1156 results about "Tunnel engineering" patented technology

The invention discloses a modeling method based on shield tunneling data feature analysis and parameter relevance, and relates to the field of tunnel engineering data processing. The method comprises the steps that shield tunneling time sequence parameters are obtained, and a non-uniform time sequence is resampled into a space-aligned standardized footage domain sequence through state cleaning and coordinate domain transformation; by means of mixed variable rejection and lagging correlation analysis, environment common cause interference is stripped, physical response delay among parameters is recognized, and a time-delay directed correlation graph model is constructed; and inputting the footage domain sequence and the graph model into a graph neural network, performing feature learning by using a time delay compensation aggregation mechanism, and outputting a key parameter influence degree set with symbols based on a prediction gradient. According to the method, the problem of data space-time dislocation caused by propelling speed fluctuation and the problem of parameter relevance misjudgment caused by physical response lag are solved, and accurate identification and explanation of shield tunneling key parameters are achieved.

The invention provides a tunnel crack identification method and system based on multi-source image processing, and relates to the technical field of tunnel engineering, and the method comprises the steps: obtaining multi-source data of a horizontal rock stratum tunnel; performing spatial registration on the multi-source data to generate a multi-modal image under the same reference system; extracting multi-modal features according to the multi-modal image, and constructing a multi-source feature map under the same space grid; performing crack initial detection on the multi-source feature map in combination with multi-scale filtering and structure tensor analysis to obtain a crack candidate region mask; accurate crack identification is carried out through the crack candidate area mask, a crack identification result is obtained by combining bedding direction constraint and a microconditional random field, and the crack identification result comprises a crack segmentation map and a crack category. The method solves the problem that existing crack identification does not consider the bedding characteristics of the horizontal rock stratum tunnel.

The invention provides a tunnel disaster source multi-attribute joint inversion method and system based on physical property constraint, and relates to the technical field of tunnel engineering and joint inversion, and the method comprises the steps: constructing a tunnel face three-dimensional geologic model, applying controlled disturbance to surrounding rock physical property parameters, analyzing the change characteristics of earthquake and electromagnetic observation response, and obtaining a tunnel face three-dimensional geologic model; establishing a quantitative mapping relation between the surrounding rock physical property parameter disturbance quantity and the multi-field response signal variable quantity; constructing a multi-dimensional sensitivity evaluation index, and generating a joint sensitivity result; the surrounding rock units are identified and divided, differentiated partition rock physical relationship constraints are constructed, and a physical multi-attribute inversion target of joint inversion is determined based on the partition rock physical relationship constraints; and on the basis of a physical multi-attribute inversion target, a multi-source joint inversion target function is constructed in combination with the joint sensitivity result, joint solving and iterative updating are carried out, and a tunnel face advanced inversion result is output. According to the invention, calamity source fine identification and risk quantitative evaluation in front of the tunnel face during the tunnel construction period are realized.

The invention discloses a shield muck volume estimation method and system based on image processing, and particularly relates to the technical field of tunnel engineering monitoring, and the method comprises the steps: obtaining muck RGB and depth images through an image collection device, generating high-precision three-dimensional point cloud data through the combination of laser scanning and a multispectral technology, and calculating the muck volume through a slicing method. And fusing the mass flow and water content data of the belt weigher, dynamically generating a calibration factor, and correcting a volume estimation result in real time. The system comprises an image acquisition module, a point cloud processing module, a volume calculation module and a dynamic calibration module, has the characteristics of automation, high precision, real-time feedback and the like, effectively solves the problems of large error and slow response of a traditional manual metering and single weighing mode, and is suitable for continuous and accurate monitoring of the volume of muck in the shield construction process.

