60results about How to "Heavy calculation" patented technology

The invention relates to the technical field of electric power data acquisition with an encryption function, and discloses an electric power data acquisition terminal with an encryption function and a method. By combining the environment data and the equipment state, the encryption process enhances the security and adaptability of data encryption. Environment and equipment data input ensures that encryption results are different, and potential safety hazards caused by static data sources are avoided. The data are reasonably combined through a seed generation formula, it is ensured that the seeds have enough randomness, and the brute force cracking risk is reduced. The key generation strategy generates a unique key through a seed, so that the attack resistance of the system is improved. The key matrix and random number generation strategy improves the unpredictability of the encryption algorithm. And dynamically updating the encryption matrix to prevent the encryption matrix from being cracked in long-term use. In the whole process, comprehensive protection of the data in acquisition, encryption and transmission is ensured, and the data is effectively prevented from being tampered or stolen.

The invention discloses a three-dimensional color modeling method and system based on multi-sensor fusion, and the method comprises the steps: obtaining monocular vision pose information, an RGB image and radar three-dimensional point cloud information, enabling the monocular vision pose information to be used for correcting a radar pose, and generating corrected point cloud information; the corrected point cloud information is screened and then projected to a specific plane; proper feature points are extracted from the projection image and the RGB image, and according to the corresponding relation between the feature points of the projection image and the RGB image, the plane point cloud of the projection image and the pixel coordinate plane of the RGB image are registered; performing fusion modeling on the point cloud and the image data by using an MRF model; according to the method, the radar pose is corrected by using visual pose information, the accumulated error influence of a system is reduced, the corrected point cloud is projected to a plane, and feature points of a projection image and a color image are extracted to establish an MRF model for describing the relationship between a pixel plane and the corresponding point cloud, so that a point cloud image which is uniformly distributed in space and contains color information is obtained.

The invention discloses a sow oestrus behavior recognition method and system based on multi-modal feature fusion, and the method comprises the steps: S1, collecting sow monitoring video and audio data, extracting sow oestrus video segment information, matching audio information of a corresponding time segment according to the sow oestrus video segment information, and carrying out the matching of the audio information of the corresponding time segment; preprocessing the data of the video segment information and the audio information to construct a data set; s2, constructing a deep learning algorithm model for sow oestrus behavior recognition by adopting a multi-modal data fusion method; and S3, obtaining a final state prediction result from a to-be-identified data set through the deep learning algorithm model for sow oestrus behavior identification, and obtaining whether the sow is in an oestrus state or not according to the prediction result. According to the invention, accurate identification of the oestrus behavior of the sow is realized.

The invention relates to the technical field of data processing, and particularly discloses a data processing method of cloud computing based on artificial intelligence, comprising the following steps: S1, calculating the average number of data packets on the same time node in different calibration periods, generating a first coordinate point, and fitting to obtain a first curve; s2, dividing the judgment period to obtain sub-periods, acquiring the number of data packets transmitted by a port in real time in the sub-periods, and drawing a curve; s3, real-time flow and comparison flow are calculated, and flow points in the coordinate system are determined; connecting the flow points to obtain a flow line, determining a flow angle, and determining a radian value of the flow angle; obtaining a flow triangle based on the flow point, and determining the area of the flow triangle; and S4, calculating an abnormal coefficient, screening the to-be-determined port according to the abnormal coefficient, and determining whether the to-be-determined port is abnormal or not. According to the method, the to-be-determined ports are screened, so that the consumption of computing resources required for carrying out abnormity judgment on all the ports is reduced.

The invention relates to a hyperspectral image classification method and device based on wavelet transform and visual ViT, and belongs to the technical field of image processing and computer vision. The method comprises the following steps: carrying out wavelet transform on an image block to generate a plurality of wavelet sub-bands, splicing along a channel to generate a new 3D representation, extracting a feature map with local context information by using 3D convolution, executing self-attention mechanism learning by using a visual ViT encoder to learn long-range dependence, and finally classifying to obtain a classification map. According to the method, the wavelet transform and the visual ViT are combined, so that the classification quality can be guaranteed, and the calculation efficiency of the hyperspectral image classification model based on the visual ViT can be remarkably improved.

