121 results about "3d laser scanner" patented technology

According to the PCB production line defect detection system and method based on image processing, a plurality of high-resolution cameras, an infrared thermal imaging camera and a 3D laser scanner are adopted, a dynamically-controlled annular LED light source, polarized light illumination and a structured light projection technology are combined, a foreground and a background are separated through a self-adaptive threshold Otsu method, and the defect detection accuracy is improved. A convolutional neural network denoising model and a frequency domain filtering technology are introduced, welding spot and line features are extracted from a preprocessed image, a coding scheme is designed, multi-modal features are fused, spatial-temporal feature analysis is introduced, fine classification and positioning are performed in combination with SVM preliminary screening and a YOLOv5 deep learning model, an online learning mechanism is introduced, model parameters are dynamically optimized, and a multi-modal image is obtained. An intelligent early warning mechanism is established, automatic grading and alarm sending are carried out, a statistical report is automatically generated, production process parameters are recorded, root cause analysis is carried out in combination with big data analysis, and potential defects are early warned in advance.

The invention discloses a welding detection method and application thereof in welding monitoring of an LNG (liquefied natural gas) storage tank. According to the scheme, 3D point cloud data, surface image data and cross-sectional image data acquired from a welding seam by combining a 3D laser scanner, an industrial camera and an ultrasonic phased array probe are subjected to multi-modal data fusion; the fusion data is input into a trained defect recognition model, so that the weld joint can have a more perfect data source in quality detection classification, and a reliable data basis is provided for weld joint detection; besides, according to the scheme, a welding seam model based on digital twinning is constructed on the basis of fusion data, in this way, when the welding seam has defects caused by abnormal welding, the welding seam model constructed by the digital twinning model can be used for positioning the defects and outputting local welding seam model data with the defects, and meanwhile, by combining a detection result, the defect detection accuracy is improved. And more visual and reliable detection feedback can be provided for background management personnel.

The invention relates to the technical field of bridge engineering construction, in particular to a bridge deck concrete flatness detection and correction method, which comprises the following steps: synchronously acquiring bridge deck point cloud, elevation and crack data through a three-dimensional laser scanner, a laser profiler and an ultrasonic sensor, and fusing to generate a three-dimensional digital model; defects such as local protrusions and wave deformation are recognized based on an intelligent analysis algorithm, causes are analyzed, and correction process parameters such as milling, cladding, grouting or ultrathin layer pouring are generated in a targeted mode; operation is executed through equipment such as a finish milling machine, closed-loop control is realized by combining real-time monitoring of a laser profiler, and finally, a traceable digital file is formed through laser detection, inspection and acceptance of an unmanned aerial vehicle and data archiving. By means of the method, the pass percent of the flatness of the bridge floor can be increased to 94% or above, the maximum height difference is controlled within 3 mm, the maintenance period of the bridge is prolonged, and the maintenance cost is reduced.

The invention provides a historical building digital modeling and outer wall diagnosis method based on multi-source data fusion, and relates to the technical field of historical building protection and digitization, the method aims at comprehensively obtaining historical building data and analyzing the condition of an outer wall body, firstly, a building main body image is captured through aerial photography of an unmanned aerial vehicle at multiple angles and multiple levels, and the flight height is 30-80 m; sites are arranged on the ground, millimeter-level scanning is conducted on the building facade through a three-dimensional laser scanner, the distance between every two adjacent sites is 10-30 m, and the sites cover the area 10-15 m away from the ground; the method comprises the following steps: firstly, carrying out multi-source data fusion on a wall body, then carrying out close-range shooting on upward view and typical local parts by using a micro lens of a single lens reflex, then preprocessing various data, and finally, measuring and analyzing the concave-convex condition of the wall body according to fused point cloud data, thereby providing accurate data support for historical building protection and research. By means of unmanned aerial vehicle aerial photography and three-dimensional laser scanning station arrangement, it is ensured that high-quality data is obtained.