The invention discloses crack-chloride ion double-triggered subsea tunnel corrosion-resistant concrete and a preparation method thereof, and relates to the field of subsea tunnel engineering materials. The concrete is prepared from the following components in parts by weight: 400 to 500 parts of Portland cement, 50 to 80 parts of fly ash, 60 to 100 parts of superfine mineral powder, 1000 to 1100 parts of coarse aggregate, 700 to 800 parts of fine aggregate, 140 to 160 parts of water, 10 to 20 parts of self-repairing microcapsules and 1 to 5 parts of a water reducing agent, the self-repairing microcapsule comprises a capsule wall material, a self-repairing material and a layered dihydroxyl composite metal oxide. A crack-chloride ion double-response system is constructed, and the limitation of traditional single trigger repair is broken through. When a crack with a certain width appears in the concrete, the capsule wall of the self-repairing microcapsule is broken to release the repairing component, so that effective filling of the crack is realized; and meanwhile, the layered double-metal hydroxide can directionally adsorb chloride ions to form a stable compound, so that the migration rate of the chloride ions is remarkably reduced.

The invention discloses a cold region tunnel freeze injury diagnosis, risk grading and control system and method, and relates to the technical field of tunnel engineering. The system comprises a basic data layer for storing disease, index and measure databases; the core analysis layer is used for diagnosing a frost heaving mechanism, identifying single-factor, double-factor and three-factor frost heaving types, calculating freezing depth and frost heaving force and analyzing sensitivity; the risk level evaluation layer is used for dividing a disease zone, a frost heaving level, a freezing injury risk and a freezing injury risk response level; and the intelligent decision-making layer constructs an intelligent comprehensive decision-making analysis platform to realize risk-measure accurate matching and closed-loop management and control. The method comprises the four steps of data acquisition and storage, frost heaving mechanism diagnosis and quantification, risk grade evaluation and intelligent decision measure matching, through multi-source data fusion, multi-factor coupling analysis and zoning and grading prevention and control, the whole-process accurate management and control of the cold region tunnel frost damage is realized, and the frost damage treatment efficiency and the tunnel operation safety are improved.

The invention provides a multi-dimensional supporting leg structure for lightweight steel ring splicing equipment, and relates to the field of tunnel engineering. The mounting base is fixedly connected with the frame, the telescopic driving mechanism is arranged between the mounting base and the supporting leg assembly, the angle adjusting mechanism is arranged between the cylinder barrel and the mounting base, and the self-locking mechanism is used for locking the cylinder barrel and the piston rod when the driving unit fails. The telescopic driving mechanism is composed of a cylinder barrel, a piston rod and a driving unit, the angle adjusting mechanism is driven through a first rotating shaft and a second rotating shaft which are perpendicular to each other and corresponding rotation, so that the cylinder barrel achieves double-shaft swing adjustment, the self-locking mechanism is composed of a locking rack, a movable tooth claw, a reset spring, an electromagnet and a permanent magnet, and power-on unlocking and power-off self-locking are achieved. According to the structure, the supporting polygon is obviously enlarged under the complex basic condition, the anti-overturning stability of equipment is improved, reliable supporting is kept when a hydraulic system fails, and the safety and adaptability of steel ring splicing operation in a tunnel are improved.

The invention discloses a tunnel monitoring method and system based on a vibrating wire sensor, and relates to the technical field of tunnel engineering construction safety monitoring, and the method comprises the steps: collecting the vibration frequency data and spatial position coordinates of the vibrating wire sensor in a monitoring region; the method comprises the following steps: calculating a time difference and an energy attenuation ratio between adjacent sensors by extracting spectrum energy density distribution, and constructing a stress wave propagation field; dividing grids in the propagation field to calculate node stress values, generating a stress field distribution cloud picture and extracting a stress concentration area; calculating a gravity center position coordinate change rate and a stress time sequence curve of the stress concentration area, and determining fracture extension parameters; and calculating a surrounding rock bearing capacity attenuation curve based on the parameters, and outputting an early warning signal when the slope exceeds a threshold value. According to the invention, real-time monitoring and early warning of the tunnel surrounding rock instability risk are realized.

The invention discloses a high-toughness impervious polymer modified cement-based grouting material and a preparation method thereof, and belongs to the technical field of building repair materials. The component A is prepared from a cementing material, an admixture, a fine aggregate, a composite expanding agent, a polymer for concrete modification, fibers, an early strength agent, a water reducing agent, a composite retarder, a defoaming agent, an air entraining agent, a nano material and a functional component. The system solves the technical contradiction of toughness-strength-impermeability in the polymer modified cement-based material, and the material has excellent comprehensive performance: the initial fluidity is greater than or equal to 330 mm, the 28d compressive strength is greater than or equal to 82 MPa, the breaking strength is greater than or equal to 16.8 MPa, the bending-compression ratio is greater than or equal to 0.19, the impermeability pressure value is greater than or equal to 2.6 MPa, and the material is suitable for the fields of prefabricated buildings, tunnel engineering and the like.

