283 results about "Curve fitting" patented technology

The invention relates to the technical field of ocean remote sensing monitoring, in particular to a remote sensing image-based warm discharge water reference temperature self-adaptive extraction method, which specifically comprises the steps of S01, data acquisition and preprocessing, S02, cumulative histogram generation, S03, curve fitting and smoothing, S04, second derivative calculation and S05, reference temperature determination. According to the method, the reference temperature is determined by analyzing the statistical distribution characteristics of the sea surface temperature data field, namely the form of the accumulative histogram, the physical demarcation point of the background water body and the warm drainage area on the temperature distribution is automatically positioned by using the second derivative, the process is completely driven by data, the interference of subjective factors is eliminated, and the accuracy of temperature distribution is improved. The method can automatically adapt to water areas with different geographical forms and different warm drainage diffusion modes, and objectivity and universality of reference temperature extraction are achieved.

The invention discloses a welding seam track identification method for impeller wrap angle welding based on point cloud data, and belongs to the field of machine welding seam identification, and the method comprises the following steps: carrying out filtering, down-sampling and clustering on original scanning point cloud; classifying the point cloud data through a region growing clustering algorithm; determining an optimal interception plane based on principal component analysis, and performing curve fitting on section data to obtain a preliminary main welding seam track; the main welding seam track is projected to a local approximate plane in a segmented mode, and accurate extraction of the main welding seam track is completed; and performing plane fitting and thickness calculation on the wrap angle surface, solving an intersection line in combination with an adjacent local approximate plane, calculating an intersection point of the intersection line and the main welding seam track, and finally generating a wrap angle welding seam track in combination with the direction of the intersection line and the wrap angle thickness. Through cooperative calculation of local plane projection and spatial intersection line solving, the whole process operation from recognition, planning to welding can be automatically completed, and unmanned intelligent welding in the true sense is achieved.

The embodiment of the invention provides a method for determining initial parameters of a transient absorption spectrum kinetics curve, and the method comprises the steps: obtaining an initial absorption point and an absorption attenuation termination point of the transient absorption spectrum kinetics curve, and determining a curve segment between the initial absorption point and the absorption attenuation termination point as a total absorption attenuation interval; carrying out weighting processing on a first-order derivative and a second-order derivative of the transient absorption spectrum dynamic curve to obtain a weighted curvature value sequence; the first N-1 weighted curvature values are selected from the weighted curvature value sequence from large to small, and the total absorption attenuation interval is divided into N absorption attenuation intervals corresponding to curve fitting orders according to sampling points corresponding to the first N-1 weighted curvature values; and determining an initial parameter based on a quantitative relationship of 1 / e of the absorption intensity attenuated to the corresponding interval starting point in each absorption attenuation interval in the exponential fitting model, wherein the quantitative relationship is that the absorption intensity at the interval starting point in each absorption attenuation interval is attenuated to the absorption intensity at the corresponding interval starting point. And the fitting efficiency and accuracy of the dynamic curve are improved.

The invention discloses an AI-based press-fitting curve intelligent analysis and standard curve generation method and system, and relates to the field of press-fitting curve analysis, and the method comprises the steps: constructing an AI classification model and a training set; training an AI classification model by using the training set to obtain a trained AI classification model; performing quality classification on the training set by using the trained AI classification model to obtain a quality classification result; performing standard curve fitting on the press-fitting curve samples with normal quality classification results to obtain a standard curve; and performing quality classification on the to-be-analyzed press fitting curve by using the trained AI classification model to obtain a quality classification result of the to-be-analyzed press fitting curve. The AI intelligent classification diagnosis of the press-fitting curve to be analyzed is automatically realized, manual intervention is reduced, the judgment consistency is improved, and the classification accuracy is improved.

