163 results about "Spatial Projection" patented technology

The invention relates to the technical field of image analysis, in particular to an ETFE film cutting control method and system based on image recognition, and the method comprises the following steps: enhancing an edge through multi-scale Gaussian filtering, extracting a gray level change rate pixel by a Sobel operator, generating a path segment, outputting a coordinate, calculating a gradient direction, constructing a direction continuous sequence, and recording an angle deviation; a dynamic window judges abnormal fluctuation to trigger calibration, a fluctuation segment vector is replaced to update a motion track, and a B spline is fitted to generate a track output cutting instruction. According to the method, multi-scale Gaussian filtering is combined with Sobel operator enhanced edge extraction continuous pixels, the fracture problem caused by a fixed threshold value is solved, vector space projection constructs a direction sequence to quantify angle deviation, dynamic window range judges fluctuation to trigger calibration, and a vector replacement strategy corrects an abnormal section control point direction. A smooth track is generated through B spline interpolation, mechanical vibration is reduced, and the flexible material cutting precision and the equipment cooperation efficiency are improved.

The invention provides a space projection error analysis-combined 4D millimeter wave radar and visual camera automatic calibration method. The method comprises the steps of constructing a sensor internal reference model; designing a composite multifunctional calibration board and a three-dimensional adjustable holder, performing rigid geometrical relationship modeling, and automatically associating physics-features-coordinates; collecting multi-frame synchronization frame pair data, and performing time sequence fine grit alignment and interpolation compensation to obtain a space-time alignment frame pair sequence; extracting cross-modal spatial constraints of the features and automatically screening and matching point pairs to obtain a high-confidence point pair set; performing point-point constraint and point-point error, point-plane error and pixel reprojection error minimization to obtain a standardized error term; and constructing an overall objective function, and performing spatial constraint and time deviation estimation to obtain corrected external parameters and synchronization deviation. According to the invention, through a full-automatic standardized process, the probability of artificial participation and error occurrence is greatly reduced; and multi-modal and multi-scene high-precision calibration is supported, and the flexibility and robustness are greatly improved.

The invention discloses a method and a system for automatically classifying heterogeneous data based on business deep learning, particularly relates to the technical field of data classification, and is used for solving the problems of limited classification accuracy and insufficient interpretability caused by cross-modal feature entanglement in the existing method. The method comprises the following steps: decoupling and separating an independent feature and a redundant feature vector through a modal implicit feature, generating a noise correction instruction based on orthogonality residual evaluation, carrying out cross-modal noise distribution consistency correction on the redundant feature, quantifying a gradient direction conflict rate in combination with a vector space projection relation, and dynamically adjusting a back propagation path. Fusion path switching is triggered through semantic matching degree and contribution degree balance monitoring, a self-adaptive classification decision boundary function is constructed, and high-precision classification of heterogeneous data and strong generalization adaptation of service scenes are achieved.

The invention relates to the technical field of three-dimensional imaging, in particular to a four-eye structured light stereoscopic vision imaging method, which comprises the following steps of: arranging four cameras and synchronously acquiring multi-view image data with structured light stripes; carrying out image preprocessing and stripe code identification on the obtained four-view-angle structured light image data, and extracting structured light stripe center line positions and corresponding space projection information under each view angle; generating three-dimensional point cloud data of the high-precision target sample by using parallax calculation and a three-dimensional reconstruction algorithm, and completing spatial registration and filtering optimization of point cloud; fusing the point cloud and the light intensity data by combining the reflection intensity information of the multi-view structured light stripes to generate a composite data set containing space and spectral information; and constructing a dense parallax field and executing three-dimensional consistency verification, and generating a high-fidelity three-dimensional reconstruction model with a complete topological relation and sparse shielding compensation capability. According to the invention, the problems of insufficient view angle coverage, shielding area information loss, difficult edge structure matching and the like of traditional stereoscopic vision imaging can be solved.