The invention belongs to the technical field of tunnel engineering, and provides a multi-physics field real-time assimilation simulation and regulation method and system in a tunnel grouting process in order to solve the problem that real-time dynamic simulation and automatic regulation are lacked in existing tunnel construction, and the real-time assimilation simulation and regulation method and system in the tunnel grouting process are provided by utilizing ensemble Kalman filtering and combining real-time monitoring data in the tunnel grouting process. Dynamically correcting parameters of the multi-physical model; time correlation in the slurry condensation process is considered, a time-varying condensation model depicting physical property changes of slurry evolving along with time is integrated, the time-varying condensation model serves as an external function in the time step length to be embedded into the multi-physical field model in correction, and the slurry flowing state is adjusted in a self-adaptive mode through numerical simulation; and generating control parameters of tunnel grouting according to a dynamic simulation result, and realizing closed-loop regulation and control of tunnel grouting. Synchronous linkage of numerical simulation and on-site working conditions is realized.

The invention discloses a tunnel deformation real-time early warning method and system based on an LSTM-CNN model, and belongs to the technical field of tunnel engineering safety monitoring. The method comprises four steps of data acquisition, spatio-temporal feature fusion processing, deformation prediction and risk assessment, and intelligent early warning and decision support: collecting multi-dimensional monitoring data through a distributed sensor network and recording spatio-temporal labels; after standardized noise reduction, extracting time trend and spatial distribution characteristics by using an LSTM-CNN fusion model, and constructing a time-space sequence data set; outputting a deformation prediction value based on the fusion features, and calculating a deviation degree in combination with a dynamic threshold model; and triggering multi-level early warning according to the deviation degree and performing visual display. The system comprises a data acquisition module, an edge calculation module, a cloud analysis module and an intelligent terminal module, and double-channel redundancy transmission is adopted to guarantee data continuity. Through spatio-temporal feature collaborative mining, dynamic threshold value adaptation and graded early warning, the deformation prediction precision and the risk assessment accuracy are improved, the transmission stability in an extreme environment is guaranteed, and the early warning decision efficiency is optimized.

The invention relates to the technical field of tunnel engineering safety, in particular to a tunnel fire multi-stage damage collaborative prediction method and system, and the method comprises the steps: constructing a data simulation fusion model, and carrying out the processing of fire and tunnel structure parameter data, and obtaining a multi-working-condition parameter database; constructing a heat conduction equation, a fire plume and wall surface heat exchange relational expression, a boundary layer correction model and a comprehensive damage evaluation model, and analyzing the equation, the relational expression and the model by utilizing a multi-physical field coupling unified boundary condition to obtain a multi-physical boundary constraint condition; obtaining a multi-physical constraint loss function based on a network architecture and a multi-physical boundary constraint condition, and further obtaining a comprehensive constraint loss function of a temperature field-stress field-damage index; constructing a PINN-LSTM network architecture and a damage evolution analysis model based on the fire ending initial state coding vector, the fire course feature vector and the cooling process feature vector; and performing linkage analysis on the function, the frame and the model to predict and monitor the transient damage and the long-term creep damage of the tunnel.

The invention relates to the technical field of tunnel engineering and intelligent construction, in particular to a shield tunneling real-time control method based on a random forest and a particle swarm optimization algorithm. The method comprises the steps that initial tunneling parameters are generated through a parameter recommendation random forest model according to geology and tunnel geometric parameters, and model hyper-parameters are optimized through a sparrow optimization algorithm; carrying out settlement prediction by utilizing the settlement prediction random forest model; if the predicted value exceeds the limit, carrying out iterative optimization by adopting a particle swarm optimization algorithm and taking the initial parameter as a starting point, and searching a global optimal tunneling parameter combination meeting the settlement requirement; finally, the optimized parameters are issued to the shield tunneling machine to be executed, the model is continuously updated based on real-time construction data, and closed-loop control is formed. According to the method, intelligent recommendation and real-time optimization of tunneling parameters can be realized, the ground surface settlement control precision and the system response speed are improved, the dependence on artificial experience is effectively reduced, and the self-adaptive capability and the intelligent level of shield construction under complex geological conditions are enhanced.

