1346 results about "Coordinate mapping" patented technology

The invention relates to the technical field of unmanned aerial vehicle control, in particular to an unmanned aerial vehicle autonomous obstacle avoidance decision-making method and system based on multi-source sensor fusion, and the method comprises the steps: achieving the time-space synchronization of a laser radar, a visual camera and a millimeter-wave radar through timestamp alignment and coordinate mapping, and constructing a dynamic obstacle grid map; fusing multi-source data based on a dynamic Bayesian network, and dynamically adjusting the confidence coefficient weight of the sensor in combination with the environment illumination intensity and the barrier surface material; and adopting a reinforcement learning model to generate an incremental obstacle avoidance strategy, and triggering a grading response instruction according to the risk assessment grade. The problem of fusion errors caused by spatial-temporal asynchronization of multi-source sensor data is solved, and the real-time obstacle avoidance success rate of dynamic obstacles is increased.

The invention provides a time division multiplexing multi-parameter synchronous sensing method and system based on a multi-core optical fiber. A multi-core optical fiber containing three heterogeneous fiber cores is embedded into a measured object, and a distributed reflection grating array forming an inclined angle with the axial direction is inscribed on the surface of each fiber core; energy exchange data between modes of all fiber cores and reflection grating wavelength shift signals are synchronously collected by adopting a time division multiplexing technology, phase difference signals are extracted through a cross correlation algorithm to serve as curvature reference values, dynamic compensation operation is carried out on the wavelength shift data and the phase signals, and accurate strain distribution is obtained after temperature interference is effectively eliminated; a coordinate transformation model is established by combining the three-dimensional geometric parameters of the spiral optical fiber, vector synthesis is performed on the curvature reference and the strain parameters, and accurate reconstruction of the three-dimensional deformation field of the measured object is realized. According to the technical scheme provided by the invention, through multi-core fiber multi-parameter synchronous sensing and three-dimensional coordinate mapping, temperature self-compensation high-precision three-dimensional deformation field real-time reconstruction is realized.

The invention discloses a point cloud data rapid processing system based on 3D vision, and relates to the technical field of point cloud data processing. The binocular acquisition module generates an anti-interference high-precision point cloud; the preprocessing module is used for reducing noise and dimensionality and retaining key geometric features; the hierarchical feature extraction module fuses curvature weight and a non-maximum suppression strategy, and improves the robustness of an ORB algorithm in rotation, scale and noise scenes; the industrial scene segmentation module accurately separates stacked objects through normal vector clustering and a dynamic region growing algorithm, and secondarily verifies boundaries in combination with a lightweight semantic model; the two-stage registration module dynamically adjusts a threshold value based on error feedback to realize pose optimization from coarse registration to fine registration; the coordinate mapping module establishes a space mapping model through multi-attitude calibration and robot multi-axis linkage trajectory optimization. The problem that in the prior art, a 3D machine vision algorithm is high in time delay is solved, the real-time performance and rapidity of 3D model recognition and feature extraction are improved, and the efficiency requirement of industrial production is met.

The invention provides a self-adaptive visual sense and force sense fusion microscopic positioning control method and system. The control method comprises the following steps: capturing an image; aligning the dynamic timestamps; carrying out non-linear mapping on a space coordinate system; visual data enhancement and feature extraction; dynamically calibrating the force sense signal; carrying out space-time registration on the multi-modal data; feature fusion based on an attention mechanism; carrying out fusion pose generation and error correction; real-time optimization of reinforcement learning parameters; generating a fuzzy sliding mode anti-interference control instruction; performing dynamic impedance protection and real-time withdrawing; fault recovery; and performance calibration. According to the method, through bilinear interpolation timestamp alignment and nonlinear coordinate mapping based on deep learning, space-time asynchronism and dimension isomerism of vision and force sense data are eliminated, and submicron-level fusion positioning precision is achieved; based on an attention mechanism and force gradient compensation, visual and haptic weights are dynamically distributed.

