660 results about "Fiducial points" patented technology

The invention discloses a point cloud differential defect detection system and detection method based on multi-feature fusion, which are mainly used for high-precision detection of surface defects of a side wallboard of a railway passenger car, and the method comprises the following steps: obtaining datum point cloud data through a designed standard side wallboard model of the railway passenger car, and collecting real-time point cloud data through a laser scanner; preprocessing the obtained point cloud data; calculating the difference between the real-time point cloud and the reference point cloud by adopting a difference method for fusing geometric features such as Euclidean distance, curvature and normal vector, namely calculating the Euclidean distance difference, curvature difference and normal vector difference between the reference point cloud and the real-time point cloud; and a comprehensive abnormal score is generated by further combining a dynamic weight fusion mechanism, and different region characteristics (such as a plane, a curved surface and an edge region) are adapted through dynamic threshold adjustment. According to the method, the defect region is segmented through the clustering algorithm, and the defect area and depth are quantified. The method has the advantages of high detection precision, strong adaptability and good real-time performance, and is suitable for complex surface defect detection in industrial production.

The invention provides a building construction site safety monitoring and early warning method and system based on the Internet of Things, and relates to the technical field of data processing.The method comprises the steps that a three-base-point dynamic topological structure is established in a target monitoring domain, a first datum point is arranged at the extension end of the axis vertical line of a slewing bearing of a tower crane, and a second datum point is arranged at the extension end of the axis vertical line of the slewing bearing of the tower crane; the second datum point is embedded in the radial section of a force bearing flange plate of the hydraulic jacking module, the third datum point is fixedly connected to the intersection joint of a deep foundation pit top beam and a supporting system, and a non-collinear vector set is constructed through three-point coordinate offset; and based on the non-collinear vector group, deformation compensation correction is performed on the dynamic calibration parameter set through a vector space topological transformation algorithm, a topological reconstruction data stream containing a displacement gradient tensor and strain energy density is generated, and a risk situation feature space is constructed based on the topological reconstruction data stream. According to the invention, the intelligent construction safety management is realized.

The invention relates to the technical field of industrial product surface quality detection, in particular to a flexible display module surface defect image recognition method, which comprises the following steps: acquiring a plurality of surface images of a flexible display module under different light sources and carrying out distortion removal processing on the surface images; reconstructing and generating three-dimensional reference point cloud data representing the current curved surface form of the module; re-projecting the distorted image to the ideal rigid plane according to the relationship, generating a plurality of corrected images, and generating a plurality of corrected images to eliminate geometric and luminosity distortion introduced by flexible deformation; obtaining a defect candidate area binary image; and extracting a multi-dimensional feature vector of the defect candidate region from the binary image of the defect candidate region, and classifying the feature vector by using a pre-trained defect classification model to obtain a defect identification result. Through the three-dimensional reference point cloud reconstruction and image re-projection technology, the problem of geometric distortion caused by surface deformation of the flexible display module is effectively solved, and misjudgment and missed judgment are avoided.

The invention relates to the technical field of robot navigation, and discloses a safety inspection robot multi-mode navigation system fused with subconscious learning. The system obtains a visual image, a depth distance, an inertial measurement unit and other multi-dimensional perception data of an inspection environment, performs environment feature extraction to generate an environment semantic topological graph, and constructs a dynamic navigation cost map and a preliminary navigation path according to the environment semantic topological graph. During path execution, the system detects abnormal navigation behaviors in real time, extracts the features of the abnormal navigation behaviors and obtains a first correction coefficient. And the system judges whether the implicit environment semantic identifier is identified, and if the implicit environment semantic identifier is identified, the corresponding path key node is taken as a semantic navigation reference point, a final navigation path is generated through fusion, and a time stamp is recorded. And if the time stamp exceeds the preset tolerance, extracting a corresponding second correction coefficient. And the system combines the basic navigation performance evaluation value, the first correction coefficient and the second correction coefficient to output a multi-modal navigation decision result.

