摘要
传统煤自燃火灾探测方法易出现误报与漏报的问题,不利于准确探测煤矿自燃火灾。针对实践中问题,综合利用探测方法之间的互补性,在多传感器、小波及神经网络理论的基础上,提出多传感器小波神经网络应用于煤自燃检测中的具体方法,以期为我国煤自燃检测做出理论贡献。
The traditional coal spontaneous combustion fire detection method prone to false positives and false negatives, is not conducive to the accurate detection of spontaneous combustion in coal mine. Aiming at the problems in practice, the complementarity between the comprehensive utilization of detection method, based on multi sensor, wavelet and neural network theory, put forward the specific method to detect multiple sensor application of wavelet neural network in coal spontaneous combustion, in order to make a contribution to the theory of coal spontaneous combustion testing in china.
出处
《煤矿机械》
2017年第4期33-34,共2页
Coal Mine Machinery
基金
陕西省教育厅科研计划项目资助(16JK1395)
关键词
多传感器
小波
神经网络
煤自燃
multi sensor
wavelet
neural network
coal spontaneous combustion