The invention relates to the technical field of fully mechanized coal mining face automation control, and discloses a working face end straightness detection method and device based on a laser radar, and the method comprises the steps: building geometric and radiation references through collecting fixed reference target data; in real-time detection, a displacement vector and an atmospheric attenuation coefficient are calculated by using an instantaneous state of a target, and double-domain dynamic correction of coordinate rigid inverse transformation and intensity threshold adaptive adjustment is performed on an original point cloud. Then, clustering segmentation and slice centroid extraction are carried out on the corrected point cloud, and an ordered feature point set is obtained; and performing multi-factor weighted curve fitting on the feature point set in combination with geometric stability and environmental credibility, constructing a form fitting curve, and outputting a straightness deviation quantitative index according to a comparison result of the curve and an ideal reference straight line. According to the invention, the interference of equipment vibration and dust attenuation on measurement is eliminated, and the robustness and precision of the straightness detection of the scraper conveyor are improved.

The invention belongs to the field of medical treatment, and relates to a dynamic birth process progress automatic monitoring method, which comprises the following steps: S1, continuously detecting and screening image frames containing intact pubis symphysis and fetal head skull halo; s2, performing standard section screening on the continuous ultrasonic image frames by using a USPNet model based on a Swin Transform architecture; s3, automatically marking a birth process progress angle and a fetal head exposure position through an AI segmentation model, and calculating a fetal head exposure value; s4, driving the three-dimensional fetal head and pelvis model based on the real-time progress angle and fetal head exposure position data, and dynamically rendering and updating a relation graph of the three-dimensional fetal head and pelvis; s5, dynamically displaying the three-dimensional relational graph of the fetal head and the pelvis; and S6, establishing a fetal head descending and uterine contraction signal time sequence curve, and estimating the descending amplitude of the fetal head in the future set time based on a linear regression or curve fitting prediction algorithm. According to the application, continuous, dynamic and accurate monitoring and visual display in the uterine contraction period can be realized, doctors are assisted in scientific decision making, and the delivery management level is improved.

The application belongs to the technical field of material surface structure detection, and provides a paper defect detection method and system, height information of each pixel point on the surface of the paper is acquired through an optical distance measuring sensor, and then a height distribution map is constructed, and the fluctuation mode of the surface structure contour of the paper is analyzed by combining convolution difference, local trend and change intensity, through curve fitting and trend clustering of the structure characteristics, typical surface structure types such as periodic corrugation and non-periodic wrinkle can be effectively distinguished, so that automatic identification of the microstructure of the paper surface and structure cause tracing analysis are realized, and meanwhile, accurate identification of the abnormal area is realized, and the universality and practicality of the system in the actual industrial scene are improved.

The invention discloses a point cloud-based reverse modeling curved surface generation method and system, and relates to the field of electric digital data processing, and the method comprises the steps: obtaining three-dimensional point cloud data of a to-be-processed engineering design product, and projecting the three-dimensional point cloud data to a preset cutting plane to obtain a two-dimensional projection point set; and performing dimension reduction processing on each projection point, calculating a local geometrical relationship between the projection point and a neighborhood point, and mapping the local geometrical relationship to a one-dimensional parameter space to obtain a one-dimensional parameter value. Clustering analysis is conducted on the two-dimensional projection point set based on the one-dimensional parameter values, the two-dimensional projection point set is divided into a plurality of point cloud clusters, and each point cloud cluster corresponds to one geometric feature curve. And sorting the projection points in each point cloud cluster according to a spatial position relationship to obtain an ordered point sequence. And identifying the geometric feature type of each ordered point sequence, performing curve fitting, and extracting parameter information to obtain the feature parameters of the engineering design product. And generating an accurate curved surface model according to the characteristic parameters. By implementing the method, the accuracy of point cloud clustering can be improved.

A manipulator execution path planning method for a complex space guided measurement task, includes: determining a measurement space of a manipulator and a starting point and a target point of a path; determining an obstructed space and a free space of the measurement space and a proportion of the obstructed space in the measurement space using a collision algorithm, and classifying and constructing a space compression model according to the proportion of the obstructed space in the measurement space to compress the measurement space and remove an invalid space; finding candidate paths for connecting the starting point and the target point by constructing an adjacent node tree connected topology network; finding a required path in the candidate paths, and performing high-order curve fitting to obtain a final path; discretizing the final path, and solving joint angles of the manipulator to obtain a joint track.

