机电工程技术2023，Vol.52Issue(12)：204-206,272,4.DOI:10.3969/j.issn.1009-9492.2023.12.047
基于GA-BP的煤矿瓦斯监控系统"大数干扰"信号辨识
GA-BP-Based Coal Mine Gas Monitoring System"Large Number Interference"Signal Identification
陈强 1刘祥洁 1廖石宝1
作者信息
- 1. 江西理工大学电气工程与自动化学院,江西赣州 341000
- 折叠
摘要
Abstract
Aiming at the problem of false alarm caused by strong electromagnetic signal interference in the data transmission process of gas sensor,under the condition of experimental simulation of"large number"interference,a large number interference signal identification method of coal mine gas monitoring system based on genetic algorithm(GA)optimized BP neural network is proposed.Firstly,according to the characteristics of fast amplitude transformation of large number interference signals,the input and output of BP neural network are determined,and then the Bayesian regularization method is used to improve the generalization ability of the network,combined with the global search ability of genetic algorithms,the weight and threshold of the network are optimized,and finally the large number interference signal identification model of GA optimized BP neural network is established.The experimental results show that the genetic algorithm can effectively reduce the training error of BP neural network,and compared with the unoptimized BP neural network,the relative error of the optimized network test signal is reduced from 10.003 to 6.096,and the normal output of the gas outburst signal will not be affected after identification,which can solve the problem of false alarm of the sensor caused by large number of interference signals in coal mines.关键词
BP神经网络/遗传算法/贝叶斯正则化/瓦斯传感器/误报警Key words
BP neural network/genetic algorithm/Bayesian regularization/gas sensor/false alarm分类
矿业与冶金引用本文复制引用
陈强,刘祥洁,廖石宝..基于GA-BP的煤矿瓦斯监控系统"大数干扰"信号辨识[J].机电工程技术,2023,52(12):204-206,272,4.
