8109results about "Foundation testing" patented technology

The present invention relates to an automatic speed regulation and grouting regulation system for construction of a deep mixing pile in a reclamation area, the main steps comprising: first, configuring and installing a multi-modal sensing system (S101) to monitor key parameters, torque, energy consumption, grouting pressure and stratum permeability of a construction site in real time; constructing a data acquisition and fusion module (S102), integrating multi-sensor data, and forming real-time mapping of stratum-construction parameters; establishing a relation model of formation input and formation response through an extended Kalman filter (EKF) and predictive control (MPC) algorithm (S103), and intelligently evaluating formation compactness and grouting quality; on the basis of a feedback closed-loop regulation and control system (S104), the stirring speed, the grouting amount and the construction pressure are adaptively adjusted in real time, and precise control is achieved; through construction data storage and self-learning optimization (S105), the system records all construction data, and through a deep reinforcement learning optimization control algorithm, the long-term construction precision is improved.

The invention relates to the technical field of foundation pit detection, and discloses a foundation pit deformation real-time monitoring method, device and system based on a BIM technology. The method comprises the steps of sensor layout and data acquisition, data transmission and preprocessing, nonlinear dynamic model construction, data fusion and optimization, foundation pit deformation prediction, BIM visual presentation and data display, intelligent support optimization and construction scheme adjustment. The device comprises a sensor assembly, a data acquisition interface, a 5G communication module, a central processing unit, a fusion and prediction unit, a man-machine interaction interface and an execution mechanism interface. The system comprises a data acquisition module, a data transmission module, a data processing module, a deformation modeling module, a data fusion module, a deformation prediction module, a visualization module and an intelligent regulation and control module. By adopting the multi-type sensor fusion and data assimilation technology, the high-precision and low-error foundation pit deformation monitoring effect is achieved, the monitoring data is more stable, and the monitoring precision is ensured to meet the engineering safety management requirement.

The invention relates to the technical field of engineering safety monitoring, in particular to a foundation pit deformation intelligent early warning system based on multi-modal fusion and a method thereof.According to the system, quality evaluation and weighting processing are conducted on multi-modal sensor data through a self-adaptive weight dynamic distribution module, and the data credibility is ensured; the multi-modal feature cross extraction module extracts and interacts features by using a specific sub-network and a multi-head attention mechanism, integrates information through a space-time diagram convolutional network, and generates accurate fusion feature representation; the multi-granularity abnormal mode identification module is combined with a mixed density network and time sequence analysis to accurately identify deformation anomalies; the causal reasoning and weight feedback module analyzes deformation reasons through a causal graph model and provides feedback for sensor weight adjustment; according to the system, the precision and reliability of deformation detection are remarkably improved, the detection precision is improved to the millimeter level, the accuracy is improved by 40%, and powerful technical support is provided for engineering safety monitoring.

The invention relates to the technical field of pile foundation engineering, in particular to a construction method of a long-pile wharf pile foundation lateral displacement prediction model. The method comprises the following steps that displacement, stress and load parameter monitoring is conducted on a pile foundation of the high-pile wharf, and real-time monitoring parameter data is generated; performing working condition identification on the pile foundation structure through the real-time monitoring parameter data to generate working condition data of the pile foundation structure; multi-source load characteristic analysis is conducted on the pile foundation structure working condition data, load coupling effect calculation is conducted, and load action data are generated; performing soil-pile interaction analysis according to the load action data to generate soil-pile response data; and performing material performance deterioration evaluation according to the soil-pile response data to generate material state data. The working condition identification method based on the multi-source monitoring data is established, comprehensive perception of the pile foundation structure state is achieved, and a reliable data basis is provided for subsequent displacement prediction.

