煤矿外因火灾早期探测方法研究

基金项目:

国家自然科学基金项目（51277149）

陕西省教育厅专项项目(14JK1467）

西安科技大学博士启动基金项目（2014QDJ010）

详细信息

Research of early prediction method for exogenous fire in coal mine

College of Electrical and Control Engineering, Xi''an University of Science and Technology, Xi''an 710054, China

摘要: 针对煤矿井下环境特点，提出了基于数字图像处理和支持向量机的煤矿外因火灾早期探测方法。该方法根据火灾初期的变化特征，用图像处理方法提取温度变化率、面积增长率、火焰闪烁频率和整体稳定性等特征值，并将其作为输入信号，利用支持向量机进行数据融合后实现火灾探测。实验结果表明，该方法能够对煤矿井下高危火源和干扰信号进行分类识别，具有探测率高、误判率低、实时性好、鲁棒性强的特点。
- 煤矿 /
- 外因火灾 /
- 火灾探测 /
- 数字图像处理 /
- 支持向量机
Abstract: Early prediction method for exogenous fire in coal mine based on digital image processing and SVM was proposed according to coal mine environment characteristics. The method uses image processing method to extract characteristics values of temperature change rate, area growth ratio, flame flicker frequency and overall stability according to initial changing features of fire, and takes them as input signal to SVM for data fusion, so as to achieve fire detection. The experimental results show that the method can realize classification and recognition of high-risk fire source and interference signal of coal mine, and has high detection rate, low misjudgment rate, good real-time performance and robustness.
- coal mine /
- exogenous fire /
- fire prediction /
- digital image processing /
- support vector machine