本文排版定稿已在中国知网网络首发,如需阅读全文请打开知网首页,并搜索该论文题目即可查看。

热红外技术识别及量化林火关键信息的方法研究

Methodology for Identifying and Quantifying Key Forest Fire Parameters Using Thermal Infrared Technology

  • 摘要: 通过开展系列林火试验,从火态变化、时间段差异和飞行高度3个维度,系统评估了热红外成像技术对火点的精准识别能力;并基于热红外辐射强度与火焰高度,解析火点态势的动态特征。结果表明:热红外技术能够对火点实现精准识别;热辐射强度随时间演化呈现出显著的阶段性特征,揭示了火点燃烧过程的五阶段性演化规律;火焰高度公式均方根误差分别为0.0321 m和0.0402 m,对称平均绝对百分比误差分别为7.07%和11.29%,线性回归模型R2分别为0.99550.9959,公式具有良好的适用性与准确性。本研究进一步验证了热红外成像技术在林火监测中的高效性和可靠性,可为森林火灾的动态监测、早期预警与应急管理提供技术支持。

     

    Abstract: A series of forest fire experiments were conducted to systematically evaluate the capability of thermal infrared imaging technology to accurately identify fire points under fire state change, time period difference, and flight altitudes. The dynamic characteristics of the fire point situation were analyzed based on the intensity of thermal infrared radiation and the height of the flame. The findings indicate that thermal infrared technology possesses the capability to accurately identify the fire point. The temporal evolution of thermal radiation intensity exhibits substantial stage characteristics, revealing a quintuple-stage evolutionary pattern in the combustion process of fire sources. The root mean square errors (RMSE) of the flame height formula are 0.0321 m and 0.0402 m. The symmetric mean absolute percentage errors (SMAPE) are 7.07% and 11.29%. And the R2 of the linear regression model are 0.9955 and 0.9959. The formula demonstrates notable applicability and accuracy. This study lends further credence to the efficacy and dependability of thermal infrared imaging technology in forest fire monitoring. The technology facilitates dynamic monitoring, early warning systems, and emergency management of forest fires.

     

/

返回文章
返回