A navigation path can be determined for an object using one or more neural networks. In various embodiments, image data is obtained that is representative of an environment in which the object is to be navigated. Relevant features are identified from the image, and a curve fit to those features. Loss values for the potential paths are scaled based at least in part upon the distance of those features in the real world. This can include, in at least some embodiments, performing the scaling as a function of the curvature of the curve fit to the features. Temporal smoothing can be performed with respect to prior path predictions in order to prevent sudden changes in the predicted path. The paths are analyzed to select a path with a highest confidence value that also at least satisfies a minimum confidence criterion. The path can be converted into three-dimensional navigation information.

This application relates to the field of golf technology, and more particularly to a top-down golf data detection method, system, and device based on multi-view vision. The method includes: entering a scene perception mode, acquiring scene images, and obtaining scene data; adjusting the parameters of the camera module and infrared lights based on the scene data; entering a target detection mode, checking if the current frame position of the golf ball in a preset number of image frames matches its initial position; if so, entering a global ball-locking mode; determining that a shot is triggered when the real-time frame position of the golf ball meets a distance threshold from its initial position; acquiring and processing images of the shot triggering process at preset intervals to establish a trajectory set of the golf ball and clubhead; performing three-dimensional curve fitting on the trajectory set to obtain the trajectory curve equation, and re-interpolating the trajectory points according to the time points based on the curve equation; calculating motion process parameters based on the interpolated trajectory points to obtain golf data.

The invention discloses a ground station antenna pointing error compensation method and related equipment. The method comprises the following steps: controlling an antenna driving shaft to sequentially rotate to a plurality of measuring points according to a preset angle step length in a preset angle range, and synchronously acquiring a command angle value output by an encoder and an actual angle value output by a gradienter at each measuring point; for each measurement point, an error value is calculated according to the relation that the error value is equal to the difference between the actual angle value and the command angle value, and an error sample set containing a plurality of data pairs is formed; and performing curve fitting processing on the error sample set to obtain a continuous and smooth error compensation function in the preset angle range, and performing ground station antenna pointing error compensation by using the error compensation function, the error compensation function being used for representing a mapping relationship between a command angle value and an error value. The problem that an existing ground station antenna pointing error compensation method is high in cost, complex in implementation or limited in compensation effect can be solved.

The application provides an image recognition-based online detection method and system for surface defects of ultra-wide and thick plates, and relates to the technical field of image recognition. The method comprises the following steps: synchronously collecting surface images and process state parameters containing final rolling temperature, rolling force distribution, laminar cooling intensity and real-time speed, firstly completing image splicing according to the final rolling temperature and the rolling force distribution to obtain a topological image; then separating a texture channel image by feature decoupling with the laminar cooling intensity as a constraint; subsequently extracting edge features of the texture channel image by Hough transformation, and introducing the rolling force distribution and the real-time speed as constraints for curve fitting to generate topological structure features; finally dynamically adjusting a kernel function by a support vector machine, and analyzing the topological structure features and a preset feature library to obtain a defect detection result. The application can effectively improve the accuracy and adaptability of defect detection under complex working conditions through deep fusion and dynamic guidance of process parameters.

The invention is a method and computer system for determining one or more parameters quantitatively characterising the interaction between an antigen and an antibody. The method comprises producing a test region carrying an antigen that produces a first luminescence spectrum, bringing into contact with the test region a sample solution comprising an antibody that forms a complex with the antigen and produces a second luminescence spectrum different from the first luminescence spectrum, recording an image (30) or images of the test region with a digital imaging device, producing a 2D histogram (40) from intensity values of the image (30), performing curve fitting on the points of the 2D histogram (40), and determining the one or more parameters by means of the fitted curve.

This invention discloses a method and system for fitting safety monitoring data based on adaptive hybrid basis functions, belonging to the field of computer-aided data analysis technology. The method achieves fully automatic high-precision curve fitting through a six-layer adaptive architecture: it automatically analyzes the trend complexity, periodicity, noise level, and nonlinearity of the data using multi-dimensional feature recognition technology; it calculates the data complexity score based on the feature analysis results and intelligently selects basis function combinations from an extended basis function library containing 32 sub-functions across 8 categories; it constructs a dynamic weighted hybrid basis function model, achieving adaptive adjustment of model parameters through time-varying weight functions and coupling correction terms; and it employs a multi-model dynamic fusion mechanism, integrating multiple candidate models based on six-dimensional confidence evaluation. This invention innovatively introduces adaptive regularization technology and a hierarchical optimization strategy, effectively balancing fitting accuracy and generalization ability, and possesses advantages such as full automation, strong robustness, and complete uncertainty quantification.

