# Real-Time Tunnel Deformation Monitoring Technology Based on Laser and Machine Vision
The current tunnel deformation monitoring technology, including non-machine vision measurement methods and machine vision measurement methods [6], however, is not effective enough. Most of the existing equipment is manually operated and susceptible to a dusty and dark environment in low visibility, and cannot meet real-time automatic monitoring and early warning requirements or provide timely warnings about dangerous deformation [7]. Non-machine vision measurement methods are widely used in tunnel deformation monitoring; however, they are susceptible to environmental and human factors, and take a long time. Tape extensometers and convergence gauge are unstable and operated manually; in addition, they are strongly influenced by environmental and human factors [8]. The leveling method mainly addresses the tunnel settlement value [9] and requires many monitoring points to be set; thus, the error accumulates with the increase in the tunnel length. The indoor global positioning system measurement method requires many reference signal transmitters; however, it is difficult to ensure the stability of the reference signal transmitters position. The traditional total station measurement method has a low degree of automation, exhibits strong subjectivity, and requires a fixed station; these features affect the tunnel construction period [10]. The new-generation total station measurement method allows stations to be freely monitored, compared with the traditional method [11; 12], but it cannot be used to monitor all kinds of tunnels because of its high cost [13]. The fiber Bragg grating measurement method [14] can be used to monitor tunnel deformation constantly over a long period of time, but it is expensive, and the relevant equipment is easily damaged. Moreover, the equipment needs to be embedded into the structure or adhered onto the structure surface during monitoring, which results in a higher demand on the environment. A deformation monitoring system based on ultrasonic sensors [15] is automatic and in real time; however, it is only suitable for small- to middle-size tunnels, and it cannot be used to realize early warnings of dangerous deformation during the construction. Terrestrial laser scanning [16] achieves tunnel deformation monitoring; however, it takes a long time to obtain and process point cloud data, and cannot realize real-time monitoring. A machine vision measurement method for tunnel deformation develops a lot in the last few years [17]; however, existing machine vision measurement methods are not suitable for real-time tunnel deformation monitoring during construction with dusty and dark environments. A three-dimensional reconstruction method based on machine vision [18] needs to take lots of photos and the data processing algorithms are complex; this takes a long time and cannot meet real-time automatic monitoring and early warning requirements. A digital close-range photogrammetric method [19] is susceptible to tunnel dust and light intensity, heavy dust and a dark environment during construction reduces photo quality and detection accuracy. A photogrammetric method for tunnel detection based on a CCD camera [20] has a higher requirement for brightness and lighting equipment; this requires external power supply; when using batteries, the equipment is heavy and not easy to install; when using an electric generator, extra great vibration is produced and this affects the result. The infrared photogrammetric method [21] reduces dust impact at the price of decreasing photo brightness; as a result, the detection accuracy is low and cannot be used for real-time monitoring. Photogrammetric techniques for monitoring tunnel deformation [22] are only suitable for tunnels without dust after excavation, and it is also susceptible to dusty and dark environments.