Method for soft measurement of effluent total phosphorus in sewage disposal process based on neural network

A technology of effluent total phosphorus and neural network, applied in neural learning methods, biological neural network models, testing water, etc., can solve the problems of not being able to detect water quality in time, taking a long time, and difficult to accurately measure important parameters

Active Publication Date: 2014-12-03
BEIJING UNIV OF TECH
View PDF4 Cites 14 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The sewage treatment process is a complex biochemical reaction process. Due to the limitation of measurement technology, some important parameters in the sewage treatment process are difficult to measure accurately
At present, the measurement methods of sewage total phosphorus TP are mainly chemical measurement method and instrument detection method. The former takes a long time and lags behind the sewage treatment process, and cannot detec...

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Method for soft measurement of effluent total phosphorus in sewage disposal process based on neural network
  • Method for soft measurement of effluent total phosphorus in sewage disposal process based on neural network
  • Method for soft measurement of effluent total phosphorus in sewage disposal process based on neural network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0076] The present invention selects 9 related variables for soft measurement of total phosphorus TP in sewage treatment effluent: sludge return flow rate, sludge age, pH, oxidation-reduction potential ORP, influent ammonia nitrogen NH3-N, influent chlorine CL, and effluent 5 days Biological oxygen demand BOD5, effluent suspended solids concentration SS, and effluent total phosphorus TP at the previous moment; the embodiment of the present invention uses the water quality analysis data of a sewage plant in 2011, and all experimental samples are 150 groups; 100 groups of data are used as training data, The remaining 50 groups are used as test data.

[0077] Using the self-organizing RBF neural network to establish the soft sensor model of the total phosphorus TP in the effluent, including the following steps:

[0078] Step 1: Initialize the neural network. The neural network structure is 9-0-1 at the initial moment, and the inputs are sludge return flow, sludge age, pH, oxidati...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention provides a method for soft measurement of the effluent total phosphorus (TP) in the sewage disposal process based on the neural network, and belongs to the field of sewage disposal field. The mechanism is complex in the sewage disposal process, and to enable a sewage disposal system to be in a good running working condition and to obtain the higher effluent quality, the procedure parameters and the water quality parameters in the sewage disposal system need to be detected. The invention provides a soft measurement model established based on the self-organization radial-based neural network to solve the problem that the effluent total phosphorus of a current sewage disposal plant cannot be obtained in real time. The initial structure and the initial parameters of the neural network are determined according to the self-organization method, the structure of the neural network is simplified, and real-time soft measurement is carried out on the effluent TP. According to the soft measurement result, the related control link in the sewage disposal process and materials in the biochemical reaction are adjusted, the quality of the effluent obtained after sewage disposal is improved, and a theoretical support and a technological guarantee are provided for safe and stable running in the sewage disposal process.

Description

technical field [0001] The invention establishes a soft sensor model of effluent total phosphorus TP in an urban sewage treatment process based on a self-organized RBF neural network. Soft measurement is one of the main development trends of detection technology and instrument research, and an important branch of advanced manufacturing technology. The invention not only belongs to the field of sewage treatment, but also belongs to the field of detection technology and instrument research technology. Background technique [0002] "The Outline of the Twelfth Five-Year Plan for National Economic and Social Development of the People's Republic of China" pointed out that it is necessary to speed up the construction of urban sewage treatment and recycling facilities nationwide, promote the reduction of major pollutants, and improve the quality of water environment. By 2015, the urban The sewage treatment rate reaches the overall target of 85%. In order to achieve this goal, from...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06N3/02G06N3/08G01N33/18
Inventor 乔俊飞蒙西武利韩红桂李瑞祥
Owner BEIJING UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products