851 results about "Underground pipeline" patented technology

The invention provides an underground pipe network defect intelligent identification and early warning method and system based on deep learning, and relates to the technical field of pipe network detection, and the method comprises the steps: employing a pipeline detection robot to obtain multi-source data, and carrying out the preprocessing; mapping the features to a manifold space, constructing a similarity matrix, and carrying out geometric difference weighted fusion; constructing an incidence matrix to calculate a spatial distance and mechanical strength, and carrying out iterative propagation to generate a defect characteristic spectrum; and acquiring an evolution sequence by adopting a self-adaptive sliding window, determining influence factors based on anti-fact intervention, and calculating a state transition probability to determine an optimal maintenance scheme. According to the method, the pipe network defect identification accuracy is improved, and pipeline state prediction and maintenance decision intelligence are realized.

The invention provides a pipe gallery disease monitoring and diagnosis method based on multi-source heterogeneous data, and relates to the technical field of disease monitoring and diagnosis, and the method comprises the steps: carrying out the data collection through a multi-mode sensor network disposed in an underground pipe gallery; fusing the multi-source heterogeneous data set based on a graph neural network to generate a dynamic sensing characteristic spectrum of the whole domain of the pipe gallery; carrying out disease evolution mode identification, and determining a pipe gallery disease risk level; and triggering the self-adaptive early warning strategy, executing the self-adaptive early warning strategy to generate a decision instruction set, and pushing the decision instruction set to the visual monitoring platform. The technical problem that potential problems are difficult to find in time and the operation efficiency of the pipe gallery is affected due to the fact that detection and risk assessment of the pipe gallery diseases depend on periodicity is solved, real-time monitoring and early recognition of the underground pipe gallery diseases are achieved through effective integration and processing of the multi-source heterogeneous data, and the method and the device have the advantages of being high in practicability and the like. And the efficiency and the safety of pipe gallery management are improved.

The invention belongs to the technical field of underground pipeline construction, and particularly relates to a multi-point synchronous jacking force distribution and posture monitoring system for ultra-long-distance pipe jacking construction and a control method. Comprising a sensor module, a data acquisition module, a control module and a hydraulic jacking device, the control module carries out numerical differentiation on displacement signals to obtain the real-time propelling speed of each jacking point, and the real-time propelling speed is compared with a preset target propelling speed to obtain speed deviation; the axial friction resistance of the corresponding pipe section is calculated according to the jacking force signal and the displacement signal; comparing the real-time attitude angle signal with a designed target attitude to obtain an attitude deviation; inputting the speed deviation, the axial friction resistance of the corresponding pipe section and the attitude deviation into a coupling control algorithm, and outputting jacking force increment or speed correction. According to the invention, the propulsion and postures of the jacking points of the main jacking station and the plurality of relay jacking stations can be kept synchronous and coordinated.

The invention discloses a multi-dimensional risk supervision method for bridge and underground pipe gallery engineering, and particularly relates to the field of underground pipe gallery engineering supervision, and the method comprises the steps: an underground structure slippage risk identification and prediction process based on pressure data driving: firstly, collecting an original pressure signal and screening effective data; establishing a standardized two-dimensional pressure field matrix by using the variation function; local gradient mutation features are recognized through Sobe l convolution, evaluation units are divided to calculate entropy distribution, entropy change abnormity is extracted, and a multi-dimensional phase space trajectory is constructed; the maximum Lyapunov index is further applied to estimate and recognize the stability state, gradient and entropy features are combined to construct a parameter inversion observation set, and a constrained optimization algorithm is adopted to iteratively solve an equivalent friction angle; constructing the time sequence into a time sequence, inputting the time sequence into an ARI MA model, executing slip rolling prediction, finally generating a risk thermodynamic diagram with confidence, and achieving the dynamic evaluation and early warning of the slip trend of the underground pipe gallery.