The invention relates to the field of civil engineering construction safety monitoring, and discloses an open caisson construction soil gushing dynamic early warning system based on multi-parameter fusion, which comprises a sensor array module, a data processing module, a dynamic parameter correlation analysis module, a self-adaptive covariance optimization module, a risk index generation module and an early warning output module, collecting data in real time through a multi-source sensor and generating a parameter vector; the dynamic parameter correlation analysis module updates the dynamic matrix on line and represents real-time correlation among soil pressure, displacement and water level; the adaptive covariance optimization module dynamically adjusts a covariance matrix and suppresses noise interference; the risk index generation module fuses the dynamic matrix, the covariance inverse matrix and the parameter vector calculation weight, and corrects the risk index in combination with the vibration state of the construction machinery; and the early warning output module triggers grading alarm and feeds back to form a closed loop optimization link. According to the invention, real-time accurate early warning and self-adaptive prevention and control of the soil gushing risk are realized.

Disclosed in the present invention is a foundation pit safety early-warning method based on multi-source monitoring data fusion. The method comprises: first constructing a foundation pit safety evaluation indicator system, and acquiring cumulative values and change rates of multi-source time-series monitoring indicators; then determining a foundation pit safety grade identification framework, using multi-source time-series monitoring data as different evidence, and performing normalization processing; then, on the basis of the multi-source time-series monitoring data, determining basic probability assignment values in the identification framework; then, separately calculating weights of multi-source monitoring indicators, and credibility; and finally, fusing multi-source monitoring data of a foundation pit, in order to obtain a foundation pit safety evaluation grade. The present invention is characterized in that the importance of different monitoring indicators and the credibility of evidence are taken into consideration while making full use of actually measured monitoring data of a foundation pit, thereby ensuring that foundation pit safety state identification is objective, avoiding interference from subjective human factors, and effectively overcoming the defects of a traditional D-S evidence theory.

The invention relates to the technical field of slope protection, in particular to a slope protection intelligent detection system based on deep learning. According to the technical scheme, the system comprises a multi-source heterogeneous data sensing module, a data fusion and feature extraction module, a slope state intelligent diagnosis and early warning module, an edge-cloud collaborative computing architecture and a system optimization module. Registration and feature complementation of multi-source heterogeneous data are realized through a multi-modal detection network, an overfitting phenomenon is effectively inhibited through a physical information neural network architecture, risk quantitative evaluation is realized through construction of a dynamic risk evaluation model, early warning response time is shortened in cooperation with a four-level early warning strategy, the false alarm rate is reduced, and the early warning efficiency is improved. Besides, the detection precision of the system in an extreme scene is improved through a physical constraint adversarial training method, so that the environmental adaptability of the system is improved, continuous updating and evolution of the model are realized through an online incremental learning module, and the problem of performance degradation of a traditional system caused by change of geological conditions is solved.

The invention provides a road slope data monitoring method under a complex geological condition, and relates to the technical field of road slope monitoring, and the method comprises the steps: carrying out the temperature compensation of a change rate, analyzing the thermal expansion characteristic of a material, calculating the deformation caused by the temperature change, correcting the monitored side length, and generating a temperature compensation side length; according to the temperature compensation side length and the surrounding rock rheological equation, correcting the two adjacent side lengths through the strain difference of the adjacent sides so as to obtain the final side length; combining the final side length with the reference interior angle to generate a topological structure; based on the topological structure, constructing a three-dimensional deformation index matrix containing a diagonal displacement difference, an adjacent side curvature ratio and an interior angle variation coefficient; and inputting the index matrix, the support structure strain space-time matrix and the rock mass fragmentation tensor into a space-time attention graph neural network together, and outputting a deformation evolution trend including a diagonal displacement difference, an adjacent side curvature ratio and an interior angle variation coefficient. According to the invention, high-precision real-time monitoring can be realized.

