Nitrate nitrogen concentration detection method based on principal component analysis and BP neural network

Aiming at the problem of inaccurate detection of the nitrate nitrogen solution concentration with interfering substances in ultraviolet spectrophotometry (UV method), a nitrate nitrogen concentration detection method based on principal component analysis (PCA) and BP neural network was proposed. First, the absorbance of the nitrate nitrogen reagent at 196 nm~631 nm was measured by the material composition detection system of the micro-spectrometer, which was divided into test set and training set. Then, the PCA was used to calculate the training set to obtain the principal components. Finally, a three-layer artificial neural network was built based on the BP algorithm. The obtained principal components were divided by 8 and input into the network for training. During the training, the leaving-one method was adopted for cross-validation. This model was used to calculate the training set and test set, the mean relative error between the obtained results and the true concentration is 2.411 5% and 1.553% respectively. The experimental results show that the method can better detect the concentration of the nitrate nitrogen reagent with interfering substances.