Multivariate robust soft measurement method about sewage treatment effluent quality index

Abstract

The invention provides a multivariate robust soft measurement method about sewage treatment effluent quality index, and relates to the technical field of the sewage treatment automatic control. The method comprises the following steps: taking a parameter real-time measured by conventional detection equipment based on industrial field as input data of a model; establishing a random weight neural network model capable of simultaneously performing multivariate dynamic prediction on the main parameters for balancing the sewage treatment effluent quality, thereby realizing robust soft measurement of BOD content, COD content, TSS content sewage quality parameters, and comprehensively describing the sewage quality parameters, thereby avoiding the hysteresis of the offline assay and the uncertainty of the manual operation. The sparse partial least square and Schweppe type general M are utilized at the same time so as to eliminate the influence on the modelling by multiple colinear and reduce the bad influence on the modelling by outlier and leverage point in the data; and meanwhile, the aim of variable selection is reached, and an estimation value of the multivariate sewage treatment effluent quality parameter at the specified dynamic time zone can be given more accurately.

Description

technical field [0001] The invention relates to the technical field of automatic control of sewage treatment, in particular to a multivariate robust soft-sensing method for water quality indicators of sewage treatment effluent. Background technique [0002] In recent years, the demand for fresh water resources in the industrial society and daily life has been increasing day by day, and the damage to the water environment has become more and more serious. How to efficiently treat discharged sewage and realize the sustainable utilization and virtuous cycle of fresh water resources is an eternal topic in the development of modernization in the world today. Sewage treatment is a very complex non-linear dynamic process in which the sewage generated in daily production and life is subjected to a series of treatments to achieve discharge targets, and it involves the sustainable development of the environment and resources. [0003] The activated sludge process is the most widely u...

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Problems solved by technology

[0006] The method reported in the above-mentioned patents and similar methods related to other relevant literatures are only for forecasting and soft measurement of a single sewage effluent water quality parameter (such as BOD content, COD content, etc.), but fail to predict the main parameters that characterize sewage water quality, namely BOD content, COD content, etc. Content and TSS content are multivariately forecasted at the same time, so it cannot fully reflect the level of sewage water quality, and the practicability is poor

Moreover, the sewage data is high-dimensional data and there is multi-collinearity in the data, and the soft measurement for the abnormal data needs to be processed; in a

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