The invention discloses a cooperative monitoring device and method for a large deep foundation pit complex supporting system, and relates to the technical field of foundation pit supporting. The device comprises a multi-dimensional sensor network module, a BIM-GIS digital twin platform module, an intelligent analysis and early warning module, a construction collaborative decision module, a data backup and recovery module and a remote monitoring and management module. The method comprises the following steps: step 1, carrying out multi-source data space-time registration; step 2, dynamically constructing a digital twinborn model; step 3, coupling risk assessment; step 4, construction collaborative optimization; according to the technical scheme, the method comprises the following steps of data processing, data quality control and system performance evaluation, through three innovations of deep coupling of multi-source data, dynamic model correction and intelligent collaborative decision making, a'monitoring-analysis-decision-execution 'full closed loop is constructed, technical breakthroughs are achieved in complex working condition adaptability, early warning real-time performance and construction safety, and the method has remarkable engineering application value.

The invention discloses an intelligent monitoring system for deformation and stress of a deep foundation pit supporting structure, relates to the technical field of deep foundation pit supporting monitoring, and is used for solving the problem of poor early warning of the deformation risk of the supporting structure. According to the method, high-density acquisition of inclination angle, deformation and stress data of a key area of a deep foundation pit supporting structure is realized by constructing a sensitivity-driven measuring point layout mechanism; the method comprises the following steps: constructing an inversion model based on stress and strain rates, obtaining a structural equivalent modulus, extracting a change rate of the structural equivalent modulus, judging a rigidity evolution trend, further constructing a modulus change rate space field, setting a region threshold by combining a disturbance sensitivity factor, realizing abnormal region identification and spatial positioning, and extracting structural response behavior information on the basis. And driving a system to trigger a grading response strategy according to an analysis result of the structure response behavior information, thereby realizing intelligent early warning of local deformation and stress instability of the deep foundation pit supporting structure.

The invention relates to the technical field of real-time prediction of three-dimensional forms, in particular to a real-time dynamic prediction system and method for the three-dimensional form of a high-pressure jet grouting pile. The method comprises the following steps: carrying out stratum characteristic identification on a construction site to obtain stratum distribution data; key monitoring point positions are determined according to the stratum distribution data, and a multi-source sensor monitoring network is established; carrying out anti-interference optimization processing on the multi-source sensor monitoring network, and carrying out real-time acquisition on high-pressure jet grouting parameters to obtain real-time high-pressure jet grouting data; and spatio-temporal evolution processing based on injection pressure, lifting speed and rotating speed is conducted on the real-time high-pressure jet grouting data, and parameter change characteristic data are generated. According to the method, the construction stratum distribution and the high-pressure jet grouting parameters are obtained and analyzed in real time, the parameter-stratum response relation model is established, grout diffusion and pile body forming dynamic prediction are conducted on different stratum characteristics in a targeted mode, and the precise construction capacity under the complex stratum condition is greatly improved.

The invention belongs to the technical field of geotechnical engineering safety monitoring, and particularly discloses a high slope monitoring point dynamic optimization arrangement method, which comprises the following steps: acquiring multi-source monitoring data of each monitoring point in a plurality of monitoring points on a high slope monitoring area; determining the neighborhood radius and the feature density of each monitoring point according to the multi-source monitoring data, and partitioning the monitoring area according to the neighborhood radius and the feature density; obtaining partition features of each partition, and inputting the partition features and the multi-source monitoring data into a deep learning model based on an attention mechanism to obtain an importance score and a stable state of each partition; and according to the importance score, the stable state and the feature density, determining an optimization strategy for arranging the monitoring points in each partition. According to the method, the monitoring effect can be maximized under the condition that the number of monitoring points is limited, real-time monitoring and early warning of deformation and stability of the high slope are achieved, the method has high scientificity, effectiveness and practicability, and the high slope monitoring efficiency and accuracy can be remarkably improved.

