Strip steel quality forecasting, furnace condition early-warning and fault diagnosis method based on partial least square

A partial least squares and quality prediction technology, which is applied in the fields of furnace condition early warning and fault diagnosis, and strip steel quality prediction, can solve problems such as time lag, limiting the qualified rate of strip steel product quality, and difficulty in finding fault factors

Active Publication Date: 2011-04-27
SHANGHAI BAOSTEEL IND TECHNOLOGICAL SERVICE +1
View PDF2 Cites 42 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The off-line experimental analysis usually has a certain time lag, which makes it possible to obtain the specific quality of the strip steel only after it has been produced for a period of time.
The existence of this problem n...

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
  • Strip steel quality forecasting, furnace condition early-warning and fault diagnosis method based on partial least square
  • Strip steel quality forecasting, furnace condition early-warning and fault diagnosis method based on partial least square
  • Strip steel quality forecasting, furnace condition early-warning and fault diagnosis method based on partial least square

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0137] Such as figure 1 Shown, below is that the present invention is further described, comprises six steps:

[0138] 1. Model Selection

[0139] There are mainly two types of quality prediction model structures: single-model structure and multi-model structure; the complexity of the actual annealing process and the diversity of strip steel specifications are considered in the modeling, and the analysis shows that different steel types (degree of quenching and tempering) affect the process The operating conditions have different requirements, which directly or indirectly affect the quality of the strip steel, that is, different model structure relationships under different working conditions. Using a single model structure to describe the relationship between quality and process variables under different working conditions will result in defects such as large model structure, overfitting of data relationships, and low prediction accuracy. Therefore, this project adopts the ...

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 relates to a strip steel quality forecasting, furnace condition early-warning and fault diagnosis method, in particular to a strip steel quality forecasting, furnace condition early-warning and fault diagnosis method based on partial least square, comprising the following steps: model selection: multiple models are adopted to describe the process characteristics of corresponding steel types; data preprocessing: data alignment based on the model is carried out, synchronization relation of process input and quality output is built and data dimensionless treatment is carried out to eliminate effect of process data on modeling precision owning to non-unity of physical units; an off-line model building; a PLS (partial least square) model for strip steel quality and process variable is built by utilizing a great amount of historical data in normal working conditions; determining control limit of an monitor-control index; determining variable quantity control limit; and on-line forecasting and on-line detection and fault diagnosis. In the invention, the model for the strip steel quality and the process variable is built by PLS algorithm, so as to realize real-time quality forecasting, process monitoring and fault diagnosis.

Description

technical field [0001] The invention relates to a strip steel quality control method, in particular to a strip steel quality prediction, furnace condition early warning and fault diagnosis method. Background technique [0002] In the cold rolling continuous annealing unit, the annealing furnace is one of the important equipment. Annealing is a heat treatment process that heats the strip steel to an appropriate temperature, keeps it warm for a certain period of time, and then cools it slowly to obtain a state close to equilibrium. The essence of annealing, for eutectoid steel and hypereutectoid steel, is the process of pearlite transformation after austenitization; for hypoeutectoid steel, it is the process of pearlite transformation after austenitic transformation process. [0003] By annealing, it is possible to achieve: [0004] (1) Eliminate the composition segregation of steel and make the composition homogeneous; [0005] Intragranular segregation due to dendrite cr...

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): G05B19/418C21D1/26C21D9/52
Inventor 陈卫东徐家倬王姝丁旭峰牛大鹏高金刚谭帅
Owner SHANGHAI BAOSTEEL IND TECHNOLOGICAL SERVICE
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