The invention relates to the technical field of stamping part detection, and discloses a stamping part size and defect synchronous detection method and system. The method comprises the steps that the multi-sensor measurement module is used for collecting line laser scanning morphology data, infrared thermal image strain data and structured light projection contour data of a stamping part; multi-sensor data registration is achieved through a feature point matching algorithm, and a three-dimensional space coordinate mapping relation is generated; calculating the thermal expansion compensation amount of the material in combination with a thermal deformation correction model; filtering the structured light projection contour data, and extracting key contour feature points and defect region boundaries; inputting the related data into a multi-source data fusion model to obtain a dimensional deviation and defect fusion detection result; based on this, a measurement path is updated through a dynamic path planning algorithm, and a synchronous detection scheme is output. The device can synchronously detect the size and defect of the stamping part, improves the detection precision and efficiency, achieves the quality grade classification, and is high in adaptability.

The invention discloses an engineering drawing label identification method and system based on multi-modal information extraction, and the method comprises the steps: obtaining an engineering drawing image, carrying out the preprocessing of the image, and setting a data structure Schema for controlling an extraction target and a relation mode; detecting a drawing label area in the drawing through the trained drawing label detection model to obtain a bounding box coordinate of each drawing label, mapping the detected bounding box coordinates back to a coordinate system of the original image, and cutting out a corresponding drawing label image from the original image; performing text recognition on the cut-out signature image, and extracting text content and corresponding textbox coordinate information; and inputting the clipped signature image and the text recognition result into a trained multi-modal information extraction model, performing information extraction according to a set Schema, and outputting a structured extraction result. According to the method, the extraction target can be flexibly defined, unified extraction of the two-tuples and the three-tuples is supported, and the extraction accuracy is high.

The embodiment of the invention provides an end-to-end automatic driving control method and device based on multi-camera fusion, and multi-view target detection and tracking are realized through spatial transformation and coordinate mapping by combining front wide-angle camera information and left and right wide-angle camera information. A multi-view feature fusion network architecture is designed, the multi-view feature fusion network architecture comprises three sub-networks of feature extraction, dynamic weight distribution and feature fusion, and the fusion weight is dynamically adjusted based on image definition, detection confidence and view overlapping degree. A geometric consistency constraint between visual angles and a reconstruction loss function are introduced, a deep neural network model is constructed, abnormal conditions such as camera shielding are effectively handled, and an accurate control instruction is output. According to the method, the defects of the traditional technology in the aspects of multi-view information fusion, shielding processing and the like are overcome, and the sensing ability and the control reliability of the automatic driving system are remarkably improved.

The invention provides a distortion correction method and system for image projection, and relates to the technical field of image processing, and the method comprises the steps: generating a geometric deformation parameter matrix and a light field attenuation vector of a projection surface through a constructed bidirectional distortion detection model, carrying out the regional analysis of the geometric deformation parameter matrix, and obtaining a curvature feature, dividing a priority correction level through curvature features, and determining a nonlinear compensation factor according to the priority correction level and a light field attenuation vector; constructing a self-adaptive projection network based on the distortion sensitive features of the projection image and the nonlinear compensation factor, and performing reverse coordinate mapping on the projection image through the self-adaptive projection network to obtain an initial correction image; determining an artifact suppression weight map through the high-frequency detail threshold value and the low-frequency smooth threshold value of the initial correction image; according to the invention, geometric deformation parameter optimization and light field attenuation compensation of image projection can be realized, so that the distortion correction precision and the anti-artifact capability are improved.

The invention provides an unmanned aerial vehicle sharing intelligent management method and system based on artificial intelligence, and relates to the technical field of intelligent control, and the method comprises the steps: constructing a space virtual geometric shape through a coordinate mapping algorithm; extracting a geometric center coordinate of the space virtual geometric shape, and calculating an offset between the geometric center coordinate and a communication coverage centroid as a first correction factor; analyzing signal coverage included angle distribution among the three position points, and generating a second correction factor in combination with a path loss model; calculating a multipath effect compensation coefficient as a third correction factor according to the signal attenuation gradient on the virtual shape boundary; fusing the first correction factor, the second correction factor and the third correction factor into a comprehensive correction value; and according to the comprehensive correction value, evaluating a communication interruption risk through a path planning neural network, and generating a multi-path transmission scheme containing a redundant relay node selection rule and a dynamic fragmentation recombination strategy. According to the invention, the communication reliability is improved.