According to the panorama camera and 3D laser scanner mobile measurement matching method, distortion correction, camera calibration and multi-lens relative orientation matching of the panorama camera are carried out based on the characteristics of the panorama camera for a monocular camera and the panorama camera; establishing collaborative matching between the laser data and the image data and a matching and fusion basis between the laser data and the image data; based on a pinhole imaging model, all parameters of camera calibration are introduced to complete camera calibration, and the relative orientation relation between the laser scanner and the panoramic camera is deduced according to a cylindrical or spherical projection method; a cooperative calibration method based on plane constraint is adopted, initial values of rotation and translation vectors between a checkerboard plane and a distance are solved by utilizing a constraint relation between the normal vector and the distance of the checkerboard plane in a laser and camera coordinate system, and finally a global optimal solution is obtained by iteratively optimizing a target equation. The method is simpler to operate and does not need too much manual intervention. And the matching precision is high, the speed is high, and the robustness is good.

The invention relates to a tunnel three-dimensional holographic splicing method and device for panoramic array camera networking, and the method comprises the steps: enabling a reference transmission camera array and a three-dimensional laser scanner on an inspection vehicle to move to different inspection positions along with the inspection vehicle for adjustment, achieving the transmission of peripheral control information at two ends of a tunnel into a measurement region, and constructing a dynamic control field; the limitation on measurement conditions is reduced; high-precision positioning and attitude determination are carried out based on fixed connection constraints of a look-around camera array and a three-dimensional laser scanner and a constructed dynamic control field, so that a measurement platform is unified to a global coordinate system, and the inherent defect of large accumulative error of a traditional three-dimensional modeling method is effectively avoided; and then the high-resolution look-around image is mapped to the three-dimensional point cloud data under the global coordinate system, so that high-resolution and high-precision three-dimensional holographic splicing of the tunnel ring surface under the global coordinate system is realized, global and local high-resolution and high-precision are achieved, and the acquisition precision of the tunnel three-dimensional hologram is greatly improved.

The invention relates to the technical field of tunnel and underground engineering construction, and discloses an intelligent closed-loop control system and method for a tunnel construction section contour, and the method comprises the steps: collecting geological-geometric data through the fusion of a three-dimensional laser scanner and a geological radar before blasting; dynamically generating a theoretical blasting contour line and adaptive blasting parameters through a convolutional neural network; iMU positioning and a PID controller are combined to realize millimeter-level accurate control of the drill boom; generating a three-dimensional deviation field by adopting an iterative point cloud registration algorithm after blasting; when the deviation exceeds a threshold value, triggering incremental learning to optimize model parameters; and finally, closed-loop iteration is formed. Through multi-source data fusion, contour and parameter intelligent generation, precise execution control, three-dimensional deviation field feedback and an incremental learning mechanism, a complete intelligent closed-loop control system is constructed, the limitation of traditional blasting design depending on experience is broken through, and the precision, efficiency and economic benefits of tunnel construction are remarkably improved.

The invention relates to an anti-collision system for combined operation of multiple ship unloaders, which is characterized by comprising radar anti-collision sensors mounted at key positions such as a traveling cart and a spiral platform of the ship unloaders; the laser range finder is mounted at a specific position of the ship unloader; the RFID tag and the radio frequency positioning module are mounted on a ship unloader track and a ship unloader walking cart; the 3D laser scanner is mounted on the ship unloader; and the PLC control system is used for receiving detection data from the radar anti-collision sensor, the laser range finder, the RFID tag and the 3D laser scanner, and controlling the ship unloader to stop moving equipment or send an anti-collision alarm signal according to preset safe distance parameters. The problems that in the prior art, a traditional anti-collision system depends on a single sensor or a technical means to achieve anti-collision, and all-directional and high-precision anti-collision protection is difficult to achieve are solved.

