163results about How to "Implement fixes" patented technology

The invention discloses a multi-point ditch flow monitoring method, and particularly relates to the field of branch ditch flow monitoring, which is used for solving the problem of complex branch ditch flow monitoring and optimization, and comprises the following steps of: constructing a branch ditch topological connection relation matrix, generating a flow characteristic curve in combination with flow and water level time sequence data, and marking interference points; generating an interference incidence matrix by utilizing two-channel interaction analysis, extracting upstream and downstream flow offset and disturbance propagation characteristics, judging an interference dominant mode according to a difference degree, and respectively calculating a flow offset compensation matrix and a disturbance propagation correction matrix; the recursive optimization model realizes segmented correction and reduces error residual errors, combines spatial-temporal feature clustering to identify abrupt change sections and generate a high-risk area key monitoring list, extracts refined data based on a high-frequency acquisition strategy to analyze abnormal causes, generates a dynamic correction result by using a prediction model, and updates a traffic balance data set. The multi-mode interference is accurately corrected, the flow distribution is optimized, and the monitoring precision and the system stability are improved.

The invention provides a 110V transformer winding insulation resistance absorption ratio detection method, which belongs to the technical field of transformer windings, and is characterized in that transformer operation state parameters and environmental influence factors are acquired through a multi-channel synchronous acquisition system, and thermodynamic and electrical models are established. The research adopts methods of principal component analysis, numerical integration and the like, an insulation resistance change rule is analyzed under a standard test voltage, a weight coefficient matrix is constructed in combination with an operation state and an environmental factor, a measured value is corrected through multiple linear regression and a correction coefficient method, and finally, the insulation resistance is obtained through statistical average and standard deviation analysis. The accurate evaluation of the insulation resistance absorption ratio of the transformer winding is realized; according to the method, the influence of the complex working environment and the operation state of the transformer on the insulation performance is fully considered, and the problem that various complex factors in the operation process of the transformer cannot be comprehensively considered and compensated in the prior art is solved by adopting the means of mathematical modeling, data correction, statistical analysis and the like; therefore, the technical problem of large deviation of the measurement result is solved.

The invention discloses a service life acceleration factor evaluation method and device for a product after storage service. The method comprises the following steps: constructing a performance parameter curve by using k performance parameters obtained by testing a to-be-evaluated product object; constructing a performance aging model, solving the performance aging model by using a least square method, calculating a product degradation rate at a specified temperature by using test data, and obtaining product activation energy after obtaining an estimated value of a performance parameter; according to the product activation energy and an Arrhenius model, acquiring an acceleration factor of the to-be-evaluated product object at any given temperature relative to the reference temperature; splicing the natural storage test data and the accelerated storage test data to obtain performance parameter degradation data and a performance parameter curve of the whole life cycle of the to-be-evaluated product object; and calculating and analyzing the spliced performance parameter curve by reusing the performance aging model and the Arrhenius model to obtain a corrected acceleration factor. According to the method, the storage life evaluation result is more accurate, and scientificity and rationality are higher.

The invention provides a positioning method, device and equipment based on multi-state color consistency constraint, which can be applied to the technical field of computers. The method comprises the steps of performing imaging simulation on a positioning point based on a three-dimensional position of the positioning point in a three-dimensional point cloud, and determining an imaging position of the positioning point in a current frame image; correcting an initial object state corresponding to the current frame image based on a projection position and an imaging position of the positioning point in the current frame image to obtain a corrected object state, and obtaining a corrected object state based on a plurality of historical poses of the inertial measurement tool, a plurality of observation colors of the positioning point, a current color of the positioning point in the three-dimensional point cloud and a color noise distribution parameter; correcting the state of the corrected object to obtain the state of the target object; and determining the target pose of the positioning object based on the state of the target object, so as to at least partially solve the technical problem of poor positioning effect in related technologies, and achieve the technical effect of improving positioning robustness and precision.

The invention belongs to the technical field of low-temperature wind tunnel tests, and discloses a method for correcting a temperature effect caused by a temperature gradient of a wind tunnel balance. The temperature effect correction method comprises the steps of obtaining temperature distribution of a wind tunnel balance in a wind tunnel test; acquiring a wind tunnel balance temperature gradient distribution mathematical model; obtaining wind tunnel balance theoretical structure thermal strain and wind tunnel balance theoretical bridge thermal output; obtaining a temperature effect correction formula caused by the temperature gradient; and obtaining corrected aerodynamic force test data. According to the method for correcting the temperature effect caused by the temperature gradient of the wind tunnel balance, the structural deformation caused by the temperature gradient in the wind tunnel balance test and the generated thermal output of the measuring bridge are evaluated through digital simulation, so that the temperature effect caused by the structural temperature gradient of the wind tunnel balance is corrected; the method can effectively improve the data quality of the wind tunnel test, and especially has an engineering practical value for the wind tunnel test with a large flow field temperature change.