The invention belongs to the technical field of microwave measurement, and discloses an outer wall hollowing microwave reflection detection method based on multi-modal fusion, which comprises the following steps: carrying out multi-modal scanning on a building outer wall to be detected, obtaining visible light image data and infrared temperature distribution data of the outer wall surface, and carrying out space registration and coordinate mapping; a unified multi-modal fusion data set is formed; performing anomaly screening on the multi-modal fusion data set, and identifying a thermal anomaly region by analyzing infrared temperature distribution data; detecting a bump or crack area in combination with texture and morphology anomaly features of the visible light image data; performing information fusion on the thermal anomaly region and the bump or crack region, and extracting candidate detection regions of suspected hollowing; high-precision recognition and quantitative evaluation of the outer wall hollowing are achieved, and the precision and stability of outer wall hollowing detection are improved.

The invention relates to the technical field of defect detection, in particular to a suturing scalpel packaging quality detection method based on optic nerves, which comprises the following steps: collecting suturing scalpel packaging images to perform angular point detection and gradient screening, obtaining alignment parameters under a unified coordinate system, calculating an optical flow displacement initial value and a residual error, and calculating an optical flow displacement initial value; an ROI sub-image is cut to extract a cutting edge contour; an orthogonal projection length is calculated to generate a cutter form mark; texture and shape features are extracted and input into a support vector machine for defect identification; a random forest regression model is called to calculate compensation parameters; according to the method, coordinate mapping is established through angular point detection and gradient screening, displacement is corrected through combination of optical flow residual and depth tracking, a cutting edge contour is extracted through ROI cutting, shape deviation is quantized through orthogonal projection, a classification basis is constructed through texture fusion, defects are identified through a support vector machine, parameters are compensated through random forest regression, and performance is optimized through closed-loop feedback.

The invention relates to the technical field of UI design, can be applied to business scenes such as financial science and technology and medical health, and discloses a page layout method based on display material driving, which comprises the following steps: obtaining page display materials and storing the materials in a material resource library, selecting target display materials and generating a page frame, inserting display blocks of preset elements in the page frame, and displaying the preset elements in the display blocks. Generating visual preview data based on layout parameters of the page frame, outputting the visual preview data to an interface rendering processing module, performing association coding on coordinate mapping data of the page frame and a content identifier of the display block to generate a structured storage file, analyzing terminal feature parameters in the access request, generating an access identifier, and displaying the access identifier to the interface rendering processing module. And generating a target display interface according to the access identifier. According to the method and the device, the association relationship between the display material and the coordinate mapping data and the content identifier is established, and the layout metadata and the rendering parameters are extracted in combination with the terminal features to complete interface generation, so that the adaptation accuracy of structured expression of page configuration and interface output is realized.

The invention relates to the field of computer vision, and particularly provides a table recognition reconstruction method and system, a terminal and a medium, and the method comprises the steps: firstly decomposing a large-size table image into a plurality of overlapped sub-images, and carrying out the table structure detection and OCR character recognition of each sub-image through parallel recognition; then, sub-graph recognition results are integrated through a coordinate mapping and confidence coefficient weighted fusion algorithm, and boundary errors are eliminated; then, automatically distinguishing common cells based on an area clustering algorithm, merging the cells and a header region, and reconstructing a complete table logic structure; further understanding header semantics through a natural language model and repairing identification errors; and finally, realizing intelligent splicing and standardized output of the cross-page table. According to the method, the memory limitation of the traditional OCR technology is broken through, an oversized table can be processed, the recognition accuracy of a complex structure is improved, and the digitization efficiency of professional documents such as financial statements and engineering drawings is improved.