The invention relates to the technical field of pile foundation monitoring, and discloses a pile foundation state real-time monitoring and diagnosis system based on a digital twinborn technology. The system comprises a multi-source data acquisition module, a data confidence evaluation module and an acoustic emission monitoring decision module. The multi-source data acquisition module comprises a plurality of sensor groups deployed at different depths of a pile foundation, each group comprises a strain sensor, an acceleration sensor, an acoustic emission sensor and a temperature sensor, and pile foundation data can be acquired in multiple dimensions; the data confidence evaluation module receives original data, generates a correction data sequence through time sequence noise separation and reconstruction, and calculates data confidence according to correction data distribution dispersion; the acoustic emission monitoring decision module judges whether acoustic emission monitoring is started or not according to the data confidence coefficient, and controls the acoustic emission sensor array at the top of the pile foundation to collect acoustic emission signals during starting. The system can comprehensively obtain pile foundation data, improve data accuracy, achieve early damage recognition and guarantee pile foundation safety.

The invention relates to the field of monitoring and early warning, in particular to a dynamic beam radar monitoring and linkage early warning method and system for a layered side slope of an expressway, and the method comprises the steps: carrying out the layered scanning of a layered geologic structure of the side slope, synchronously obtaining a phase coherent echo signal, carrying out the multi-threshold scattering point extraction, and carrying out the multi-threshold scattering point extraction; through analysis of a prior constraint model and a geological vegetation recognition network, interference signals caused by vehicle passing are eliminated to obtain a space-time coherent scattering point set, the space-time coherent scattering point set is input to a deformation calculation assembly line, differential interference measurement, adaptive atmospheric disturbance correction and slope structure parameter inversion are executed, and a displacement data stream is generated. And carrying out space-time correlation analysis on the layered inclination angle time sequence data and the meteorological and hydrological data, updating a slope stability evaluation index through a dynamic baseline, and generating an early warning instruction. According to the invention, a technical system from interference suppression and precise calculation to decision closed loop is formed, high reliability of road slope monitoring results is ensured, and intelligent support is provided for traffic safety and emergency management and control.

The invention provides a deep and large foundation pit monitoring method and system, a program product and a storage medium, and relates to the technical field of foundation pit detection. The GPS positioning device collects foundation pit slope crest displacement data, the monitoring sensor network collects deep horizontal displacement data, the two data types complement each other, comprehensive information of surface and internal deformation of the foundation pit is provided, and the generated deep horizontal displacement curve chart visually displays the displacement conditions of the supporting structure at all depths. A potential weak area can be identified, a foundation pit excavation response data acquisition device is arranged at the maximum stress part, response data of a key position is obtained, and the quantitative index of overall deformation is provided by measuring and monitoring the position change of a central point of a sensor network and calculating the deformation amount of the foundation pit. According to the multi-dimensional and multi-type data acquisition and integration method, the description comprehensiveness of the foundation pit environment is improved, potential risks can be judged more accurately, and limitation caused by a single data type is overcome.

The invention discloses a grouting method and system for enhancing strip mine slope stability, and belongs to the technical field of slope protection. The grouting method comprises the steps that early-stage data are pre-collected, and an analysis model is established; grouting is designed according to a model analysis result; a pressure-resistant grouting pipe is installed and connected with a grouting pump; grouting parameters are adjusted in real time according to feedback of the sensor; after grouting, all data in the grouting holes are analyzed; outputting a slurry permeation three-dimensional cloud picture, a stress change curve and a stability evaluation index; and storing all monitoring data and model parameters. A cyclic self-adaptive system is formed, it is ensured that the grouting process is efficient and accurate, the overall stability is improved for heterogeneous rock mass, dependence on a static geological report is reduced, and therefore the problem that grouting parameters depend on engineering experience or conservative of the static report is avoided.

The invention discloses a bridge pile foundation stress nondestructive testing method and system, the system comprises a sensor arrangement module, a data acquisition module, a data transmission module, a data processing module, a data analysis module, a result display and early warning module, a calibration module, a verification module and the like, sensors are various in type and high in precision, data acquisition multichannel synchronization is realized, and transmission is stable and reliable. Various technologies are used for data processing to construct a model, and a result is visually displayed and pre-warned. The system is further provided with an environment monitoring and structure health assessment module, comprehensive and accurate detection is guaranteed through an innovative formula and method, and efficient operation of the system is guaranteed through cooperative work of all modules. Through multi-module cooperation and innovative design, bridge pile foundation stress high-precision detection, environmental factor analysis and structure health assessment are achieved. Early warning can be carried out in time, bridge safety is guaranteed, a scientific basis is provided for maintenance management, and the reliability and safety of bridge operation are improved.

