Abstract: The present disclosure provides a determining device for the weathering resistant capability of clastic rocks in a tunnel based on feldspar features, which overcomes the shortcomings of current evaluation methods, is easy to operate, can be used to detect the type, content, and crystal structure of feldspar in a rock stratum, and integrates the information by combining a computer deep learning method to determine the weathering resistant capability of clastic rocks containing different types of feldspar in a tunnel, with high accuracy.

Abstract: A TBM-mounted surrounding rock wear resistance testing system and method, the system including: a fixing module, arranged on a TBM, the module has a movable end for extending to the surrounding rock of a tunnel; a surrounding rock polishing module on the movable end, the module includes a polishing mechanism for test area; a surrounding rock wear resistance testing module on the movable end, follows the movable end moving the test area, and including a mechanism for testing the wear resistance of the polished test area and a drive mechanism thereof; and a central control module, configured to control the motion states and operations of the fixing module, the surrounding rock polishing module and surrounding rock wear resistance testing module, and determine the wear resistance of the surrounding rock according to the wear resistance test result. The system can polish tunnel surrounding rock during TBM excavation and test wear resistance.

Abstract: A system and method for identifying lithology based on images and XRF mineral inversion solving the problem that conventional lithology identification relies on manual work, which is time-consuming, subjective and can cause misjudgment. The identification system includes an autonomous vehicle; an X ray fluorescence spectrometer probe, and tests surrounding rock element information; image collection device; and vehicle-mounted processor. The processor inverts the received surrounding rock element information into mineral information based on a Barthes-Niggli standard mineral calculation method; and receive surrounding rock images and a corresponding inclination angle thereof, convert the surrounding rock images into image information in a one-dimensional vector format, splice the image and mineral information which is in a one-dimensional format, and distinguish the spliced information based on a preset neural network to identify rock lithology.

Abstract: A system and method for identifying lithology based on images and XRF mineral inversion solving the problem that conventional lithology identification relies on manual work, which is time-consuming, subjective and can cause misjudgment. The identification system includes an autonomous vehicle; an X ray fluorescence spectrometer probe, and tests surrounding rock element information; image collection device; and vehicle-mounted processor. The processor inverts the received surrounding rock element information into mineral information based on a Barthes-Niggli standard mineral calculation method; and receive surrounding rock images and a corresponding inclination angle thereof, convert the surrounding rock images into image information in a one-dimensional vector format, splice the image and mineral information which is in a one-dimensional format, and distinguish the spliced information based on a preset neural network to identify rock lithology.

Abstract: An intelligent lithology identification system and method based on images and spectrum technology. The intelligent lithology identification system includes a rock shape analysis system, an image identification system, a sample processing system, a spectrum analysis system, and a central analysis and control system; wherein the central analysis and control system determines the final lithology of a sample according to the rock identification results from the image identification system and the analysis results from the spectrum analysis system. The technical solution further identifies the content and type of minerals by using spectrum technology, integrates and analyzes the results of spectrum analysis and image identification, and finally gives the lithology of the rock, which greatly improves the accuracy of lithology identification.

Abstract: A system and a method identify an adverse geological body in a tunnel based on hyperspectral technology analysis. The system includes a wall-climbing robot, a controller, and a signal processor, wherein the wall-climbing robot is provided with a plurality of groups of hyperspectral light sources and receivers, and the hyperspectral light sources and the receivers are arranged at intervals; the controller is configured to control the operation of the wall-climbing robot to ensure that the wall-climbing robot moves on a tunnel face according to a set spiral path; and the signal processor communicates with the receivers to receive the acquired spectrum data, draws a mineral distribution map of the tunnel face with the path raveled by the wall-climbing robot as a plane, and identifies an adverse geological body by identifying categories and distribution characteristics of the representative minerals.

Abstract: A predicting system and method for the uniaxial compressive strength of rock include a point loading strength test module, a longitudinal wave velocity test module, a rock rebound value test module and a strength prediction module, wherein the longitudinal wave velocity test module performs longitudinal wave velocity tests on the rock, and transfers the longitudinal wave velocity of the rock to the strength prediction module; the rock rebound test module performs rebound test on the rock, and transfers the rebound value of the rock to the strength prediction module; the point loading strength test module performs image acquisition on a fracture surface of the rock after being loaded and fractured by the point loading test, and calculates the area of the fracture surface; and the strength prediction module outputs a uniaxial compressive strength prediction result of the rock according to the received information and a preset prediction model.

