1320 results about "Underground pipeline" patented technology

The invention discloses an underground pipe network leakage detection method fusing big data analysis and machine learning. The underground pipe network leakage detection method comprises the step of deploying an acoustic sensor, a pressure sensor and a flow sensor at preset positions of an underground pipe network. Performing noise reduction and standardization processing on the acquired operation data, extracting frequency domain, energy and time sequence characteristics of acoustic signals to generate acoustic characteristic vectors, and calculating initial space coordinates of a leakage position based on time difference of arrival of the acoustic signals and sensor arrangement; and generating a pressure feature vector, and analyzing the spatial-temporal correlation of the flow data to generate a flow feature vector. And fusing acoustic, pressure and flow feature vectors to form a multi-dimensional feature vector, inputting the multi-dimensional feature vector and the initial space coordinates into a pre-trained cascade deep learning model, and outputting the leakage probability and the leakage position of underground pipe network leakage. And when the leakage probability exceeds a preset threshold value, triggering an alarm mechanism. According to the invention, efficient detection and accurate positioning of underground pipe network leakage are realized, and high real-time performance and positioning accuracy are achieved.

The invention relates to an intelligent detection and evaluation method and system for underground pipeline defects, and the method comprises the following steps: S1, collecting multi-modal data of an underground pipeline based on an inspection robot, and transmitting the multi-modal data to an intelligent detection and evaluation platform; s2, the intelligent detection and evaluation platform preprocesses the collected multi-modal data; s3, performing defect detection on the underground pipeline based on the preprocessed multi-modal data; s4, constructing a three-dimensional model of the underground pipeline, and superposing a defect detection result into the three-dimensional model; and S5, based on the three-dimensional model of the underground pipeline, performing intelligent evaluation on the underground pipeline, and generating a pipeline condition evaluation report. According to the invention, the efficiency and reliability of underground pipeline defect detection are effectively improved.

The invention belongs to the technical field of earthquake disaster scene construction, and discloses an earthquake disaster scene construction method based on big data, and the method comprises the following specific steps: 1, multi-source heterogeneous data collection and preprocessing ground structure data collection: employing a multi-platform remote sensing technology to obtain urban building group space distribution characteristics; a three-dimensional coupling model of an underground pipe network and a ground building is constructed by integrating multi-source data, so that the defect of isolated analysis of a ground system and an underground system in a traditional method is overcome, and synchronous simulation of a dynamic association process of pipe network fracture and building damage is realized; the additional influence of pipe network failure on the building foundation stability and the linkage effect of soil erosion caused by leakage fluid are accurately analyzed, meanwhile, a time-space association rule of pipe network fracture events and multiple types of secondary disasters such as building fire disasters and fire fighting failure is established, and the building group function paralysis risk and the disaster diffusion range under different damage degrees are dynamically predicted; and the disaster evolution path is displayed in real time through a visual platform.

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 relates to the technical field of underground pipe gallery distributed intelligent control, and discloses an underground pipe gallery intelligent illumination and energy consumption optimization system, which comprises a dynamic credibility evaluation module for analyzing multi-modal environment sensing data in real time and generating a dynamic credibility score; the edge-cloud collaborative optimization module is used for realizing distributed collaborative learning through local model fine tuning and global knowledge distillation; and the event-driven resource allocation module dynamically optimizes a lighting strategy and a communication priority based on credibility scores and emergency information, and through multi-modal data cross validation and adaptive weight adjustment, the robustness of anomaly detection is significantly improved, and misjudgment caused by sensor failure or environmental interference is effectively suppressed; the dynamic planning algorithm is used for synchronously optimizing energy consumption and equipment service life, efficient balance of safety and energy efficiency is achieved, the system is particularly suitable for complex underground environments and can automatically adapt to sudden anomalies, and the intelligent level and the energy utilization efficiency of pipe gallery illumination are remarkably improved.

