosity of such interested ternary solution with the given data set. As a result, in one mode of using total experimental data as calibration data and validation data, the relative deviations of estimated viscosities are less than ±1.24%. In the other mode, by taking total experimental data except the ones for estimation as calibration data, the relative deviations are less than ±3.47%. In the same way, the density of ternary solution can be also estimated with deviations less than ±0.11% and ±0.30% respectively in these two models. The satisfactory and accurate results show the extraordinary efficiency of Moving Least Squares behaved in signal approximation for multi-functional sensors.