1658 results about "Soil horizon" patented technology

A soil layer detection drilling device includes a drilling cylinder, and a soil-sampling assembly is provided inside the drilling cylinder. When the soil is drilled, equipment is in a vertical state, a controller is turned on to control a rotary motor to rotate, and the drilling cylinder is driven to drill the soil with the cooperation of drive wheels and a drive belt. Four slide blocks are evenly distributed around an outer circumference of a sliding disk and are matingly connected with slide grooves provided on an inner wall of the drilling cylinder, so when the drilling cylinder rotates, the soil-sampling assembly also rotates. A conical head first in contact with the ground starts to drill the ground, then the drilling cylinder gradually drills into a soil layer, and the drilling cylinder is idled as the drilling cylinder arrives at a certain depth, to clear soil on auger blades.

The invention provides a geological exploration drilling device and method for geotechnical engineering design, and relates to the technical field of geological sampling, the geological exploration drilling device comprises a vehicle body, a propelling mechanism, a drill rod and a drill bit, the drill rod comprises a plurality of sampling barrels and locking assemblies arranged between every two adjacent sampling barrels, the drill bit comprises a drill barrel arranged at the bottom of the drill rod, a spacer bush arranged in the drill barrel and a plurality of cutting plates arranged on the side wall of the spacer bush at equal intervals in a sliding mode, the knocking assembly is arranged on the support, and the knocking assembly can strike the exterior of the drill rod in the process that the propelling mechanism drives the drill rod to vertically move. A soil core pressed into the drill rod can be cut off from an external soil layer, the bottom of the drill rod is sealed, it is prevented that in the upward moving process of the drill rod, the soil core slides off to affect soil sample collection, the drill rod can be assembled according to needs so that the soil core can be conveniently divided into multiple small sections, the soil core in the drill rod can be stably taken out, and the working efficiency is improved. The soil core is prevented from being taken out from a relatively long drill rod and fractured and crushed to influence subsequent detection.

The invention relates to the technical field of data processing, and discloses a method and a system for detecting a soil body around a pipeline based on a ground penetrating radar. The method comprises the following steps: performing generalized reflection coefficient modeling on soil layer distribution data to obtain reflection coefficient model data, and calculating the reflection coefficient model data through a Bayesian inversion framework to obtain soil dielectric characteristic data; performing feature parameter extraction on the dielectric feature data of the soil body to obtain feature vector data of the soil body, and performing anomaly identification on the feature vector data of the soil body to obtain data of an abnormal region of the soil body; and performing fuzzy hierarchy analysis on the soil body abnormal region data to obtain risk index data, and performing correlation analysis on the risk index data and the pipeline position feature data to obtain risk assessment data of the soil body around the pipeline. Based on the obtained quantification result of the dielectric parameters of the soil body, the accuracy of abnormal region identification is improved, and the accuracy of detection of the soil body around the pipeline by the ground penetrating radar is further improved.

The invention provides a geotechnical engineering earthquake sand liquefaction discrimination method and system, and relates to the technical field of geotechnical engineering, and the method comprises the steps: collecting site basic data (a site parameter table, earthquake acceleration and pore pressure time history data); establishing a preliminary numerical model and applying boundary conditions to correct the preliminary numerical model into a complete numerical model; the pore pressure ratio and the shear strain distribution are obtained through nonlinear dynamic analysis, and the liquefaction risk is comprehensively evaluated; a key soil layer observation scheme is made according to the prediction result, field verification is carried out, and a final judgment result is obtained by combining actual measurement and numerical simulation. According to the method, numerical analysis and actual measurement data are combined, the sand liquefaction risk is rapidly and accurately evaluated, and field testing and observation are guided.

The invention provides an automatic pavement settlement monitoring method and system based on a shield undercrossing airport runway. The dynamic database is constructed by collecting operation parameters such as shield tunneling machine propelling pressure, cutterhead torque and synchronous grouting pressure in real time and combining three-dimensional deformation data obtained through laser scanning. Strain sensing units are arranged in the soil layers to form a layered monitoring network, strain changes of the soil layers of different depths are collected, and spatial correlation is established between the strain changes and the tunneling position. And analyzing a spatial attenuation rule through a dynamic association processing unit, and generating a multi-dimensional feature data set. And establishing a settlement prediction model, fusing the shield dynamic load sequence and the layered strain conduction characteristics, and outputting settlement distribution information. And the system automatically compares the settlement difference value of the adjacent areas with a preset safety threshold value, and generates a graded early warning signal after verification of the three-dimensional deformation data space. According to the technical scheme provided by the invention, real-time three-dimensional prediction and spatial verification type graded early warning of settlement of the airport runway are realized.