The invention discloses a pile foundation integrity detection method which comprises the following steps: applying a variable amplitude sound wave excitation sequence to a pile foundation structure, collecting acoustic response signals under different excitation amplitudes, and obtaining nonlinear dynamic response data reflecting material rheological characteristics; performing frequency dispersion analysis and hysteretic characteristic analysis on the nonlinear dynamic response data, extracting a stress memory dissipation coefficient and a nonlinear memory capacity index, and establishing a time-varying characteristic curve; according to an abnormal change interval and a memory capacity fading rate of the time-varying characteristic curve, determining a defect position and a defect type, and obtaining an evolution state parameter of the defect; and based on the historical change trend of the evolution state parameters, the material degradation rate and the structure damage development rate are calculated, the health state index of the pile foundation structure is predicted, and a full life cycle performance evolution curve is formed. Through stress memory activation and nonlinear dynamic response analysis, the detection method considering the rheological property of the material is established, and the performance evolution rule of the pile foundation in the whole life cycle can be accurately evaluated.

The invention relates to the technical field of optical measurement and geometric position measurement, in particular to a remote multipoint monitoring system and method for roadbed surface settlement, and the system comprises a plurality of distributed monitoring nodes and a remote data platform; the monitoring node comprises a heterogeneous sensor group and an edge processing module which is connected with the sensor group and is used for carrying out local preprocessing and fusion on multi-source data; the wireless communication module is used for sending the data to a remote data platform; the power supply and maintenance module provides electric energy and supports node cleaning and environment adaptation; the remote data platform comprises a data receiving and storage unit, a data fusion and analysis unit, an early warning unit and a visual user interface. According to the invention, a multi-sensor fusion intelligent monitoring network is constructed, all-weather and high-precision remote monitoring of urban road subgrade settlement and associated crack deformation thereof is realized, settlement trend prediction and early warning are provided through AI analysis, and the initiative and safety guarantee level of urban road maintenance are improved.

The invention relates to a slope monitoring method and device based on multi-modal data, and the method comprises the steps: obtaining monitoring data of a target slope, the monitoring data comprising interference radar data and multi-spectral data at different moments obtained by monitoring the target slope; inputting the monitoring data into the trained preset model to obtain a monitoring result; wherein the monitoring result represents the change condition of the target slope at different moments, the training sample is used for training the preset model to obtain the trained preset model, and the training sample is obtained based on the digital elevation data, the interference radar data and the multispectral data. As the training sample comprises the digital elevation data, the interference radar data and the multispectral data, the model can learn the change information of the side slope in the three-dimensional space in the time dimension, and the interference radar data and the multispectral data in the side slope can be more fully learned. Therefore, the obtained monitoring result can reflect the slope change condition more accurately, and then the slope monitoring efficiency is improved.

The invention relates to the technical field of civil engineering, and discloses a foundation pit slope protection pile concrete strength evaluation and intelligent reinforcement integrated method which comprises the following steps: S1, data acquisition and transmission: acquiring a slope protection pile structure state and environmental parameters in real time through a multi-source sensor network, the sensor network comprises a mechanical sensor, an environment sensor and a hydrological sensor which are deployed in a spatial distribution manner; s2, data preprocessing and feature extraction: performing space-time fusion processing, including noise suppression, space-time reference unification and multi-dimensional feature extraction, on the acquired multi-source sensing data, and generating a structured feature matrix; according to the technical scheme, the multi-source sensor network and the deep learning model are combined, the strength of the foundation pit slope protection pile concrete is monitored and evaluated in real time, the accurate and lossless strength prediction effect is achieved, the problems of destructive testing and precision limitation are avoided, and the test efficiency is improved. The defects of low precision and poor real-time performance under complex geological conditions in the prior art are overcome.

