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. The method comprises the steps that firstly, collecting sewage treatment process data samples containing normal working conditions and abnormal working conditions, enabling data of sewage treatment operation variables and data of effluent quality variables to serve as an input data matrix and an output data matrix respectively, and standardizing two matrixes; then constructing a KPLS model, mapping an input sample to a high-dimensional feature space, introducing a Gaussian kernel function to obtain a Gram matrix K, and solving a score matrix; calculating the density value of an input sample point, calculating a construction function and drawing a construction function image to determine the number of clusters; and finally, clustering the score matrix based on an FCM algorithm to obtain a membership matrix, and monitoring the abnormal working condition in the sewage treatment process according to the membership matrix. The high-dimensional data can be subjected to dimensionality reduction, nonlinear data can be processed, the clustering number can be accurately and conveniently determined, and the monitoring timeliness and accuracy are improved.

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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