Abstract: Disclosed is a comprehensive inspection vehicle for a subway tunnel, including a positioning system, an acquisition system and a flatcar. The flatcar runs on a railway of the subway tunnel. The positioning system and the acquisition system are arranged on the flatcar. The positioning system includes a laser ranging module and an inertial navigation module. The comprehensive inspection vehicle further includes an independent power supply system and a central control system arranged on the flatcar. The independent power supply system supplies power for the acquisition system, the positioning system and the central control system. The central control system includes an acquisition industrial computer and a positioning industrial computer which are respectively connected to the acquisition system and the positioning system.

Abstract: The invention discloses a method for detecting service performance of a tunnel lining based on defect characteristics of the tunnel lining. A tunnel, an external load and stratum conditions are simulated by establishing a model using a model test method. A structural stress failure test for the model is carried out, and test results of the defect characteristics of a simulation lining of the model are recorded. A corresponding relationship between the defect characteristics of the simulation lining and the remaining bearing capacity interval is established according to the recorded test results. Detection results of defect characteristics of the tunnel lining are recorded using an in-situ detection method, and a remaining bearing capacity interval of the tunnel lining is determined based on the detection results according to the corresponding relationship between the defect characteristics of the simulation lining and the remaining bearing capacity interval of the model.

Abstract: The invention discloses a method for detecting service performance of a tunnel lining based on defect characteristics of the tunnel lining. A tunnel, an external load and stratum conditions are simulated by establishing a model using a model test method. A structural stress failure test for the model is carried out, and test results of the defect characteristics of a simulation lining of the model are recorded. A corresponding relationship between the defect characteristics of the simulation lining and the remaining bearing capacity interval is established according to the recorded test results. Detection results of defect characteristics of the tunnel lining are recorded using an in-situ detection method, and a remaining bearing capacity interval of the tunnel lining is determined based on the detection results according to the corresponding relationship between the defect characteristics of the simulation lining and the remaining bearing capacity interval of the model.

Abstract: Disclosed is a comprehensive inspection vehicle for a subway tunnel, including a positioning system, an acquisition system and a flatcar. The flatcar runs on a railway of the subway tunnel. The positioning system and the acquisition system are arranged on the flatcar. The positioning system includes a laser ranging module and an inertial navigation module. The comprehensive inspection vehicle further includes an independent power supply system and a central control system arranged on the flatcar. The independent power supply system supplies power for the acquisition system, the positioning system and the central control system. The central control system includes an acquisition industrial computer and a positioning industrial computer which are respectively connected to the acquisition system and the positioning system.

Abstract: An on-line tunnel deformation monitoring system based on image analysis and its application comprises identification points, an IP camera, a central control computer, as well as a transmission network and the application of the system includes the following steps: 1) lay the identification points; 2) the central control computer controls the zoom photography of the IP camera periodically; 3) the IP camera transmits the photos to the central control computer; 4) the central control computer conducts self-adaptive filtering transformation for the photos; 5) the central control computer conducts grayscale threshold transformation; 6) the central control computer conducts image edge detection to obtain the identification points; 7) calculation of the arch crown settlement displacement and the arch springing convergence displacement of the identification points; 8) judge whether the arch crown settlement displacement and the arch springing convergence displacement are both less than the set thresholds, and if they