The present invention discloses a method for detecting the out-of-roundness of train wheels based on three-dimensional information, including image acquisition and preprocessing, laser centerline extraction, laser coordinate transformation and wheel out-of-roundness detection. The present invention only needs to use a small number of linear array cameras and a combination of 3D laser scanner modules to generate multiple two-dimensional image data and laser scanning data with depth information, extract the tread area of ​​the laser scan, and reconstruct the wheel tread profile with depth information based on an elliptical model. Whether it is the local out-of-roundness of the wheel or the overall out-of-roundness, the method of the present invention can accurately calculate it through the wheel tread profile data, and generate a test report in a timely and dynamic manner for the customer to review and repair.

The invention provides a self-adaptive robot grinding and polishing machining system and method for a difficult-to-grind complex component, and the machining system comprises a 3D laser scanner which is used for carrying out modeling according to the shape and size of a workpiece, and automatically dividing a grinding region and carrying out self-adaptive path planning according to geometrical characteristics; the mechanical arm is used for clamping a workpiece to move according to a planned path; an abrasive belt floating polishing device; and the grinding device is provided with a self-adaptive grinding and polishing mechanism capable of moving up and down in the axial direction, and the self-adaptive grinding and polishing mechanism is used for conducting constant-force grinding on the workpiece, compensating tool abrasion in real time, conducting radial vibration auxiliary grinding and replacing a grinding head according to requirements. The multi-process combined robot grinding and polishing system can be used for grinding the round corner transition position of a narrow inner concave surface and a stepped right-angle concave surface of a workpiece, self-adaptive process division is carried out on the workpiece according to geometrical characteristics according to the precise grinding requirements of various complex components difficult to grind, and a plurality of devices are integrated together to form the multi-process combined robot grinding and polishing system; and all-dimensional grinding operation on the difficult-to-grind complex component is achieved.

The invention discloses a visual recognition paint spraying robot system and an operation method thereof, and relates to the technical field of automatic paint spraying, and the technical scheme is that the visual recognition paint spraying robot system comprises a robot system module which comprises a hardware module and a software module; the hardware module comprises a visual acquisition unit module, a spraying execution module, a paint supply module, a safety protection unit module and a control terminal module, and the software module comprises a visual identification subsystem module, a path planning subsystem module, a monitoring and alarm subsystem module and a safety control subsystem module. The high-precision paint spraying system has the beneficial effects that through the high-resolution industrial camera, the 3D laser scanner and an advanced visual recognition algorithm, information such as grooves, defects and sizes of workpieces can be precisely recognized, high-precision paint spraying of complex workpieces is achieved in combination with a self-adaptive path generation algorithm, the paint spraying quality and the product percent of pass are greatly improved, the production efficiency is improved, and the production cost is reduced. And the whole paint spraying process is smoother and more efficient.

The invention relates to a rapid measurement method and device for cavitation damage of a water turbine runner and computer equipment. The method comprises the following steps: acquiring point cloud data collected by a 3D laser scanner for the surface of the turbine runner; determining a cavitation erosion area according to geometric features of the point cloud data; according to the point cloud data corresponding to the cavitation erosion area, the cavitation erosion damage area, the cavitation erosion damage depth and the cavitation erosion damage volume are determined; and according to the cavitation erosion area, the cavitation erosion damage area, the cavitation erosion damage depth and the cavitation erosion damage volume, determining a cavitation erosion damage measurement result of the water turbine runner. According to the method, based on the characteristics of high precision and interference resistance of the 3D laser scanner, the area with cavitation erosion is determined by using the acquired point cloud data, the area, depth and volume of the cavitation erosion area are calculated, an accurate cavitation erosion damage measurement result of the water turbine runner is generated, the limitation of a detection environment and an operation condition on cavitation erosion damage detection is avoided, and the accuracy of the detection result is improved. And efficient cavitation damage detection is realized, so that the safety of the hydroelectric equipment is improved.

