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Fuzzy BP neural network based glass tempering process parameter setting method

A technology of BP neural network and process parameters, applied in glass tempering, biological neural network models, glass manufacturing equipment, etc., can solve the problems of not meeting modern production scale, high requirements for technical personnel, increasing production costs, etc., and achieve error rate Low, high setting accuracy, quality-enhancing effect

Active Publication Date: 2015-11-25
ZHEJIANG SCI-TECH UNIV
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AI Technical Summary

Problems solved by technology

If the process parameters are not set properly, it will cause cracks in the glass, uneven surface and other problems, which will affect the product quality.
In the prior art, the process parameters of glass tempering are mostly set by technicians based on experience, which greatly increases the production cost, and has high requirements for technicians, which cannot meet the needs of modern production scale

Method used

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Embodiment Construction

[0033] The present invention will be described in detail below in conjunction with specific embodiments.

[0034] A method for setting process parameters of glass tempering based on fuzzy BP neural network, comprising:

[0035](1) Obtain several initial samples, each initial sample includes the glass type of a batch of glass, the thickness of the glass, the number of glass blocks in a heat, the total area of ​​the glass, and the corresponding process parameters.

[0036] In this embodiment, the initial samples are extracted from a large amount of historical data. The number of initial samples in this embodiment is 180. Historical data is input in txt format. In order to ensure that it can be input and extract initial samples, the historical data must meet specific format restrictions. In this embodiment, all historical data are input in txt format, and then the initial samples are directly extracted from the historical data in txt format through corresponding extraction code...

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Abstract

The invention discloses a fuzzy BP neural network based glass tempering process parameter setting method. The process parameter setting method comprises: according to an initial sample, training a BP neural network; dividing existing tempered glass into multiple categories; obtaining the optimal process parameters of each category according to the already trained BP neural network; establishing a process database according to the process parameters of all the categories; directly judging the category of to-be-tempered glass; directly choosing the process parameters corresponding to the category from the technology database; and setting the tempering process parameters of the to-be-tempered glass by utilizing the chosen process parameters. According to the fuzzy BP neural network based glass tempering process parameter setting method, the BP neural network is used to directly obtain the optimal process parameters of the to-be-tempered glass in the tempering process, so that the degree of dependence on artificial experience is reduced and the production cost is reduced; the process parameter setting method is realized through a computer, so that the setting precision is high, the error rate is low, the quality of the tempered glass can be improved, and the production efficiency is greatly improved.

Description

technical field [0001] The invention relates to the technical field of glass tempering, in particular to a process parameter setting method for glass tempering based on a fuzzy BP neural network. Background technique [0002] With the development of economic globalization, our country puts forward the requirements for the production demand and quality standards of industrial and civil glass products to be in line with the world's advanced level. As a safety glass, tempered glass is obtained from the original glass after tempering. Its impact strength is four times or more higher than that of ordinary glass. When it is broken by external factors, it will not form a sharp "knife surface", but It becomes almost uniform small granular glass slag, which has the advantage of not being easy to hurt people. Therefore, in the use of safety glass in the global automotive industry, construction industry, instrument and furniture industries, tempered glass accounts for more than 60%. C...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06N3/02C03B27/00
CPCY02P40/57
Inventor 黄静
Owner ZHEJIANG SCI-TECH UNIV
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