The invention relates to the technical field of design analysis, in particular to a soft soil deep foundation pit earth excavation construction scheme planning method and system.The soft soil deep foundation pit earth excavation construction scheme planning method comprises the following steps that a three-dimensional geological model is built based on geological exploration data, and rheological parameters, shear strength parameters and permeability coefficients of all soil layers are extracted to serve as layering parameters; according to the layering parameters and preset supporting structure rigidity parameters, a soil body rheological rate compensation coefficient is calculated, and an earthwork block excavation scheme with the grading thickness difference is generated; and in the excavation process, the displacement rate and pore water pressure data of the supporting structure are collected in real time, and when a monitoring value exceeds a preset threshold value, a dynamic adjustment instruction of the block excavation scheme is triggered. According to the method, the layering thickness and the blocking form are intelligently controlled according to different sensitivity levels, the matching coping capacity for soft soil instability inducements is improved, and the limitation that a single physical parameter dominates in traditional blocking design is broken through.

The invention provides a method and system for predicting the uplift bearing capacity of a mud mixed pile. According to the method, modeling is carried out by integrating geomechanics and monitoring data. The method comprises the following steps: firstly, acquiring geometric parameters of a multi-layer heterogeneous soil layer interface, constructing a database through a mechanical test, and improving the reliability by combining gradient recognition and cooperative verification of pile deformation and load data; dividing longitudinal segmentation units, adjusting anti-slip parameters to generate a space mapping table, establishing a debonding dynamic model containing an interlayer retardation effect, simulating a debonding expansion process, and outputting load evolution data. And judging the maximum load of the critical state based on data convergence analysis, and taking the maximum load as a predicted value of the uplift bearing capacity. According to the technical scheme, through dynamic parameter mapping and debonding process simulation, accurate prediction of the uplift bearing capacity of the pile foundation in a complex soil layer is achieved, and the defect that a traditional model is insufficient in characterization of interlayer heterogeneity and dynamic debonding behaviors is overcome.

The invention discloses a method for predicting shield tunneling parameters under a composite stratum, which comprises the following steps of: collecting and sorting shield tunneling historical data under the composite stratum, including geological parameters and construction parameters, and performing abnormal value elimination, missing value filling and data standardization; the geological parameters and the geometric parameters are combined according to the tunneling ring number, and a quantitative geological matrix of each ring is generated; the geometric parameters represent the position of the soil layer relative to the tunnel excavation face by adopting 1-5 codes, and input dimension unification is ensured through zero filling alignment; a CNN-Attention-SVR model is constructed, and the CNN-Attention-SVR model is trained; new geological data are input into the trained model, tunneling parameters are predicted, and construction adjustment is guided; reliable technical support and decision basis are provided for tunnel construction under the composite stratum condition, and therefore the overall safety and economical efficiency of shield construction are improved.

The invention relates to the technical field of civil engineering, in particular to a karst development area cast-in-situ bored pile construction method which comprises the following steps: based on construction position information, collecting electromagnetic wave data of a target area at multiple angles and depths, and recording rock layer, karst cave and crack data to obtain geological data of the target area. According to the method, a data basis is provided for geological three-dimensional model construction by utilizing electromagnetic wave data and identifying a rock layer, a karst cave and a crack, the prediction precision of the model is improved by simulating the response of karst, a fault and a soft soil layer to a structure, and the prediction accuracy of the model is improved by combining the evaluation of chemical erosion and physical erosion effects of a target karst development area on the cast-in-place pile. The long-term influence of the environment on the pouring material is predicted, the stability and safety of the structure are improved, the long-term sustainability of a target engineering project under the karst complex geological condition is ensured, and the scientificity and efficiency of construction planning are improved by combining drilling position analysis and construction path planning.

The invention discloses a scouring pile foundation reinforcement method based on an MICP curing technology, which comprises the following steps: acquiring initial environment information such as scouring pit parameters, water flow parameters, tide period and seawater salinity of a delimited area around a pile, and determining grouting parameters such as a grouting window period and a safe flow velocity threshold value and a matching numerical value of a bacterial liquid concentration, a urea concentration and a calcium ion concentration; a grouting assembly composed of a first grouting pipe and a second grouting pipe which are spliced up and down is arranged, and grouting holes are formed in the side wall of the second grouting pipe which is pre-buried in a soil layer; after MICP slurry is prepared according to blending parameters, the slurry is injected into a soil layer in combination with grouting parameters, and meanwhile, the grouting process is dynamically adjusted by monitoring the resistivity of a soil body in real time; and after grouting is completed, the assembly is dismantled, and supplementary grouting is conducted on the local area according to the detection result. According to the method, the accuracy and reliability of pile foundation reinforcement are achieved through environmental parameter adaptation, grout dynamic regulation and control and layered detection and reinjection.

The invention relates to the technical field of intelligent construction. The invention provides a rainwater garden construction control method and system based on BIM dynamic rainfall flood simulation. The method comprises the following steps: integrating target area data and real-time weather forecast, and constructing a fusion model; importing the fusion model into a coupling engine, simulating an extreme rainfall scene, and generating a dynamic hydrological load map; according to the dynamic hydrological load map, reverse iterative calculation is carried out, and a three-dimensional parameterized design model is output; decomposing the three-dimensional parameterized design model into a layered construction instruction set, and constructing a real-time twinborn body on a BIM platform; field data are collected and compared with real-time twinborn bodies, and when the soil layer permeability coefficient deviation is larger than a preset threshold value or the process conflict risk, a re-optimization instruction is triggered, and the mechanical operation sequence is adjusted. The problems that due to the fact that existing rainwater garden static design and experience construction cannot dynamically respond to the complex hydrological environment and construction disturbance, facility efficiency is low, failure is prone to occurring, and the construction rework rate is high are solved.

The invention discloses a shield tunneling machine or TBM hob associated characteristic abrasion analysis method and system, and belongs to the technical field of associated characteristic analys.The method comprises the steps that parameter data related to cutter abrasion are collected in real time, and a parameter time sequence is constructed; calculating a change curve of the statistical characteristics, the derivative characteristics and the rock-soil layer, and updating a parameter sequential sequence; analyzing a dynamic change condition of a parameter time sequence, calculating a feature importance score by using a random forest algorithm, avoiding interference by unimportant information in an analysis process, and constructing an associated feature model; according to the method, three-dimensional point cloud data of a rock-soil layer is constructed, fused point cloud data containing a tool wear label is generated, rich dimension data is provided, a point cloud model used for judging the state of the tool is constructed, the risk of misjudgment and missed judgment is reduced, and the state of the tool is judged; once it is judged that the cutter is damaged, a cutter damage signal is generated, and a powerful guarantee is provided for safe and efficient operation of the shield tunneling machine or the TBM.

The invention belongs to the technical field of construction control, and particularly discloses a dry-method precise positioning construction control system and method based on machine learning. Multi-dimensional data such as drilling resistance, vibration frequency, shovel head angle deviation, position and soil layer hardness are acquired in real time through a multi-source data acquisition module; the deviation calculation module carries out dynamic comparison analysis based on data corresponding to a preset sampling area, the dynamic adjustment module dynamically optimizes the drilling speed and angle through a multi-condition triggering mechanism and a transfer adjustment rule, and finally the control execution module generates a precise control instruction to drive the Luoyang shovel to execute deviation correction action. Through multi-dimensional data fusion analysis and a real-time dynamic adjustment strategy, the path precision and the stratum adaptability of the drilling operation are remarkably improved, meanwhile, the adaptability of equipment to stratum sudden change is improved, the construction risk under the complex geological condition is reduced, and collaborative optimization of the drilling efficiency and the operation safety is achieved.

