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Time sequence classification analysis method and system for glass quality influence factors

A technology of time series and influencing factors, applied in manufacturing computing systems, data processing applications, instruments, etc., can solve problems such as energy consumption, impact, and reduction of oxygen content in the kiln

Active Publication Date: 2021-05-04
WUHAN UNIV OF TECH
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Problems solved by technology

On the other hand, the quality of glass production is also affected by fluctuations in furnace pressure
If the kiln pressure is too high, the oxygen content in the kiln will be reduced, causing a corresponding impact. If the kiln pressure is too low, cold air will enter the kiln, and the preset temperature cannot be reached.
In order to maintain a stable temperature, fuel consumption must be increased at this time, resulting in unnecessary energy consumption
If too much cold air enters the kiln, it will also cause the reduction flame to be unable to maintain normally, which will have a greater impact on the quality of the produced glass

Method used

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  • Time sequence classification analysis method and system for glass quality influence factors

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Embodiment Construction

[0035] The technical solution of the present invention will be described in detail below in conjunction with the accompanying drawings and embodiments.

[0036] The invention can provide a model for time series classification and analysis of glass quality influencing factors. The present invention combines the machine learning model with the glass manufacturing process, analyzes and models time series data such as furnace temperature, pressure, natural gas flow, oxygen flow, and pressure, and finds key factors that affect glass quality, thereby improving glass quality. Production yield. The random forest algorithm and tree-based integrated model xgboost and lightgbm models of the present invention classify time series data and glass quality data. The tree-based model will split each feature in the classification process, and find the optimal split point to generate a tree, so as to realize the classification of time series. At the same time, after the three models are traine...

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Abstract

The invention provides a time sequence classification analysis method and system for glass quality influence factors, and the method comprises the steps: obtaining original time sequence data collected by each sensor on a glass production line and corresponding glass quality data, and adding a label to the glass quality data according to a glass quality index; segmenting the time sequence data to correspond to glass quality labels; performing feature construction on the processed time sequence data through data analysis, and analyzing and finding out relatively important time sequence features; dividing a training set and a verification set, respectively using a random forest, xgboost and lightgbm modes to construct a time sequence classification model, and iteratively training the model; the importance score obtained on the basis of a Permutation implication feature selection method and the importance score obtained by weighting results obtained by feature importance functions of corresponding models on the basis of prediction accuracy of a random forest model, an xgboost model and a lightgbm model are integrated, and a factor analysis result influencing the glass quality is obtained so as to correspondingly control factors on a glass production line.

Description

technical field [0001] The invention belongs to the field of glass production quality control analysis, in particular to a scheme for time series classification and analysis of glass quality influencing factors. Background technique [0002] Glass manufacturing is a complex and energy-intensive process. In recent years, with the rapid development of glass technology, the problem of low glass yield has become one of the most concerned issues today. The glass manufacturing process is a complex process, and the glass melting furnace is the core production process that consumes about 70% to 80% of the total energy consumed by the entire manufacturing process. [0003] Glass melting furnace is a typical melting furnace in industry, which is very complicated as a chemical process. It is influenced by many factors, such as furnace temperature, pressure, natural gas flow, oxygen flow, kiln pressure and flue temperature. From a technical point of view, it is important to observe t...

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Application Information

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IPC IPC(8): G06K9/62G06N20/20G06Q10/06G06Q50/04
CPCG06N20/20G06Q10/06395G06Q50/04G06F18/211G06F18/24323Y02P90/30
Inventor 邹承明李吉祥
Owner WUHAN UNIV OF TECH
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