基于光纤气体检测技术的煤矿自然发火预测预报系统

 分析了近红外光谱吸收式气体检测的基本原理以及煤矿采空区自然发火特征气体的选择，通过使用近红外激光光谱吸收式光纤气体传感器对采空区火灾特征气体浓度检测，报道实现了一套基于多种气体参数的火灾预测预报系统。系统使用分布反馈式半导体激光器（DFB LD）作为光源，光源驱动为低频锯齿波信号叠加高频正弦波信号，通过锁相放大器实现信号提取。根据采空区三带静态分布理论，给出了判断采空区自然发火危险程度的判定方法。该系统全部使用光纤进行井下信号传输和气体检测，使得检测精度更高，不带电工作，实时性更强，系统更加稳定可靠。

Spontaneous combustion prediction in coal mine goaf based on fiber sensing of gas

The principle of gas detection with spectrum absorption is explained and the typical gas in coal mine is given. A goaf spontaneous combustion prediction system with multiple parameters is introduced in detail. The system uses a distributed feedback diode laser as light source, which is driven by a low frequency sawtooth wave overlapped with a high-frequency sinusoidal signal. Signal extraction is achieved with a lock-in amplifier. The method to determine spontaneous combustion of coal mine goaf is explained according to the theory of static distribution of three zones. The system uses fiber to detect gas and transmit signal, which makes the real time detection accurate, stable and reliable due to absence of electricity.