The invention provides a subway construction management method and device in a complex sensitive environment, and relates to the technical field of subway construction management, and the method comprises the steps: obtaining first information which comprises construction region shield propulsion parameter time sequence data, building settlement monitoring data, underground pipeline distribution data and micro-seismic sensor array data; preprocessing the first information to obtain a three-dimensional geological influence map fusing underground structure-stress response-dynamic disturbance; performing semi-variation function modeling and spectrogram co-training clustering algorithm joint optimization on the three-dimensional geological influence map to generate a multi-layer heterogeneous map structure; performing dynamic graph convolutional network and graph integral propagation model co-evolution on the multilayer heterogeneous graph structure to generate a risk cascade prediction model; and solving the prediction model to obtain a global management scheme of subway construction. According to the invention, subway construction full-life-cycle management with controllable risk, timely response and dynamic strategy adjustment is realized.

The invention belongs to the technical field of underground pipeline detection and defect identification, and particularly discloses an underground pipeline defect detection method based on image and point cloud data fusion, and the method comprises the following steps: collecting a video image and laser radar point cloud data of the inner wall of an underground pipeline, and carrying out the synchronous pairing of an image frame and a point cloud frame based on a timestamp; performing defect identification on the synchronized image frames to obtain a defect region ROI; based on a pre-calibrated external parameter matrix of a camera and a laser radar, converting the synchronously acquired point cloud data coordinates into an image coordinate system, calculating through internal parameters of the camera to obtain pixel coordinates, and screening out a point cloud point set falling into a defect region of interest (ROI) as a defect point cloud subset; and sequentially carrying out denoising, registration and clustering segmentation on the defect point cloud subset to obtain a three-dimensional point cloud structure of the defect, and calculating a quantization parameter of the defect based on the three-dimensional point cloud structure. According to the invention, automatic real-time detection and accurate quantification of pipeline defects can be effectively realized.

The invention relates to the technical field of information management, in particular to an underground pipeline gallery risk monitoring method and device. According to the method, a heterogeneous sensing terminal network is used for sensing a target underground pipeline gallery according to a fast and slow time sequence, and a pipeline gallery monitoring anchor point set is determined; performing cross-modal interaction on a heterogeneous sensing terminal network based on the pipeline and pipe gallery monitoring anchor point set to obtain a pipeline and pipe gallery monitoring anchor point multi-modal fusion feature set; performing anchor point risk assessment according to the pipeline and pipe gallery monitoring anchor point multi-modal fusion feature set, and obtaining a pipeline and pipe gallery monitoring anchor point risk factor set according to an assessment result; and when the pipeline and pipe gallery monitoring anchor point risk factor set is greater than or equal to a preset anchor point risk factor threshold value, triggering a risk early warning instruction. According to the method, accurate identification and dynamic early warning of the key risk points of the underground pipeline gallery are achieved through fast and slow time sequence sensing and cross-modal feature fusion processing based on the monitoring anchor points.

The invention provides an underground pipeline leakage detection method and system based on physical enhancement thermal inertia imaging, and belongs to the technical field of pipeline detection, and the method comprises the steps: obtaining an earth surface thermal field and environment meteorological parameters of a current target area; the surface thermal field and the environmental meteorological parameters are input into a double-flow physical information neural network model, a predicted background thermal field is obtained, the double-flow physical information neural network model is obtained through training based on leakage-free historical data and a total loss function, and the total loss function comprises physical loss items determined based on a one-dimensional heat conduction partial differential equation; calculating a space-time residual image of the earth surface thermal field and the predicted background thermal field, and obtaining an apparent thermal inertia distribution map of the earth surface based on the space-time residual image and environmental meteorological parameter inversion; and detecting whether the underground pipeline in the target area leaks based on the space-time residual map, the apparent thermal inertia distribution map and a preset condition. According to the invention, the accuracy of underground pipeline leakage detection can be improved.

The invention provides a line migration and modification scheme optimization evaluation method based on a multi-dimensional constraint condition, and the method comprises the steps: obtaining the position information of an urban underground pipeline, extracting the buried depth of an unlabeled pipeline and an intersection point according to the position information of the underground pipeline, carrying out the labeling, and obtaining the pipeline distribution data containing a three-dimensional coordinate and the buried depth deviation; pipeline horizontal distance information in the preliminarily optimized layering scheme is extracted, whether the distance meets the safety requirement or not is judged through a space geometry algorithm, and if not, horizontal distance parameters are adjusted, and adjusted horizontal distance parameters are obtained; acquiring damage degree data of the protection layer, and if the damage degree exceeds a preset threshold value, establishing a pipeline layout model with real-time response by dynamically updating a vertical layering standard and a horizontal spacing parameter; and according to the optimized pipeline collaborative distribution scheme, calculating a pipeline space utilization efficiency index, and carrying out iterative updating on the pipeline layout model to obtain a pipeline layout optimization result adapted to the dynamic environment.