The application discloses a formation fluid identification method, comprising the following steps: acquiring first infrared spectrum data and second infrared spectrum data of a formation section to be interpreted; performing curve fitting on the first infrared spectrum data to obtain a fitting curve, determining a first factor according to an extreme value of a first wavelength section of the fitting curve, determining a second factor according to an opening and area integral of the fitting curve, and determining a third factor according to a center of a second wavelength section of the fitting curve; calculating a standard deviation curve of a standard deviation of longitudinal absorption at all wavelengths of a same depth point according to the second infrared spectrum data, and calculating a peak tailing factor of the standard deviation curve; and determining a type of the formation section according to the first factor, the second factor, the third factor and the peak tailing factor. The application further discloses a system, a computer device and a readable storage medium.

This invention provides a parameter anomaly diagnosis and early warning method for the material head production process based on a curve band. It utilizes historical data to screen normal batches; calculates the maximum and minimum values ​​of parameters in the screened historical data; performs curve fitting using a linear regression model for all maximum and minimum values; and determines in real time whether the parameter falls within the curve band range. The method proposed in this invention first filters historical data to identify abnormal batches, and then uses the curve band as the anomaly judgment criterion, effectively avoiding the shortcomings of existing technologies.

The application provides a kind of ore grade distribution real-time detection method, system and equipment, it is related to mining technical field, method mainly includes: based on the operation map of mining area, centralized control center determines blast design hole coordinate;Automatic drill travels to a hole position and is in position;Automatic drill carries out drilling operation, obtains drill cuttings and records operation parameters in real time;Automatic detection platform is sampled to drill cuttings by sample collection device continuously by continuous flow;Through drying, tabletting, analysis processing, ore grade content and internal profile structure diagram, and match corresponding hole data;Based on ore grade content, internal profile structure diagram and hole data, single-hole model characteristic curve is obtained by fusion;The above operation is carried out to all hole positions;The average value of the single-hole model characteristic curve of adjacent hole positions is calculated, and curve fitting is carried out to obtain the ore grade spatial distribution imaging map.The scheme can provide intuitive guidance for ore dressing of mine, and can greatly improve the mining efficiency and quality.

This invention proposes an efficient system and method for processing objective data from helicopter flight simulators. The system includes a data preprocessing module for preprocessing acquired complete flight data, including data fusion and time-series correction; a data segmentation module for segmenting the raw simulator objective data based on helicopter configuration, control variable changes, and flight status to obtain segmented data; a batch processing module for providing a batch processing entry point for multiple sets of segmented data, simultaneously importing multiple sets of segmented data and multiple data parameters into one or more other processing modules for processing; an outlier removal module for identifying and removing outliers from the batch-processed segmented data; a curve fitting module for correcting the data after outlier removal; and a filtering module for recovering the true information as much as possible from the segmented data containing interference.

The invention provides a numerical control turning adaptive compensation control method based on a contour error prediction model, and belongs to the technical field of numerical control turning compensation control. In order to solve the technical problem that contour errors occur in the numerical control turning machining process, actual contour coordinate values of at least three positions of a workpiece to be detected are collected in an automatic or manual detection mode; on the basis of the collected coordinate values, one of a least square method, an NX curve fitting method and trigonometric function calculation is adopted, arc fitting processing is conducted on the collected data, an arc contour with the minimum error is solved, and the actual contour value of the workpiece is obtained; according to the calculated actual contour value of the workpiece, running a preset program, automatically adjusting a cutter compensation value, and controlling compensation operation; the method is applied to adaptive compensation control of numerical control turning.