The invention relates to the technical field of water flow monitoring, and particularly discloses a flow monitoring method and system based on video image analysis and processing. The method comprises the following steps: carrying out communication acquisition of image monitoring and water level monitoring at a plurality of monitoring acquisition sites; performing video frame extraction and image preprocessing; feature point detection and displacement analysis; converting the water surface flow velocity into a plurality of station water surface flow velocities, and performing fitting correction; and calculating station flow data of the plurality of monitoring acquisition stations. Water surface image data are obtained through image monitoring and water level monitoring communication collection of a plurality of monitoring collection sites in combination with video frame extraction and image preprocessing, the site pixel flow velocity is calculated through feature point detection and displacement analysis, the site pixel flow velocity is converted into corrected water surface flow velocity through a space projection model, and site flow data are calculated. Non-contact full-flow monitoring is achieved, the potential safety hazard that equipment needs to be arranged in water in a traditional method is eliminated, the maintenance difficulty is remarkably reduced, and the method is particularly suitable for flow monitoring in flood periods and dangerous water areas.

The invention relates to the technical field of vehicle vision calibration, and discloses a DMS camera calibration method based on computer vision. The method comprises the following steps: acquiring a multi-view original image sequence in a target vehicle cockpit, and synchronously acquiring a camera mounting position, a view angle, an inclination angle and an environment illumination intensity parameter; after distortion correction is carried out on the original image sequence, edge features of a calibration reference object in each frame of image are extracted through image recognition, and an initial calibration matrix containing a mapping relation between pixel coordinates and physical coordinates is generated; constructing a three-dimensional space projection model based on the initial calibration matrix, and adjusting rotation and translation parameters of the model by using an iterative optimization algorithm to enable the error between a virtual imaging position and an actual edge feature to be minimum; and extracting an internal parameter matrix and an external parameter matrix of the optimized model, fusing the internal parameter matrix and the external parameter matrix into a final calibration parameter, and writing the final calibration parameter into a DMS camera firmware storage area. According to the method, the DMS camera calibration accuracy and environmental adaptability are improved, and stable technical support is provided for driver state monitoring.

The invention discloses a three-dimensional engineering quantity calculation method and system based on multi-modal data, a medium and a product, and relates to the field of engineering data computation.The method comprises the steps that two-dimensional engineering drawing data are received, converted into three-dimensional grid data and imported into a 3DMax platform, and a three-dimensional component model is generated; extracting spatial positioning data and component attribute data of each component in the three-dimensional component model, and calculating a spatial projection overlap ratio; classifying the components greater than a preset coincidence threshold value into the same space association group, and generating a plurality of component space groups; calculating and generating a component parameter table; the component codes serve as index keys, the engineering quantity calculation rules are written into associated fields of a component parameter table, and an engineering quantity calculation matrix is generated; identifying an updated target component code; and re-calculating the geometric parameters corresponding to the target component codes based on the 3DMax platform, and updating the engineering quantity data according to the geometric parameters and the calculation rules in the engineering quantity calculation matrix. By implementing the method, the engineering quantity statistical efficiency can be improved.

The invention discloses a waterlogging panorama construction method based on panorama stitching and spatial projection, and the method comprises the steps: image collection and feature extraction: obtaining a multi-view waterlogging image from a monitoring video, and extracting and matching key points to establish a spatial feature relation; panoramic stitching and projection transformation are carried out, a point cloud model is constructed, a projection matrix is generated, multi-view images are stitched into a hexahedral panoramic image, and the calculation efficiency is optimized; spherical mapping and visualization: mapping the panoramic image to the inner wall of the sphere to realize immersive display; target detection and positioning are carried out, a waterlogging area is identified through deep learning, the ponding range is calculated in combination with camera parameters, and accurate monitoring is achieved; and panoramic browsing and dynamic updating are carried out, an interactive panoramic system is constructed, the ponding range and the change trend are displayed in real time, and the emergency response capability is improved. Through fusion of computer vision and space projection technologies, multi-view panoramic stitching and three-dimensional display are realized, and the coverage range, the real-time performance and the visualization capability of waterlogging monitoring are improved.