The invention provides a distance measurement curve drawing method and a vehicle, and the method comprises the steps: obtaining distance measurement data collected by a vehicle distance measurement sensor, carrying out the data processing of the distance measurement data, and obtaining a first coordinate point set of obstacles around the vehicle in a pre-constructed rectangular coordinate system; and converting each first coordinate point in the first coordinate point set from a rectangular coordinate system to a polar coordinate system to obtain a second coordinate point set, determining a curve parameter for drawing a Bezier curve according to the second coordinate point set, and drawing the Bezier curve corresponding to the ranging data according to the curve parameter. According to the method, the curve parameters are directly determined through the coordinate values of the obstacles under the polar coordinate system, so that drawing of the Bezier curve is controlled, it is avoided that the Bezier curve is drawn in a loop iteration mode in the traditional drawing process, consumption of computing resources in the Bezier curve drawing process is reduced, and the drawing efficiency of the Bezier curve is improved. The calculation burden and drawing calling times of the image processor of the vehicle end are reduced, and the vehicle end performance is improved.

The invention belongs to but not limited to the technical field of laser welding numerical simulation, and particularly relates to an adjustable annular light spot modeling method and system.The method comprises the steps that a center light beam and an outer ring light beam are discretized, points of the center light beam on a point focal plane are generated, points meeting Gaussian distribution within a certain range are generated, the points serve as one point on a straight generatrix, and the point on the straight generatrix is obtained; generating a straight bus; generating points of the outer ring light beam on the ring focal plane, generating a certain range of points conforming to Gaussian distribution, expanding the generated points to an outer ring region, and calculating coordinates, corresponding to the ring focal plane, on a beam combining surface according to the transformed coordinates and the radius of the beam combining surface of the outer ring light beam and the central light beam; according to each generated point, generating points at certain circular intervals by taking the distance from the point to the center as a radius; the positions and directions of the generated points are recorded, and each beam of discrete light is endowed with certain energy.

The invention discloses a bonding wire defect detection method based on point cloud. The method comprises the following steps: detecting and positioning integrated circuit image information through a YOLOV8 network; enabling the position detected by the YOLOV8 network to correspond to the point cloud range of the three-dimensional point cloud marking network, and marking the point cloud in the position range as the point cloud of interest; importing the point-of-interest cloud into a bonding wire welding spot extraction network for detection and classification of bonding wires, welding spots and substrates; and carrying out plane fitting on the point cloud of the substrate, and detecting the arch height and span of the bonding wire welding spot. According to the invention, the welding spot bonding wire is directly positioned to a point cloud within a certain range through a two-dimensional positioning and three-dimensional detection technology, so that the detection speed of the welding spot bonding wire is improved; the provided abnormal point elimination network improves the detection precision of the arch height and span of the bonding wire welding spot; a calculation model based on Euclidean is provided, and a space rectangular coordinate system is established; and calculating the arch height information of the bonding wire according to the difference between the vertex center of the bonding wire and the mass center of the welding spot in the Z-axis direction.

The present invention provides a speech recognition method, device, equipment and storage medium, comprising collecting audio signals; preprocessing the audio signals to obtain target audio signals; extracting target acoustic features of the target audio signals; using a dynamic time warping algorithm to perform similarity matching between the target acoustic features and pre-stored reference acoustic features, and outputting the target acoustic features with the highest similarity as results; wherein the step of preprocessing the speech signals comprises pre-emphasizing the audio signals, and performing non-overlapping framing on the pre-emphasized audio signals to obtain a plurality of non-overlapping signal frames, adding a connection frame to the front end or the back end of each signal frame, and windowing each signal frame after the connection frame is added, so that the frames are non-overlapping and coherent, thereby ensuring the validity of the acoustic features and greatly reducing the computational complexity.

