1907 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 discloses an ultra-deep underground pipeline detection method and device, a storage medium and a program product, and the method comprises the steps: transmitting a multi-frequency electromagnetic wave signal, receiving an acoustic response generated by the multi-frequency electromagnetic wave signal, and determining an underground geological structure in combination with a preset geological material frequency spectrum database. A composite detection signal is generated by simulating an underground propagation path of a multi-frequency electromagnetic wave signal and performing phase adjustment and power adjustment. And finally determining position information and depth information of the pipeline in the generated underground structure image by transmitting a composite detection signal and processing a return signal by using a time reversal mirror technology. According to the method, multi-frequency electromagnetic wave signals, acoustic response analysis, geological material characteristics and signal processing technologies are comprehensively utilized, and the precision and reliability of ultra-deep underground pipeline detection can be effectively improved.

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 utility model relates to the technical field of pipeline settlement detection, in particular to a pipeline settlement detection device which comprises a pipeline supporting assembly, the pipeline supporting assembly comprises a pipeline base, a hoop is fixedly arranged at the top of the pipeline base, the hoop comprises two pipe clamps which are symmetrically connected in an abutting mode, a pipeline is arranged in the hoop, and the pipeline is arranged on the pipeline base. Bolts are arranged on the hoop to fasten the two pipe clamps, mounting through holes are vertically formed in wing plates at the two ends of the hoop, detection assemblies are arranged in the mounting through holes, and limiting protection shells are arranged outside the detection assemblies; according to the pipeline settlement detection device, the position of the pipeline is detected through the detection assemblies arranged at the two ends of the underground pipeline supporting assembly, data transmission is conducted through the displacement sensor, detection is conducted in combination with a computer, manual work, station arrangement, observation and recording are not needed in the measurement process, the influence of weather conditions is avoided, and the detection efficiency is improved. The device is high in detection efficiency, simple in structure, low in cost and low in maintenance and calibration cost.

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.

Apparatus and method for transporting and laying pipe segments or sections directly in a ditch dug for underground pipeline installation, minimizing use and size of right-of-way adjacent the ditch. The apparatus has a mobile unit with support configured to align weight of the pipe segments or sections with the longitudinal central axis of the mobile unit. Caterpillar tracks carry and move the apparatus, which can be controlled remotely. The apparatuses transport and lay pipe segments by cooperating in tandem formation while maintaining alignment of the weight of the cable with the longitudinal central axis of each of the mobile units.

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 an underground pipe network multi-dimensional early warning method and system based on optical fiber sensing, and the method comprises the steps: building a detection system of a detection region based on each parameter combination, a corresponding detection position and a detection time period, collecting a grade change diagram corresponding to the detection system, and carrying out the grade control of the detection system. Defining a real-time early warning level of the underground pipe network according to the positions of the plurality of early warning points, the number of the plurality of early warning points and the road section corresponding to the underground pipe network; a corresponding optical fiber system is constructed based on a plurality of optical fiber sensors, and abnormal events of the plurality of optical fiber sensors are optimized in real time in the optical fiber system so as to define the dynamic detection level of the detection area of the underground pipe network. According to the dynamic detection level of the detection area of the underground pipe network, the real-time early warning level of the underground pipe network and the load corresponding to the road section, multi-dimensional early warning of the underground pipe network is triggered, and the early warning accuracy and response timeliness of the underground pipe network under multiple dimensions based on the multiple optical fiber sensors are guaranteed.

The invention relates to the technical field of pipeline robots, in particular to a pipeline robot suitable for underground pipe network detection. Comprising an equipment shell, a detection assembly, a first underwater camera, a second underwater camera and two fixing mechanisms, the two fixing mechanisms are symmetrically arranged; the equipment shell is arranged between the two fixing mechanisms, and a first electric telescopic rod used for driving the barrel on one side to move in the length direction of the barrel is installed in the equipment shell. A mounting shaft is rotationally mounted on the equipment shell, a second power assembly used for driving the mounting shaft to rotate is mounted in the equipment shell, and the mounting shaft is connected with the barrel on the other side; the detection assembly is mounted on the mounting shaft; and the first underwater camera and the second underwater camera are respectively arranged at the outer ends of the cylinder bodies at the two sides. The robot has good stability and can easily cross obstacles in the pipeline.

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 relates to the technical field of research and development of pipeline repair materials, and discloses an underground pipeline repair material based on UV resin and a preparation process thereof. The underground pipeline repairing material based on the UV resin is prepared from the following raw materials in parts by weight: 40 to 60 parts of unsaturated polyester resin, 1 to 5 parts of crosslinking diluent, 5 to 8 parts of thickening agent, 5 to 8 parts of preservative, 5 to 15 parts of dibutyl phthalate and 10 to 30 parts of photoinitiator. The novel underground pipeline repairing material based on the UV resin is researched, developed and prepared, and the material has excellent mechanical performance and corrosion resistance and can be used as a raw material used in a trenchless pipeline repairing and reinforcing method.