The invention relates to the technical field of pipeline GIS, and discloses a pipeline GIS system and method. The method comprises the following steps: acquiring GIS underground pipe network topological data of a target area in a GIS system, and acquiring an earth surface abnormal data set of the target area through an unmanned aerial vehicle; performing multi-channel classification and weighted spatial interpolation on the surface anomaly data set to obtain surface anomaly risk distribution data; performing spatial correlation analysis through a heterogeneous attention module to obtain a spatial attention weight and earth surface anomaly propagation characteristics; performing time-space synchronization analysis on the surface abnormal data set and the GIS underground pipe network topology data to obtain risk cascade propagation data; and performing risk judgment on the risk cascade propagation data to obtain a safety state early warning result of the underground pipeline, and generating an unmanned aerial vehicle route adjustment instruction and a GIS system response instruction. According to the method, the complex space association relationship between the surface anomaly and the underground pipeline can be automatically identified and quantified, and the anomaly detection precision and credibility are improved.

The invention belongs to the technical field of data acquisition, and provides an underground pipeline detection data acquisition method and system, and the method comprises the following steps: collecting underground pipeline drawing data of a target region, and determining the information parameters of underground pipelines; performing field exploration, marking a ground outcrop point of the underground pipeline, and preliminarily judging the trend of the pipeline; detecting the underground pipeline through an electromagnetic method or a ground penetrating radar, and determining the position and the burial depth of the underground pipeline; reflected and scattered sound wave signals propagated through the internal fluid of the underground pipeline are collected through sound wave detection, and the state of the internal fluid is evaluated; fusing different detection data to generate an underground pipeline space model; by comprehensively using the electromagnetic method, the ground penetrating radar and the sound wave detection technology, the position, the burial depth and the internal fluid state information of the underground pipeline can be comprehensively collected, the physical position of the pipeline is determined, the state of the internal fluid of the pipeline is evaluated, and the accuracy and the reliability of the detection result are effectively improved.

The invention belongs to the technical field of electric power and communication engineering, and particularly relates to an intelligent line patrol instrument based on multi-band electromagnetic induction and TDR fusion, and the intelligent line patrol instrument comprises a signal transmitting end which comprises a main control unit, a multi-band electromagnetic signal generator, a TDR pulse module and a self-adaptive coupling circuit. And the signal receiving end comprises a three-axis magnetic field sensor, an ADC module, an FPGA processing unit, a DSP processing unit and a touch display screen. The invention relates to an intelligent line patrol instrument combining multi-band electromagnetic induction and time domain reflection (TDR) technologies, which is used for path tracking, depth measurement and high-precision fault positioning of underground cables and optical cables, and is particularly suitable for underground pipeline maintenance and construction scenes under complex electromagnetic environments (such as transformer substations and dense pipeline areas).

The invention provides an underground pipe network engineering drawing drawing method and system based on a standard legend library, and relates to the technical field of engineering drawing, and the method comprises the steps: obtaining pipeline space positions, connection relations and initial data of legend information; retrieving the standard legend with the highest matching degree by using a deep neural network to generate a two-dimensional engineering drawing; the two-dimensional drawing is converted into a three-dimensional model, and the pipeline layout with the collision risk is adjusted through an optimization algorithm based on field potential flow; and automatically updating and outputting an engineering drawing according to the optimized three-dimensional model. According to the method, intelligent optimization of pipeline layout is realized, and the drawing efficiency and accuracy are improved.

The invention discloses a Beidou, inertial navigation and vision-coordinated underground pipeline robot positioning method, which comprises the following steps: firstly, an inertial measurement unit is used to obtain the acceleration and angular velocity information of the robot and correct its output, and then an odometer is used to obtain the mileage data of the robot and identify the pipeline connection point so as to correct its output, and then the angular velocity and mileage information are fused to realize the preliminary prediction of the posture state of the pipeline robot; then, the internal and external parameters of the IMU and the visual sensor are calibrated, and SIFT feature extraction and matching are performed on each captured frame of the image; then, the data of the IMU, mileage information and the binocular camera are fused in a tightly coupled manner, and a nonlinear optimization method is used to obtain the robot posture information with higher accuracy; finally, the three-dimensional position information returned by the Beidou positioning sensor is used to perform posture constraints, and the robot posture information with local accuracy and global drift-free is obtained, so as to realize the precise positioning of the pipeline robot.