The invention provides a slope excavation engineering quantity calculation system and method based on point cloud, and the method comprises the steps: reading the slope geological data of hydropower engineering to construct an initial three-dimensional model, and collecting the multi-stage point cloud data through a three-dimensional laser scanner; performing equidistant gridding on the point clouds of the model region according to an X / Y axis, calculating the spatial similarity and color similarity of the point clouds in grids, and dividing sub-data sets according to threshold values; fitting an excavation surface through a Delaunay triangulation network, calculating an XY plane projection area, and calculating an average Z-direction distance from a subset to the surface of the initial model; the node weight of the triangulation network is corrected by fusing rock stratum interface parameters, finally, the excavation engineering amount is dynamically output through summation of the product of the projection area of each subset and the average distance, and when the deviation of adjacent stages exceeds 10%, cross validation is conducted in combination with a profile method. According to the method, the precision and the real-time performance of slope excavation engineering quantity calculation can be improved, and automatic integration of lithologic characteristics and mechanical attributes is realized.

The invention provides a building point cloud intelligent completion and feature extraction method based on oblique photography, and belongs to the technical field of three-dimensional imaging and laser point cloud. The method comprises the following steps: acquiring initial point cloud scanning data of a building, wherein the initial point cloud scanning data is measured based on a three-dimensional laser scanner; performing clustering on the initial point cloud scanning data to obtain a plurality of clustered initial point cloud distribution areas; for each initial point cloud data distribution area, calculating the point cloud data missing degree of the initial point cloud data distribution area through point cloud data feature extraction; and determining a point cloud completion mode of each initial point cloud distribution area according to the plurality of point cloud data missing degrees corresponding to the plurality of initial point cloud data distribution areas. According to the invention, the corresponding targeted point cloud completion mode can be intelligently selected according to the distribution characteristics of the initial point cloud data, and the integrity and accuracy of the three-dimensional point cloud data of the building are improved.

The invention provides a road disease distribution visualization method and system, and the method comprises the steps: a data collection module collects disease data in real time through an industrial camera, a three-dimensional laser scanner and an integrated navigation device carried by a mobile detection vehicle, and carries out the time-space synchronization and preprocessing; the disease analysis module realizes multi-source data space alignment based on position data, identifies a disease boundary in an image through semantic segmentation, maps the disease boundary to scanning data, extracts a disease point set and calculates disease area, depth and volume parameters; the decision module fuses historical and real-time disease parameters and weather data, generates a disease evolution trend in combination with a time sequence prediction model, and marks a high-risk area through a risk index; the visualization module dynamically renders disease marks on a three-dimensional map, supports time axis interaction to display historical changes, and performs thermodynamic diagram dynamic rendering on a high-risk area. According to the invention, multi-dimensional dynamic monitoring and risk early warning of road diseases are realized, and the road maintenance decision-making efficiency is improved.

The invention discloses a high-stacking-layer-number visual guidance system for automatic stacking after plate cutting, and relates to the technical field of plate processing automation, and the system comprises a plate information acquisition module which uses a 3D laser scanner and a high-definition industrial camera to obtain the three-dimensional contour and surface characteristics of a plate; the data processing module performs noise reduction, calibration and feature extraction; the mechanical analysis module evaluates the mechanical property and collapse risk of the stack; the intelligent planning module optimizes the stacking position and direction; the execution guide module accurately grabs and stacks and adjusts deviation in real time; according to the invention, by integrating a multi-mode sensing system, plate features are accurately collected and rapidly classified, and reliable data are provided for stacking planning; the mechanical and intelligent planning module dynamically evaluates the risk, optimizes the stacking scheme, and improves the space utilization rate and stability; meanwhile, a closed-loop control system calibrates execution actions in real time, millimeter-level precision is ensured, and adaptability to complex working conditions is greatly enhanced.

