基于傅里叶变换红外光谱探测的火灾早期过程特征信息研究

通过对火灾过程中各种特征参量进行分析,提出采用CO作为早期火灾探测的探测对象,并在此基础上建立起基于傅里叶变换红外光谱仪的完善试验系统。通过该实验系统进行了大量早期火灾加热阴燃及燃烧试验,经过光谱定量分析得到其各自CO浓度变化数据。在数据分析的基础上通过时间序列分析建模建立起CO浓度数据的二阶自回归模型,提取出表征火灾整体特性的过程特征信息参数1和2。通过相平面分析表明:真假火灾的过程特征信息参数具有明显的区域分布差异性,利用这种特性可以快速将真假火灾分辨出来。大量试验结果证实该探测方法能够在火灾发生早期及时对真假火灾进行有效辨别。

Research on Process Character Information in Early Fire Based on Fourier Transform Infrared Spectrum Detection

CO was chosen as an early fire detection factor through analyzing all kinds of characters in the process of fires, and an experiment system was established based on Fourier transform infrared spectrometer. Through this system, lots of early fire experiments were carried out, and the authors got the CO concentrations of all kinds of materials. Using the concentration of CO, an autoregressive integrated model was established by time series analysis, then the process characters phi1 and phi2 were extracted from them. Through analyzing the phase graph of the process characters, it was found that the real fires and the nuisance fires were distributed in different regions. Plenty of experiments indicate that this detection method can discriminate between real fire sources and nuisance sources quickly when fires occur.