The method uses wavelet transform and principle component analysis to preprocess fault signal, afterward training and testing wavelet neural network with the preprocessed fault characteristic data.

In addition, creation of digital maps base on MFL signal after preprocessed, clear visual display wall of the overall situation.

The MLR mathematical model that established with orthogonal signal correction plus first derivative and mean centre preprocessed spectra shows the best result for glucose and fructose.