The invention relates to the technical field of image analysis, in particular to a dispensing track optimization control system based on visual template conversion, which comprises a visual template analysis module, a contour point position correction module, a track vector generation module, a multi-parameter linkage feedback module and an optimal path planning module. According to the method, a boundary is extracted through clustering pixel superposition brightness and channel weight, a line segment frequency screening track is counted, feature stability and precision are enhanced through datum line construction, a deviation value is calculated through gradient direction segmentation boundary, a matching degree is improved through tangent point interpolation correction contour, and a weight factor is generated through included angle change and tool parameter normalization. A reference point is optimized through superposition increment, a path fusion tool attribute dynamic adaptation parameter is adopted, a multi-dimensional data fusion visual offset and floating weight real-time adjustment track is acquired, an execution point and an adjustment vector are superposed to calculate a distance matrix, an optimal path is screened through minimum distance and energy consumption, efficiency and consumption are both considered, and the system robustness and execution economical efficiency are remarkably improved.

The invention relates to a transcranial magnetic stimulation high-precision positioning method, device and equipment based on optical navigation. Comprising the steps of selecting non-coplanar reference points based on a three-dimensional brain model of a patient, obtaining image coordinates and physical coordinates of all the reference points, carrying out corresponding point matching through the image coordinates and the physical coordinates, calculating and generating an optimal rigid transformation matrix, carrying out target registration error calculation, and realizing registration of an image coordinate system and a physical coordinate system. And according to the registered brain tissue conductivity parameters, calculating electric field space distribution induced by the transcranial magnetic stimulation coil in a target brain area, dynamically correcting stimulation target point coordinates of the virtual coil, and according to a completed coordinate system registration result, dynamically displaying the position and direction of the virtual coil corresponding to the transcranial magnetic stimulation coil on the three-dimensional brain model. And synchronously updating the brain slice view based on the corrected target point coordinates, and highlighting the actually stimulated brain region boundary. According to the method, adaptive neural navigation is driven through electric field remapping, and compensation target point correction is achieved.

The invention discloses an HDI micro blind hole laser drilling processing method and system, and relates to the field of HDI drilling processing, CO2 laser drilling is firstly carried out on a plate, then UV laser shaping is carried out, finally quality detection is carried out, and the core is that a plurality of local datum points distributed in a matrix mode are preset on the HDI plate to be processed. In the CO2 laser drilling process, the drilling task and the positioning action of the local datum point are executed alternately through a control program. By periodically measuring the actual position of the adjacent local datum point in the machining period, the dynamic position offset generated in the area due to the heat effect can be captured in real time, and the machining coordinates of the follow-up target drilling point in the area can be corrected in real time through the offset. The continuous local dynamic compensation effectively overcomes the dynamic thermally induced deformation problem which cannot be handled by the traditional single global correction, so that the drilling precision in the large-size and high-density machining process is ensured.

The invention discloses a terminal crimping quality detection method and system, and relates to the technical field of terminal crimping image detection. Comprising the steps that space coordinates of a standard datum point in a crimping image are determined, and the standard datum point is used for representing the space coordinate position, meeting the standard terminal crimping inspection standard, between a corresponding wire and a terminal notch. According to the method, the crimping samples which do not meet the standard terminal crimping inspection standard are rapidly removed in a spatial positioning mode, and then the crimping sample thermal imaging images which do not meet the standard terminal crimping inspection standard are obtained on the crimping surfaces of the crimping samples by means of trigger logic. According to the method, the crimping samples are detected, the invisible faults of the crimping samples are judged based on the set standard terminal crimping inspection standard, and finally different commands are input to the crimping equipment according to the types and severity levels of the invisible faults, so that the rapid detection of the crimping samples and the dynamic adjustment of the crimping equipment are realized, and the stability of the monitoring dimension of the crimping quality is ensured.

