Flue gas desulfurization oxidation system fault prediction method based on machine learning algorithm

A machine learning, oxidation system technology, applied in the field of industrial flue gas treatment, can solve the problems of increasing the oxidation air flow, increasing the risk of failure, adverse absorption, etc. consumption effect

Pending Publication Date: 2022-03-11
江苏昆仑互联科技有限公司
View PDF0 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

On the other hand, increasing the oxidation air flow rate and increasing the liquid level of the oxidation liquid tank will lead to overload operation of the oxidation fan, increase energy consumption, and increase the risk of failure; the lower pH value of the absorption liquid is also not conducive to SO 2 absorb

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
  • Flue gas desulfurization oxidation system fault prediction method based on machine learning algorithm
  • Flue gas desulfurization oxidation system fault prediction method based on machine learning algorithm
  • Flue gas desulfurization oxidation system fault prediction method based on machine learning algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0043] In order to have a further understanding of the purpose, structure, features, and functions of the present invention, the following detailed descriptions are provided in conjunction with the embodiments.

[0044] Please refer to figure 1 figure 2 image 3 as well as Figure 4 , the present invention provides a method for predicting a failure of a flue gas desulfurization oxidation system based on a machine learning algorithm, which is characterized in that it includes the following steps:

[0045] S1: Collect the historical operation data of the flue gas desulfurization device as the sample set data;

[0046] S2: Organize the sample set data collected in S1 into the type and format required by machine learning, and form the sample data of machine learning through data cleaning;

[0047] S2-1: Delete the missing values ​​in the sample set, and sort from small to large to get the sequence of each parameter {X 1 ,X 2 ,X 3 ,……X n};

[0048] S2-2: Order Q L =X (n / 4...

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 flue gas desulfurization oxidation system fault prediction method based on a machine learning algorithm. The machine learning algorithm model is applied to fault prediction and early warning of the oxidation air system of the flue gas desulfurization device. Through machine learning, historical operation data of the wet desulphurization device are analyzed by adopting an OLS linear regression algorithm model, internal logic of each operation characteristic parameter and the oxidation performance of the desulphurization device is mined, a principle model of an oxidation reaction is dominated, and the method is used for fault prediction of the wet desulphurization device. And operators can conveniently master the health state of the oxidation air system of the desulfurization device in real time. Fault prediction and early warning of the oxidation air system of the wet desulphurization device are realized, an algorithm model participates in operation control, and the power consumption of an oxidation fan can be reduced by reducing the excess amount of oxidation air, optimizing the density and the PH value of oxidation liquid and reducing the liquid level height of an oxidation tank in time, so that the operation cost of the desulphurization device is reduced.

Description

technical field [0001] The invention belongs to the field of industrial flue gas treatment, and in particular relates to a method for predicting a failure of a flue gas desulfurization oxidation system based on a machine learning algorithm. Background technique [0002] my country is a large country of coal. At present, coal is still the main fuel for industrial use. While coal releases heat during combustion, it also produces a large amount of particulate matter, SO 2 , greenhouse gases and other pollutants, causing ecological environment pollution. Wet flue gas desulfurization technology is one of the desulfurization methods commercially applied in the world. It can efficiently remove sulfur oxides in flue gas, and the by-products are easy to recycle resources. It is a good way to control atmospheric SO 2 Pollution most effective flue gas desulfurization technology. Contains SO 2 The flue gas enters the desulfurization device, and in the desulfurization tower is in cont...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/27G06N20/00B01D53/50B01D53/78G06F119/02
CPCG06F30/27G06N20/00B01D53/501B01D53/78B01D2258/0283G06F2119/02
Inventor 周玲霞贾义李承泉陈效良张勇
Owner 江苏昆仑互联科技有限公司
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

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap