1156 results about "Soil horizon" patented technology

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 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 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 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.

The invention discloses an intelligent adjusting system and method for soil layer penetrating power of a shield tunneling machine. The intelligent adjusting system comprises a sensor array, wherein the sensor array is annularly and uniformly distributed around a cutter head of the shield tunneling machine; the risk level module is used for calculating a similarity matrix between section rings by adopting a Gaussian kernel function, dividing performance communities through a Louvain algorithm and outputting geological risk levels and corresponding coordinates; and the intelligent decision module integrates a multilayer convolutional neural network, fuses sensing data and a network analysis result in real time, and generates dynamic instructions of the cutterhead rotating speed, the propelling speed and the grouting pressure. The shield tunneling machine soil layer penetrating power intelligent adjusting system achieves real-time monitoring and intelligent analysis of multi-dimensional information such as soil layer hardness, pore water pressure, ground stress and temperature by integrating a high-precision multi-dimensional sensing module, a risk level module and an intelligent decision module. The system can automatically adjust the cutterhead rotating speed, the propelling speed and the grouting pressure of the shield tunneling machine according to the geological risk grade.

The invention discloses a ground subsidence monitoring system under the condition of ultra-large water level drawdown, and relates to the technical field of foundation pit dewatering, a seepage field change analysis module arranged on the system can analyze the movement process of underground water in a soil body of a foundation pit wall according to water body state data monitored in real time and in combination with the saturation state and permeability of the soil body, and the seepage field change analysis module can analyze the movement process of underground water in the soil body of the foundation pit wall through the module. The system can automatically perform hierarchical division on the soil body in the foundation pit wall, obtain the spatial and temporal distribution of the water head of each soil layer in the precipitation process, make the subsequent stress analysis and settlement evaluation more accurate, and accurately calculate the effective stress change of the soil body in the precipitation process based on the spatial and temporal distribution of the water head of each soil layer. And the additional stress influence of the settlement of the upper layer soil layer on the lower layer soil layer is analyzed, so that the settlement volume of each layer of soil body is obtained, and the stress and settlement monitoring based on stratified analysis enables the system to carry out detailed evaluation on differential settlement and interlayer stress change, so that the risk of structural instability caused by settlement difference is effectively prevented.

The present invention relates to a deep cement mixing pile construction parameter optimization method and system, a device and a medium. The method comprises: according to survey information of a construction area, determining in the construction area soil layer information corresponding to different depth segments, the soil layer information comprising soil layer types and soil layer parameters corresponding to the soil layer types; presetting an age and, for each soil layer type, presetting multiple groups of construction parameters corresponding to the soil layer type, and separately combining into input information each group of construction parameters, the set age, the soil layer type and the soil layer parameters corresponding to the soil layer type; inputting each group of input information into a constructed pile quality prediction model, so as to obtain pile quality corresponding to each group of input information, and denoting as target construction parameters the construction parameters in the input information having the pile quality satisfying a design requirement; and combining the target construction parameters of different soil layer types with each other, so as to obtain a plurality of construction parameter combinations of a mixing pile, the construction parameters in the construction parameter combinations corresponding to different soil layer types.

The invention relates to a composite foundation settlement calculation method considering karst rock-soil interface grouting, which is characterized in that n layers of covering layers are arranged on a limestone karst area, the thicknesses of soil layers are respectively h1, h2,..., hn, the compression moduli of the corresponding soil layers are respectively Es1, Es2,..., Esn, the pile length of a composite foundation reinforcing pile is L, and the m layer is reinforced; the distance between the bottom face of the reinforcing pile group and the bottom face of each soil layer is Zm, Zm + 1,... and Zn, after karst grouting is considered, the compression modulus increasing coefficients of the soil layers above the bedrock face are lambda1, lambda2,... and lambdan, the lambdan is larger than or equal to 1.0, and the total settlement of the composite foundation is the product of the sum of the settlement S1 of the reinforcing area and the settlement S2 of the underlying layer and the settlement experience correction coefficient ms. According to the method, a composite foundation settlement calculation formula is improved, the soil layer compression modulus improvement coefficient lambda is introduced into the settlement calculation process, the synergistic effect of karst grouting and composite foundation reinforcement is comprehensively considered, and the settlement calculation precision of the high-speed rail karst roadbed composite foundation is remarkably improved.

The invention relates to the field of safety supervision, and particularly discloses a deep foundation pit construction quality safety supervision system and method. Firstly, a pithead image, collected by a camera, of a deep foundation pit construction site, deep foundation pit side wall soil layer inclination displacement measurement text data collected by an inclinometer and underground water level values, collected by an underground water level monitoring device, at a plurality of preset time points are obtained, then feature extraction and correlation analysis are conducted on the three parts through the deep learning technology, and the deep foundation pit side wall soil layer inclination displacement measurement text data and the underground water level values are obtained. And finally, a classification result is obtained through a classifier to judge whether a deep foundation pit construction quality safety early warning is sent out or not, so that potential safety hazards are found in time, early warning is carried out in advance, and smooth proceeding and safety of engineering construction are guaranteed.

The invention discloses a standard soil layer sequence division method for foundation soil. The method comprises the following steps: generating a unified engineering geologic feature data set; forming a multi-dimensional engineering geologic feature sample set; obtaining parameters of the trained improved ultra-dense connection neural network model; obtaining an initial drilling sequence prediction result; encoding the initial drilling sequence prediction result into a drilling sequence embedding vector according to a drilling sequence, and generating a cross-drilling sequence alignment matrix; and generating a standard soil layer code and corresponding confidence information to obtain a standard sequence division result. According to the invention, full-process automatic integration of design, modeling and construction is supported, and consistency, rechecking performance and digital management capability in engineering application are improved.

The invention discloses a sampling device for engineering geological exploration, and relates to the technical field of engineering geological sampling, the sampling device comprises a bearing frame, a mounting frame arranged on the bearing frame, and a sampling unit arranged on the mounting frame, and the sampling unit is used for sampling and collecting geological soil of different depths. A lifting mechanism matched with the sampling unit is arranged on the mounting frame, the lifting mechanism is used for accurately adjusting the depth during sampling operation, and an adjusting mechanism is arranged on the bearing frame and is used for adjusting the position of the mounting frame; by arranging the sampling unit, the soil layer can be rapidly drilled, the drilling efficiency is improved, the geological exploration time is saved, after the preset depth is reached, an operator adjusts the closed state of the soil sampling disc, the sampling drill bit continues to rotate, soil is guided to enter the interior to be stored, and geological soil sampling at different depths is achieved.

The invention provides a method and device for predicting the pile-forming strength of a high-pressure jet grouting pile, and relates to the technical field of pile-forming strength prediction.The method comprises the steps that construction parameters are collected in real time through a multi-source sensor, a construction parameter matrix is constructed, and the soil layer boundary depth and the dielectric constant are obtained through geological radar scanning so as to distribute static weight factors; and calculating an intensity correction coefficient based on geological parameters of the core sample, finally establishing an intensity prediction model fusing the dynamic weight, the slurry solidification time, the temperature influence factor and the geological correction coefficient, and setting a three-level early warning mechanism. The core innovation of the scheme is that construction parameters and geological characteristics are dynamically coupled, the model precision is remarkably improved through double calibration of geological radar and core data, and the problem that a traditional method is insufficient in adaptability to soil layer difference is solved through introduction of a geological correction coefficient; and the real-time closed-loop optimization of the construction process is realized through the multi-sensor time synchronization application.

The invention discloses a testing device and a testing method for a permeability coefficient characteristic curve of wicking geotextile, and belongs to the technical field of permeability coefficient testing. A to-be-tested wicking geotextile and a soil layer are laid between an upper plate body and a lower plate body of a test unit of the test device; the two sealing covers are located at the two ends of the upper plate body and the two ends of the lower plate body respectively. Each of the first hollow column and the second hollow column comprises a hollow column section positioned above the upper plate body and below the lower plate body, the hollow column sections distributed up and down are communicated with a gap between the upper plate body and the lower plate body, and each hollow column section is filled with a soil body and forms a test soil column; the load output end of the load applying unit is used for applying a vertical load to the top of the test soil column and the upper plate body. The test device disclosed by the invention can really simulate the occurrence condition of the wicking geotechnical cloth in the roadbed engineering; the testing method based on the testing device can rapidly test the permeability coefficient of the wicking geotextile, and a characteristic curve of the permeability coefficient of the wicking geotextile is obtained.