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 relates to the field of underground pipe gallery space detection, in particular to an underground pipe gallery detection method based on unmanned aerial vehicle point cloud scanning, and the method comprises the steps: 1, arranging a reflector plate, and collecting the three-dimensional coordinates of the reflector plate in an absolute coordinate system; 2, performing three-dimensional laser scanning when the unmanned aerial vehicle flies, performing point cloud acquisition at the entrance of the underground pipe gallery, acquiring spatial point cloud data by a laser radar carried by the unmanned aerial vehicle, and recording environment image information by a visual sensor; 3, establishing a relative coordinate system associated with spatial features, and carrying out point cloud SLAM calculation; step 4, calculating overground and underground continuous spatial point clouds based on an SLAM algorithm, and extracting three-dimensional coordinates in the scanning point clouds; 5, converting the point cloud in the relative coordinate system to an absolute coordinate system by using a Rodrigue matrix conversion method; and step 6, acquiring real spatial position information of the underground pipe gallery. The real spatial position of the underground pipe gallery in an absolute coordinate system is obtained through continuous scanning of the unmanned aerial vehicle in combination with ground GNSS measurement.

The embodiment of the invention provides an underground pipeline extraction method, system and device based on point cloud and a storage medium, and belongs to the technical field of point cloud space geometry extraction. According to the scheme, underground pipeline point cloud data are obtained; segmenting the pipeline point cloud data to obtain a segmentation result; when the segmentation result is a single-pipe scene, principal component analysis and cylinder fitting are carried out based on all pipeline point cloud data to obtain a normal vector and a pipeline radius of each data point; performing plane cutting according to the normal vector to obtain a tangential plane, and obtaining a pipeline center line based on the tangential plane; determining a distance threshold parameter according to the radius of the pipeline; based on the distance threshold parameter, performing segmented straight line fitting on the pipeline center line through a random sampling consistency algorithm to obtain a center line point set; performing feature extraction on the center line point set to obtain feature points; determining a connection relationship of adjacent feature points according to the geometrical relationship; the pipeline reconstruction model obtained based on the connection relation can be suitable for complex scenes, and the calculation efficiency is improved.

The invention provides an urban lifeline pipeline corrosion risk early warning method based on digital twinning, and the method comprises the following steps: S1, obtaining pipeline internal operation parameters, pipeline external environment parameters and external corrosion rate data according to a monitoring control system and detection equipment; s2, constructing an internal corrosion rate prediction model based on digital object fusion and a physical guidance neural network; s3, constructing an external corrosion rate prediction model based on a particle swarm optimization algorithm and a relevance vector machine; s4, performing completion and time registration on the external corrosion rate data of the pipeline according to a spline interpolation method; s5, constructing a pipeline corrosion risk grading early warning method; and S6, according to the steps S1 to S5, establishing an underground pipeline full-life service cycle corrosion risk early warning system based on digital twinning. According to the method, real-time corrosion risk grading early warning and residual life prediction are achieved for the multiphase flow underground pipeline in the full-life service cycle, and detection, maintenance and maintenance work of the multiphase flow underground pipeline under the corrosion risk is guided.