The invention belongs to the technical field of pipeline maintenance, and particularly relates to a pipeline dislocation alarm device for underground pipe gallery management, which comprises a pipeline detection robot main body, and detection cameras and water conveying pipes which are axially mounted on the outer side of the pipeline detection robot main body at equal intervals, one end of the pipeline detection robot body is rotationally connected with a cylindrical protective cover through a damping bearing, a rotary high-pressure flushing mechanism is arranged, the rotary high-pressure flushing mechanism can rotate and spray water at the same time, sludge at the dislocation position of a pipeline can be flushed in an all-dimensional mode, and the pipeline detection robot is more convenient to use. The situation that sludge adheres to the inner wall of the pipeline and influences the dislocation strength detection accuracy of the dislocation strength detection mechanisms on the dislocation position of the pipeline can be avoided, the two sets of dislocation strength detection mechanisms are controlled to contract inwards through the expansion mechanism after detection is completed, the dislocation strength detection mechanisms can be stored and protected, and the dislocation strength detection mechanisms can be prevented from being damaged.

The underground pipeline detection robot comprises a vehicle body capable of being folded and adjusted, the vehicle body comprises a first middle vehicle body and a second middle vehicle body, and an adjusting mechanism is arranged between the first middle vehicle body and the second middle vehicle body; the adjusting mechanism comprises a driving gear rotating at one end of the second middle vehicle body and a driven gear fixedly connected with the first middle vehicle body. Through the design of the supporting rollers, the robot can be stably supported in the pipeline and assists in vertical steering, and the flexibility of the robot is further improved; a camera is rotationally arranged on a vehicle body at the end part of the robot and can shoot the internal condition of the pipeline in real time and transmit data to the outside, so that personnel can conveniently observe and analyze in real time; the sampling part comprises a miniature spiral conveyor, a collecting bottle and a metal exhaust pipe, negative pressure in the collecting bottle is pumped out through a vacuum pump, and chippings collected in the miniature spiral conveyor are sucked into the collecting bottle, so that subsequent detection and analysis are facilitated.

The invention relates to a forward design method and device for an urban underground pipeline model, and relates to the technical field of pipeline modeling. The method comprises the following steps: acquiring pipeline parameter information and pipeline arrangement condition data of an underground target pipeline of a city; generating a three-dimensional pipeline path of the target pipeline according to the arrangement information, the elevation information and the pipeline arrangement condition data; generating an initial three-dimensional pipeline model according to the pipeline type parameters and the three-dimensional pipeline path; acquiring a first model associated with the target pipeline according to the position area coordinates; determining conflict points of the initial three-dimensional pipeline model based on the first model; and performing avoidance re-planning processing on the initial three-dimensional pipeline model based on the conflict points to obtain a three-dimensional pipeline model. According to the scheme, the convenience and accuracy of generating the urban underground pipeline model are improved.

The utility model discloses an underground pipeline detector for engineering investigation, which comprises a walking frame and a support frame, the support frame is mounted in the walking frame, a servo motor is mounted on the side wall of the support frame, a connecting block is mounted at the output end of the servo motor, a connecting rod is mounted at one end of the connecting block, and a connecting rod is mounted at the other end of the connecting block. A hinge shaft is installed at the end, close to the connecting block, of the connecting rod, the connecting rod is movably connected with the connecting block through the hinge shaft, an L-shaped shaft is installed at the end, away from the hinge shaft, of the connecting rod, the L-shaped shaft extends into the supporting frame and is movably connected with the supporting frame, and a pin shaft is installed at the end, close to the connecting rod, of the L-shaped shaft. According to the utility model, the detector can be conveniently folded, extended and stored in a linkage manner, the angle can be conveniently rotated, adjusted and used for detection, the detector can be conveniently and rapidly stored and protected, the detector can be adaptively used by people with different heights, and the use convenience is improved.

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 discloses a gas leakage source identification system and method based on multiple sensors and a storage medium, and relates to the technical field of probability analysis. Detection data of the sensors in records and effective relative diffusion coefficients of soil are collected; constructing a gas diffusion model when the underground pipeline leaks by using the collected data; the optimal monitoring distance when the underground pipeline is monitored is calculated through the historical leakage opening length, and a monitoring point is made on the underground pipeline within the diffusion area through the optimal monitoring distance; calculating the dangerousness of each region in the diffusion area, determining a high-risk region according to the dangerousness, and placing a gas detection sensor in the high-risk region; aiming at each formulated monitoring point, inputting all data into a gas diffusion model to generate an adjoint equation of each gas detection sensor; the accompanying probability equation of each monitoring point is obtained, the accompanying probability is calculated, and the position of the underground pipeline gas leakage source is searched according to the accompanying probability.