Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Cement finished product specific surface area prediction method and system

A technology of specific surface area and cement products, applied in neural learning methods, measuring devices, biological neural network models, etc.

Active Publication Date: 2019-09-10
YANSHAN UNIV
View PDF4 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] Based on this, it is necessary to provide a method and system for predicting the specific surface area of ​​cement products to solve the problem of time-varying delay between the variable data and the indicators to be measured in the process of predicting the specific surface area of ​​cement products, and to change the status quo of delay measurement, and Realize low-cost measurement of specific surface area of ​​cement products

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
  • Cement finished product specific surface area prediction method and system
  • Cement finished product specific surface area prediction method and system
  • Cement finished product specific surface area prediction method and system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 2

[0113] The method for predicting the specific surface area of ​​cement products in this embodiment first selects the experimental value of the specific surface area of ​​the cement product at the previous moment and the particle size distribution value of the cement product measured by the particle size analyzer from the database of the cement grinding system, respectively AB particle size45um, AB particle size>60um, AB particle size>80um, a total of 6 input variables. Combining the technology of sliding window time series with convolutional neural network, and using back propagation technology to fine-tune the weights, a well-trained specific surface area prediction model is established. The specific flow model diagram is as follows figure 2 shown.

[0114] figure 2 Schematic diagram of the structure of the specific surface area prediction model trained for Example 2 of the present invention.

[0115] see figure 2 , the method for predicting the specific surface area of ...

Embodiment 3

[0155] This embodiment provides a system for predicting the specific surface area of ​​cement products, including:

[0156] The data acquisition module is used to obtain the data of the finished cement product to be tested; the data of the finished cement product to be tested includes the particle size data of the finished cement product to be tested at the current moment and the experimental value of the specific surface area of ​​the finished cement product to be tested at a previous moment; the particle size data includes multiple particle size values; each said particle size value belongs to a different particle size range.

[0157] Prediction module for inputting the data of the finished cement product to be tested into the trained specific surface area prediction model to obtain the predicted value of the specific surface area of ​​the finished cement product to be tested; the trained specific surface area prediction model is obtained through a convolutional neural networ...

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 discloses a cement finished product specific surface area prediction method and system. The method comprises the following steps: obtaining to-be-tested cement finished product data, wherein the to-be-tested cement finished product data comprises granularity data of the to-be-tested cement finished product at the current moment and a specific surface area experimental value of the to-be-tested cement finished product at the previous moment; the granularity data comprises a plurality of granularity values; the particle size values belong to different particle size ranges; inputting the to-be-tested cement finished product data into the trained specific surface area prediction model to obtain a specific surface area prediction value of the to-be-tested cement finished product,wherein the trained specific surface area prediction model is determined through a convolutional neural network algorithm and a back propagation algorithm. The method solves the problem of time-varying delay between the variable data and the to-be-measured index in the cement finished product specific surface area prediction process, and is low in measurement cost.

Description

technical field [0001] The invention relates to the technical field of performance prediction and prediction of cement products, in particular to a method and system for predicting the specific surface area of ​​cement products. Background technique [0002] As one of the basic raw material process industries, the cement manufacturing industry plays an important role in economic construction. The cement grinding process is an important process of cement production. The specific surface area of ​​cement products is an important parameter to evaluate the quality and performance of cement products. Accurate prediction of the cement ratio table can be used for the optimization of cement grinding process scheduling, the reduction of comprehensive energy consumption and the improvement of cement products. provide a basis for the evaluation. [0003] For a long time, high-quality, high-yield, energy-saving and consumption-reducing goals have been the relentless pursuit of the ceme...

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): G06N3/04G06N3/08G01B21/28
CPCG06N3/084G01B21/28G06N3/045
Inventor 郝晓辰李泽史鑫杨跃赵彦涛
Owner YANSHAN 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
PatSnap group products

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