The invention discloses a suspension system dynamic model calibration method based on an optimization algorithm, and belongs to the technical field of software. The invention aims to solve the problems of existing Kamp; and C, a performance calibration method is low in efficiency and long in period, and the problem that calibration work is repeated and failed due to a parameter interaction effect exists. Therefore, the invention provides a method which comprises the following steps: carrying out a sample vehicle suspension Kamp; c, testing to obtain test data; the method is based on sample car parameters and Kamp; c, establishing a whole vehicle model according to test data; a suspension Kamp is used; carrying out DOE calculation and parameter sensitivity analysis by taking the characteristics C as variables, and selecting Kamp sensitive to the whole vehicle performance; c characteristics are used as benchmarking items; a suspension rigid-flexible coupling dynamic model is established in ADAMS software, and a secondary development script is written to realize automatic operation; carrying out Kamp by taking model part parameters as variables; c, performing DOE calculation and sensitivity analysis on each working condition, and selecting each key Kamp; c, taking characteristic sensitive part parameters as benchmarking variables; kamp of simulation and test is used; c curve matching is taken as an optimization target, an optimization function is established, and Kamp is carried out; the model C is subjected to benchmarking solution, and a high-precision suspension Kamp is output; and C model. Compared with the prior art, the method has the advantages that the optimization algorithm is introduced, so that the suspension Kamp is realized; due to automation and high precision of C model calibration, the working efficiency and benchmarking precision are greatly improved, and a high-precision suspension dynamical model can be output.

The invention discloses a to-be-welded weld center track real-time labeling method based on bidirectional edge enhancement and geometric constraint fitting, and relates to the technical field of automatic auxiliary welding. The method comprises the following steps: performing directional gradient edge enhancement on a weld image, fusing with an original image, and inputting into a deep learning network to extract an edge; candidate line segments are obtained through Hough transform, and effective weld boundary pairs are screened out based on groove width and parallelism constraint; calculating midpoints of the boundary pairs to form a central point set, and performing cubic B-spline curve fitting to obtain a smooth trajectory; and finally, the fitting track and the real-time deviation between the fitting track and the welding gun are displayed in an augmented reality mode in an overlapping mode. According to the method, the robustness and accuracy of welding seam edge extraction under complex interference are remarkably improved through directional enhancement and geometric constraint, and accurate extraction and visual interaction of a welding seam center track are achieved through high-precision curve fitting and AR visualization.

The present application belongs to the field of wind power generation, and specifically discloses a wind deviation quantitative evaluation method, system, device and medium, comprising: obtaining sampling data, performing standardization processing, cleaning unit operation data, excluding the influence of factors such as control difference, turbulence intensity difference and blade damage after eliminating abnormal data, and taking the screened unit as an evaluation object; taking the power coefficient CP expected value as a characteristic parameter to reduce the influence of power fluctuation and randomness on wind deviation evaluation; calculating the effective wind speed interval of wind deviation, and selecting the constant CP control wind speed interval of the unit to reduce the data amount requirement; calculating the expected CP under each wind deviation angle and performing normalization processing, and finally performing wind deviation curve fitting to further weaken the fluctuation influence; deriving the fitted curve and calculating the inflection point, comparing with the set early warning judgment rule, issuing an alarm and giving a quantitative evaluation conclusion, and guiding the wind deviation correction.

The application relates to the technical field of meter detection, and discloses an SF6 meter pressure monitoring method and system based on image recognition. The method matches feature points of an SF6 meter image to be recognized and a preset meter template image by using a SURF algorithm, determines the positions of pointers in the SF6 meter image and the distribution of the dial scale, and thus determines the meter reading of the SF6 meter image. The meter reading of each SF6 meter image and the change of the environment temperature of the SF6 meter acquired in advance are subjected to curve fitting, the relative deviation of a characteristic curve of the SF6 pressure change with the temperature to a preset characteristic curve of the standard SF6 pressure change with the temperature is calculated, the change rate of the relative deviation is compared with a preset rate threshold, the change trend of the SF6 pressure in a preset period is determined according to the comparison result, and thus the SF6 pressure change can be monitored in time and effectively, and the SF6 pressure monitoring precision is improved.

