Innovative Sensor Design Method of Industrial Ceramic Product Modeling Based on Immune Optimization Algorithm

A new method based on immune optimization algorithm was proposed for modeling and design of industrial ceramic products. Based on the joint coding of fuzzy rules and membership function parameters, an improved immune optimization algorithm was used to realize the synchronous optimization of industri...

Full description

Saved in:
Bibliographic Details
Published in:Journal of sensors 2022-06, Vol.2022, p.1-7
Main Author: Gu, Chihui
Format: Article
Language:English
Subjects:
Antibodies
Antigens
Artificial intelligence
Aspect ratio
Ceramics industry
Control theory
Design techniques
Designers
Distortion
Fuzzy control
Genetic algorithms
Immune system
Industrial design
Innovations
Inspection
Medical research
Memory
Neural networks
Optimization
Optimization algorithms
Product design
Product modelling
Sensors
Simulation
Software
Temperature control
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:A new method based on immune optimization algorithm was proposed for modeling and design of industrial ceramic products. Based on the joint coding of fuzzy rules and membership function parameters, an improved immune optimization algorithm was used to realize the synchronous optimization of industrial ceramic product modeling. A superheated steam temperature control system is taken as an example to carry out simulation tests. The results show that the ratio of the unit volume to the side length is between 0 and 1, which is called the mass of the grid element. Zero is the worst quality and one is the best. Element aspect ratio and distortion degree are also basic inspection indexes. The average mass of vacuum glass is 0.86, the aspect ratio is 1.71, and the element distortion degree is 0.13, indicating that the grid quality is well divided. It is proved that using the improved immune genetic algorithm to optimize fuzzy control can overcome the defects of the traditional genetic algorithm and ensure the faster and more stable search for the optimal rule base and membership function.
ISSN:1687-725X
1687-7268
DOI:10.1155/2022/4300643