Sewage chemical oxygen demand soft measuring method based on support vector machine and neural network
A chemical oxygen demand and support vector machine technology, applied in the field of sewage chemical oxygen demand soft measurement, can solve problems such as inability to achieve precision, achieve good precision, reduce contradictory data, and fast speed.
Inactive Publication Date: 2010-12-22
FUDAN UNIV
View PDF5 Cites 40 Cited by
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
The second problem lies in the construction method of the neural network
Due to the diversity of sewage status and the limitation of the selection of auxiliary variables, this requirement is often not fully satisfied, often resulting in the failure to achieve the ideal accuracy when estimating the leading variable with the analog output of the soft sensor
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 moreImage
Smart Image Click on the blue labels to locate them in the text.
Smart ImageViewing Examples
Examples
Experimental program
Comparison scheme
Effect test
Embodiment
[0046] In this embodiment, the sequencing batch activated sludge method built in the laboratory is selected as the sewage treatment process, and the performance and feasibility of the present invention are verified through simulation.
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
Login to View More
Abstract
The invention relates to a sewage chemical oxygen demand soft measuring method based on a support vector machine and a neural network, belonging to the technical field of sewage treatment. In the invention, the water quality parameters pH, dissolved oxygen, redox potential, a pH rate of change, a dissolved oxygen rate of change and a redox potential rate of change are selected for carrying out soft measurement on the water quality parameter chemical oxygen demand. By adopting the support vector machine, the input data are classified according to all water quality parameters and the parameter rates of change, and the proper neutral network is selected for respectively training to realize the real-time effective estimate of the water quality parameters. The test on the testing system shows that the method has good precision and general applicability.
Description
technical field [0001] The invention belongs to the field of sewage treatment, and in particular relates to a soft measurement method for chemical oxygen demand in sewage. Background technique [0002] Chemical Oxygen Demand (COD, Chemical Oxygen Demand) is the amount of oxidant consumed when a certain strong oxidant is used to treat water samples under the condition of strong acid and heating, expressed in terms of oxygen concentration (mg / L). A comprehensive indicator of total organic matter. The content of organic matter in water is one of the important indicators for grading the environmental quality of natural water bodies. It is the fundamental factor that causes the water body to turn black and smelly, and it is also the basis for judging whether the water body is polluted by domestic sewage and industrial wastewater. Many countries have stipulated the maximum value of COD, a water quality parameter that can be discharged into natural water bodies. [0003] At prese...
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
Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G01N33/18G06N3/02G06N3/08
Inventor 张杰冯辉雷中方张建秋胡波
Owner FUDAN UNIV
Who we serve
- R&D Engineer
- R&D Manager
- IP Professional
Why Patsnap Eureka
- Industry Leading Data Capabilities
- Powerful AI technology
- Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.
© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com