The invention relates to a trajectory prediction model robustness enhancement method based on dynamic subspace projection decomposition. Comprising the following steps: firstly, extracting hidden layer semantic features containing historical tracks and map topology through a multi-modal feature encoder; secondly, constructing a dynamic routing mechanism based on scene self-adaption, and calculating projection weights of input features on a plurality of expert subspaces; then, executing truncation projection operation based on orthogonal decomposition, retaining core semantics located in a low-dimensional space, and filtering out adversarial disturbance located in an orthogonal complementary space; and finally, introducing a feature consistency constraint training mechanism, taking the reconstructed features of the clean sample as anchor points, and compulsively aligning the purified features of the confrontation sample with the anchor points. Compared with the prior art, the method has the advantages that the robustness of the model in white box gradient attack, black box query attack and physical semantic deception scenes is remarkably improved through feature purification of a physical level and structured consistency constraint, and the prediction reliability of the automatic driving system is ensured.

The invention relates to the technical field of medical teaching assistance, and provides an artificial intelligence-based medical virtual patient simulation system, which comprises a virtual patient generation module, which is used for carrying out pathological fusion analysis on disease model data and an individual difference database based on an artificial intelligence model to obtain personalized pathological feature vectors, and carrying out spatial projection on the personalized pathological feature vectors through a spatial projection algorithm, generating a virtual patient based on the pathological feature vector, wherein the virtual patient is used for indicating feedback of a corresponding clinical operation instruction set; the real-time interaction module is used for acquiring and analyzing a clinical operation instruction set to obtain a virtual physiological parameter disturbance value, and performing dynamic deduction on the pathological feature vector according to the virtual physiological parameter disturbance value to obtain physical sign data of a virtual patient; and the intelligent evaluation feedback module is used for calculating a spatial similarity score of the clinical operation instruction set and the standard data set based on the multi-dimensional evaluation matrix, and generating a clinical operation quality report based on the spatial similarity score and the physical sign data. The quality and effect of medical education and training can be improved.

The invention discloses an intelligent positioning method for a TBM disassembly supporting tool, and the method comprises the steps: installing laser ranging sensors at four corners of a supporting tool frame, forming space projection mapping with a shield body four-quadrant reflection target, collecting target distance data, comparing the target distance data with a pre-stored shield body theoretical axis model, and calculating a deviation value; the controller converts the axial deviation into a hydraulic cylinder stroke instruction to drive the four supporting hydraulic cylinders to conduct cooperative adjustment, when the pressure sensor monitors that the pressure difference exceeds 0.8 MPa, the compensation amount is recalculated, and historical ovality data is called to calculate an inclination angle correction value; the double-inclination-angle adjusting oil cylinder is controlled for compensation and secondary verification, and if the radial deviation range is exceeded, adjustment is returned; after three times of cross validation are completed, a hydraulic cylinder self-locking mechanism and a positioning pin are locked, positioning parameters are encrypted and stored, and a completion signal is triggered. The method is used for improving the positioning precision and efficiency of shield tunneling machine disassembling operation, effectively reduces the contact damage risk between the supporting tool and the shield body, and is particularly suitable for large shield tunneling machine disassembling engineering with the diameter larger than 8 m.

The invention relates to the technical field of perception fusion, and discloses a tug fusion enhanced perception method based on target tracking and obstacle recognition, which comprises the following steps: processing an AIS, an optical fiber compass, a Beidou RTK, a laser radar, a millimeter wave radar and a panoramic camera on a tug to establish a ship coordinate system; and collecting message data of the AIS and combining with the MMSI information to screen the target ship to obtain the initial position of the target ship. And predicting the state sequence of the target ship to obtain the position, speed and heading information of the target ship. And carrying out target identification on the image, outputting identification results of semantic levels of the ship, the buoy and the quay wall, and carrying out space projection alignment with radar data. And fusing the processed results to obtain a fusion result, and performing early warning according to the fusion result. According to the method, the target ship relative pose resolving precision and the obstacle recognition reliability are improved, the sensing link time delay is shortened, and the driver blind area risk is reduced.