The present application discloses a method, device and storage medium for positioning a mobile terminal based on satellites, including: determining a first mobile terminal, and using the first mobile terminal to send a first positioning signal to multiple first satellites respectively; when multiple first satellites respond to the first positioning signal, multiple first satellites respectively send a first return message to the first mobile terminal; based on the first return messages of multiple first satellites, calculate the first distance between the first mobile terminal and each first satellite; use the first mobile terminal to send a second positioning signal to the second satellite, when the second satellite responds to the second positioning signal, the second satellite sends a second return message to the first mobile terminal, wherein the second return message contains a predetermined first error information; and use the first error information and the first distance to determine the second distance. The technical effect of reducing the amount of calculation of the mobile terminal and improving the technical efficiency of the mobile terminal is achieved.

The invention relates to a personnel detection method and device, an electronic device and a storage medium, and the method comprises the steps: obtaining to-be-analyzed module length data transmitted by a wireless device; wherein the wireless device and the wireless signal detection device are a pair of wireless signal receiving and transmitting devices constructed in advance; calculating the variance of the to-be-analyzed modulus length data to obtain an initial variance calculation result; calculating the variance of the initial variance calculation result to obtain a quadratic variance calculation result; performing statistics on the initial variance calculation result and the quadratic variance calculation result to obtain a target variance calculation result; and when the target variance calculation result is greater than a preset threshold value, determining that the personnel exist in the personnel detection area. According to the invention, the problems of inaccurate personnel detection and large calculation amount are solved, the accuracy of personnel detection is improved, and the calculation amount is reduced.

The present invention provides a method for correcting residual range motion of synthetic aperture radar images, which can be applied to the field of synthetic aperture radar imaging self-aggregation technology. The method includes: in response to determining that there is pixel offset in the image to be processed, preprocessing the image to be processed to obtain an initial image corresponding to the image to be processed; dividing the initial image to obtain multiple initial sub-images; calculating the autocorrelation normalized cross-power spectra corresponding to the multiple initial sub-images to obtain initial pixel offset data corresponding to the multiple initial sub-images; generating target pixel offset data based on noise data of the initial pixel offset data corresponding to the multiple initial sub-images; obtaining residual range motion corresponding to the initial image according to the target pixel offset data; and performing residual range motion correction on the initial image to obtain a corrected image corresponding to the initial image. The present invention also provides a method, apparatus and device for correcting residual range motion of synthetic aperture radar images.

The present invention belongs to the field of electromagnetic wave technology, and discloses a very low frequency scattering method of anisotropic ionosphere in medium and low altitude based on the transmission matrix method. The present invention establishes a low ionosphere layered model structure considering the anisotropy of the ionosphere. First, the transmission matrix of the anisotropic layered structure is derived and verified. Then, based on the transmission matrix, the scattering characteristics of the very low frequency electromagnetic waves in the above-mentioned ionosphere layered structure under different conditions are accurately calculated, and the propagation law is summarized. This work provides a reliable calculation model for the propagation of very low frequency in the low and medium ionosphere, and greatly improves the accuracy of its propagation and scattering parameter calculation. This has important guiding and reference value for studying the propagation of very low frequency electromagnetic waves in the atmosphere.

The present invention discloses a laser altimetry data and high-resolution stereo image registration method and device, the method comprising: obtaining a laser point, a laser footprint image and a stereo image to be registered; taking the laser point elevation as a reference, correcting the reference image and the stereo image to be matched on the current layer of the pyramid to obtain the corrected image; using the sub-pixel phase correlation algorithm and the resolution of the current layer of the pyramid to calculate the geographic offset of the corrected stereo image to be matched relative to the corrected reference image; repeating the correction and offset calculation at each layer of the pyramid until the geographic offset of the stereo image to be matched at the bottom layer of the pyramid relative to the reference image is calculated; completing the positioning of the laser point on the stereo image to be registered according to the geographic offset to obtain the registered image. By implementing the present invention, high-precision registration of satellite laser footprints and high-resolution stereo images is achieved, laying a foundation for using laser high-precision elevation data to assist in improving the application of stereo image mapping.