The invention discloses an on-bridge pedestrian abnormal behavior identification and early warning method based on intelligent monitoring, and relates to the technical field of bridge engineering, and the method comprises the steps: carrying out the registration of a current visible light image and a current infrared image, and obtaining a registration dual-mode image based on a current image coordinate system; considering current bridge deformation to establish a current coordinate mapping conversion model for mapping pixel coordinate points in the current image coordinate system to physical coordinate points of a current bridge physical space coordinate system; obtaining the current three-dimensional actual coordinates of the pedestrian; recognizing abnormal behaviors of the pedestrians on the bridge based on the current three-dimensional actual coordinates of the pedestrians and acquiring current dynamic risk score values of the pedestrians; and determining the current risk level of the pedestrian according to the current dynamic risk score value of the pedestrian and a preset risk threshold value to realize multi-level linkage protection response. The method provided by the invention solves the technical problem in the prior art that the current actual coordinate of the pedestrian is difficult to accurately obtain due to environmental interference, and the abnormal recognition of the pedestrian on the bridge is inaccurate.

The invention relates to the technical field of physical education, in particular to a physical education method and system based on multimedia and holographic AR fusion, and the method comprises the following steps: collecting the motion data of a trainee based on a multi-source sensor array, constructing a motion parameterized model, and generating a holographic projection generation module through the cooperation with a standard motion database; a holographic AR teaching image is generated in real time, an environment perception module is combined to carry out adaptive projection on illumination and spatial layout, a spatial positioning module is used to establish coordinate mapping between a trainee and a virtual image, and a multi-channel feedback device is started to output visual, tactile and auditory signals. And finally, comparing the action parameters with the standard action data to automatically generate a training report containing wrong action labels and correction suggestions. According to the method, the motion capture precision and the interactive immersion can be effectively improved, and efficient and extensible technical support is provided for modern physical education and training.

The invention discloses a fresh food quality monitoring method fusing fresh food after-ripening characteristics and logistics data, and relates to the field of food science and technology, and the method comprises the steps: collecting logistics environment data, logistics process data and fresh food ontology data in real time through a distributed sensor network; time stamp synchronization and space coordinate mapping technologies are adopted, space-time alignment is carried out on heterogeneous data with different sampling frequencies, and a unified data matrix is established; the method comprises the following steps: establishing a variable parameter dynamical model comprising variety difference factors, harvest maturity and environment interaction coefficients based on post-harvest physiological mechanisms: dynamically updating model parameters of various varieties in different logistics scenes through a federated learning framework crossing supply chain nodes; when the quality attenuation curve predicted in real time deviates from a preset threshold value, graded early warning is triggered, and logistics parameter adjustment suggestions are generated. According to the invention, full-link accurate management and control of fresh products from a supply chain to a consumption terminal is realized through multi-dimensional technology collaboration.

The invention discloses a submarine cable fault online diagnosis and positioning method and system based on an optical fiber sensing technology, and relates to the technical field of optical fiber sensing, and the method comprises the steps: obtaining a real-time strain data flow of a submarine cable through a distributed optical fiber strain measurement device; carrying out space-time alignment and abnormal value correction processing on the original data set, and constructing a target data set; coordinate mapping is carried out on the target data set and a geographic information system of a submarine cable laying line, and a fault diagnosis layer with multi-dimensional visualization features is generated; an interactive fault analysis panel is generated on a geographic information system interface, and the deviation ratio between the strain theoretical threshold value and the actual measurement value of each monitoring point in the target data set is calculated; according to the submarine cable fault online diagnosis and positioning method and system based on the optical fiber sensing technology, rapid positioning of fault features is achieved, the fault response efficiency is improved, and long-term stable operation of a submarine communication network is ensured.