The invention discloses a spatial projection regularization method for sound source localization and sound field reconstruction and a related device, and belongs to the technical field of sound source localization. Specifically, according to the method, an equivalent source method model is utilized, and an external radiation sound field of a sound source to be measured is simulated through a series of virtual sources. Then, according to the first sound pressure transfer matrix from the virtual source arrangement surface to the holographic measuring point plane and the sound pressure of the holographic measuring point, a space projection regularization algorithm is used for solving the inverse problem, and therefore the equivalent source intensity is obtained; and then, reconstructing an external radiation sound field of the sound source to be detected by using the second sound pressure transfer matrix and the equivalent source intensity. And finally, by taking the maximum sound pressure amplitude as a standard, screening field points in an external radiation sound field so as to determine the position of the sound source to be detected. According to the space projection regularization algorithm, truncation processing of the vector space is carried out with the projection size of the measurement information in the vector space as the criterion, real information is reserved, and noise interference is restrained to the maximum extent.

The invention provides an automatic space coordinate registration method and device based on a 3D Gaussian splash model, and the method takes RTK data as a strong constraint to be embedded into SFM optimization, and achieves the deep fusion. During coordinate registration, coarse registration and fine registration are combined, scale and global alignment is solved through coarse registration, and detail optimization is achieved through appearance-geometry double constraints in fine registration; finally, a differentiable optimization framework is put forward, the differentiable rendering characteristic of the 3DGS is utilized, joint optimization and deep coupling are carried out on the space projection loss and the normal vector constraint loss of the fine registration loss function and the 3D Gaussian rendering loss function, the registration error directly guides Gaussian parameter adjustment, meanwhile, the model rendering effect reversely constrains the registration precision, and the precision of the 3D Gaussian rendering is improved. And cooperative improvement of registration precision-model details is realized. The 3D Gaussian splash model is not only a result of coordinate registration, but also a participant of registration optimization, and the problems that a traditional method depends on manual registration, and the cross-coordinate system deviation is large are solved.

The invention provides a precision machining and 3D printing mixed manufacturing execution system, and relates to the technical field of data processing, and the system is used for dividing a three-dimensional model into a configuration area and a finishing area, generating a layer-by-layer closed contour path, obtaining configuration path data, extracting a boundary segment close to the finishing area, and obtaining a configuration path data set; calculating a space projection vector on a finishing target surface to obtain primary finishing path data; calculating a boundary torsion value; superposing interference offset in a historical sample path to a primary finishing path; calculating an interference amplitude index; the fitting path data and the configuration path data are subjected to path connection and unified processing according to the manufacturing sequence, and a mixed execution path instruction is obtained. Precise machining and 3D printing are integrated, and path overlapping, empty cutting or unnecessary machining is avoided.

The invention discloses a power distribution system harmonic source positioning method based on subsystem division, and aims to improve the accuracy and anti-interference capability of harmonic source identification in a power distribution system. According to the method, firstly, an obtained voltage signal is preprocessed, frequency domain feature information is extracted, a subspace projection operator is constructed through singular value decomposition, and effective extraction of each harmonic component in the signal is achieved. Then, carrying out subsystem division on the power distribution system according to the position of the tail end measurement point, for each subsystem, respectively injecting simulated harmonic current into each candidate node by adopting a virtual harmonic injection method, and calculating the response of the node to the tail end voltage; and comparing a simulation result with a measured value, constructing an error vector, screening out a node with the minimum error as a backup harmonic source node, and finally positioning the harmonic source node through zero setting of a connection node and a correction strategy of the most downstream node. The method is suitable for a multi-node and multi-source coexistence large-scale power distribution network harmonic suppression scene.