The embodiment of the invention discloses an underground pipeline simulation operation method and device based on spatial distribution. A specific embodiment of the method comprises the steps of collecting a multi-source underground pipeline data set in a target city area; performing data standardization on each piece of multi-source underground pipeline data in the multi-source underground pipeline data set to generate a standardized multi-source underground pipeline data set; establishing an initial underground pipeline three-dimensional structure model; performing pipeline space alignment on the initial underground pipeline three-dimensional structure model to generate a target pipeline three-dimensional structure model; and adding the target pipeline three-dimensional structure model to a three-dimensional pipe network visual distribution diagram layer in a preset target urban area underground distribution network global twin space, and performing underground pipeline simulation operation on the three-dimensional pipe network visual distribution diagram layer according to preset pipeline operation parameters. According to the embodiment, the accuracy of the generated target pipeline three-dimensional structure model can be improved.

The invention discloses an underground pipeline detection method and system based on multi-source data fusion and intelligent analysis, and belongs to the technical field of pipeline detection. The method comprises the steps of collecting multi-source data of a target area; wherein the multi-source data comprises electromagnetic signal data, electromagnetic wave reflection data and sound wave propagation data; performing filtering and normalization preprocessing on the multi-source data to obtain target data; constructing a multi-source data fusion model to perform feature level fusion on the target data to generate a fusion feature vector; an underground pipeline recognition model based on deep learning is constructed to intelligently analyze and recognize the fusion feature vector, and a recognition result of the underground pipeline is obtained; and marking and displaying the identification result on an electronic map in a visual mode. According to the invention, by fusing data collected by various detection technologies and applying an intelligent analysis algorithm, the accuracy, reliability and efficiency of underground pipeline detection are improved, and the limitation problem of the existing detection technology is solved.

The invention discloses an underground pipeline intelligent leakage detection method and device, and relates to the field of intelligent leakage detection.The method comprises the steps that a high-frequency pressure sequence of a target pipe section is collected, and based on the Boltzmann superposition principle, the high-frequency pressure sequence is used for constructing a neural lag operator network by taking the environment temperature as a heat rheological regulation factor; taking the full historical stress-strain memory field tensor as input, carrying out non-local memory characteristic and hysteresis loop analysis, carrying out point-by-point differential processing on a high-frequency pressure sequence and the intrinsic nonlinear hysteresis response signal of the pipe, stripping non-stationary background fluctuation, avoiding modulation interference of material nonlinearity on a fluid signal, and obtaining a non-linear hysteresis response signal of the pipe. The method comprises the following steps: extracting the abnormal residual error of the fidelity fluid dynamics, constructing a spatio-temporal evolution Poincare section, inputting the spatio-temporal evolution Poincare section into a convolutional neural network, judging the real leakage negative pressure wave and the random drift of the sensor through the morphological difference of attractors on the spatio-temporal evolution Poincare section, and eliminating the periodic false alarm caused by the rheological property of the material.

The invention discloses an underground pipe network dynamic risk detection and early warning method, which comprises the following steps that firstly, a multi-source heterogeneous database is constructed, various data are integrated to form a core database, and the construction step comprises the step of collecting various data; and then data standardization processing is carried out, and various coding and normalization operations are carried out. Then constructing a spatial-temporal characteristic matrix; then, a hybrid model containing a multilayer perceptron and a convolutional neural network is constructed for deep learning training, and a model input layer contains multiple feature tensors and has related strategies; and then the model score is mapped to a geographic information system to generate a risk thermodynamic diagram, a threshold value is set to trigger an early warning signal, linkage with an emergency platform is carried out, and three-dimensional visual display is carried out. Cross-regional cooperative training and risk trend analysis can be carried out in the model, and a digital twin platform can be embedded to realize dynamic simulation detection. According to the method, a comprehensive data basis is constructed, a complex relationship is mined, model performance is improved, and decision support is provided for pipe network risk management and control and the like.