The invention discloses a joint test system, a silicon carbide metasurface grating detection method and a silicon carbide metasurface grating detection device, and belongs to the technical field of semiconductor detection. A synergistic excitation signal is generated by regulating a light source and a microwave source and is applied to the silicon carbide metasurface grating to be measured to form a light intensity and microwave field interference pattern. The method comprises the following steps: synchronously acquiring data through multiple channels, constructing a multi-dimensional matrix through time alignment, marker feature extraction and coordinate mapping, extracting defect features to establish a reference model, calculating deviation degree to judge quality, and carrying out abnormal point screening, candidate region construction and coupling verification on a defect grating to divide a potential defect region. For a potential defect area, excitation parameters are dynamically adjusted through a gradient descent algorithm, and defect grades are divided by combining the characteristic defect degree and the area. According to the invention, the problems of insufficient single-mode detection, low multi-mode alignment precision and blind adjustment of excitation parameters are solved, cross-band cooperative detection and intelligent grading are realized, and the detection reliability is improved.

The invention relates to the technical field of pipeline inspection, in particular to a defect identifying and positioning method. Comprising the following steps: generating a uniform node feature tensor through coordinate mapping and feature fusion by synchronously collecting a pipeline inner wall image, an ultrasonic echo and an electromagnetic eddy current signal; constructing a space-time heterogeneous feature graph, integrating three types of relationships of a space adjacent edge, a time evolution edge and a semantic similarity edge, and dynamically optimizing a graph structure by utilizing a trainable fusion factor; a heterogeneous edge decoupling convolution and dynamic attention mechanism is designed, space-time semantic features are extracted through channels, neighborhood information is aggregated, and high-resolution defect classification is achieved; based on a classification result and a residual tensor of an original feature, a defect space position is accurately predicted through a coordinate inversion network, and positioning robustness is improved by combining positioning confidence score and weighted aggregation; and finally fusing the equipment track and the pipeline three-dimensional model to realize defect geographic coordinate mapping and interactive visualization. According to the method, the defect identification precision and the positioning reliability in a complex pipeline environment are remarkably improved.

The invention provides an electronic clinical medical assessment method and system for an ophthalmology diagnosis and treatment scheme, and relates to the technical field of medical information, and the method comprises the steps: 1, carrying out the multi-scale edge detection calculation of an input ophthalmology image-text mixed medical record image, and obtaining a medical record image; the method comprises the following steps: extracting a boundary contour of a text labeling area and a hand-drawn lesion schematic diagram through adaptive threshold segmentation and morphological closed operation, and establishing a coordinate mapping table containing text block circumscribed rectangular coordinates, geometric positions of key anatomical mark points of the schematic diagram and symbol spacing characteristics; 2, constructing a two-channel attention gating network based on the coordinate mapping table, fusing the semantic features of the text region and the morphological features of the schematic diagram through a dynamic weight distribution strategy, and generating a multi-modal fusion feature matrix with a spatial alignment relationship; according to the method, through multi-modal feature fusion, triangular verification region confidence regulation and control and three-dimensional topology modeling, analysis and structured output of ophthalmology image-text medical records are realized, and the spatial alignment of diagnosis and treatment information is improved.

The invention belongs to the field of computer vision and industrial defect detection, and discloses a steel coil end face defect detection method and system based on CBAM-BiFPN and multi-loss optimization, and the method comprises the steps: image preprocessing and region extraction: extracting a steel coil end face region through OpenCV and other image processing methods; dividing the high-resolution image into a plurality of small blocks and performing data enhancement; the method comprises the following steps: constructing a YOLOv11 network based on CBAM-BiFPN, introducing a CBAM attention mechanism and BiFPN feature fusion structure, and constructing an improved YOLOv11 detection network; multi-loss function joint optimization training is carried out, and model training is carried out in combination with loss functions such as Focal Loss and WIoU; and fusion of detection results and defect reconstruction output: reconstructing original image defects of all tile image detection results in a space coordinate mapping and redundant region fusion mode, and realizing high-precision overall detection output. Compared with a traditional method, the method still has the high recognition capability in a complex background and low-contrast scene, the detection precision and stability are obviously improved, and higher industrial adaptability and practical value are achieved.