The invention discloses a real-time virtual environment view layout algorithm based on spherical space guidance. The algorithm comprises the following steps that an original view is acquired and preprocessed; abstracting into a circular structure and completely mapping to a constructed spherical view projection structure; weight analysis is carried out, a preset threshold value is compared, a high-weight standard view set and a low-weight standard view set are divided, and dynamic batch layout optimization processing is carried out on the high-weight standard view set; constructing a space pressure function field for the low-weight standard view set, and determining a target position by using a space pressure field guiding method; smooth movement from the current position to the target position is achieved through a Bezier curve interpolation method; and when the viewpoint or view angle change exceeds the threshold value, re-calculating the layout until the change amplitude is smaller than the threshold value, and generating a final layout. According to the method, the spherical space projection and the adaptive mechanical model are combined, the large-scale view layout is optimized, the method has the advantages of being efficient, stable and real-time, and the data visualization effect in the virtual environment is improved.

The invention provides a regional electromagnetic intelligent evaluation method and system based on spectral entropy weighting, and the method comprises the following steps: collecting electromagnetic spectrum data and the motion state of a patrol vehicle, and constructing a virtual aperture data matrix through the motion information; space covariance analysis and subspace projection are carried out on the matrix, multipath scattering interference is separated and eliminated, and a pure field intensity sequence is obtained through reconstruction. By calculating the normalized spectrum entropy of the Doppler power spectrum of the pure field intensity sequence, an inverse proportion weight coefficient representing the signal confidence is generated; and weighting the weight to a pure field intensity sequence, and mapping the pure field intensity sequence to a geographic space. And dynamically adjusting the density of the evaluation grid according to the field intensity gradient, and finally carrying out weighted centroid calculation based on inverse proportion weight to obtain a regional electromagnetic environment evaluation result. According to the method, the technical problem that a regional evaluation result is not accurate due to the fact that multipath components cannot be separated and single-point data quality cannot be evaluated in traditional mobile patrol is solved.

The present invention provides an intelligent adaptive calibration method and system, which relates to the field of calibration technology. The method comprises the following steps: based on real-time motion data, performing spatiotemporal clustering on a real-time asynchronous event stream, and performing time alignment with a current RGB image frame to generate purified event clusters; accumulating the purified event clusters into event grayscale images, and inputting the purified event clusters into a dynamic perception network together with the current RGB image frame to output a static mask; based on the purified event clusters, mapping the event coordinates to the coordinate system of the current RGB image frame, and performing spatial projection filtering in combination with the static mask to form a static feature point set; constructing an objective function based on the static feature point set and performing nonlinear optimization to obtain real-time calibration parameters and calibration residuals; updating motion constraint parameters based on the real-time calibration parameters, and dynamically adjusting the static mask segmentation threshold of the dynamic perception network according to the calibration residuals. The present invention improves the robustness and practicality of a multimodal vision system in complex dynamic environments.

The invention relates to an industrial code reading control method and a high-speed response system based on device collaborative optimization, and the method comprises the steps: synchronizing image data and three-dimensional coordinates of a plurality of visual devices, and generating a multi-view image sequence with a unified timestamp; extracting two-dimensional bounding box coordinates of the target object to establish a motion trail prediction model; constructing a space projection relation by combining the three-dimensional coordinates of the equipment; fusing the multi-view data to solve the three-dimensional position and attitude of the target object; calculating illumination, object distance and motion blur coefficients in real time based on pose parameters, and dynamically adjusting exposure time, gain and focal length of each device; acquiring an image by using the adjusted equipment, detecting a code system area, and performing geometric correction to generate a standardized image; and outputting a code reading result after decoding. And through multi-device collaborative optimization and dynamic parameter adjustment, the decoding success rate and efficiency under complex working conditions are remarkably improved.

The invention relates to the technical field of unmanned aerial vehicles, and discloses a detection method and an electronic device based on a mooring platform unmanned aerial vehicle, and the method comprises the steps: obtaining visible light, infrared, laser radar, positioning and inertial measurement data; constructing a local geographic coordinate system and realizing space projection and time sequence synchronization of multi-modal data; performing dynamic weighted fusion on each modal feature through a multi-modal cross attention fusion network to generate a high-dimensional semantic feature map; and performing target detection and thermal anomaly discrimination based on the feature map. The electronic device comprises a multi-modal sensing unit, a space-time alignment module, a time synchronization module, a multi-modal fusion module and a target discrimination module. According to the invention, through a unified space-time alignment and adaptive fusion mechanism, high-precision and high-robustness comprehensive detection can still be realized under severe conditions such as dark light, haze or shielding, and long-time stable operation is guaranteed by relying on a mooring platform.