Provided is a method for judging geology of a time-delayed extremely intense rockburst as to deep tunnel engineering. Information about geological structures is recorded according to methods such as geological mapping and advanced geological prediction of the tunnel face. Geometric characteristics of burst craters formed during the rockburst are recorded by utilizing advanced geological drilling and profile scanning technologies in a rockburst-damaged zone. 3D geostress in the rockburst-damaged zone is measured by using a stress relief method or a hydraulic fracturing method to determine the orientation of the maximum principal stress. A 3D numerical calculation model is established based on initial geostress testing results and physical and mechanical parameters of rock and structural discontinuities obtained through on-site geological investigations. By conducting excavation simulations under different combinations of structural discontinuities and performing numerical calculation, the risk of time-delayed extremely intense rockburst disasters at current locations after tunnel excavation is judged.

The invention provides a deep tunnel excavation physical simulation test three-dimensional stress field real-time prediction method, and relates to the technical field of tunnel engineering. Comprising two stages of model construction and training and model use. In the model construction and training stage, a physical constraint reference model is constructed, and training optimization is completed; and in the model use stage, real-time prediction of a stress field of a deep engineering physical simulation test is realized through the trained and optimized model. The method has breakthrough advantages in the aspects of physical law constraint, real-time monitoring data fusion, training loss stability, boundary stress condition accuracy and the like, and is a high-reliability three-dimensional stress field prediction method oriented to a deep complex environment.

The invention discloses a shield tunnel muck improvement parameter prediction method and system, and relates to the technical field of tunnel engineering construction.The method comprises the steps that a multi-modal sensor is arranged at a key part of a shield tunneling machine, and tunneling parameters, stratum parameters, multi-modal sensor signals, muck physical properties and modifier injection parameters are collected; then, extracting change characteristics, calculating mutation sensitive factors and carrying out working condition judgment; constructing a normal prediction sub-model library and a sudden change quick response model, calculating a stratum model adaptation index and performing model suitability judgment; establishing a working condition coupling prediction model by using a graph neural network, extracting nonlinear coupling characteristics, calculating a working condition coupling index and judging prediction stability; actual construction performance data are collected and compared with a model prediction result, a prediction correction index is calculated, deviation analysis is carried out, and a corresponding correction strategy is triggered. According to the method, intelligent prediction and dynamic correction of shield tunnel muck improvement parameters can be achieved, and the safety and stability of the construction process are improved.

The invention relates to the field of tunnel engineering, in particular to a tunnel multi-physics field coupling simulation and support design method considering construction disturbance, which comprises the following steps of: modeling a disturbance source, collecting disturbance factor information introduced in a tunnel construction process or an external environment, establishing a disturbance source model to represent the spatial position, intensity and evolution characteristics of a disturbance source; constructing a three-dimensional disturbance propagation function; coupling the three-dimensional disturbance propagation function with a multi-physical field model, and introducing disturbance as a source item into a tunnel heat-water-force coupling model; according to the construction method customization mechanism, modeling parameters and solving strategies are adjusted according to the characteristics of different tunnel construction methods, and corresponding disturbance source model parameters, boundary conditions and constitutive relation adjustment coefficients are set according to the different construction methods. The problems that disturbance modeling is rough, a disturbance propagation mechanism is idealized, the disturbance propagation mechanism is disjointed with a multi-physical field model, and a construction method is not included in a disturbance response system are solved.

