Data fusion of the super saturation sensor of magma in sugar boiling process

摘要

The super saturation of magma, a main parameter in the boiling process control, usually is measured by electrical conductivity, but the output of sensor is influenced with the pure degree and temperature of magma. To eliminate that interference, the output would be done with by data fusion method based on the neural network. Using the measured value of electrical-conductivity sensor, syrup's Brix and temperature as the inputs, the network is trained by BP algorithm to achieve the fused output. The results of test shows that the data fusion method based on the artificial neural network could effectively eliminate the change of Brix and temperature has influenced on the supersaturation, and then could attain precise and stable output value.