摘要
隧道爆破块度是评价其爆破质量的一个重要因素,对于隧道中光照强度低、单一光源光照不均、爆破后烟尘大等不利环境下拍摄的照片,目前难以通过常规图像处理方法获取隧道爆破块度。基于ACE+CLAHE算法提出了一种新的隧道爆破块度图像分析法,结合图像分块切割,排除了低光强度、光照不均、爆破烟尘对图像照明度、对比度的干扰,再通过双边滤波、二值化算法、图像开运算、分水岭算法等图像处理方法可获取隧道爆破块度分割图,完成隧道爆堆岩块的分割。通过现场实例的图像分析,验证了此方法可较好地区分岩块目标,识别隧道爆堆的块度。相关经验可供类似隧道爆破作业参考。
The tunnel blasting fragment degree is an important factor to evaluate the blasting quality.However,it is difficult to accurately obtain the tunnel blasting fragment by conventional image processing methods because photos are taken in unfavorable environments such as low light intensity,uneven illumination of single light source and large smoke and dust after blasting.Based on ACE and CLAHE algorithm,a new image analysis method for tunnel blasting fragments was proposed.Combined with image block cutting,the interference of low light intensity,uneven illumination and blasting smoke and dust on image illumination and contrast was eliminated.Through bilateral filtering,binarization algorithm,image opening operation,watershed algorithm and other image processing methods,the segmentation image of tunnel blasting fragments can be obtained,and the segmentation of tunnel blasting rock block can be completed.Through the image analysis of a field example,it is verified that this method can better distinguish rock targets and identify the fragmentation of tunnel blasting.The relevant experience can be used as a reference for similar tunnel blasting operations.
作者
姬付全
梁晓腾
杨林
江鸿
毛永强
JI Fuquan;LIANG Xiaoteng;YANG Lin;JIANG Hong;MAO Yongqiang(CCCC Second Harbor Engineering Co.,Ltd.,Wuhan 430040,China;Key Laboratory of Long and Large Bridge Construction Technology in Transportation Field,Wuhan 430040,China;Transportation Infrastructure Intelligent Manufacturing Technology R&D Center,Wuhan 430040,China)
出处
《人民长江》
北大核心
2022年第11期125-129,共5页
Yangtze River
基金
湖北省科技厅项目(2021EJD012)。
