Patent classifications
E21D9/003
ENVIRONMENTAL MONITORING APPARATUS AND METHOD FOR MINE TUNNELING ROBOT
An apparatus includes a current excitation source, a roadheader telescopic protection cylinder, an electric rotating apparatus, auxiliary cutting teeth, a cutting head entity, a transmission shaft, an optical fiber ring protective housing, an optical fiber ring, an optical fiber current sensor control unit and a recovery electrode. The apparatus transmits an auxiliary current I.sub.e and a monitoring current I.sub.d to a coal seam. The auxiliary current I.sub.e and the monitoring current I.sub.d are homologous currents that are incompatible, and the auxiliary current I.sub.e squeezes the monitoring current I.sub.d, so the monitoring current I.sub.d monitors the environment of the coal seam. The monitoring current I.sub.d flows to the coal seam as, and a return current I.sub.f flows through the transmission shaft and a roadheader expansion part. The optical fiber ring measures the return current I.sub.f, when the roadheader is heading forward and encounters abnormal geological bodies.
AUTOMATIC MICROSEISMIC MONITORING-INTELLIGENT ROCKBURST EARLY WARNING INTEGRATED SYSTEM AND METHOD FOR TUNNEL BORING MACHINE (TBM)-BASED CONSTRUCTION
An automatic microseismic monitoring-intelligent rockburst early warning integrated method is further provided.
Safety early warning method and device for full-section tunneling of tunnel featuring dynamic water and weak surrounding rock
A safe early warning method and device for full-section tunneling of a tunnel featuring dynamic water and weak surrounding rock, comprising establishing a dynamic coordinate system with an origin thereof moving along a tunnel excavation line, recording the moving distance of the origin, conducting three-dimensional laser scanning with the origin as a center to obtain point cloud data including coordinate data, collecting surrounding rock data; conducting deformation fitting on the point cloud data, calculating a fitting residual error, removing a noisy point, and conducting preprocessing; combining data of preprocessed point cloud, surrounding rock, and the tunnel excavation line to construct a tunnel excavation dynamic model; conducting stress analysis according to the model and determining whether to send out a safety early warning signal. The device comprises a three-dimensional laser scanner, a geological radar device, a displacement module, an industrial computer, a data transmission module, an alarm, and a server.
Method for boring with plasma
Systems to bore or tunnel through various geologies in an autonomous or substantially autonomous manner can include one or more non-contact boring elements that direct energy at the bore face to remove material from the bore face through fracture, spallation, and removal of the material. The systems can automatically execute methods to control a set of boring parameters that affect the flux of energy directed at the bore face. Systems can further automatically execute the methods to trigger an optical sensor to capture images at the bore face, generate temperature profiles, identify spall fragments and hot zones and/or adjust a set of boring controls. For example, the system can execute methods to adjust a standoff distance between the system and the bore face, and adjust power and/or gas supply to the non-contact boring element.
HALF-CAST MARK IDENTIFICATION AND DAMAGED FLATNESS EVALUATION AND CLASSIFICATION METHOD FOR BLASTHOLES IN TUNNEL BLASTING
The present disclosure relates to a half-cast mark identification and damaged flatness evaluation and classification method for blastholes in tunnel blasting, including the following steps: S1-2: photographing first and second contrast images as well as a half-cast mark image after blasting; S3-6: performing denoising, gray-scale processing and binary processing on the above images, and identifying a boundary of a half-cast mark in each of the images; S7-9: determining a flatness damage variable, a quantitative relation among an area of a half-cast mark region, the damage variable and a fractal dimension, and a damage value of the half-cast mark image; S10-11: forming five-dimensional (5D) eigenvectors to obtain multi-dimensional digital information features of the images; and S12-13: selecting eigenvectors of 60 images as training data to input to a naive Bayes classifier (NBC), and taking eigenvectors of remaining 30 images as classification data to input the above well-trained NBC for classification.
Ram accelerator augmented drilling system
Systems for drilling or tunneling include an assembly for accelerating a projectile into a region of geologic material. An interaction between the projectile and the geologic material extends a borehole and forms debris. The debris may be reduced in size by moving the debris to a crushing device. The reduced-size debris is then moved toward the surface using fluid movement. Water jets or other types of devices may be used to cut or deform a perimeter of a region of geologic material before the projectile is accelerated to control the shape of the borehole and the manner in which debris is broken from the geologic material.
ADVANCED GEOLOGICAL PREDICTION METHOD AND SYSTEM BASED ON PERCEPTION WHILE DRILLING
An advanced geological prediction method and system based on perception while drilling, and relates to advanced geological prediction. The solution includes: acquiring drilling parameters during drilling; obtaining physical and mechanical parameters of tunnel surrounding rocks by inversion based on drilling parameters; acquiring rock slag or powder based on flushing fluid collected during drilling; acquiring geochemical characteristic parameters of rock slag or powder; and obtaining at least one adverse geology recognition result and surrounding rock classification result using a pre-trained deep learning model, and realizing advanced geological prediction. Combined with advanced geological drilling, the solution reflects geological characteristics from changes of physical and mechanical properties of tunnel surrounding rocks and changes of geochemical characteristic parameters. Advanced prediction of geology ahead of a tunnel face is realized by collection and analysis of drilling parameters and flushing fluid during advanced drilling and the fusion of big data and a deep learning algorithm.
TUNNEL BORING MACHINE HAVING A DEVICE FOR DETECTING A CONTENT OF CRITICAL GAS
A device for detecting a content of critical gas in a mining chamber of a tunnel boring machine includes a separation module by which a fluid fed in via an extraction line connection is cleaned of solid and liquid components. A gas line arrangement arranged downstream of the separation module in the flow direction of the fluid carries the fluid, including substantially only gaseous components, through a pressure reducer and through a flow control valve of a metering module by which the gas to be analyzed can be delivered in a controlled manner assisted by a double diaphragm pump and a pressure stabilizer to a gas analysis unit even at high pressures in the cavity.
TUNNEL BORING MACHINE
In a tunnel boring machine with a shield skin (106) extending in a longitudinal direction, a sensor unit (118) for detecting convergences has a number of hydraulic distance sensors (121) equipped with an extendable probe (124) with extension path measurement. By virtue of the distance sensors (121), the distance between the shield skin (106) in the area of the relevant distance sensor (121) and the surrounding rock mass (103) can be detected as a distance value, so that the thickness of an annular gap (115) can be determined. The distance sensors (121) are arranged in the longitudinal direction of the shield skin (106) at a measuring distance which corresponds to a typical ring width of a tubbing (112). A central unit evaluates the distance values of the distance sensors (121) to determine convergences.
METHOD AND SYSTEM FOR REAL-TIME PREDICTION OF JAMMING IN TBM TUNNELING
A method and system for real-time prediction of jamming in TBM tunneling. The method includes: (1) obtaining actually measured TSP physical property parameters by applying a TSP method; (2) analyzing value ranges and change trends of the TSP physical property parameters obtained in real time; (3) establishing a TSP physical property parameter sample database of a TBM tunnel; (4) establishing a mapping relationship between TSP physical property parameters and occurrence or not of jamming; (5) establishing a mapping relationship between time sequence values of tunneling parameters and occurrence or not of jamming; and (6) forecasting a TBM jamming risk in real time, and storing reliable data into the TSP physical property parameter sample database. The method and system can effectively obtain a state of surrounding rocks in time, thereby providing real-time forecasting of TBM tunneling jamming, avoiding occurrence of accidents to some extent, and improving the TBM tunneling efficiency.