The invention relates to the technical field of road settlement monitoring and early warning, in particular to a road settlement monitoring analysis and early warning system based on artificial intelligence. Comprising a monitoring area division module, an influence factor monitoring analysis module, a road state monitoring analysis module, a soil layer state monitoring analysis module, a settlement area identification module, a settlement degree analysis module, an early warning execution module and a display terminal. Through cooperative work of a plurality of modules such as monitoring area division, influence factor analysis, road state and soil layer state monitoring and the like, a potential settlement risk area can be found and identified in time, and corresponding early warning and execution instructions are automatically triggered according to different settlement degrees, so that the settlement risk is effectively improved. Therefore, the traffic of vehicles is limited, the ground load is reduced, and time is won for first-aid repair and reinforcement work, so that the safety of roads and infrastructures is effectively protected, and the smoothness and safety of urban traffic are improved.

The embodiment of the invention provides a water conservancy project intelligent processing system based on BIM and GIS. The water conservancy project intelligent processing system comprises the steps that material strength and construction timestamps of engineering components are extracted through a BIM parser to generate a topological relation graph; combining the remote sensing image and the geological data through a coordinate converter to determine a three-dimensional terrain field; establishing a spatial Hash grid correlation topological relation graph and a three-dimensional terrain field; constructing a digital twinborn body containing structural stress distribution and a hydrodynamic model on the basis of a correlation result; executing Monte Carlo simulation in the digital twin according to the real-time sensor data to generate a prediction scene set; when abnormal data is monitored, performing reverse tracing along the topological relation graph to generate a multi-factor association graph; and optimizing a disposal plan weight coefficient through a reinforcement learning algorithm and updating the knowledge base. Pixel-level matching of the rock-soil layer permeability coefficient and the concrete member strength is achieved, the system can recognize the coupling relation between a geological weak area and a structural high-risk point, meanwhile, a knowledge graph containing a construction time sequence is constructed, and a cause chain of quality defects can be traced.

The invention provides a geological data driving path optimization and settlement prediction method for pipe jacking construction, and relates to the technical field of artificial intelligence. The method comprises the following steps: firstly, acquiring sparse drilling point location geological data, constructing a geological data set including soil layer types, forming continuous geological feature tensors through multi-dimensional interpolation, and generating a path vector sequence by combining starting and ending points and building distribution to represent crossing tracks of different paths under geological conditions; and constructing a path graph topological structure through a graph coding neural network, performing feature propagation, obtaining a path comprehensive score vector, and screening an optimal path meeting structural integrity and settlement response constraints. Further identifying settlement trend sensitive points by utilizing the settlement risk prediction values and the accessibility scores of the nodes, constructing a settlement trend map and calculating settlement transaction coefficients. And the transaction coefficient is fed back to a path generation link and is used for iteratively optimizing path sampling density and node distribution so as to realize dynamic correction and stable convergence of a path scheme.

The invention provides a computer-aided slide-resistant pile and anchor cable build-in depth design method, and relates to the technical field of slide-resistant pile and anchor cable design, and the method comprises the following steps: collecting drilling data of an engineering site, and establishing a three-dimensional geologic model containing spatial distribution of each soil layer; determining a feasible range of design parameters; according to the soil layer space distribution and parameters, a slope stability analysis model considering the supporting effect of the slide-resistant piles and the anchor cables is established and used for calculating the slope stability safety coefficient under the given design parameters; and taking the minimum construction cost as a target function, determining an optimization constraint condition according to the slope stability analysis model, carrying out iterative optimization on the design parameters in a feasible range by adopting an optimization algorithm until an optimization convergence condition is met, and outputting an optimal design parameter. The problems that a traditional design method excessively depends on experience, multiple influence factors are difficult to consider, and the calculation efficiency is low can be solved, and the design level of the built-in depth of the slide-resistant pile and the anchor cable is improved.

The invention discloses a shield tunneling machine cutterhead abrasion monitoring and analyzing method and system in tunneling, and mainly relates to the technical field of shield tunneling machine engineering. Comprising the following steps: interactively arranging monitoring sensor arrays on the surface of a shield tunneling machine cutterhead and a cutter, extracting monitoring data of a preset monitoring window, and obtaining a monitoring data array sequence; obtaining a cutterhead operation feature set; working soil layer state characteristics are obtained; acquiring a tool surface acquisition image; and performing tool edge comparison on the tool standard image and the tool surface acquisition image to obtain a tool comparison result, and taking the tool comparison result as a cutterhead wear analysis result. The method has the beneficial effects that the technical problems that in the prior art, when the abrasion state of the tunneling shield tunneling machine cutterhead is analyzed, the mastering degree of the cutterhead stability condition implied in the monitoring data is low, and the monitoring and analysis reliability is poor are solved, and the technical effect of improving the abrasion monitoring and analysis accuracy of the shield tunneling machine cutterhead is achieved.