The invention discloses a construction method of an assembly type vibration isolation trench. The method comprises the following steps: firstly, designing and prefabricating a vibration isolation trench unit according to construction site conditions, underground water flow and vibration isolation requirements, including site analysis, size material determination, simulation optimization and quality inspection; before construction, field survey is carried out, topography and geology are covered, underground pipeline detection and vibration source analysis are carried out, the excavation path and depth are determined, and field preparation is made. And then digging a trench by using special equipment according to the design, controlling trench wall parameters and carrying out acceptance inspection. And then gravel and an anti-seepage film are sequentially laid at the bottom of the groove, and a drainage facility is additionally arranged according to needs so as to install a vibration isolation layer. The prefabricated units are lifted, adjusted and connected, then light materials are filled, then fine sand and geotechnical cloth are covered, and soil is recovered. And finally, adjusting and optimizing according to a result through vibration and acoustic testing. According to the method, through multiple layers of vibration isolation materials, firm connecting pieces and strict testing, the vibration isolation effect and stability are remarkably improved, and an effective scheme is provided for engineering vibration isolation.

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 provides a buried pipeline stress monitoring system and method, and relates to the technical field of pipeline monitoring, and the system comprises a TMR sensor; the full-bridge strain gauge group is configured to acquire stress data of the to-be-measured pipeline; the monitoring module is configured to obtain historical data; training the linear model by using the historical environment magnetic field data and the historical stress data to obtain an initial magnetic field stress model; updating model parameters of the initial magnetic field stress model by using a least square method to obtain a target magnetic field stress model; and inputting the environment magnetic field data and the stress data into the target magnetic field stress model to obtain target stress data so as to solve the problems that a single sensor is mainly adopted for measurement in the current pipeline stress monitoring process, and the measurement process is easily interfered by factors such as temperature drift and magnetic field fluctuation, so that the monitoring precision cannot meet the actual demand, and the measurement accuracy is poor. And the real stress state of the pipeline is difficult to reflect.

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 invention discloses an auxiliary construction device for a municipal underground pipeline, and relates to the technical field of auxiliary construction of underground pipelines, the auxiliary construction device for the municipal underground pipeline comprises a construction vehicle, a lifting frame is fixedly mounted at the top of the construction vehicle, and a motor is fixedly mounted on the surface of the construction vehicle; a conveying mechanism is arranged on the surface of the construction vehicle, the excavating device comprises a sliding shaft, a sliding box, a first connecting plate, an equipment box, a drilling barrel, a fixing plate, a double-shaft motor, a first reciprocating lead screw, a drill bit, a rotating plate, a moving plate and a hole expanding ring, and a first sliding groove is formed in the surface of the lifting frame. According to the auxiliary construction device for the municipal underground pipeline, when the drilling barrel is withdrawn, the moving plate can move in the direction away from the rotating plate under the action of soil or rock walls and drive the hole expanding ring to move, the excavated soil wall pipeline is expanded through a construction vehicle, and the space needed by pipeline laying is expanded on the basis of an original hole channel.

The invention provides a combined sand drain drainage structure suitable for a high slope. The combined well drainage structure comprises a row of vertical sand well structures arranged in the side slope along the slope surface line of the side slope and siphon drainage structures arranged at the bottom ends of the row of vertical sand well structures. The vertical sand well structure comprises a vertical well hole, a water permeable pipe and a gravel inverted filter layer, and the water permeable pipe is filled with gravel; the siphon drainage structure comprises a siphon water guide pipe, a horizontal drainage well structure and an inclined drainage pipe. Rainwater of the high slope is collected through the sand wells, the rainwater is collected into the horizontal drainage wells under the action of gravity, underground water collected by the horizontal drainage wells is drained from the drainage holes in the lowest end of the supporting structure through the siphon guide pipes, then negative pressure is generated in the horizontal drainage wells, and drainage of the vertical sand wells is further accelerated. The construction difficulty of the deep drainage structure of the high slope is reduced, and it is guaranteed that underground water enriched under the effects of rainfall, underground pipeline water leakage and the like can be drained in time and rapidly.