The invention relates to the technical field of electronic component detection, in particular to an IC (integrated circuit) carrier plate detection method based on surface state image extraction, which comprises the following steps: acquiring a gray image, analyzing structural parameters, extracting gradient features, detecting boundary disturbance, integrating the image, calculating an abnormal score, identifying a defect position area, extracting features and outputting an identification result. According to the invention, by analyzing the structure parameters of the bonding pad in the gray level image, calculating the edge line segment, the center coordinate and the spacing, and constructing the two-dimensional coordinate system, the regional positioning reference is enabled to have geometric consistency, the coordinate mapping is combined with the gradient direction change frequency and the continuous aggregation point, the boundary disturbance identification precision is improved, and the image division is executed based on the disturbance region. According to the method, non-functional region mixing is effectively avoided, a clustering and probability model is introduced after region gray level statistics, a deviation scoring mechanism is constructed, gray level feature abnormity is accurately recognized, the discrimination capability of small-amplitude and low-contrast defects is improved, and the selectivity and target focusing performance of feature detection are enhanced.

The invention discloses a high-power microscope intelligent scanning method for a bone marrow smear, which comprises the following steps: S1, automatically dividing a scanning area: acquiring a bone marrow smear image by adopting a front camera, and selecting an optimal scanning area through a multi-dimensional quality evaluation model; s2, intelligent partitioning and focusing point distribution: dividing an optimal scanning area into N * M sub-areas, determining P focusing sampling points by adopting a layered sampling strategy, and establishing a three-dimensional coordinate mapping table; s3, multi-point focusing data acquisition: according to a preset coordinate mapping table, driving an objective table and an objective lens assembly to move to each sampling point in sequence, and constructing an N * M * P-dimensional focusing data matrix; s4, performing focal plane fitting by a least square method: performing three-dimensional plane fitting on the acquired data; and S5, intelligent scanning imaging: calculating the theoretical optimal focal length of each position in the scanning path according to the fitting function, and driving the objective lens assembly to adjust the focal length in real time for scanning imaging. According to the invention, the scanning area identification accuracy and the image definition uniformity are automatically improved in the whole process.

The invention discloses a fixed dual-runway FOD detection method based on multi-source circumferential scanning, and belongs to the technical field of data fusion detection, and the method specifically comprises the steps: synchronously obtaining dual-runway multi-polarization echo data through a fixed circumferential scanning rada; performing time-varying clutter suppression by combining an adaptive clutter cancellation method matched with a dynamic background template and a runway material feature library, and generating a time-frequency domain three-dimensional feature matrix through time-frequency analysis; synchronously collecting and preprocessing image data, and marking a target area through a constant false alarm rate algorithm and image detection; a multi-source data geographic coordinate mapping model is established, data registration and cross validation are completed under a runway physical coordinate system, and real-time tracking of a real FOD target is realized based on radar and image fusion data through multi-dimensional confirmation of radar polarization / micro-motion features and image visual features; according to the method, the FOD detection accuracy and the position identification precision are improved through multi-source data fusion, the false alarm rate is effectively reduced, and a guarantee is provided for safe operation of an airport.

The invention belongs to the technical field of physical field reconstruction, and provides a battery multi-physical field reconstruction method and system based on a physical information radial basis function, and the technical scheme comprises the steps: obtaining the multi-physical field measurement data of the surface of a battery; mapping the obtained multi-physical field measurement data from one-dimensional length coordinates to a coordinate space where the surface of the battery is located; structured grids are constructed on the surface of the battery, corresponding physical information is introduced according to the characteristics of different physical fields, a radial basis interpolation function is obtained by combining the interpolation weight, and physical field measurement data mapped to a coordinate space where the surface of the battery is located are interpolated through the radial basis interpolation function to obtain a corresponding physical field predicted value at any grid. The multi-physics field reconstruction method has high resolution and physical consistency, and solves the problems that a traditional method depends on a complex physical model, is insufficient in interpolation precision and lacks physical constraints and the like.