The invention discloses a three-dimensional crustal stress field visualization construction method under a complex geological structure condition, and relates to the technical field of crustal stress field analysis. Comprising the following steps: in a to-be-analyzed area, obtaining characteristic data such as density and Poisson ratio of a surface rock-soil layer, a sedimentary layer, a parent material layer and a bedrock layer through well drilling; applying seismic waves, acquiring longitudinal wave and transverse wave speeds of each rock-soil layer by using a geophone, and calculating a shear modulus and a bulk modulus; and establishing a finite element model to analyze the strain tensor under the load, and calculating the stress tensor in combination with the modulus. Calculating pore water pressure, and correcting the stress tensor to obtain effective stress. Fault feature information is obtained through a geological report, and the stress tensor is further corrected to obtain accurate and effective stress. And constructing a three-dimensional geologic model and dividing grids, mapping accurate and effective stress to each grid unit, and completing visual construction of the crustal stress field by utilizing visual software. Safety and economic benefits are effectively improved, and risks caused by geological factors are reduced.

The invention relates to the technical field of soil layer drilling, in particular to an efficient underground water quality detection sampling device which comprises a base, a fixing seat is further arranged on the base, and a device storage structure and a sample storage structure are arranged on the left side and the right side of the fixing seat respectively; a supporting structure is further arranged in the middle of the fixing base and comprises a vertical plate, a transverse plate, an axial motor, a mounting base, a lead screw, a guide rod and a drill rod. The drill rod is connected with the mounting seat through a rotating piece; the drill rod comprises a drill bit, a rod body, a sampling water pump and a sampling pipe; a sampling hole is further formed in the drill bit, and a liquid collecting cavity which is coaxially distributed is formed in the center in the rod body; a first cavity and a second cavity which are distributed from inside to outside are further formed in the rod body and located on the outer side of the liquid collecting cavity, and the sampling hole extends inwards, penetrates through the first cavity and the second cavity and is communicated with the liquid collecting cavity. The device is reasonable in structural design, filtering, collecting, sampling and storing operation of underground water at different heights can be completed on the basis that efficient drilling of underground water soil layers at different depth positions is achieved, and the using effect is good.

The invention discloses an automatic identification method for a popular shallow soil landslide disaster risk area. The method comprises a landslide risk area identification method and an intra-area landslide threat house identification method. The method comprises the following steps: firstly, acquiring terrain, soil layer structure, vegetation and rock-soil distribution information of a region through a remote sensing technology, and performing data acquisition and processing by adopting remote sensing images, infrared images, laser radar data and synthetic aperture radar data to generate a high-precision digital elevation model and a geologic structure map; through data fusion and analysis, in combination with information such as soil layers, terrains and vegetation, a potential landslide risk area is identified, and houses in the landslide risk area are identified and evaluated. According to the method, the identification precision of the landslide risk area and the threatened house is improved, and efficient and accurate technical support is provided for early warning and prevention of landslide disasters. The system has the advantages of automation, high efficiency and accuracy, and can be widely applied to real-time monitoring, risk assessment and emergency management of landslide disasters.

The invention relates to the technical field of drilling of soil layers or rocks, and particularly discloses a rotating speed-temperature-abrasion shield cutter intelligent sensing method. Comprising the steps of micro-synchronous acquisition, coupling feature extraction, physical modeling and synthesis, multi-scale thermal anomaly separation, physical constraint neural network prediction, time sequence evolution prediction, dynamic threshold risk decision, adaptive sampling scheduling and online increment calibration. According to the method, the early warning threshold value is dynamically adjusted based on prediction error distribution, flexible switching among different reliability requirements can be achieved, and the problem of early warning or missing report is avoided. Meanwhile, the sensing sampling frequency and the early warning level are linked, the data resolution can be automatically improved in the high-risk stage, calculation and transmission resources are saved in the low-risk stage, and efficient utilization of the computing power and the bandwidth by the monitoring system is achieved; therefore, distribution drifting caused by geological condition changes and cutter updating can be coped, the effective service life of the model can be prolonged, and shutdown maintenance is almost not needed.