The present invention discloses a method for correcting the measured values ​​of the parameters of the thermal system of a power station based on automatic differentiation, comprising: constructing a parameter measurement balance relationship model of the thermal system of a power station according to the arrangement of the thermal system and measuring instruments of the power station studied in practice; obtaining the measured value data of each measuring point under a certain working condition, generating the mean and covariance matrix of the measured value; calculating the Jacobian matrix of the residual of the system balance equation with respect to the measuring point variables by the automatic differentiation technology; constructing a constrained optimization problem with respect to the correction amount of each measuring point of the system, solving the correction amount of the measured value of the measuring point; calculating the gross error criterion, judging whether the measured value of each measuring point has a gross error, locating and eliminating the possible gross error; after eliminating the gross error in the measured data, obtaining the corrected measured value of each measuring point variable of the system through the correction amount calculation result. The present invention can speed up the calculation speed of the measured value of the thermal system of a power station and improve the accuracy of the calculation result.

The invention discloses a target detection neural network training method, a trained target detection neural network is improved based on a YOLO v7 algorithm, and the target detection neural network comprises a neck network and four detection heads which are respectively corresponding to a first level to a fourth level of a backbone network.

The invention discloses a post-pond transplanting ridge searching navigation line identification method based on circularity and edge pixel point jump, and belongs to the technical field of ridge culture agriculture visual identification. The method comprises the steps of image acquisition, image boundary smoothing processing, color conversion, threshold segmentation, denoising processing, edge detection, midpoint extraction and navigation line fitting. A depth camera is used for obtaining a depth image, then a traditional RGB image is converted into an HSV image to reduce the influence of an illumination condition on furrow recognition, an H component is used for carrying out next-step processing, threshold segmentation is carried out to obtain a binarized image, a morphological denoising method and an area threshold method are used for removing most noise interference in the image, and the image recognition accuracy is improved. The method comprises the following steps: firstly, performing depth denoising on an image based on circularity calculation, extracting a ridge pit boundary by utilizing edge pixel point jump, then solving a midpoint coordinate point of an image pixel by utilizing abscissas of two boundary points of a ridge pit, and finally realizing navigation line fitting of the ridge pit by utilizing the point coordinates and utilizing a least square method.

The present invention relates to the field of radar detection technology, and discloses an obstacle detection method, device, equipment and storage medium. The obstacle detection method comprises: extracting voxel features from road point cloud information to obtain density-based voxel features and reflectivity-based multidimensional feature vectors corresponding to each voxel in the road point cloud information; obtaining density-based voxel features and reflectivity-based multidimensional feature vectors corresponding to adjacent voxels according to the multidimensional feature vectors; synthesizing the multidimensional feature vectors and the density-based voxel features and reflectivity-based multidimensional feature vectors corresponding to adjacent voxels to obtain target voxel features corresponding to each voxel; performing obstacle detection on the target voxel features through a voxel neural network model to obtain a road obstacle detection result, which does not significantly increase the overall calculation amount of the model, thereby improving the obstacle detection efficiency.

The application discloses a kind of calculation methods for simulating toxic and harmful gas diffusion concentration in three-dimensional virtual training environment, S1, determine toxic gas diffusion effective influencing factor;S2, the physical model corresponding to training environment is constructed, and the effective influencing factor of gas diffusion is derived;S3, according to gas toxic dose and shelter size, sparse grid is divided, and grid density is distinguished;S4, CFD model is constructed, and the concentration of simulated harmful gas diffusion is calculated;S5, concentration value time sequence situation result offline database of a period of time is established, and gas concentration situation result is stored;S6, when training, in virtual environment, quickly display.The method of the present application can consider terrain, building, meteorological conditions and other factors affecting gas concentration diffusion, can measure the gas diffusion concentration value of any point in space in real time, and its diffusion concentration value is realistic and practical, so that the simulation effect of harmful gas diffusion concentration value in virtual reality chemical hazard simulation training environment is more realistic and credible, and the training effect is improved.

The present invention relates to a method for estimating the motion of a surface target, comprising the following steps: a. preprocessing the motion point data of a surface target with low measurement accuracy; b. estimating the motion speed and direction of the surface target. The present invention can accurately estimate the speed and heading of the surface target.