The invention discloses a sewage treatment device with a dosing function, and relates to the field of sewage treatment.The sewage treatment device comprises pretreatment equipment, the water outlet end of the pretreatment equipment is connected with a plurality of sedimentation tanks through underground pipelines, rotating columns are installed on the inner sides of the sedimentation tanks, and each rotating column comprises a dosing tank and a water outlet tank; a water outlet groove is formed in the sedimentation tank, chemicals are added into the sedimentation tank through the water outlet groove, the inner wall of the sedimentation tank is fixedly connected with a slag discharging channel and a slag discharging opening, the slag discharging channel is fixedly connected to one side of the slag discharging opening, a discharging opening of the slag discharging opening is externally connected with slag discharging equipment through a pipeline, and a material collecting unit, a material guiding mechanism and an auxiliary assembly are arranged on the outer wall of the rotating column. Through cooperation of parts such as the collection hopper, when the collection hopper moves to the highest point of the first abutting plate, the opening is aligned with the scum discharging opening to pour out scum as much as possible, and therefore the scum cleaning efficiency is improved.

The invention discloses a pipeline patrol system based on an Al intelligent algorithm, and relates to the technical field of pipeline patrol, the pipeline patrol system comprises an information acquisition end for information interaction, a server and an execution patrol end, the server comprises an analysis identification module and an execution control module, the execution patrol end comprises an unmanned aerial vehicle and a pipeline robot, the information acquisition end is used for acquiring environmental information in an oil and gas pipeline area. Inspection and fault detection can be effectively carried out in various environments, the continuity and stability of pipeline inspection are ensured, the unmanned aerial vehicle can efficiently cover the high altitude and the difficult-to-reach area of the pipeline, the pipeline robot can go deep into the underground pipeline for inspection, the requirement for manual inspection is reduced, and the working efficiency is improved. And the coverage range and the meticulous degree of patrol are improved, the patrol efficiency is greatly improved, the fault detection time is greatly shortened, and the patrol frequency and the patrol accuracy are improved.

The invention discloses an urban underground pipeline life cycle safety monitoring method and system based on big data. The method comprises the following steps: acquiring full life cycle multi-source data of an urban underground pipeline; performing fusion preprocessing on the multi-source data, and constructing a pipeline digital twinborn model; performing real-time monitoring on the pipeline operation state by using a space-time correlation analysis algorithm, and extracting abnormal features; based on a pre-constructed deep learning risk assessment model, performing grading assessment on the pipeline safety state, and generating a risk grade; predicting the remaining service life of the pipeline through a service life prediction algorithm in combination with historical fault data and real-time monitoring data; and generating a maintenance decision suggestion according to the risk level and the remaining service life, and realizing full-life-cycle safety monitoring of the underground pipeline. A digital twinborn model is constructed through multi-source data fusion, and dynamic visual management of the whole life cycle of the underground pipeline is achieved. Through combination of time-space correlation analysis and a deep learning algorithm, pipeline abnormal features are accurately identified, and the risk assessment accuracy is improved.

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 utility model relates to the technical field of desilting equipment, in particular to a stirring desilting device capable of achieving desilting, which comprises a hollow desilting head and an adjusting assembly, a cavity of the desilting head is divided into a middle suction chamber and a stirring chamber arranged on the periphery of the suction chamber, a desilting pump is arranged in the suction chamber, an inlet of the desilting pump is connected with a suction pipe, and the suction pipe is connected with the stirring chamber. An outlet of the dredging pump is connected with a shunt pipe; a plurality of arc-shaped water outlet holes are formed in the periphery of the stirring chamber, a silt discharging channel and a backflow channel are formed in the left side and the right side, opposite to each other, of the flow dividing pipe correspondingly, the silt discharging channel is connected with a silt discharging pipe, the adjusting assembly is arranged on the flow dividing pipe, and the end, away from the flow dividing pipe, of the backflow channel communicates with the stirring chamber through a water flowing pipe. Water in the underground pipeline can generate circulation to stir deposited sludge, the water and the sludge are stirred and mixed to form muddy water, then the muddy water is pumped out under the action of the desilting pump, the working intensity of workers is relieved, water resources are saved, and the desilting effect is good.