The invention discloses a sponge city high-terrain rainwater management method and system, particularly relates to the technical field of rainwater prediction management, and is used for solving the problem of poor high-terrain rainwater prediction management scheduling. For a high terrain small watershed, data such as elevation, permeability coefficient, soil layer thickness and vegetation coverage are collected and preprocessed, a continuous physical field is generated, a facility pipe network is mapped, and then grid units are divided; a multivariate predictor is constructed based on grid cell center attributes, edge node increment fine adjustment is issued after cloud training, and a model is optimized through scene matching and federal learning; after rainstorm, automatically extracting observation and prediction residual increment to train a neural network and generating a confidence interval; and the edge nodes divide risks according to the confidence interval, the flood control water depth and the minimum infiltration threshold value and output gate opening and pump set power suggestions, so that the high-terrain small-watershed extreme rainstorm peak prediction precision and response time efficiency are remarkably improved, and refined risk perception scheduling and rainwater resource utilization are realized.

The invention discloses a cast-in-situ bored pile digital construction control method which comprises the following steps: S1, collecting historical data, and establishing a cast-in-situ bored pile construction information database; s2, geological modeling is established, and a pile hole area three-dimensional stratum and soil layer distribution corresponding to all pile holes are generated in a fitting mode; s3, according to the cast-in-situ bored pile construction information database, finding out average construction efficiency and cost data under various hole forming processes of similar stratums in various stratums of a pile hole area, and calculating the construction period and cost of different hole forming processes of a single pile for construction management personnel to select the hole forming processes and equipment specifications; s4, monitoring early warning and auxiliary decision making in construction; and S5, post evaluation analysis. According to the system and the method, key construction parameters of the bored pile are automatically monitored by relying on core construction equipment and devices, the production dynamic state of the bored pile is visually displayed through online monitoring and early warning of the key parameters by the system and the platform, a friendly interactive interface is provided for operators, and construction parameter selection is assisted.

The invention belongs to the field of soil rock engineering, and provides a three-surface integrated geologic structure modeling method for a deep and large foundation pit in a river-adjacent region, which comprises the following steps: acquiring physical and mechanical parameters and hydrogeological information of the deep and large foundation pit in the river-adjacent region; dividing spatial distribution of different soil layers and rock stratums; describing the influence of water level time variation on the pore water pressure and subsurface erosion of the surrounding rock of the foundation pit through an unstable seepage equation; dividing a finite element or finite difference grid, and applying a dynamic water level and ground load boundary condition; gradually unloading and analyzing the evolution of an underground water flow field and a soil-rock deformation field in each excavation step, and enabling the water surface-ground-soil-rock surface coupling effect to penetrate through the whole excavation process; and numbering the support members, sequentially simulating local failures of the support members, recording the maximum horizontal displacement, the maximum vertical displacement or the change curve of the safety coefficient along with the number of the failure members after each failure of the foundation pit, quantifying the redundancy of the support system, and identifying key members. According to the scheme, the accuracy of the model is improved.

The invention discloses a shield tunneling machine tunneling key parameter real-time multi-step prediction method based on ST-GCN-LSTM, and the method comprises the following steps: obtaining the operation data of a shield tunneling machine under a normal working condition, and carrying out the preprocessing of the operation data; analyzing the preprocessed operation data, and determining related variables of total thrust, cutterhead torque, cutterhead rotating speed, penetration and propelling speed average value tunneling key variables; respectively calculating the control limit of each tunneling key variable for different soil layers, and training a multi-step prediction model based on an ST-GCN and LSTM combined model; acquiring operation data of the shield tunneling machine in real time, inputting the operation data into the trained model for preprocessing, dynamically predicting tunneling key parameter values of multiple steps in the future, and judging whether predicted values continuously exceed a control limit or not; according to the method, real-time multi-step prediction of the tunneling key parameters can be carried out in combination with soil layer classification, and prediction inaccuracy caused by changes of external factors such as soil layers is reduced.