The invention provides a method and system for calculating bushing electric field distribution based on a two-dimensional axial symmetry model, and belongs to the technical field of power equipment simulation, and the method comprises the steps: 1, carrying out the dimension reduction processing of an actual transformer bushing three-dimensional structure according to the actual geometric structure symmetry of a transformer bushing, and obtaining an actual transformer bushing electric field distribution value; extracting a transformer bushing two-dimensional axisymmetric model capable of reflecting the actual structure of the bushing; 2, establishing a temperature field simulation model based on the two-dimensional axisymmetric model of the transformer bushing extracted in the step 1, and calculating the two-dimensional temperature field distribution of the transformer bushing; 3, establishing an electric field simulation model based on the two-dimensional axisymmetric model of the transformer bushing extracted in the step 1, coupling the temperature distribution of the transformer bushing obtained in the step 2 into the electric field simulation model, and calculating the two-dimensional electric field distribution of the transformer bushing; and 4, performing circumferential scanning on the calculation result of the two-dimensional electric field distribution of the transformer bushing, restoring the three-dimensional electric field distribution of the transformer bushing, and obtaining the three-dimensional electric field distribution of the transformer bushing.

The invention provides a multi-modal salient target detection method combining dynamic routing with multiple asymmetric windows, and belongs to the field of image processing. The method comprises the following steps: S1, processing visible light and thermal infrared image pairs by using two parallel neural network branches to form visible light and thermal infrared feature maps of each layer; s2, performing division by using windows with different sizes, and obtaining large feature maps and small feature maps of different layers; s3, applying a dynamic path selection strategy to acquire high-level features after weighted aggregation, acquiring global features and acquiring enhanced features of different layers; s4, the aligned features of different layers are obtained; and S5, combining the zeroth layer of the visible light and thermal infrared feature map to obtain a predicted saliency map. According to the method, features of different layers are dynamically selected and weighted, multi-size window modeling is carried out for correlation of different modes of unaligned salient regions by utilizing a visual attention mechanism, the problem that a data set needs to be aligned in RGBT salient target detection is solved, and the prediction performance is excellent.

The present invention relates to the field of data processing, and in particular to a data processing system for monitoring the safety status of users in a building area. When a computer program is executed by a processor, the following steps are implemented: sampling according to a preset sampling interval to obtain a sampled image data set, and combining a target building area information set to obtain a user safety information set, a first user safety probability set, and a user safety status corresponding to each target building area, and monitoring the user safety status by screening out s sampled images from each target video data, thereby reducing the amount of calculation and improving the monitoring efficiency, and extracting a first image area corresponding to a non-user and a second image area corresponding to a user, as well as the distribution of non-user pixel points and user pixel points in each image area, and combining the weight corresponding to each pixel point to obtain the center of gravity corresponding to each area, so as to characterize the safety status corresponding to the non-user and the user as a whole, thereby improving the accuracy of the monitoring result of the user safety status.

The invention discloses a load control method based on an original energy consumption demand of a user. The method comprises the following steps: constructing an initial load model according to the original energy consumption demand of the user; if the energy supply gap is a conventional energy supply gap, regulating and controlling the load model by adopting a translation method or a segmentation method; if a sudden energy supply gap is formed and a power peak is formed, carrying out peak regulation and control on the load model by adopting ultra-short-term interruption; if the energy supply gap still exists, the energy supply system adopts an interruption control mechanism to terminate load energy supply meeting a user interruption condition, and the load control is ended; and a user energy consumption demand load model at the current moment is introduced into the load model of the load regulation and control, an updated load model is obtained, and next load control is started. The range and degree of load control are completely based on the original energy demand proposed by the user, the control process is on the premise of meeting the user demand, load control is carried out to a greater extent according to the controllable range of the load, and the energy consumption satisfaction of the user is considered.

The present invention provides a statistical energy analysis subsystem identification method based on reduced-order modal energy cluster analysis. First, a modal analysis is performed on a discretized finite element model of a structure to obtain the modal frequency and modal energy of the structure within the analysis frequency band; then, the modal energy matrix is ​​reduced in order using principal component analysis to extract the main features in the modal information; and then, a cluster analysis is performed on the reduced-order modal energy matrix to identify the statistical energy analysis subsystem of the structure. The traditional statistical energy analysis subsystem identification method requires the calculation of multiple load conditions, which has a large amount of calculation, low identification accuracy, and poor calculation stability. The method proposed in the present invention only requires a finite element modal analysis of the structure, and the main modal energy information is extracted through principal component analysis, which greatly improves the identification accuracy of the statistical energy analysis subsystem.