The invention belongs to the technical field of leakage detection, and particularly relates to an existing building basement side wall leakage three-dimensional detection system and method based on an intelligent wall-climbing robot. The detection system comprises an intelligent wall-climbing robot platform, a multi-modal detection sensor group, a data processing and analysis system and a user interaction terminal, wherein the multi-modal detection sensor group is carried on the intelligent wall-climbing robot platform; the intelligent wall-climbing robot platform comprises a moving adsorption system, a moving mechanism, a positioning navigation system, a posture adjusting mechanism and a communication power supply device. The multi-modal detection sensor group comprises an infrared thermal imager, a high-resolution visible light camera, a 3D laser scanner, a wall penetrating radar, a capacitive humidity sensor and an ultrasonic thickness gauge; the data processing and analysis system comprises an edge computing unit and a cloud analysis platform; the edge calculation unit is responsible for real-time data acquisition, preprocessing, sensor control and motion control. According to the existing building basement side wall leakage three-dimensional detection system and method based on the intelligent wall-climbing robot, full-thickness detection coverage from the surface layer to the deep layer, conversion from manual operation to full-automatic wall climbing and crossing from single-point detection to path tracking are achieved.

The invention provides an automobile damping bushing gluing automatic control method and system, and the method comprises the steps: collecting the gluing thickness, uniformity, coverage, weight deviation, surface defect number, drying temperature and environment humidity data in real time through a high-precision 3D laser scanner, a weighing sensor, an infrared thermometer and a humidity sensor; the method comprises the following steps: establishing a gluing quality evaluation model based on collected data, dynamically adjusting weight and setting production conditions, dynamically adjusting the pressure and rotating speed of a rubber roller according to a quality evaluation result, dynamically controlling the drying temperature in combination with rubber roller parameters and environment humidity, and adjusting the feeding speed according to drying temperature fluctuation and the quality evaluation result through surface temperature feedback correction. A big data platform is constructed to record production data, pilot operation is carried out before formal gluing, parameters are optimized, comprehensive monitoring and intelligent regulation and control of the gluing process are achieved, and the product quality and the production efficiency are remarkably improved.

This invention relates to the field of hydropower station construction, specifically disclosing an intelligent splicing method for elbow pipes based on digital pre-assembly. The method includes: S1: Establishing an absolute coordinate measurement control network in the pre-assembly area; S2: Setting a checkerboard target for positioning on the surface of the elbow pipe block and scanning the block using a 3D laser scanner; S3: Performing multi-site point cloud splicing based on the center coordinates of the target sphere to reconstruct a complete block point cloud model; S4: Processing the complete block point cloud model using a voxel grid centroid sampling method; S5: Establishing a theoretical BIM model and placing it in the coordinate system of the control network to obtain the ideal installation posture; S6: Using an iterative nearest-point algorithm, matching the simplified block point cloud model with the theoretical model in spatial pose to obtain the final installation posture of the elbow pipe block; S7: Based on the final installation posture, calculating the theoretical installation coordinates of the checkerboard target center, generating adjustment commands, and positioning the elbow pipe block according to the commands. This method solves the technical problems of low efficiency and poor accuracy in traditional elbow pipe component assembly, as well as difficulties in segment alignment due to accumulated manufacturing errors.

1. Name of the product in this design: 3D Laser Scanner (UCL360 Nano). 2. Application of this design: This design is intended for use with a 3D laser scanner. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key features: the front view.

A system for conducting a non-contact survey of an overhead crane runway system using a survey apparatus that is alternately located in the crane bay or on a crane bridge girder. Disclosed more particularly is a system for testing an overhead crane runway beam 3D alignment or an overhead crane runway rail 3D alignment using a 3D laser scanner.

