The Three-Dimensional Fluorescence Spectroscopy Recognition of the Mineral Oil Based on the Wavelet Neural Network

The singular value eigenvectors are often used to recognise the different kinds of mineral oil. The eigenvectors are obtained by the Excitation-Emission Matrix (EEM) factorization from the three-dimensional fluorescence spectroscopy. They are complicated and not easy to be recognised by the simple formula. A new type neural network-wavelet neural network (WNN) was introduced. The singular value eigenvectors were used to be the input of the WNN. The mapping relation was obtained by the WNN between the singular value eigenvector and the species of the mineral oil. The WNN realized the recognition of the different kinds of mineral oil. The experiment result indicates that the right of the distinguish rate is 95%. The WNN has much higher resolution and less training times than BP networks.