The invention relates to the technical field of tunnel engineering, and particularly discloses a trolley loading device and method for tunnel lining splicing, the trolley loading device comprises a hoisting transfer mechanism, bearing turnover mechanisms are arranged on the two sides of the hoisting transfer mechanism, and transfer feeding mechanisms are further arranged at the lower ends of the two sides of the hoisting transfer mechanism; the hoisting and transferring mechanism comprises a supporting frame, a guide rail pair sliding rail I, a guide rail pair sliding seat I, a supporting plate, a motor I, a winding roller and a steel wire rope I; the bearing turnover mechanism comprises a first bearing, a first shaft rod, a rope wheel, a second steel wire rope, a second bearing, a second shaft rod, a second motor and a bearing plate. According to the scheme, efficient hoisting and accurate positioning of the duct piece are achieved through the hoisting and transferring mechanism, the arch structure design of the supporting frame provides a stable supporting foundation, the duct piece can stably move left and right through cooperation of a guide rail pair sliding rail and a sliding base, a motor drives a winding roller to wind and unwind a steel wire rope, and the hanging design of a hook is combined; and vertical lifting of the duct piece is achieved.

The invention provides a tunnel support self-adaptive adjusting method and system based on rock mass-support feedback, and relates to the technical field of tunnel engineering support. The method comprises the following steps: acquiring surrounding rock strain data and stress data through a sensor network arranged in tunnel surrounding rock, and generating original monitoring data; calculating the surrounding rock strain energy density by using a data processing unit; matching the strain energy density with a preset energy stage feature through an adaptive control algorithm to generate an energy stage matching result; determining an energy state stage based on a stage confirmation module and generating an energy stage identifier; a supporting mode switching instruction is generated through a supporting mode mapping querier; and finally, the supporting control unit adjusts the working parameters of the supporting structure, real-time monitoring of the energy state of the surrounding rock and dynamic matching of the supporting parameters are achieved, the adaptability and safety of tunnel supporting are effectively improved, and the hysteresis of manual intervention is reduced.

The invention mainly relates to the technical field of tunnel engineering, and provides a tunnel surrounding rock grading dynamic correction method based on image texture features in order to improve the accuracy and real-time performance of surrounding rock grading under complex geological conditions. An improved deep residual network model integrated with an attention mechanism is input and introduced, the model improves the precision of single-point surrounding rock grade identification based on key textures, an initial prediction value of the surrounding rock grade is obtained, and meanwhile a time sequence prediction model is introduced; the whole excavation process is regarded as a continuous geological sequence based on the multi-source surrounding rock feature vectors of the current excavation cycle and at least one previous historical cycle, a time sequence trend value of the surrounding rock grade is obtained, a self-adaptive weight is set, the surrounding rock grade initial prediction value and the time sequence trend value of the surrounding rock grade are smoothed and corrected, and the surrounding rock grade is obtained. Therefore, the accuracy and the stability of the surrounding rock grading result are improved.

The invention discloses a tunnel dew formation and icing rapid monitoring method and system based on a space-time phase change cooperation mechanism, and relates to the technical field of tunnel engineering safety monitoring and freeze injury prevention and control. Establishing a tunnel geometric model and a heat-humidity-turbulence multi-field coupling physical model; synchronously acquiring heat and humidity physical property parameters and outdoor hourly meteorological parameters; taking the outdoor hourly meteorological parameters as Dirichlet boundary conditions and initial conditions of a heat-humidity-turbulence multi-field coupling physical model; determining a heat and humidity exchange coupling process of the tunnel wall surface and the internal environment, and defining heat and humidity transfer parameters under an unsteady state boundary; performing discretization processing on the tunnel geometric model by adopting a grid division strategy; by setting a dew point temperature threshold value and an icing temperature threshold value, a condensation risk area is judged, dynamic changes of the thickness of an ice layer are quantified, and monitoring of tunnel condensation and icing is achieved. The method can effectively reflect the distribution rule of multiple physical fields on the surface and in the tunnel in any time, accurately judge the risk area and quantify the thickness of the ice layer.