The invention discloses an underground pipeline settlement monitoring device and monitoring method.The underground pipeline settlement monitoring device comprises a static force level gauge mechanism which is connected in series and monitors pipeline settlement through changes of the internal liquid level, and further comprises a vibration air compression mechanism and an opening and closing mechanism which are communicated and both arranged on the static force level gauge mechanism; the protection mechanism is arranged on the opening and closing mechanism, a connecting hose is arranged in the protection mechanism and used for communicating the adjacent static force level gauge mechanisms, and an extrusion mechanism is arranged outside the protection mechanism and used for applying pressure to the interior of the protection mechanism. The static leveling instrument has the beneficial effects that when vibration exists at a measuring point, the vibration air compression piece reciprocates in the air compression cylinder under vibration and can suck air along the one-way valve and press the air into the opening and closing mechanism, the first sliding piece is pushed to move downwards, and a liquid inlet and a liquid outlet of the static leveling instrument mechanism are blocked; the liquid is prevented from flowing between the liquid storage tank and the connecting hose due to vibration, so that the liquid level is prevented from changing due to vibration to influence the detection precision.

The invention discloses a method and a device for detecting and positioning an underground pipeline containing a ferromagnetic material. According to the invention, the fluxgate sensors and the position and attitude sensors are installed on the support frame, and the support frame is driven to rotate, so that rapid magnetic scanning measurement of the underground pipeline is realized, and the trend, the horizontal position and the depth of the pipeline are estimated. According to the invention, the efficiency is greatly improved by adopting a rotary scanning strategy, the problem of uneven or muddy ground is avoided, and the method is suitable for detecting a ferromagnetic target with a slender structure; the direction and depth of the pipeline are estimated by using the coordinates of the extreme points of the magnetic field, and the positions of ferromagnetic targets which are non-uniformly distributed along any straight line can be estimated; the method does not need an accurate magnetic field value, is suitable for a complex environment with strong interference, is short in estimation time, and supports real-time positioning of the pipeline; and the corresponding pipeline depth below each measurement node is estimated by using the measurement data of the plurality of measurement nodes at different heights, so that the method can be applied even if the pipeline is not horizontally buried.

The invention relates to the technical field of ground source heat pumps, and discloses a safety monitoring method and device of a ground source heat pump system, multi-dimensional real-time data such as the rotating speed of a circulating pump, the pipeline pressure and the environment temperature are collected through a multi-point sensor, and dynamic monitoring of the running state is achieved through noise filtering and time sequence analysis. When abnormity is detected, a comprehensive operation matrix is constructed in combination with historical operation records, and stress distribution of the underground pipeline is reversely calculated through the structured grid division technology. Based on a stress distribution sequence, a future stress evolution trend is analyzed and predicted by adopting linear regression, and a potential safety risk level is determined. And finally, dynamically adjusting the data acquisition frequency according to the risk level, and generating a self-adaptive safety monitoring strategy. Intelligent safety monitoring of the ground source heat pump system is achieved, potential risks can be found in time, prevention measures can be taken, and the operation safety and reliability of the system are effectively improved.

To provide a novel technology for planning renewal of existing pipelines within a renewal range.SOLUTION: An AI-based buried pipeline renewal planning system comprises an acquisition unit that obtains pipeline type information including pipeline renewal costs per pipeline type attribute, a renewal budget that is an annual budget for renewing existing pipelines within a renewal scope, and a renewal priority of pipelines, a pipeline type attribute determination unit that determines post-renewal pipeline type attributes for existing pipelines within the renewal scope, and a planning unit that formulates renewal plans for the existing pipelines within the renewal scope including renewal costs when the existing pipelines within the renewal scope are renewed to the post-renewal pipeline type attributes and renewal timing within the budget.SELECTED DRAWING: Figure 1

The invention relates to the field of deformation monitoring, in particular to an underground pipeline deformation real-time monitoring method and device, equipment and a medium. The method comprises the steps that through real-time connection with equipment such as an optical fiber sensor and a three-dimensional laser scanner, spectral signals can be received in real time, three-dimensional point cloud data can be collected, and data collection delay is avoided. In a data processing link, whether a strain distribution map is generated based on a spectral signal or a deformation displacement vector is determined from three-dimensional point cloud data, an efficient algorithm is adopted to quickly complete calculation and analysis, and the data processing time is greatly shortened. Moreover, the electronic equipment continuously monitors the strain distribution map and the deformation displacement vector in real time, and once it is monitored that the strain gradient and the displacement change rate of the monitoring node in the pipeline deformation field model exceed threshold values, an early warning mechanism is triggered immediately, deformation early warning information is generated, and the real-time performance of underground pipeline deformation monitoring is improved.