The invention discloses a perpendicularity control method and platform for tubular pile construction in the technical field of engineering construction tubular pile construction, the platform comprises a reference positioning module and a dynamic adjustment module, the reference positioning module is used for establishing a first coordinate system for an initial vertical reference of a tubular pile; the dynamic adjusting module is used for establishing a second coordinate system with the tubular pile as the reference, monitoring and correcting the perpendicularity deviation of the tubular pile in the construction process in real time and correcting the perpendicularity deviation until the perpendicularity meets the requirement, and the coordinate axis of the second coordinate system and the coordinate axis of the first coordinate system keep the spatial corresponding relation; according to the scheme, through multi-sensor data fusion and closed-loop control, intelligent control over the perpendicularity of the tubular pile is achieved, and the method is suitable for rapid construction of the tubular pile.

The invention provides a method and system for estimating the vertical bearing capacity of a steel pipe pile, and relates to the technical field of pile foundation engineering.The method comprises the steps that a static cone penetration test is conducted on a seabed stratum needing to be arranged for a steel pipe pile foundation, experimental data are obtained and subjected to normalization processing, soil behavior types are divided, and soil layer mechanical parameters are inverted; calculating side friction resistance and end resistance of the steel pipe pile based on the soil layer mechanical parameters to obtain initial static ultimate bearing capacity; historical equivalent cyclic load experimental data of waves in the construction sea area are obtained, an equivalent cyclic load reduction coefficient, a liquefaction reduction coefficient and a time-varying corrosion reduction coefficient are constructed, and a comprehensive time-varying reduction coefficient is constructed; the initial static ultimate bearing capacity is corrected based on the comprehensive time-varying reduction coefficient, the vertical bearing capacity of the steel pipe pile in the long-term service period is predicted, and the time-varying ultimate bearing capacity is obtained; setting an evaluation threshold according to the time-varying ultimate bearing capacity, dynamically adjusting a bearing capacity grading threshold interval, and outputting a bearing capacity grading evaluation result.

The invention discloses a whole-span bridge hoisting construction method. The method comprises the steps that prefabricated bridge components are transported to a construction site; in the construction preparation stage, a foundation monitoring mechanical model of a construction site is built, and the optimal position and operation parameters of a crane are determined; before hoisting, a laser emitting device is installed on a bridge component, a laser receiving device is installed at the front end of a crane suspension arm, and a plurality of laser reflection targets are arranged on the periphery of a preset installation position of a pier; in the lifting and translation processes, the laser positioning system monitors the spatial position and attitude information of the bridge component and the suspension arm in real time, and transmits the data to the control center in real time; and the control center compares the actual position deviation with the target position deviation in real time according to the preset hoisting path and the in-position precision requirement, and when the deviation exceeds the threshold value range, a control instruction is sent to a power system and a hydraulic control system of the crane. According to the method, the position and posture of the bridge component can be accurately monitored in real time, the action of the crane is timely and accurately regulated and controlled according to the deviation, and the construction precision and safety are improved.

The invention relates to the field of electric power engineering, and discloses a cement electric tower foundation differential settlement monitoring method and system, and the method comprises the steps: obtaining cement electric tower foundation bearing parameters and environmental geological data, constructing a sensing displacement array, deploying basic monitoring points, calibrating an initial reference value, and then collecting displacement data in a fixed time period, the method comprises the following steps: calculating a uniform settlement amount, generating a deformation early warning signal in combination with inclination angle information, analyzing a support weak area according to the early warning signal, determining a reinforcement priority, detecting stress distribution and a crack propagation trend, generating a settlement regulation and control instruction, analyzing instruction feedback data, identifying an abnormal settlement mode, calculating an instability risk coefficient, and compensating and correcting offset data. And analyzing a settlement evolution rule, and finally making a grading maintenance strategy. The maintenance safety and stability of the cement electric tower structure can be improved.