The invention relates to the technical field of construction progress monitoring, in particular to a construction progress multi-dimensional dynamic monitoring method based on the Internet of Things and BIM, and the method comprises the following steps: obtaining a component number and a planned time period through the BIM, collecting an action label, a three-dimensional coordinate and space projection matching time, and generating a component behavior set through DBSCAN clustering; the method comprises the following steps: slicing an action sequence to calculate frequency and coverage proportion; classifying component states to generate progress deviation; matching the deviation with a Hungary algorithm to calculate a coupling map; extracting a mechanical track and path included angle, normalizing and correcting the included angle to generate a deviation sequence, and grading track segments to generate a dynamic monitoring index set. According to the method, time-space association is established based on component numbers and coordinate projection, a classification model is constructed by using time slice coverage to identify progress deviation, task chain coupling is analyzed through bidirectional matching, a deviation sequence is generated through included angle correction, a delay amount and coverage rate evaluation system is established, and progress deviation tracing and abnormal early warning are achieved.

The invention discloses a key structure parameter design method for a main driving bearing of an ultra-large type shield tunneling machine, and relates to the field of design of the main driving bearing of the ultra-large type shield tunneling machine. The key structure parameter design method comprises the following steps: acquiring a rock-soil CT image of a stratum, a crack distribution image and working parameters of the shield tunneling machine, and extracting a rock hardness gradient, a crack direction angle and a soil layer non-uniformity index; generating geologic feature data; establishing a circumferential load prediction model according to the geological characteristic data, and calculating an equal angle value and an overturning moment to obtain dynamic load spectrum data; constructing a contact angle distribution function based on the dynamic load spectrum data, and generating asymmetric contact angle three-dimensional curve data; seamless butt joint with CAM is achieved through space projection transformation, the performance of the bearing is finally embodied, finite element analysis shows that stress distribution is more uniform, the service life of the bearing is prolonged, and cutting force and material loss are reduced through technological parameter optimization.

The invention provides a multi-modal session emotion recognition method and system based on missing modal reconstruction. The method comprises the following steps: collecting multi-modal emotion data; the multi-mode emotion data is preprocessed; reconstructing missing modal information for the preprocessed data by using a label coding and feature fusion method; projecting the reconstructed features of the audio mode and the video mode to a text mode space, and training an emotion recognition model; and inputting the reconstructed three modal features into an emotion recognition model for emotion classification. The invention provides a modal reconstruction and text space projection method, and the performance of an emotion recognition model under the condition of modal deficiency is remarkably improved.

The application relates to an additive manufacturing heating power self-adaptive control method based on infrared thermal imaging, which adopts an infrared thermal imaging camera to collect a global temperature field of a printing plane in real time, divides the temperature field into multiple heating sub-regions according to the spatial projection positions of curing lamp tubes, introduces an inter-region thermal coupling coefficient matrix to quantitatively separate the neighborhood thermal crosstalk suffered by each sub-region, extracts intrinsic temperature components reflecting only the heating contribution of each lamp tube, and constructs a real deviation signal after removing the coupling interference. The proportional-integral-derivative algorithm is used to independently calculate the power adjustment increment of each sub-region based on the intrinsic temperature deviation, the amplitude is corrected, and then the pulse width modulation driving signal is converted, so that the differential power self-adaptive adjustment of the lamp tubes at different spatial positions is realized. The scheme decouples the thermal crosstalk, so that the control decisions of each channel are independent of each other, the coupling oscillation caused by the shared heat conduction path of adjacent channels is avoided, and the printing surface temperature uniformity and product forming consistency are improved.

