Research on fire detection in coal mine based on GA-improved Wavelet Neural Networks

被引：3

作者：

Zhao, Hong ^{[1
]}

机构：

[1] China Jiliang Univ, Hangzhou, Zhejiang, Peoples R China

来源：

MECHATRONICS AND INTELLIGENT MATERIALS II, PTS 1-6 | 2012年 / 490-495卷

关键词：

Fire detection; image processing; GA-improved; wavelet; neural network;

D O I：

10.4028/www.scientific.net/AMR.490-495.1636

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In coal mine the forecast on fire is mainly based on the smoke, gas and temperature parameters to recognize, and sometimes it has leak check and wrong check, therefore a novel method for mine fire based on image processing is presented. First the data are obtained by infrared CCD, then the blaze characters are extracted and they are entered into the GA-improved wavelet neural networks model after being quantization, finally the fire can be detected. The experiment results show that this method can recognize fire signals and it reduced leak forecast, and also it is more reliable and has stronger antigambling ability. It will inevitably play an important role in coal mine safety production..

引用

页码：1636 / 1639

页数：4