A reference point is arranged on the ground to calibrate a ground world coordinate system, a robot base coordinate system is established based on robot base features, and a rigid transformation matrix between the two is calculated to achieve spatial alignment. A multi-sensor network is constructed, a visual sensor and a laser radar are associated to a double-reference coordinate system, and data are synchronously collected and unified to the same coordinate system. And according to the spatial consistency error of the data, dynamically evaluating the credibility weight of the sensor, constructing a joint error equation, and based on least square method optimization, weighting fusion data and outputting calibration parameters. According to the invention, the problems of dependence on single sensor precision, lack of a system-level calibration scheme and complex calibration process are solved, and the calibration precision and efficiency of the robot system are improved.

The invention discloses a split type long-focus visible light assembly fog-penetrating compensation method, system and device, and relates to the monitoring technology, and the method comprises the steps: recording clear points of different focusing values according to the focusing feedback value range of a long-focus lens at a specified environment temperature, switching fog-penetrating mode virtual focus, and carrying out the manual focusing on the condition that an image is clear again, recording the offset P1 of the focusing value to obtain a first relation curve of the fog penetration shift of the focusing value; acquiring a change value of an inner focus offset P1 in a target temperature range and a corresponding value of the temperature by taking the specified environment temperature as a reference point to form a second relation curve; and searching based on the first relation curve and the second relation curve to obtain the offset P for compensating the movement of the focusing motor. The method is used for solving the problem of image virtual focus after the split type long-focus visible light assembly switches fog penetration.

The embodiment of the invention provides a ceramic diaphragm automatic positioning system based on high-precision visual feedback and closed-loop control, and the system comprises a parameter reference setting module which is used for setting a theoretical reference point and a visual detection parameter; the real-time visual detection module is used for collecting an image of the to-be-stacked film and outputting an image coordinate of the mark point; the core operation module is used for converting the image coordinates of the mark points into actual coordinates based on the visual detection parameters, reading a theoretical reference point of the current to-be-stacked diaphragm and calculating a position error vector between the actual coordinates and the theoretical reference point, and the position error vector comprises a translation compensation amount and a rotation compensation amount; and the motion control and closed loop feedback module is used for receiving the position error vector and generating a control instruction to drive the workbench to move. According to the system, through parameterized reference setting, real-time visual detection, intelligent error calculation and real-time motion compensation, the technical limitation is effectively overcome, and the lamination alignment precision and efficiency are remarkably improved.

The invention relates to a three-dimensional grid model processing method, computer equipment, a readable storage medium and a program product. The method comprises the steps of performing voxelization on a three-dimensional grid model of a target object to obtain a plurality of voxels corresponding to the target object in a preset reference space; determining the visibility value of the voxel according to the projection information of the voxel under the preset camera visual angle; determining a position relation label of the voxel relative to a reference point according to a communication relation between the voxel and the reference point in a preset reference space; screening out a target voxel from the voxels according to the visibility values and the position relation labels of the voxels; and determining model characterization parameters of the three-dimensional grid model according to the spatial information of the target voxel in the three-dimensional grid model. By adopting the method, the generation precision of the three-dimensional model can be improved.

The invention belongs to the technical field of airport clearance safety, and discloses an airport clearance ultrahigh ground feature extraction method fusing LiDAR point cloud and a panoramic segmentation model, and the method comprises the steps: collecting point cloud data in an airport clearance protection region through employing an unmanned plane airborne LiDAR, and carrying out the noise filtering, outlier elimination and datum point-based elevation standardization; constructing a data set with semantic tags and instance numbers, inputting the data set into a SuperCluster panoramic segmentation model, sequentially executing feature extraction, adjacency relation construction, edge weight distribution, local supervision and super-point aggregation, and outputting a segmentation result with semantics and instances; extracting a highest point in each instance point set, and performing spatial comparison with an inner horizontal plane, an approach plane and a transition plane limiting plane established according to an ICAO standard to obtain an instance category, a highest point coordinate, an intrusion depth and a spatial relationship; and performing three-dimensional visual display on the judgment result through the clearance supervision platform.

