基于多传感器的隧道异常自动巡检系统的设计

为及时发现隧道内渗漏水和裂缝病害,提早采取应对措施而降低损失和节省成本,设计了一套基于多传感器的隧道自动巡检系统。通过分析隧道内渗漏水和裂缝表现出的特征,针对渗漏水现象,通过红外热成像设备获取环境的温差伪彩图,设计出一种多邻域生长动态异常区域识别算法检测漏水点;针对裂纹细小难以识别的问题,通过大面阵工业相机获取高分辨率图像,并提出一种基于相机标定的图像拼接方法获取隧道内全部视场,从而扩大裂纹检测范围。将传感器模块化安装在隧道运动巡检设备中,构建一套完整的网络架构,进行信息交互和数据传输。实验结果证明该系统有较强的可靠性和鲁棒性,渗漏水检测算法误检率低,可有效检测出温度异常区域;图像拼接算法成像质量高、拼接速度快。

Design and Implementation of Tunnel Anomaly Detection System Based on Multi-Sensor

In order to discover the leakage and crack diseases in tunnel in time, take early measures to reduce losses and save costs, a set of automatic tunnel inspection system based on multi-sensor was designed. By analyzing the characteristics of leakage water and cracks in tunnels, aiming at the phenomenon of leakage water, a multi-neighborhood dynamic anomaly region recognition algorithm was designed to detect leakage water by using infrared thermal imaging equipment to obtain pseudo-color image of temperature difference in the environment. Aiming at the problem that the cracks were small and difficult to identify, a high-resolution image was obtained by large-area array industrial camera, and a phase-based image was proposed. The image mosaic method of machine calibration obtained all the field of view in the tunnel, so as to expand the crack detection range. Then, the sensor module was installed in the tunnel motion inspection equipment, and a complete network architecture was constructed for information exchange and data transmission. The experimental results showed that the system had strong reliability and robustness, and the leakage detection algorithm has low false detection rate, which could effectively detect the abnormal temperature area. The image mosaic algorithm had high imaging quality and fast mosaic speed.