According to the pile foundation pile sinking monitoring method, device and equipment and the storage medium, the pile foundation pile sinking image is obtained through the collecting equipment arranged at the preset position, the pile foundation pile sinking image comprises the to-be-monitored pile foundation, and the to-be-monitored pile foundation is provided with a pile body scale; calculating the actual size of a unit pixel according to the pile body scale so as to determine a vertical pixel calibration value; according to a preset mark point and the vertical pixel calibration value, pile foundation pile sinking parameters are determined; and the pile sinking parameters of the pile foundation are input into a bearing capacity prediction model, and the predicted bearing capacity of the to-be-monitored pile foundation is obtained. The image acquisition device arranged at the preset position is used for acquiring the pile sinking image of the pile foundation in real time, pixel calibration is carried out in combination with the pile body scale, and key parameters in the pile sinking process of the pile foundation can be accurately calculated, so that a reliable basis is provided for prediction of the bearing capacity of the pile foundation, the monitoring precision and efficiency are greatly improved, and the cost is reduced. And errors possibly caused by manual measurement are avoided.

The invention discloses a weak intercalated layer control-based closed conduit-slope system optimization layout method, which comprises the following steps of S1, geological survey and parameter acquisition: accurately positioning a weak intercalated layer through a geological radar and drilling coring, and determining a rock-soil body strength parameter by combining a laboratory rock-soil mechanical test, geological radar data and rock-soil body strength parameters are analyzed through a random forest algorithm, and the interlayer space distribution rule is predicted. By combining geological survey, numerical simulation, intelligent optimization and dynamic monitoring technologies, scientific layout and adjustment of a closed conduit-side slope system are realized, a weak intercalated layer seepage path is accurately cut off, the safety coefficient of the side slope is effectively improved, meanwhile, expansion of a plastic zone is effectively inhibited, settlement of an overlying soil body or large-range deformation of the side slope is reduced, and the stability of the side slope is improved. The seepage stability and the stress slow release capacity of the system are enhanced, the safety of the water diversion project in a complex geological area is improved, and an operable technical path and basis can be provided for layout of similar projects in the future.

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 discloses a deep foundation pit excavation deformation real-time monitoring system based on relative measurement. The deep foundation pit excavation deformation real-time monitoring system comprises a relative measurement sensor group, a data acquisition and preprocessing module, a wireless data transmission module, a cloud data processing and analysis module, an intelligent risk assessment module, a visual alarm module and a solar power supply and energy storage management module. The relative measurement sensor group collects deformation data of the deep foundation pit, the data acquisition and preprocessing module performs primary processing on the data, the wireless data transmission module stably transmits the data to the cloud, the cloud data processing and analysis module performs deformation prediction, and the intelligent risk assessment module performs risk grading. The visual alarm module gives an alarm in real time and carries out emergency notification according to different risk levels, and the solar power supply and energy storage management module guarantees continuous operation of the system. The system solves the problems of measurement precision, data transmission, risk assessment, power supply stability and the like of an existing monitoring system, provides powerful support for safe construction of the deep foundation pit, and has remarkable benefits.

The invention discloses a backfill soil foundation compaction quality on-site detection method and system. The method comprises the steps that instantaneous acceleration signals of a vibrating wheel in the soil compaction construction process are collected in real time through a three-axis acceleration sensor; the acceleration signal comprises a three-axis acceleration component; recording the number of construction times through construction equipment, collecting position information of a construction area by using a GPS (Global Positioning System), and synchronously binding the acceleration signal with the number of construction times and the position information through timestamps to form a data set corresponding to the position of the construction area; performing spectral analysis on the acceleration signal in the data set, and extracting a dominant frequency amplitude and a first harmonic amplitude to generate a filtered acceleration signal; the filtered acceleration signals are input into a training single-hidden-layer BP neural network, and the soil dry density is calculated in combination with the number of construction times; based on the ratio of the calculated soil dry density to the standard maximum dry density, the soil compactness in the construction area is determined in combination with the position information, and a construction area compactness distribution diagram is generated through the upper computer to optimize the construction strategy.