The invention discloses a 3D visual guidance steel box girder pushing and position adjusting method based on Beidou positioning. The method comprises the steps that a Beidou positioning device and an inclinometer are installed at a positioning datum point and a horizontal datum point of a steel box girder respectively; feature identifiers are installed on the box girder segments, and visual devices are correspondingly installed on the outer sides of the box girder segments and are used for monitoring three-dimensional displacement of the feature identifiers in the pushing process in real time; monitoring data of the Beidou positioning device, the inclinometer and the visual device are collected in real time, a dynamic three-dimensional model of the steel box girder is established, and the pushing posture and the pushing stroke of the steel box girder are adjusted on the basis of the dynamic three-dimensional model till the current box girder section reaches the designed mileage. According to the method, the dynamic characteristics of the steel box girder are perfected by taking the Beidou positioning data as the reference and utilizing the visual monitoring data and the inclination angle monitoring data, and the steel box girder pushing dynamic three-dimensional model is established, so that the pushing posture and the pushing stroke of the steel box girder can be automatically and accurately adjusted in the pushing process, and the efficiency and the safety of pushing construction are ensured.

The invention discloses a vibration monitoring and displacement identification method for a towering steel structure based on machine vision, and relates to the technical field of towering steel structures. Comprising the following steps: S1, visual acquisition and reference calibration: arranging visual acquisition equipment in the height direction and the circumferential direction of the towering steel structure according to mechanical characteristics of a vertical stiffness mutation region and a dynamic response sensitive part of a geometric asymmetric distribution characteristic of the structure; a three-dimensional coordinate system is established based on a structure installation reference surface, fixed reference monitoring points are arranged in a tower foot symmetric area and a mast antenna root, three-dimensional coordinate data of the reference points are synchronously collected, the collection range completely covers a node concentration area and a key stress part of a structure transparent area, and a continuous image sequence of the structure surface is captured in real time; the resolution and the sampling frequency of the visual acquisition equipment are determined according to the inherent frequency of the structure and the vibration response characteristics, and calibration is completed through reference point coordinates after the equipment is installed; s2, carrying out image preprocessing and feature enhancement; S3, carrying out feature point extraction and trajectory tracking; S4, carrying out vibration displacement calculation and twin fusion; and S5, carrying out multi-source verification and structural state linkage treatment.

A system is disclosed for providing extrinsic calibration of a camera to a relative working environment of a programmable motion device that includes an end-effector. The system includes a fiducial located at or near the end-effector, at least one camera system for viewing the fiducial as the programmable motion device moves in at least three degrees of freedom, and for capturing a plurality of images containing the fiducial, and a calibration system for analyzing the plurality of images to determine a fiducial location with respect to the camera to permit calibration of the camera with the programmable motion device.

The invention discloses a magnetic flux detection method and device. The method comprises the following steps: determining a first position of a target magnet in a to-be-detected product relative to a reference point, a second position of a horizontal axis and a longitudinal axis during measurement of a visual system, and a third position of a magnet center of the target magnet in the visual system relative to the reference point; based on the first position, the second position and the third position, determining a fourth position of the horizontal axis and the longitudinal axis during measurement of the laser displacement sensor; the laser displacement sensor is controlled to move to a fourth position, and a fifth position where the vertical shaft is located and a target reading value of the laser displacement sensor are obtained; based on the fifth position, the target reading value and the target measurement gap, determining a vertical axis position during measurement of the three-dimensional magnetic field camera; based on the first position, the second position and the third position, horizontal axis and longitudinal axis positions during measurement of the three-dimensional magnetic field camera are determined; and acquiring target magnetic flux data at the horizontal axis position, the longitudinal axis position and the vertical axis position. According to the invention, the detection efficiency and detection precision of the magnetic flux can be improved.