The invention relates to the technical field of UV printing, and discloses a packaging box UV printing method and device and computer device.The method comprises the steps that feature extraction is conducted on CAD model data of a packaging box, and a feature data set of the packaging box is obtained; carrying out coordinate mapping on the working space of the robot to obtain a conversion matrix and space calibration data of the mounting position of the UV nozzle; edge detection and feature point matching are conducted, and position coordinate data and posture angle data of the UV printing area are obtained; performing multi-section track planning on the ink jet track to obtain initial jet printing track control data; and performing synchronous control calculation on the UV light source to obtain a UV light source power modulation parameter and UV light source trigger time sequence data. According to the method, by dynamically adjusting the power output and the triggering time sequence of the UV light source, uniform curing of the ink droplets is achieved, the problem that curing of the ink droplets at different positions is not uniform is effectively solved, and the printing quality is improved.

The invention relates to the technical field of computer vision and artificial intelligence, and discloses a computer vision-based hundred-million-pixel panoramic situation awareness method and system, and the method comprises the steps: synchronously collecting original local field-of-view images through multiple cameras; independently executing target detection and semantic segmentation in an original image domain; constructing local-to-global coordinate mapping based on the calibration parameters; projecting the target features to a global coordinate system and detecting a cross-view-field target; extracting multi-view-field texture, edge and color features, and performing weighted fusion according to a visible area; according to the method, through identification preposition and semantic level feature fusion, geometric splicing distortion is avoided, the cross-boundary identification precision is improved, the calculation load is reduced, target continuous tracking and situation real-time output in a high-density scene are realized, and the method has high engineering suitability and industrial popularization value.

The invention discloses a printer nozzle real-time vertical calibration method and device based on the visual technology and a storage medium, and relates to the technical field of printers, a camera module collects a calibration plate image, establishes a coordinate mapping relation, prints a calibration pattern and identifies a pixel position, and dynamically adjusts nozzle parameters after converting the calibration pattern into a physical offset. According to the method, automatic high-precision calibration is achieved, meanwhile, the laser displacement sensor and the fuzzy PID controller are combined, the calibration precision and stability are improved, environment compensation, vibration suppression and multi-camera cooperation strategies are introduced, the calibration reliability is ensured, the method is slightly influenced by human factors, the calibration precision and efficiency are improved, errors are reduced, and the printing quality is improved.

The invention discloses a fire-fighting non-destructive detection method based on multi-modal detection, and relates to the technical field of fire-fighting engineering, and the method comprises the following steps: carrying out the rapid scanning of fire-fighting equipment through an ultrasonic array, analyzing and positioning a suspected defect region based on a time domain reflection signal, and generating a three-dimensional coordinate mapping model; and performing multi-angle X-ray projection acquisition on the positioning area, and generating an internal structure cross-sectional image through a three-dimensional reconstruction algorithm. According to the fire-fighting non-destructive detection method provided by the invention, by integrating various technical means such as ultrasonic array scanning, X-ray tomography, thermal imaging analysis and microwave sealing detection, comprehensive and accurate identification of potential defects of fire-fighting equipment is realized, and the dimensionality and precision of defect detection are improved; the structural integrity of the equipment is kept to the maximum extent, extra risks caused by destructive detection are avoided, and the reliability and accuracy of detection are improved through a data fusion algorithm.

The invention provides a virtual imaging method and system applied to virtual shooting, computing equipment and a storage medium, and relates to the technical field of virtual imaging. The method comprises the following steps: synchronously acquiring object surface reflection characteristic data by using a multi-wavelength light source, and generating various imaging parameters through an image feature extraction network; the dynamic attitude data and binocular vision depth information are fused, and virtual and real scene dynamic space coordinate mapping is constructed; calculating the surface reflection intensity distribution of the virtual object in real time through a light propagation simulation module in combination with the specular reflectance and deformation correction parameters, and dynamically adjusting the relative position of the virtual object and the real light source; generating a continuous and smooth shadow boundary transition effect based on a material attenuation model; and performing space-time calibration on the shadow effect by using the dynamic attitude sequence to realize frame-level synchronous rendering of virtual and real light source positions and shadow changes. According to the technical scheme provided by the invention, through optical parameter modeling and dynamic path optimization, the problem of light and shadow distortion of the virtual object in a real scene is solved.