Research on Sugar Concentration Sensing Based on Real-Time Polarization and Interaction Effects

This paper presents a non-contact method for detecting the sugar concentration in solutions based on real-time polarization characteristics and an interaction effects model. The feasibility of using polarization imaging technology for sugar concentration detection is analyzed. By analyzing the Stokes parameters, a linear regression model is developed to establish the interaction effects between sugar concentration and both the degree of linear polarization (DoLP) and the angle of linear polarization (AoLP). A three-beam polarization imaging system is used to simultaneously capture the polarization images of sucrose solutions with varying concentrations, and the SIFT algorithm is employed to eliminate image shifts. The results show a strong linear correlation between sugar concentration and both AoLP (R2 = 0.998) and DoLP (R2 = 0.968). The addition of the interaction effect model significantly improves the prediction accuracy, with an RMSE of 0.36934 and a relative error within ±5%. This method features a simple experimental setup, enables multi-angle simultaneous measurements, and offers advantages such as non-contact operation, ease of use, and high precision (average relative error < 5%). It provides a new approach for sugar concentration detection in food, industry, and other fields.