This invention discloses a landslide deformation monitoring method based on slope radar and 3D scanning, comprising: simultaneously acquiring deformation echo signals and high-density point cloud data using slope radar and a 3D laser scanner; constructing a simplified point cloud model using a point cloud topology optimization algorithm; spatiotemporally registering the multi-source data; building a multi-field coupling analysis framework by combining a slope stress-deformation coupling model; analyzing the temporal evolution of deformation using a dynamic deformation time-series model; extracting key parameters such as deformation rate and cumulative deformation; and realizing 3D dynamic display through a deformation data visualization analysis platform. This invention, through spatiotemporal registration, multi-field coupling analysis, and time-series modeling, accurately captures deformation characteristics and abrupt change patterns, balancing monitoring accuracy and efficiency, providing comprehensive and intuitive technical support for landslide risk prevention and control, and is applicable to landslide deformation monitoring scenarios with complex slope terrain.

This invention provides a process for welding positioning ribs in a nuclear power generator, comprising the following steps: S1: Place the generator base horizontally on a platform and level it; S2: Mark the machining allowance line and hammer a punch; S3: Turn the generator base upside down, place it upright on the platform, and level it; S4: Install the positioning rib welding fixture according to the marked circular line in S2 and spot weld it in place; S5: Pull steel wires at the slots of the positioning rib welding fixtures at both ends of the generator base; S6: Weld the limiting round steel; S7: Remove the steel wires and hoist the positioning ribs in groups; S8: Adjust the positioning rib welding fixtures so that the positioning ribs are tightly attached to the limiting round steel; S9: Assemble the support blocks and spot weld them in place; S10: Use a 3D laser scanner to detect the position and dimensions of the positioning ribs and record the data; S11: Weld in sequence, and perform flat welding on all welds; S12: Grind the welds and perform 100% flaw detection. S13: Remove the positioning rib welding fixture, and finally use a 3D laser scanner to detect the position and size of the positioning rib, and record it for future reference.

The invention discloses an automobile front fingerboard selective post-processing method based on visual inspection, and belongs to the technical field of intelligent manufacturing of automobile parts, and the method comprises the following steps: 1) collecting surface and internal defect data of a front fingerboard by using a 2D linear array camera, a 3D laser scanner and a thermal infrared imager, and extracting defect feature vectors containing 18 features; 2) inputting the defect feature vector into an improved Transform neural network, and outputting an optimal post-processing process scheme including a process type, a tool type, process parameters and a processing path; according to the invention, through multi-modal visual fusion detection and 18-dimensional feature extraction, the detection accuracy of tiny and complex defects is high; the intelligent decision-making model realizes accurate matching of defects and processes, the material removal amount error control is accurate, and the coating thickness uniformity is improved; a processing path is optimized through a genetic algorithm, and the postprocessing time of a single front fingerboard is shortened in combination with quick remodeling of the robot; and the reinforcement learning automatic optimization process reduces the manual debugging time.

This application relates to a method, apparatus, and computer equipment for rapid determination of cavitation damage in a turbine runner. The method includes: acquiring point cloud data collected by a 3D laser scanner on the surface of the turbine runner; determining the cavitation erosion region based on the geometric features of the point cloud data; determining the cavitation damage area, cavitation damage depth, and cavitation damage volume based on the point cloud data corresponding to the cavitation erosion region; and determining the cavitation damage measurement result of the turbine runner based on the cavitation erosion region, cavitation damage area, cavitation damage depth, and cavitation damage volume. This method leverages the high precision and anti-interference characteristics of the 3D laser scanner to identify cavitation erosion areas using the collected point cloud data, calculate the area, depth, and volume of the cavitation erosion region, and generate accurate cavitation damage measurement results for the turbine runner. This avoids the limitations imposed by the detection environment and operating conditions on cavitation damage detection, achieving efficient cavitation damage detection and thus improving the safety of hydroelectric equipment.

