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作 者:代东林 邹小春 DAI Dong-lin;ZOU Xiao-chun(China Merchants Chongqing Highway Engineering Testing Center Co.Ltd.,Chongqing 400067,China)
机构地区:[1]招商局重庆公路工程检测中心有限公司,重庆市400067
出 处:《公路》2023年第4期232-237,共6页Highway
基 金:重庆市社会事业与民生保障科技创新专项重点研发项目,项目编号cstc2017shms-zdyfX0007。
摘 要:针对隧道入口“黑洞效应”现象,提出将接近段靶标视距作为监测与评估的客观依据。在入口洞内等间距布设若干圆形靶标,洞外视觉最不利位置处设置高清摄像机采集靶标区域图像,基于BP神经网络算法建立以图像特征、洞外亮度和观察距离为输入量的靶标可见度计算模型。根据靶标可见度求解实时的靶标视距,并结合行业标准对停车视距的相关要求,实现“黑洞效应”在线监测及其严重程度的分级评估。最后以某高速公路运营隧道为例介绍了监测与评估技术的实际应用。For the phenomenon of“black hole effect”at the tunnel entrance,it is proposed to take the sight distance of the target in the approach section as the objective basis for monitoring and evaluation.Several circular targets are arranged inside the tunnel entrance at equal intervals,and a high-definition camera is set at the most unfavorable position outside the tunnel to collect the image of the target area.Based on BP neural network algorithm,a target visibility calculation model with image features,brightness outside the tunnel and observation distance as inputs is established.According to the target visibility,the real-time target sight distance is obtained,and combined with the relevant requirements of the industry standard for the stopping sight distance,the online monitoring of the“black hole effect”and the graded assessment of its severity are realized.Finally,the practical application of monitoring and evaluation technology is introduced relying on a highway tunnel in operation.
关 键 词:隧道工程 黑洞效应 隧道入口 机器视觉 监测与评估
分 类 号:U453.1[建筑科学—桥梁与隧道工程] U491.4[交通运输工程—道路与铁道工程]
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