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作 者:薛天山 李永强 郝跃 贺东东 武国鹏 白怡明 Xue Tianshan;Li Yongqiang;Hao Yue;He Dongdong;Wu Guopeng;Bai Yiming(Guoneng Xinjiang Zhundong Energy Co.,Ltd.,Urumqi,Xinjiang 830000;CCTEG Shenyang Engineering Company,Shenyang,Liaoning 110015)
机构地区:[1]国能新疆准东能源有限责任公司,新疆乌鲁木齐830000 [2]中煤科工集团沈阳设计研究院有限公司,辽宁沈阳110015
出 处:《非金属矿》2025年第2期87-91,共5页Non-Metallic Mines
基 金:山西省高等学校哲学社会科学研究项目(2022ZSS2SX237)。
摘 要:为了准确获取岩体特征信息,提出一种基于改进Deep Labv3+算法的矿山岩体阴影数字化方法。针对Deep Labv3+算法的特征提取网络,运用轻量级的MobileNetV2网络替换原来的Xception以减少参数计算量,提高计算速度,并动态调整通道权重。通过改进后的算法实现矿山岩体结构面阴影的自动识别及数字化处理,包括结构面阴影骨架提取、交点消除、长度计算等。结果表明,改进Deep Labv3+算法的像素准确率最大值达93.65%,平均值为87.65%,类别准确率平均值为89.12%,平均交并比为79.34%,均优于对比算法。矿山岩体结构面阴影数字化处理结果偏差小,可靠性高,能较好反映实际测量情况。该方法提升了矿山岩体阴影数字化的有效性与可靠性,为矿山岩体处理提供了新的有力途径。In order to obtain the characteristic information of rock mass accurately,a digitization method of mine rock mass shadow based on improved Deep Labv3+algorithm is proposed.For the feature extraction network of Deep Labv3+algorithm,the lightweight MobileNetV2 network is used to replace the original Xception to reduce the parameter calculation,improve the calculation speed,and dynamically adjust the channel weight.Through the improved algorithm,the automatic identification and digital processing of structural plane shadow of mine rock mass are realized,including extraction of structural plane shadow skeleton,intersection elimination,length calculation,etc.The results show that the improved Deep Labv3+algorithm has a maximum pixel accuracy of 93.65%,an average of 87.65%,an average class accuracy of 89.12%,and an average crossover ratio of 79.34%,all of which are superior to the comparison algorithm.The digital processing results of structural plane shadow of mine rock mass have small deviation and high reliability,can reflect the actual measurement situation better.This method can improve the effectiveness and reliability of mining rock mass shadow digitization,and provide a new powerful way for mining rock mass treatment..
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