The invention relates to the technical field of surface mounting, and discloses an SMT (Surface Mount Technology)-based patch vision correction method, which comprises the following steps: S1, a calibration stage: constructing a double-coordinate system mapping model based on a PCB (Printed Circuit Board) plane, and establishing a nonlinear distortion compensation matrix according to the patch thickness; s2, a pickup stage: a CCD shooting camera is arranged at the top of the suction nozzle, a top CCD is triggered to shoot when the suction nozzle picks up an element, and pin coplanarity data is extracted; s3, a positioning stage: setting a reference point at the top of the PCB, scanning the PCB reference point through a CCD, and calculating a deviation between an actual position and a theoretical coordinate by using an algorithm processor; and S4, compensation execution: the motion shaft system dynamically adjusts the mounting path according to the deviation vector. The visual correction method based on SMT pasting has the advantages of accurate pasting and the like, and solves the problems of pasting position offset, low efficiency and unstable precision caused by factors such as vibration of an element feeder, mechanical transmission errors and thermal deformation of a PCB (Printed Circuit Board) due to dependence on manual calibration in the existing SMT pasting process.

The invention discloses an industrial robot grabbing and positioning system based on computer vision, and relates to the technical field of grabbing and positioning, and the system comprises a projection calculation module which is used for determining a roller direction unit vector of a roller based on a calibration plate image, and constructing a projection data pair based on the calibration plate image and the roller direction unit vector; the data acquisition module is used for generating a one-dimensional cosine curve based on the projection data pair and the candidate angular frequency set of the protection window; the image correction module is used for performing coordinate correction on the pixel coordinates of the calibration plate image based on the one-dimensional cosine curve to obtain a corrected image; the key point extraction module is used for carrying out geometric feature extraction on the correction image to obtain a key point set; and the pose optimization module is used for determining the optimal pose of the calibration plate relative to the camera based on the internal reference matrix of the camera and the three-dimensional reference point set and the key point set of the calibration plate. The grabbing stability and reliability of the robot are improved.

The invention relates to the technical field of automatic plug-in mounting equipment, in particular to a double-reference-point correction method, which comprises the following steps of: acquiring image information of a first reference point and a second reference point arranged on a lower camera module, and determining an actual coordinate when an upper camera is aligned with the first reference point based on the image information of the first reference point; comparing with a preset fixed coordinate value to generate a coordinate system translation correction parameter; calculating an included angle between a connecting line of two points and the X-axis direction based on the image information of the two datum points, and generating a coordinate system rotation correction parameter; according to the method, two correction parameters are integrated to update a plug-in machine coordinate system, a lead screw back clearance elimination operation is adopted to improve the basic positioning precision, a correction effect verification and historical data analysis mechanism is established, a double-reference-point design is adopted for the first time, the problems of coordinate system origin offset and X-axis orthogonality change are solved at the same time, and the precision of the plug-in machine is improved. And the long-term stable operation of the plug-in machine and the consistency among different machines are ensured.

The invention discloses a vibration table test sample real-time deformation monitoring system based on machine vision. The vibration table test sample real-time deformation monitoring system comprises an active modulation light source module, a multi-camera high-speed acquisition subsystem, a real-time deformation analysis unit, a full-field strain field reconstruction module, a motion compensation fusion module and a vibration synchronous control interface. An active modulation light source is synchronous with vibration, and motion blur is effectively eliminated in cooperation with a narrow pulse width design; the multi-camera orthogonal layout is combined with the vibration isolation base, so that stable acquisition of images is guaranteed; and the high-contrast coding datum point and dynamic tracking module accurately obtains the 6-DOF displacement. The rigid body and the elastic deformation can be accurately separated through a digital image correlation method and motion compensation fusion. High-frequency updating of a full-resolution strain field is achieved through multi-scale feature fusion, and monitoring intuition and safety are improved through an online visualization and early warning module. The system can realize high-precision, real-time and full-field deformation monitoring, meets complex vibration test requirements, and provides reliable data support for material and structure performance evaluation.