The invention relates to the technical field of tunnel engineering monitoring and construction, and discloses a shield construction tunnel full deformation prediction method based on artificial intelligence. The method comprises the following steps: acquiring a geological sensing data stream, a construction operation data stream and a historical deformation case library; performing multi-modal data fusion on the geological sensing data flow and the construction operation data flow to generate a construction environment map with consistent time and space; searching a case sequence matched with the current construction environment map from a historical deformation case library, performing feature significance evaluation through the case sequence, and identifying a dominant feature group of full deformation prediction; constructing an algorithm preferential engine based on the dominant feature group; activating an algorithm preferential engine to perform parallel processing on the construction environment map, and generating an adaptability measurement set of each algorithm; integrating the adaptability measurement set and real-time construction limiting conditions, and selecting an optimal prediction algorithm by adopting a trade-off decision-making mechanism; and generating a full deformation prediction model, and integrating the model to a shield construction monitoring platform.

The invention relates to the technical field of tunnel engineering building materials, in particular to a double-slurry synchronous grouting material based on shield silty-fine sand and a preparation method of the double-slurry synchronous grouting material based on shield silty-fine sand. The liquid A is prepared from, by weight, 20%-30% of cement, 30%-50% of shield silty-fine sand, 5%-10% of bentonite, 5%-15% of mineral admixture, 0.1%-0.5% of stabilizer and 20%-30% of water, and the stabilizer is a water-soluble high-molecular polymer; the solution B is a water glass solution, and the volume ratio of the solution A to the solution B is (10-15): 1; the double-slurry synchronous grouting material further comprises a retarder and a coagulant, the retarder is citric acid, and the coagulant is a nano Ca (OH) 2 crystal nucleus. Bidirectional and gradient regulation and control of the gelation time between 5s and 100s can be realized through the coagulant and the retarder, and diversified requirements of different geological conditions and construction progress on slurry operation time are met.

The invention discloses a karst stratum tunnel disaster sensing method and system based on multi-source information, and belongs to the technical field of tunnel engineering safety monitoring, and the method comprises the steps: building a monitoring index data set, converging the monitoring index data set to a cloud end, carrying out the time-space registration, and generating a multi-dimensional time sequence data field; calculating data uncertainty of each monitoring area by adopting an information entropy theory, calculating spatio-temporal evolution characteristics, and performing classifier identification by combining a deformation field space gradient to obtain a key monitoring area; adaptively adjusting the acquisition frequency of the sensor, and starting supplementary monitoring equipment for encrypted observation; performing space-time response calculation by adopting a machine learning algorithm to generate a tunnel disaster evolution prediction result; and carrying out grading threshold comparison and numerical simulation verification on the prediction result to realize effective identification and perception of the disaster evolution state. According to the method, the technical means of combining multi-source data fusion, the information entropy theory, machine learning and self-adaptive monitoring is adopted, and dynamic, accurate and predictive perception of the tunnel disaster evolution process can be achieved.

The invention provides a tunnel health monitoring method based on distributed optical fiber sensing, and relates to the technical field of tunnel engineering health monitoring, and the method comprises the steps: carrying out the risk assessment of a tunnel through employing an analytic hierarchy process, setting a differential optical fiber laying scheme according to an assessment result, and laying distributed optical fiber sensors on the inner surface of a tunnel lining; the method comprises the following steps: acquiring original strain data through Brillouin optical time domain analysis, and preprocessing by using a moving average filtering algorithm; building a finite element model based on actual physical data of the tunnel, inverting strain data into full-field node displacement, and obtaining a complete strain tensor of a finite element unit; performing unit-level strain state evaluation, time sequence trend risk evaluation and spatial clustering risk evaluation to obtain a comprehensive risk value; and setting a dynamic evaluation threshold interval, and completing tunnel accurate region health evaluation. Accurate monitoring and risk assessment of the tunnel health state are achieved, and the method can be widely applied to the field of safety monitoring of highway and railway tunnels.

The invention discloses a tunnel peripheral hole smooth blasting parameter intelligent optimization system and method, and relates to the technical field of blasting, and the system comprises a data management module, a factor identification module and a parameter optimization and scheduling module. Dynamic adjustment and scheduling optimization of the blasting parameters are achieved by collecting blasting data in real time, extracting key parameters, screening influence factors in combination with a factor recognition algorithm and constructing a parameter scheduling optimization model, and the system can effectively improve scientificity and accuracy of blasting design, so that efficient, accurate and self-adaptive optimization of the blasting parameters can be achieved; and the requirements of high quality and high efficiency of modern tunnel engineering construction are met.