This application belongs to the field of coherent diffraction imaging technology, specifically disclosing an ultra-low dose coherent diffraction imaging method and apparatus. Based on a blind source separation strategy, this application uses principal component analysis to process the acquired diffraction signals, performing noise separation and updating in reciprocal space. This effectively separates mixed noise energy into noise components, thus avoiding crosstalk to the reconstruction process and significantly improving the convergence stability and robustness of coherent diffraction imaging when reconstructing diffraction signals with extremely low signal-to-noise ratios under ultra-low exposure doses. Simultaneously, this application constructs noise components separately for each scanning position and correlates noise components at different positions through low-dimensional spatial projection, achieving non-stationary noise separation. This enables more effective handling of random noise caused by the low quantum efficiency of ultra-short band detectors, thus maintaining extremely high noise robustness and reconstruction accuracy even under ultra-low exposure doses, achieving an effective improvement in resolution.

This invention discloses a hierarchical continuous attractor network based on intrinsic time constant gradients, belonging to the fields of artificial neural networks and cognitive computing. The network includes a spatial input extraction module, multiple continuous attractor layers, a spatial projection module corresponding to each layer, and a wave packet decoding module. Each layer has a preset and fixed time constant during initialization, and the time constants of each layer monotonically increase from the bottom layer to the top layer. The same external spatial input is projected to each layer in parallel. The bottom layer tracks instantaneous spatial changes with a shorter relaxation time, while the top layer accumulates slowly varying spatial statistics with a longer relaxation time. The cyclic connection weights of each layer are initialized with translation-invariant functions to form a continuous attractor manifold, and are fine-tuned online by superimposing Hebbian enhancement and weight decay. This invention can form multi-timescale spatial representations, improving the stability and precision of representations in high-frequency spatial regions.

The application discloses a kind of variable working condition diagnosis methods of rotary reducer based on multi-view transfer, belong to fault diagnosis technical field.The method is first to the multiple visual vibration data collected is preprocessed and constructs variable working condition data set;Through fourier transform, extract each visual spectrum feature;Typical correlation analysis is used to construct embedding class discriminant transferable feature objective function, combined with maximum mean difference technique reduces the distribution difference between training and testing field, and introduces multi-view consistency constraint;Through generalized feature decomposition, solve common subspace projection, extract multi-view features with discriminant and transferability;Finally, nearest distance classifier is used to realize the fault diagnosis under variable working condition.The application effectively solves the problem that rotary reducer has poor generalization ability due to data distribution difference under variable working condition, improves the accuracy and reliability of fault diagnosis.

The invention provides a vehicle positioning method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining first position coordinates of a target vehicle in a satellite coordinate system at a plurality of different moments in a preset time period through a satellite; through a preset transformation matrix, converting each first position coordinate into a second position coordinate in a pixel coordinate system; based on the projection relation between the target vehicle in the pixel coordinate system and the current driving road, whether the second position coordinate at the current moment is reserved or not is determined; if the second position coordinates are reserved, taking the second position coordinates at the current moment as the position of the target vehicle in the preset time period, so as to display a position identifier corresponding to the target vehicle in a map; and if not, deleting the current second position coordinate. Based on the space projection relation between the vehicle and the road, the vehicle positioning deviation is corrected, so that the vehicle position is accurate, and the vehicle positioning visual display is more accurate.

This application relates to the field of plasma physics technology and provides an asymmetric inversion method and apparatus based on a matching mechanism for plasma diagnostics. The method acquires plasma magnetic flux data, observation lines, and measurement integral values. The magnetic flux data is preprocessed to obtain preprocessed magnetic flux data. Based on the preprocessed magnetic flux data, a closed magnetic surface uniquely matched to each observation line is determined. A lower triangular matrix is ​​constructed based on each observation line and the closed magnetic surface. An inversion equation is constructed based on this lower triangular matrix and the measurement integral values. Finally, the inversion equation is solved to determine the parameter distribution values ​​of the plasma. This method achieves three-dimensional spatial projection of the observation lines and magnetic flux, rapidly determining the position of the closed magnetic surface using geometric relationships, thus improving computational efficiency. Simultaneously, it accurately establishes a one-to-one correspondence between the closed magnetic surface and the observation lines, making the ill-posed problem in solving the matrix equations a unique solution, improving the success rate of solving using the stacking method, and significantly reducing computational errors.