The invention relates to a global measurement field construction method for a complex scene, and the method comprises the steps: fixedly arranging a plurality of target seats which are suitable for the placement of laser reflection target balls of a laser tracker in the scene, and enabling the target seats to serve as visual reference points; laying a laser tracker station; measuring three-dimensional coordinate values of the laser tracker stations and the visual reference point and laser interference ranging values of the laser tracker stations and the visual reference point, and obtaining measurement data of the visual reference point under different laser tracker stations; the method comprises the following steps: constructing a spatial transformation relationship among station coordinate systems of laser trackers, converting measurement data of the laser trackers to a global coordinate system, and constructing a global measurement field; and carrying out adjustment optimization on the obtained global measurement field. According to the method provided by the invention, high-precision measurement field construction oriented to large-size complex-structure parts is realized, the precision and robustness of coordinate calculation are improved, and the problem that traditional measurement field construction in a complex scene is easy to block is effectively solved.

The invention discloses a self-adaptive alignment method of a chip substrate, and aims to solve the problem of high-precision alignment of a chip and a driving substrate in display panel manufacturing. Obtaining an initial dot matrix of the first substrate chip array through a visual sensor, determining a target sub dot matrix with the highest matching degree with a standard sub dot matrix by adopting a global-local double-layer screening mechanism, and obtaining a regularized intermediate dot matrix through affine transformation; then, density-distance two-dimensional threshold dynamic clustering is utilized, a clustering threshold is adaptively adjusted based on kernel density estimation, noise points are removed, and a processed dot matrix is obtained; the method gets rid of traditional marking dependence, utilizes a dynamic threshold to adapt to different dislocation scenes, realizes multi-feature angular point positioning to improve robustness and reduce angular point positioning errors, finally fuses topology centrality and geometric features, determines angular points through a weighted voting mechanism, takes the angular points as alignment reference points, and remarkably improves bonding precision and production efficiency.

The invention relates to the technical field of spring quality detection, in particular to an online intelligent detection method and system based on a spring integrated punch forming part, and the method comprises the steps: marking a plurality of reference points, and preparing a conical blank; determining whether the pre-pressed inner circle is qualified or not based on the first ring distance standard deviation, and determining whether the pre-pressed outer circle is qualified or not based on the second ring distance standard deviation; the pressure distribution of the male die in the main pressing process is adjusted based on the judgment result that the deviation of the pre-pressing inner circle and the deviation of the pre-pressing outer circle are consistent; preparing a semi-finished spring, determining a plurality of cone generatrixes, and compensating a mold gap according to the angle deviation proportion of the cone generatrixes; preparing a finished spring, and optimizing pressure distribution according to the thickness standard deviation of the finished spring; the system comprises a data acquisition module for acquiring data, a data preprocessing module for preprocessing the acquired data, and a detection control module for controlling an online detection process. The production quality of the spring is improved.

The invention discloses a navigation method of a surgical instrument, equipment, a medium and a program product, relates to the technical field of surgery, and discloses the navigation method of the surgical instrument, comprising: acquiring a calibration module DR image and a calibration module optical image; based on the imaging position of the mark point in the DR image of the calibration module and the imaging position of the mark point in the optical image of the calibration module, determining a conversion matrix between an optical tracking system coordinate system and a DR imaging plane coordinate system, and recording the conversion matrix as a first conversion matrix; the surgical instrument is tracked through the optical tracking system, the instrument feature points of the surgical instrument are projected to the DR image of the patient based on the first conversion matrix, the actual position of the surgical instrument can be presented in real time in the DR image of the patient on the basis of not depending on three-dimensional CT image equipment, and therefore the surgical precision and the operation convenience of a doctor are improved.

The invention discloses a process manufacturing method of a cut image, which belongs to the technical field of laser cutting, and comprises the following steps of: acquiring a grid area covered by a cut graph of a material to be processed, dividing the cut graph into a plurality of vector diagrams according to the grid area, and performing slotting compensation processing on each vector diagram to obtain a corresponding cutting track; obtaining attribute information of the multiple primitives, determining a reference point of the vector diagram according to the attribute information of the primitives and the cutting trajectory, determining a light-off position on the primitives according to the reference point, the included angle and the vertex, and performing path optimization on the vector diagram according to the light-off position and the cutting trajectory to obtain a target cutting trajectory, the laser machining parameters of the cutting pattern are set based on the target cutting track and the to-be-machined material, hole blasting or hole punching caused by unstable laser of the cutting starting point can be prevented, it is guaranteed that the cutting effect of the to-be-cut material is optimal, the size precision meets the requirement, and the laser cutting efficiency is also improved.