The invention relates to the technical field of tunnel engineering prefabricated part production, in particular to a large-diameter duct piece independent kiln assembly line conveying prefabricating method and system. S2, a reinforcement cage and an embedded part are installed; s3, concrete is precisely poured and vibrated; s4, pre-curing and surface treatment; s5, carrying out roller way type flow conveying; s6, hydration heat-driven dynamic maintenance is carried out; and S7, demolding and finished product detection. And S8, mold circulation. According to the large-diameter duct piece prefabricating production line, through technical innovation in multiple aspects of mold, conveying, maintenance, control and the like, the core technical problem in existing large-diameter duct piece prefabricating production is solved, high-precision, high-efficiency, low-energy-consumption and green production of large-diameter duct pieces is achieved, and the large-diameter duct piece prefabricating production line has remarkable technical advantages and wide application prospects and is suitable for large-diameter duct piece prefabricating production. The method can be widely applied to infrastructure construction projects such as shield tunnels, open caisson projects and underground comprehensive pipe galleries.

The invention discloses a drilling, deslagging, charging and blocking integrated device, which belongs to the technical field of tunnel engineering and open-air engineering blasting equipment, and comprises a mobile vehicle body, a multi-link structure, a drilling and deslagging device, an explosive filling device and a stemming blocking device. The drilling and deslagging device is used for drilling and discharging drilling cuttings; and the explosive filling device independent track is arranged above the drilling machine beam track in parallel and is used for accurately conveying detonators and emulsion explosives into holes. After drilling is completed, the explosive filling device moves downwards in parallel to be aligned with the hole site for charging; after charging, the device moves upwards to drive the stemming plugging device to reach an orifice, and drilling cuttings discharged by drilling are directly used as stemming raw materials for automatic compaction and plugging. The problems that in the traditional blasting construction process, equipment is frequently switched, the manual operation efficiency is low, high-risk link manual operation needs to be conducted, and stemming raw materials need to be prepared independently are solved, automatic continuous operation of the whole process of drilling, charging and plugging is achieved, and the construction efficiency and intrinsic safety are remarkably improved.

The invention provides a safe alignment device for light-weight steel ring splicing equipment, and relates to the field of tunnel engineering, the safe alignment device comprises a first connecting plate, a second connecting plate and a third connecting plate, a second mounting interface is formed in one side, far away from the first connecting plate, of the second connecting plate; the middle connecting plate is arranged between the first connecting plate and the second connecting plate; the angle adjusting mechanism is installed between the first connecting plate and the middle connecting plate and used for driving the middle connecting plate to rotate around a first axis relative to the first connecting plate, and the first axis is perpendicular to the plate face of the first connecting plate; the flexible connecting mechanism is used for connecting the middle connecting plate and the second connecting plate, so that the second connecting plate can float relative to the middle connecting plate; and the locking mechanism is mounted on the middle connecting plate and has a locking state and an unlocking state. The device gives consideration to the carrying stability and the mounting alignment efficiency, and has the effect of improving the steel ring piece attaching quality and the construction safety.

The invention provides a tunnel lining surface crack detection method and system, and relates to the technical field of tunnel engineering, and the method comprises the steps: obtaining a lining surface image and a crack label of a detected tunnel, and a lining surface image of a to-be-detected tunnel; performing feature extraction on the lining surface image based on a visual cell mechanism to obtain perception feature maps of the detected tunnel and the to-be-detected tunnel; embedding mapping and contrast learning constraint are carried out through the perception feature map of the detected tunnel and the crack label, and a crack embedding space is obtained; mapping the perception feature map of the tunnel to be detected to the crack embedding space, and performing distribution alignment on the detected tunnel embedding features and the tunnel embedding features to be detected in the crack embedding space through a confrontation mechanism; and generating a lining surface crack detection result of the to-be-detected tunnel through the aligned crack embedding space. According to the method, the problem that cracks and non-cracks are difficult to stably distinguish due to inconsistent crack feature distribution in different tunnel scenes in an existing detection method is solved.