基于红外小目标检测技术的煤样表面温度梯度与破裂关系

Relationship Between Coal Sample Surface Temperature Gradient and Rupture Based on Infrared Small Target Detection Technology

在分析单轴受压煤样表面破裂特征的基础上,提出煤样表面的红外图像检测属于小目标检测,进而用小目标检测的形态学神经网络方法对实验得到的红外图像进行分析。实验表明,该方法能有效检测煤样表面的温度异常点,进一步分析发现单轴受压煤样的应力应变曲线与其红外图像温度异常点的变化曲线存在对应关系。该方法可以应用到煤矿矿压监测领域,对煤矿安全生产起到一定的积极作用。

Based on the analysis of the surface rupture characteristics of the coal sample in early rupture stage under uniaxial compres- sion, it is foundput forward that the infrared image detection of coal sample surface rupture points arewere small targetstarget detection. The morphological neural network method applied for small target detection is employedwas used to detect analyze the infrared image small rupture targetsfrom the tests. The Experiments experiments showed that this method can could effectively detect the coal surface temperature anomalies of coal sample surface. And , and it was obtained that the correspondence between the stress - strain curve of coal samples and the temperature anomaliesabnormal points in of infrared image under uniaxial eompressionis discussed. This method can be used to imorove the technoloaw of monitoring coal mine nressure to guarantee the safetv of coal mining.