The invention provides a mine water prevention and control risk early warning method and system based on earthquake and geology fusion, and belongs to the field of soil layer or rock drilling, the method comprises the steps that real-time earthquake data of an earthquake monitoring module and geological exploration data of a geological exploration module are received, and the geological exploration module comprises a drilling detection module and a hydrogeological analysis module; based on the real-time seismic data, the geological exploration data and a preset water prevention and control risk early warning model, obtaining a risk level including a risk level and a corresponding water prevention and control execution measure; triggering target execution equipment such as drilling equipment to perform prevention and treatment according to execution measures; drilling a monitoring hole and arranging an optical fiber osmometer to collect osmotic pressure data at a first risk grade; at the second risk level, grouting plugging is conducted on the crack drilling grouting holes; constructing a water guide hole in the aquifer at the third risk level, and guiding underground water to a safe area through a drainage pump group. According to the method, multi-source data are fused to realize graded accurate early warning and prevention.

The invention discloses an automatic deviation rectifying method for long-distance jacking of a pipe-jacking tunneling roadway, and relates to the technical field of automatic deviation rectifying of pipe tunneling, which comprises the following steps: collecting the compactness, water content and hardness data of a soil layer in a tunneling path in real time through a multi-point distributed sensing device, and calculating the deviation of the pipe-jacking tunneling roadway in combination with soil parameters and pipe-jacking equipment propulsion mechanical characteristics; and generating a geological condition profile map, constructing a resistance distribution model, predicting resistance change trends under different geological conditions, and establishing a correction early warning mechanism. According to the invention, through real-time stress monitoring, multi-point sensing and intelligent feedback control, the accuracy, efficiency and complex geology adaptability of pipe-jacking tunneling are improved. The equipment can quickly identify resistance abnormity, dynamically regulate and control propulsion in real time, reduce the influence of asymmetric force, and reduce personal error and construction loss. And in combination with a geological profile map, the equipment actively deals with soil layer changes through automatic deviation correction, the clamping stagnation problem is solved, safety and continuity are guaranteed, and risks and cost are reduced.

The invention relates to the field of intelligent irrigation, and discloses an intelligent irrigation system and method for a crop root system, and the system comprises a root zone sensing module which is used for collecting soil environment parameters through multi-mode soil sensor arrays disposed at soil layers of different depths, generating a sensing matrix, and transmitting the sensing matrix to a root zone sensing module; the sensing matrix is used for representing water potential, pH value, nutrient concentration and temperature information in each soil layer; and the root system density analysis module is connected with the root zone sensing module, and is used for constructing a root system density weight matrix based on root system space distribution information obtained by underground computed tomography, and multiplying the sensing matrix by the root system density weight matrix element by element to generate a root zone state vector. Accurate generation of regulation and control signals is achieved, the micro-fluidic execution module can adjust the irrigation flow and the fertilization proportion in real time according to the actual requirements of the root zone, and therefore it is guaranteed that the rhizosphere environment is always close to the optimal physiological interval.

The invention belongs to the technical field of geotechnical engineering testing and site investigation, and provides a shear wave velocity estimation method based on a piezocone penetration test, which can accurately and conveniently estimate the shear wave velocity. The method specifically comprises the following steps of S1, carrying out a pore pressure static sounding test on a plurality of drill holes in a site, and obtaining pore pressure static sounding basic parameters and shear wave velocity of each drill hole tested in the depth direction, S2, interpreting derived parameters according to the pore pressure static sounding basic parameters, S3, carrying out soil layer division, soil type identification and soil body type judgment, and S4, carrying out soil layer classification, soil type identification and soil body type judgment. S4, selecting data tested by the same soil body type as an analysis object, performing fitting analysis on the scatter diagrams of the cone tip resistance and the shear wave velocity of the piezocone penetration test to obtain a fitting formula, and S5, obtaining normalized cone tip resistance and normalized shear wave velocity based on the cone tip resistance and the shear wave velocity, substituting the normalized cone tip resistance and the normalized shear wave velocity into the fitting formula in the step S4, and introducing a soil classification index to obtain a soil classification result. And obtaining a calculation expression of the optimal estimation shear wave.