A support frame for 3D laser scanner measurement includes: a base, fixed legs, a fixed pan / tilt head, a first height fine-tuning unit, and a second height fine-tuning unit. The 3D laser scanner is mounted on top of the base, and the fixed legs are pivotally connected to the bottom of the base. The fixed legs are positioned on the ground. The fixed pan / tilt head is positioned between the base and the 3D laser scanner. The first height fine-tuning unit is located below the fixed pan / tilt head, extending from the top to the bottom of the base. The second height fine-tuning unit is located inside the first height fine-tuning unit, extending from the top of the fixed pan / tilt head to the bottom of the first height fine-tuning unit. This invention solves the technical problem of the limited vertical field of view of the 3D laser scanner, resulting in a scanning blind zone near the bottom of the support frame, and avoids the technical problem of the fixed legs of the support frame swinging after being brought together, leading to damage to the fixed legs.

The application discloses a train wheel defect detection method based on three-dimensional information, which comprises data acquisition, data preprocessing, laser line extraction, laser coordinate transformation, three-dimensional wheel splicing and defect detection. The application adopts the combination of multiple linear array cameras and 3D laser scanner modules to generate multiple two-dimensional image data and laser scanning data with depth information, extracts wheel laser center line data through a complex image processing algorithm, reconstructs the three-dimensional profile of the wheel with depth information, splices the three-dimensional information of the complete wheel, compares the local depth information, finds out the area with large depth change, finally detects the defects of the tread and the rim surface of the complete wheel, obtains the information such as the area, position and depth of the defect area, and dynamically generates a detection report for the customer to review and repair in time.

This provides a method for predicting acid-etched wall morphology based on a mathematical model. [Solution] The method involves using a 3D laser scanner and fluid finite element software to perform 3D modeling on the rock slab fracture surface, obtaining a fracture space model, and then, based on the fracture space model, coupling the pressure field and velocity field of the fracture space model to obtain a solution, thereby obtaining the fluid dynamics parameter distribution within the fracture, inputting this fluid dynamics parameter distribution into a constructed acid-rock reaction mathematical model, obtaining the erosion mass of each wall node, using the erosion mass of each wall node to obtain the erosion depth corresponding to the wall, and then, using the fracture space model, removing the influence of the erosion depth corresponding to the wall to obtain the wall morphology after acid etching, thereby completing the prediction of the acid-etched wall morphology.

The invention discloses a weld defect phased array detection fusion method, and belongs to the technical field of nondestructive detection. The method specifically comprises the following steps: S1, continuously scanning a current welding seam through a 3D laser scanner to obtain 3D point cloud data about the welding seam, and scanning the surface of the welding seam through an industrial camera to obtain surface image data about the welding seam, performing multi-modal data fusion on the 3D point cloud data surface image data of the welding seam to obtain a first fusion data model about the welding seam, and dividing the first fusion data model into a plurality of areas; and S2, matching the first fusion data model and the welding seam parameters with the welding seam historical record data, and judging the defect possibility of each region of the current welding seam according to a matching result to plan a scanning strategy. The automatic detection process reduces manual participation, is especially suitable for welding seam detection under high-altitude, low-temperature or dangerous working conditions, reduces personnel safety risks, and makes up for the defect that traditional phased array detection lacks surface geometric measurement capability.

This invention discloses an image recognition and correction system based on an optical model and environmental perception, belonging to the field of image processing technology. The system includes an environmental perception module: This module acquires multi-medium refractive index, interface 3D morphology, and initial image data through a refractive index sensor, a 3D laser scanner, and a vision camera. This data is then dynamically corrected and fused from multiple sources to form an environmental perception dataset. The invention constructs an optical model based on the environmental perception data and combines it with an interference compensation sub-model to calculate the light propagation path. This interference compensation sub-model can quantify the interference effects of impurities, temperature gradients, and other interference factors in the medium by analyzing relevant data acquired by the environmental perception module, generating compensation terms that are integrated into the light propagation equation. This corrects the light propagation path, ensuring the accuracy of the light propagation path calculation and providing solid and reliable data support for subsequent image recognition and correction, thus improving the accuracy and quality of image recognition and correction.