This application discloses a method and system for measuring operating condition information for vehicle energy management control. The method includes: determining the type of operating condition information; quantifying the uncertainty of static information using empirical entropy if the information is static; and measuring the information content of static information by reducing the entropy of empirical entropy; and quantifying the uncertainty of dynamic information using information entropy if the information is dynamic; and measuring the information content of dynamic information by reducing the entropy of information entropy. According to this method for measuring operating condition information for vehicle energy management control, by classifying the operating condition information and measuring static and dynamic information using empirical entropy and information entropy respectively, the operating condition information can be measured in a standardized manner.

The application provides a driver output current detection method, which comprises the following steps: recording data and calculating average value and waveform sinusoidal degree according to the above method after the system reaches steady state; if the difference between the calculation result of the measured driver output current and the reference data of the detection equipment is within a reasonable range, the test is qualified, otherwise the test is unqualified. The application adopts a phase-locked loop method to determine the current zero-crossing point, and adopts an equivalent approximate method to measure the harmonic distortion rate and compare the transient error of the reference waveform to judge the waveform sinusoidal degree, so that the calculation efficiency and accuracy are improved from the above aspects.

This invention belongs to the field of path planning, specifically relating to a method for obtaining the shortest path between nodes. The method first obtains the sets of cut vertices on the original graph through several traversals, and then maps the cut vertex set subgraphs corresponding to these sets of cut vertices into a high-level tree of nodes. Preprocessing and parallel shortest path queries are then performed using the high-level tree with the cut vertex set subgraphs as the smallest unit, thereby obtaining the overall shortest path. This method transforms the shortest path analysis for a large number of nodes in a topologically complex original graph into a shortest path analysis for cut vertex sets. It eliminates a large number of useless nodes when obtaining the shortest path, saving related calculations and reducing computational load, thus improving the speed of shortest path acquisition. Furthermore, preprocessing is performed on the subgraphs formed by cut vertex sets, avoiding the computationally cumbersome problem of directly obtaining the shortest path for complex topological structures of large subgraphs.

The present invention belongs to the technical field of household appliance identification, and discloses a non-invasive electrical appliance identification method, system, medium, equipment and terminal. The current of the electrical appliance is synchronously sampled by using a current transformer and a voltage zero-crossing detection circuit; the synchronously sampled current data is processed by using an MCU to obtain the parameters of the fundamental phase of the current, the amplitude ratio of each harmonic to the fundamental wave, and the energy ratio, and the characteristic quantity of each electrical appliance is calculated by using the current parameters; the type of the electrical appliance that has changed is determined by extracting dynamic characteristic values ​​from the changing data, and the type and quantity of the current electrical appliance are intelligently identified by combining accumulation and CUSUM. The present invention takes into account low cost, low power consumption, and high recognition accuracy, and is easy to industrialize and promote; it has a learning function, can autonomously learn new electrical appliances, and the identification of electrical appliances is not limited to the types of electrical appliances built-in at the time of leaving the factory; training a small amount of data for a single electrical appliance can accurately identify the combined electrical appliances.

The present application discloses a method, device, equipment and storage medium for calculating a diffusion angle coefficient, which relates to the field of high temperature engineering. The method comprises: a processing device determines multiple radiation surfaces of a target space, selects an sth radiation surface and a kth radiation surface from the multiple radiation surfaces, determines an hth radiation surface from the multiple radiation surfaces, the hth radiation surface, the sth radiation surface and the kth radiation surface are different radiation surfaces, determines the occlusion between the sth radiation surface and the kth radiation surface by judging the positional relationship between the sth radiation surface, the kth radiation surface and the hth radiation surface, and calculates the diffusion angle coefficient according to the occlusion. The method can reduce the amount of calculation and improve the calculation efficiency.