This invention relates to a method, system, and medium for measuring the spatial parameters of a monocular target object based on a 2D camera. The method includes: acquiring a calibration board image and an original distorted image captured by the 2D camera; calibrating the calibration board image using a calibration algorithm to obtain calibration parameters; correcting the original distorted image using the calibration parameters to obtain a corrected image; performing target detection; and outputting the external contour and target contour feature points of the target object; classifying the target contour feature points into upper boundary feature points and lower boundary feature points; calculating the relative distance between the target object and the 2D camera based on the lower boundary feature points and the calibration parameters; and performing curve fitting on the upper and lower boundary feature points and the lower boundary feature points, respectively, and calculating the actual height of the target object based on the calibration parameters. Compared with existing technologies, this invention has advantages such as improved measurement accuracy and adaptability to complex boundary targets.

The application discloses a crack feature extraction and quantification method and device based on a point cloud large language model, and relates to the technical field of civil engineering structure health monitoring. The method comprises the following steps: according to a two-dimensional image data set and a three-dimensional point cloud data set, performing cross-modal semantic analysis by using a crack feature analysis large model to obtain a crack semantic recognition result; performing skeleton line fitting by using a curve fitting method according to the crack semantic recognition result and the three-dimensional point cloud data set; performing crack feature quantification according to a crack local point cloud subset data set and a three-dimensional skeleton curve of the crack to obtain a crack structured feature; and performing time sequence comparison reasoning by using the crack feature analysis large model according to the crack structured feature and a feature description text based on a crack trend inquiry text to obtain a crack development trend prediction result. The application is a crack feature extraction and quantification method with high precision and strong explainability by combining three-dimensional point cloud data processing and a large language model.

The application discloses a tunnel boring machine space dynamic compensation seismic wave advanced detection method and system, comprising: receiving the reflection echo data of the current space position; compensating the reflection echo data according to the attenuation compensation factor of the current space position, wherein the attenuation compensation factor of the current space position is obtained by a trained neural network, and the prediction process comprises: after curve fitting of the attenuation compensation factor of the reflection echo data of the detected space position, the attenuation compensation factor of the next space position is predicted by using the trained neural network; the compensated reflection echo data is subjected to geological body imaging by using the equal travel time imaging method, and the geological body detection result is obtained according to the amplitude difference on the imaging profile. The space dynamic compensation algorithm of the mechanical wave attenuation is used to adaptively correct the attenuation compensation factor at the next tunneling surface, so as to compensate the received reflection echo data and enhance the identification ability of the reflection echo.

The application discloses a wind speed power curve fitting abnormal data filtering method based on a rank difference method, and the method comprises the following steps: acquiring wind speed and power data; encoding ranks of the wind speed and power data respectively, and calculating rank differences of each data point; wherein each data point contains a group of wind speed and power value pairs, and the rank difference is the difference value of the power rank and the wind speed rank; centering the wind speed based on the rank difference; merging the centered wind speed into a data set and filtering; and fitting the data set into a curve based on the Bien method. Through the processing scheme of the disclosure, the data filtering effect is effectively improved.

The invention discloses a parameter transformation method of an equivalent thermal network model and a related device, and the method comprises the steps: obtaining the complex frequency domain network impedance of a Foster thermal network model through curve fitting; according to the complex frequency domain network impedance of the Foster thermal network model, all thermal parameters in the Cauer model are solved in an admittance solving mode, and the thermal parameters of the Cauer model can be obtained through thermal parameter transformation of the Foster model by means of the method and the related device.

The present application mainly relates to handwriting modeling technical field, in order to solve the problem of low degree of actual character restoration in the handwriting drawing effect of existing soft pen handwriting drawing method, the present application provides a kind of soft pen handwriting drawing method, the soft pen note drawing method of the present application first establishes stroke feature model to different stroke sample, obtains the vector coordinate data Pf of each stroke point;According to the angle formed by the stroke and horizontal direction, stroke interval division is carried out;Obtain the relevant parameters of each stroke point in the writing process;Get the stroke point set of current writing track;Curve fitting is carried out to stroke point set, and closed area is formed, and the closed area is filled to obtain the final soft pen writing track.