Abstract: The present disclosure provides a determining device for the weathering resistant capability of clastic rocks in a tunnel based on feldspar features, which overcomes the shortcomings of current evaluation methods, is easy to operate, can be used to detect the type, content, and crystal structure of feldspar in a rock stratum, and integrates the information by combining a computer deep learning method to determine the weathering resistant capability of clastic rocks containing different types of feldspar in a tunnel, with high accuracy.

Abstract: A TBM-mounted surrounding rock wear resistance testing system and method, the system including: a fixing module, arranged on a TBM, the module has a movable end for extending to the surrounding rock of a tunnel; a surrounding rock polishing module on the movable end, the module includes a polishing mechanism for test area; a surrounding rock wear resistance testing module on the movable end, follows the movable end moving the test area, and including a mechanism for testing the wear resistance of the polished test area and a drive mechanism thereof; and a central control module, configured to control the motion states and operations of the fixing module, the surrounding rock polishing module and surrounding rock wear resistance testing module, and determine the wear resistance of the surrounding rock according to the wear resistance test result. The system can polish tunnel surrounding rock during TBM excavation and test wear resistance.

Abstract: An integrated test device and method for filling karst cave deposition and tunnel intermittent water and mud inrush disasters. The device includes a mixing tank, water tank, water collection tank and plurality of depositing tanks, wherein mixing tank outlet is connected to one end of a pipe, the other end of the pipe extends to one end of the water tank, the plurality of depositing tanks are arranged underwater tank at intervals, the water collection tank is arranged at the water tank's other end, and a detachable baffle is arranged in the water tank and in front of each depositing tank. The deposition and consolidation of filling media and water and mud inrush can be simulated and observed through the setting and cooperation of the plurality of depositing tanks, different working conditions can be simulated by changing the flow rate, sample concentration, particle gradation, depositing height and displacement.

Abstract: A full-automatic rock specimen image acquisition device and method, the device includes a central controller and a lighting system, a rock mass attitude control system, a dust system and an image acquisition system connected to the central controller respectively; the lighting system includes a lighting chamber and light sources with adjustable light intensities, and the light sources with adjustable light intensities are uniformly arranged in the lighting chamber; the rock mass attitude control system includes a rotating stage disposed in the lighting chamber for carrying the rock, a rock holder disposed on the stage, and a rotating gripper disposed above the stage for turning over the rock; and the dust system is connected to the lighting chamber, and can diffuse the dust into the lighting chamber through an air compressor and control the dust concentration in the lighting chamber through an electrostatic precipitator.

Abstract: A full-automatic rock specimen image acquisition device and method, the device includes a central controller and a lighting system, a rock mass attitude control system, a dust system and an image acquisition system connected to the central controller respectively; the lighting system includes a lighting chamber and light sources with adjustable light intensities, and the light sources with adjustable light intensities are uniformly arranged in the lighting chamber; the rock mass attitude control system includes a rotating stage disposed in the lighting chamber for carrying the rock, a rock holder disposed on the stage, and a rotating gripper disposed above the stage for turning over the rock; and the dust system is connected to the lighting chamber, and can diffuse the dust into the lighting chamber through an air compressor and control the dust concentration in the lighting chamber through an electrostatic precipitator.

Abstract: An intelligent lithology identification system and method based on images and spectrum technology. The intelligent lithology identification system includes a rock shape analysis system, an image identification system, a sample processing system, a spectrum analysis system, and a central analysis and control system; wherein the central analysis and control system determines the final lithology of a sample according to the rock identification results from the image identification system and the analysis results from the spectrum analysis system. The technical solution further identifies the content and type of minerals by using spectrum technology, integrates and analyzes the results of spectrum analysis and image identification, and finally gives the lithology of the rock, which greatly improves the accuracy of lithology identification.