The invention relates to the technical field of underground pipeline detection, in particular to a Hertz signal digitization method and system for underground pipeline detection. A digital detection excitation signal with stable Hertz frequency is generated by adopting a phase accumulation mechanism of a DDS (direct digital synthesis) technology and digital interpolation translation; a controllable random jitter frequency division strategy is introduced to generate multiple groups of single-frequency-point voltage signals to reduce spectrum aliasing and background noise; a response signal is sampled and filtered through a high-precision ADC and a self-adaptive FIR low-pass filter; and carrying out detection analysis and alarm on the target underground pipeline in combination with the frequency band energy normalization analysis and feature vector construction of the wavelet sub-band. According to the invention, digital improvement can be carried out on a 512 Hz analog signal detected by a traditional underground pipeline, and the sensitivity, the anti-interference capability and the signal processing precision of underground pipeline detection are greatly improved.

The invention relates to an underground pipeline disease intelligent detection and evaluation method and system, and the method comprises the following steps: S1, obtaining underground pipeline multi-source heterogeneous data, and constructing an underground pipeline detection knowledge graph; s2, according to the detection task instruction, based on a multi-modal detection robot, obtaining a pipeline multi-modal original data set; s3, preprocessing the obtained multi-modal original data set of the pipeline to obtain a structured feature data set; s4, constructing an intelligent recognition model, performing defect detection, and outputting a final defect intelligent recognition result through a multi-modal data fusion decision algorithm; s5, performing three-dimensional space positioning on each identified defect according to an intelligent defect identification result, automatically marking the three-dimensional space on a digital pipe network map, and quantifying an RBI risk index of each defect; and S6, according to the RBI risk index of each defect, calling the underground pipeline detection knowledge graph to intelligently match the optimal trenchless repair scheme, and obtaining a detection report. According to the invention, the speed of underground pipeline disease detection and the consistency of evaluation are effectively improved.

This invention relates to the field of pipeline robot technology, specifically a pipeline robot suitable for underground pipeline network inspection. It includes a housing, a detection component, a first underwater camera, a second underwater camera, and two fixing mechanisms; the two fixing mechanisms are symmetrically arranged; the housing is located between the two fixing mechanisms, and a first electric telescopic rod for driving one side of the cylinder to move along its length is installed inside the housing; a mounting shaft is rotatably mounted on the housing, and a second power component for driving the mounting shaft to rotate is installed inside the housing; the mounting shaft is connected to the other side of the cylinder; the detection component is mounted on the mounting shaft; the first and second underwater cameras are respectively mounted on the outer ends of the two side cylinders. This invention has good stability and can easily overcome obstacles inside pipelines.

The invention discloses a sound wave detection method and system for an underground pipeline, and the method comprises the following steps: 1, dynamically adjusting the detection height in the radial direction of a pipeline through a lifting adjustment device of a first sound wave detection mechanism, and enabling a sound wave transmitting end to adapt to the inner walls of pipelines with different pipe diameters; 2, a rotation driving device of a second sound wave detection mechanism controls a sound wave transmitting end to conduct multi-angle rotation scanning around the axis of the pipeline, and the circumferential area of the cross section of the pipeline is covered; 3, based on the pipeline inner diameter D, the material acoustic characteristics and the preset coverage rate eta, motion parameters are generated through a dynamic optimization algorithm; 4, collecting a reflected sound wave signal and carrying out multi-stage processing; through the implementation of the method, a dynamic optimization algorithm of full-dimensional scanning coverage enables the screw pitch error of a spiral track to be small, 100% non-blind area coverage of the cross section of the pipeline is achieved, the self-adaptive focusing lens controls the sound beam focusing angle error to be within + / -2 degrees, and the detection sensitivity of the thin-walled pipe is improved.

