A monitoring method of sewage treatment process based on kpls and fcm

Abstract

The invention relates to the technical field of sewage treatment quality monitoring and provides a sewage treatment process monitoring method based on KPLS and FCM. This invention first collects sewage treatment process data samples under normal working conditions and including abnormal working conditions, uses the data of sewage treatment operation variables and effluent quality variables as input and output data matrices respectively, and standardizes the two matrices; then builds a KPLS model and converts the input The sample is mapped to the high-dimensional feature space, the Gaussian kernel function is introduced to obtain the Gram matrix K, and the score matrix is ​​solved; then the input sample point density value is calculated, the constructor function is calculated and the constructor image is drawn to determine the number of clusters; finally, based on the FCM algorithm, The score matrix is ​​clustered to obtain the membership matrix, and abnormal working conditions of the sewage treatment process are monitored based on the membership matrix. The invention can reduce the dimensionality of high-dimensional data and process nonlinear data, accurately and conveniently determine the number of clusters, and improve the timeliness and accuracy of monitoring.

Description

technical field [0001] The invention relates to the technical field of sewage treatment quality monitoring, in particular to a sewage treatment process monitoring method based on KPLS and FCM. Background technique [0002] With the acceleration of urbanization and industrialization in our country, the society's demand for fresh water resources is increasing day by day. It is necessary to accelerate the construction of urban domestic sewage treatment and disposal facilities and improve the capacity of urban domestic sewage treatment. Activated sludge sewage treatment process is currently the main method of urban sewage treatment. Activated sludge purification of sewage mainly includes three processes: initial adsorption, microbial metabolism, formation of flocs and precipitation. Adsorption, decomposition and oxidation are carried out to separate it from sewage, so as to achieve the purpose of purifying sewage. [0003] At present, biochemical oxygen demand ([BOD]), chemica...

AI Technical Summary

Problems solved by technology

However, the sewage treatment process data has high dimensions and nonlinearity. The traditional FCM algorithm cannot handle high-dimensional and nonlinear data, which increases the difficulty of process monitoring, reduces the reliability of fault detection, and has a great impact on the quality of sewage effluent. impact, resulting in certain economic losses and even accidents

At the same time, the number of clusters of the FCM algorithm needs to be preset artificially, which has great limitations in practical applications.

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