Open AccessApplication of a Wavelet Packet and SOM Neural Network in Wastewater Treatment Fault
Author(s) -
Lü Ming
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/782/5/052016
Subject(s) - fault (geology) , artificial neural network , wavelet , computer science , feature vector , wavelet packet decomposition , network packet , feature (linguistics) , pattern recognition (psychology) , artificial intelligence , energy (signal processing) , wavelet transform , mathematics , geology , statistics , seismology , computer network , linguistics , philosophy
In order to solve the problem of fault diagnosis in sewage treatment, a fault diagnosis method combining wavelet packet and improved self-organization mapping (SOM) neural network was proposed. In this method, the fault of sewage treatment is decomposed into three types by wavelet packet, and then decomposed into several frequency bands to calculate the energy of different frequency bands. By using the ratio of these energy values to the energy values of normal operating frequency bands, the feature vector of fault diagnosis of sewage treatment fault is constructed to extract fault features. SOM neural network of 3 x 3 was designed, and the neural network training was carried out using the energy fault feature vector [1], so as to determine the network parameters and achieve the purpose of fault diagnosis. The simulation results show that the fault diagnosis method is effective and accurate.