The invention relates to the technical field of intelligent environment detection, and particularly discloses an underground pipe gallery detection method based on a robot and a pipe gallery detection robot, and the method comprises the steps: obtaining the topological data of a pipe gallery through a multi-source sensing device, constructing a three-dimensional space model of the pipe gallery through the combination of a high-precision Beidou / UWB fusion positioning technology, and obtaining a three-dimensional space model of the pipe gallery; geometric parameters and initial defect distribution of the to-be-detected pipe gallery are marked; based on the three-dimensional space model, a pipe gallery detection robot is deployed, and multi-dimensional data of the pipe gallery environment and the equipment state are synchronously collected in the advancing process; according to the invention, robot inspection is introduced, so that personnel are prevented from being directly exposed in a dangerous environment, the safety risk of the inspection personnel is remarkably reduced, and the problem of high risk in manual inspection is effectively solved; meanwhile, through an automatic and intelligent robot inspection mode, the robot flexibly shuttles around the pipe gallery, all-directional and dead-corner-free detection of the pipe gallery is achieved, the inspection time is greatly shortened, and the detection comprehensiveness and accuracy are remarkably improved.

The invention relates to a spraying anti-corrosion device for an underground pipeline of a building, and belongs to the technical field of pipeline spraying equipment. The spraying anti-corrosion device for the underground pipeline of the building comprises a frame body, a movable frame and a first air cylinder, the frame body and the movable frame are connected in an inserted mode, and the first air cylinder is fixedly installed on the frame body; free adjustment can be conducted according to the anti-corrosion spraying position of the underground pipeline, free switching of two states is conducted, in-pipe locking and positioning can be conducted on the underground pipeline when anti-corrosion spraying is conducted on the outer wall of the underground pipeline in the first state, it is ensured that the underground pipeline is in a stable rotating state when the outer wall of the underground pipeline is sprayed, and the underground pipeline is matched with a horizontally-moving movable spraying head; and in the first state, efficient and stable operation of anti-corrosion spraying of the outer wall of the underground pipeline is achieved, in the second state, one positioning mechanism is disconnected with the underground pipeline, the other positioning mechanism can be matched with the spraying mechanism to conduct anti-corrosion spraying on the inner wall of the underground pipeline, and the device can conduct anti-corrosion spraying operation on the two different positions of the inner wall and the outer wall of the underground pipeline.

The invention relates to the technical field of underground pipeline detection, in particular to an underground nonmetal pipeline detection positioning method and system. The method comprises the steps that multi-source heterogeneous data such as road surface vibration, echo imaging, a thermal radiation sequence and environment field intensity in a target area are acquired and preprocessed, and an original observation set containing spatio-temporal information is constructed; time-frequency joint representation of vibration and echo is realized based on a self-supervised multi-mode feature coding network, thermal radiation texture anomaly is extracted by a space-time convolution converter, and domain-invariant high-dimensional features are formed; conformal attention cross-modal alignment is adopted, the features are mapped to a unified hidden space, key boundaries are screened through gating mutual information, and a comprehensive feature map containing dielectric constant gradient and elastic wave guiding characteristics is generated through fusion; and carrying out topological reasoning by combining a graph neural network with a as-built graph and facility position priori, generating a candidate pipeline network, checking pruning by ray tracing arrival time consistency and a thermal diffusion time delay rule, and outputting pipeline space distribution and three-dimensional coordinates.

The invention relates to the technical field of pipeline repairing devices, in particular to a pipeline trenchless repairing device and process based on CIPP. The repairing device comprises a repairing assembly which is of a hollow structure and used for repairing the sealing performance of the deeply-buried underground pipeline, sealing covers used for keeping the sealing performance of the repairing assembly are arranged at the two ends of the repairing assembly correspondingly, communicating assemblies are inserted into the portions, in the two sealing covers, of the two ends of the repairing assembly correspondingly, and the sealing covers penetrate through the interior and the exterior of the repairing assembly; the hot water injection device is used for injecting hot water into a cavity of the repairing assembly; after the forked pipe inflates the pressure-bearing cavity, the pressure-bearing plate located near the air outlet of the forked pipe is driven by air pressure to drive the anti-skid plate to slide in the radial centrifugal direction of the inner film layer, so that the anti-skid plate easily slides out of the limiting groove, and during the period, the spring deforms to store elastic potential energy; and the anti-skid plate pushes the inner wall of the inner film layer to fix the outer wall of the outer film layer in the to-be-repaired pipeline, so that the air bag cloth is prevented from axially deviating after the inner film layer is filled with hot water.