The invention relates to the technical field of machine vision detection, in particular to a protein chip automatic quality inspection method based on machine vision and related equipment.The method comprises the steps that parameter information and image data are obtained, communication connection is established, mechanical motion errors are compensated through datum point positioning, images are preprocessed and spliced, and defect types are recognized. And outputting an analysis conclusion and establishing closed-loop feedback and data tracing. According to the method, the protein chip quality inspection automation is realized, the detection precision and efficiency are improved, the problems of large error, low efficiency and data non-traceability in traditional manual detection are solved, and reliable quality control technical support is provided for industrial production.

The invention belongs to the technical field of coal mine underground safety production monitoring, and discloses a multi-mode intelligent identification method and system for bending deformation of a fully-mechanized face top plate, and deformation monitoring and early warning of the fully-mechanized face top plate are achieved by fusing two-dimensional images and three-dimensional point cloud data. The method comprises the following steps: firstly, splicing images of adjacent cameras to form a roof panorama, and identifying two-dimensional deformation characteristics such as cracks through an improved YOLOv8 model; synchronously processing point cloud data acquired in real time, obtaining stable key points through information entropy screening and clustering, and then performing cloud registration with the reference point by using an ICP algorithm to obtain three-dimensional deformation characteristics of the roof; then, performing alignment and bidirectional verification on the two-dimensional and three-dimensional deformation features to obtain a fusion result; finally, the result is compared with a preset threshold value, and grading early warning is triggered. According to the method and the system, multi-mode accurate sensing and safety early warning of the roof state are realized.

The invention discloses a rivet neglected loading detection method and system based on CAD digital-analog point cloud mapping, and the method comprises the steps: 1, carrying out the collection and preprocessing of an aircraft panel rivet image, and constructing a data set; 2, inputting an aircraft panel rivet image in the data set into the target detection model to obtain a rivet centroid coordinate; 3, performing coarse positioning and fine positioning on the rivet; 4, sending the fine positioning area to a detection head of the target detection model to obtain a predicted rivet neglected loading result, constructing a total loss function by using the real rivet neglected loading result and the predicted rivet neglected loading result, circulating the steps 2 to 4, and minimizing the total loss function until the total loss function is converged; and 5, detecting rivet neglected loading by using the target detection model and the semantic segmentation model on the equipment end to obtain a detection result. According to the method, deep fusion is carried out on point cloud geometric feature analysis and a combinatorial optimization method, a closed-loop coarse registration process without manual intervention is formed, and the workload of manual reference point selection is reduced.

The invention discloses a soft soil foundation structure visual monitoring network and navigation system synchronous settlement early warning method, and relates to the technical field of geological monitoring and investigation. The soft soil foundation structure visual monitoring network and navigation system synchronous settlement early warning method comprises the steps that S1, image data, time signal data and environment data in the soft soil foundation monitoring process are collected and preprocessed, and a standardized soft soil foundation state data set is constructed; s2, evaluating the spatial offset characteristic of the reference point, and dynamically adjusting the stability identifier and the subsequent replacement trigger condition of the reference point; s3, analyzing the image semantic consistency of the candidate reference points, and screening stable replacement points; s4, the coordinate consistency of the replacement reference points is evaluated, and the spatial positions of the reference points are dynamically corrected; and S5, performing difference comparison on the multi-base-station monitoring data after rollback correction, and repairing curve abrupt change. The problems that the visual reference is prone to drifting and an automatic repairing mechanism is lacked under the condition that the reference point in the soft soil foundation is unstable are solved.