The invention provides a safety monitoring method and system for an underground pipeline of a municipal road, and the method comprises the steps: arranging multiple types of sensors along the underground pipeline, and collecting the original monitoring data, such as stress, vibration, gas concentration, soil humidity and displacement; the original data is sent to a preprocessing module, time synchronization, abnormity elimination, deletion completion and normalization are completed, and a standardized feature matrix is generated; indexes such as structure variability, trend change rate and sensitivity responsivity are calculated based on the feature matrix, and a health score vector is generated through a feature fusion mechanism; performing density clustering and boundary segmentation in combination with the spatio-temporal index of the score vector, and extracting a high-risk section which changes violently or has an abnormal trend; the section features are combined with historical data, risk levels are calculated through a rule judgment mechanism, and two-dimensional layers of corresponding positions are generated; and accessing the layer to an operation and maintenance platform, completing early warning linkage, instruction generation and log archiving, and synchronously writing into a security evaluation database.

The invention discloses a municipal public engineering underground pipe network intelligent monitoring and early warning system based on the Internet of Things, which aims at solving the problems of unstable data transmission, inaccurate fault prediction and the like of the existing system and is composed of a sensing layer, a transmission layer, an edge intelligent layer and a cloud control center layer. The sensing layer acquires multi-source data by multiple types of sensors, and the transmission layer adopts an LPWAN and OPLC hybrid communication architecture to guarantee data transmission; the edge intelligent layer analyzes data in real time by using a deep learning model, and the cloud control center layer realizes accurate early warning through big data and the model. In addition, the system has the functions of intelligent power supply, AR / VR visualization, multi-layer safety protection and self-diagnosis and self-healing. Through practical verification, the system effectively reduces the accident rate of the pipe network, greatly improves the operation and maintenance efficiency, effectively guarantees the safe and stable operation of the pipe network, and improves the municipal management level.

The invention discloses an underground pipeline distribution detection method and system based on a ground penetrating radar, and relates to the field of underground pipe network engineering. The method comprises the steps of performing orthogonal grid division on a to-be-detected interval based on grid preset parameters, performing GPR orthogonal scanning on a grid detection area, and determining an initial trend of an underground pipeline according to a first vertex and a second vertex; adjusting the initial trend of the underground pipeline based on the initial vertical scanning direction; on the basis of the adjusted direction of the underground pipeline, continuing to perform GPR scanning on the grid detection area until scanning of the grid detection area is completed, and inputting obtained radar original data into the image detection model to obtain a first type of parameter value corresponding to the underground pipeline; and inputting the first type parameter value and the second type parameter value into a pipe diameter prediction model to obtain a pipe diameter value. According to the invention, through linkage of the three modules, intelligent and efficient cooperative one-stop service of detection image analysis, detection path planning and detection remote control can be realized.

The invention relates to the technical field of underground pipeline protection, in particular to an intelligent cathode protection device for an underground pipeline, which comprises a ground and a frame, the frame is buried below the ground, a clamping mechanism is arranged in the frame, two cushion blocks are fixedly mounted on the upper surface of the ground, and the two cushion blocks are fixedly mounted on the lower surface of the ground. The two cushion blocks are fixedly connected to the lower surface of the power box. The rotating wheel is buckled in the shell, the rotating wheel is protected, the rotating wheel is prevented from being collided, and then a first clamping plate is prevented from being separated from the underground pipeline; an electrode wire penetrates through a through hole in the frame to be connected with a power box; the frame and the underground pipeline are filled with soil to be buried, and the frame and the underground pipeline are buried below the ground; the underground pipeline is fixed through the internal structure of the frame, the frame and the internal structure can be made of stainless steel materials, the outer wall is coated with anti-corrosion paint, corrosion in soil is avoided, and the clamping mechanism cannot be cracked by insects to be broken when the clamping mechanism is located underground.