The invention discloses an early failure identification method and device of a battery and a storage medium, and belongs to the technical field of electrochemistry. The method comprises the following steps: carrying out impedance test on a battery by using an alternating current impedance spectroscopy measurement technology, and recording test data information of the battery in the test process; constructing an impedance information data set by taking the frequency as the serial number of the test data, taking the type of the test data as the characteristic and taking each test point as a sample; determining characteristic data of the battery, judging an electrochemical process in charging and discharging of the battery in combination with the impedance data, and establishing a neural network; and fitting the impedance data of the battery based on a neural network, dividing the weight of impedance response of each internal interface between an internal electrode and an electrolyte in the battery and a cross-linked part of the internal electrode and the electrolyte by using the neural network, and judging the battery with early failure. According to the invention, the technical problem of difficulty in early warning of battery failure is solved.

The invention discloses a wing regular metal structure stress simulation data dimensionality reduction and correction method, which comprises the following steps: firstly, carrying out wing regular metal structure finite element simulation, respectively obtaining data such as grid nodes and node stress values under dense grid and sparse grid conditions, and completing data preparation; carrying out data clustering analysis by utilizing a distance-based clustering algorithm, calculating the distance between each nearest neighbor point and the central point, and obtaining a plurality of nearest neighbor points with the nearest distance and node stress values corresponding to the nearest neighbor points; calculating the stress value of the target point according to the distance weight and the node stress of each nearest neighbor point; correcting the stress value of the target point by using the maximum value of the stress value of the target point and the relative error of the concentrated stress to obtain a corrected stress value; and finally, calculating a relative error between the concentrated stress and the maximum stress of the structure as a second relative error, and correcting the corrected stress value again. According to the method, dimension reduction and correction of large-scale and high-dimension finite element simulation data can be realized, and the accuracy degree is high.

The invention discloses a teaching auxiliary device for a female pelvic floor organ prolapse repair operation, and belongs to the technical field of female pelvic floor repair teaching aids. The pelvic floor teaching device comprises a pelvic floor simulation mold, pelvic floor teaching gloves and an auxiliary display system, wherein audible and visual alarms and contact sensors are arranged at the positions of organs in the pelvic floor simulation mold. The pelvic floor teaching glove solves the problems that an existing green hand is difficult to practice an operation and resources of a corpse dissecting teaching aid are tight, the pelvic floor teaching glove is inserted into the pelvic floor simulation mold through the vagina by wearing the pelvic floor teaching glove, the probe at the front end and the contact type sensor are used for sensing each other, and if the pelvic floor teaching glove mistakenly enters an organ which is not required to be examined, the audible and visual alarm gives an alarm; various simulation teaching scenes are set, the image is blurred through the image blurring module to simulate the serious bleeding phenomenon, an operator observes the actual condition of a simulation operation through the display terminal, it is ensured that the teaching auxiliary device has the visualization, guiding and feedback functions, and the defects that a green hand is difficult to learn and simulation tools are tight are overcome.

The invention provides a battery capacity correction method suitable for an intermittent data loss scene, and relates to the application field of a battery technology. The method comprises the following steps: in a mode based on intermittent data loss, marking a capacity actually corresponding to a unit SOC change in a discharge process as an actual denominator, clustering the actual denominator, obtaining a theoretical capacity corresponding to the unit SOC change, and marking the theoretical capacity as a standard denominator; according to the method, a difference value between a standard denominator and an actual denominator is utilized to carry out capacity compensation on a current data loss position, and only one of data loss positions of the same SOC is selected for compensation, so that a corrected ampere-hour integral capacity value is obtained. According to the method, the influence of data loss on the ampere-hour integral capacity value is greatly overcome, the universality and accuracy of the battery diagnosis technology in a data loss scene are improved, the feasibility of data loss vehicle diagnosis early warning is guaranteed, and a guarantee is provided for the safety of a new energy vehicle.

The invention relates to a polarization / inertial navigation integrated navigation method of an embedded unmanned aerial vehicle kinetic model, which comprises the following steps of: expanding a three-dimensional attitude error angle, a speed error, a position error, an angular speed error and a thrust coefficient error of the unmanned aerial vehicle kinetic model into inertial navigation state parameters as state quantities to form system state quantities; establishing a system state equation; taking the course angle calculated by the polarization sensor and the attitude, the speed and the position of the unmanned aerial vehicle kinetic model as quantity measurement, and establishing a system measurement equation; establishing a credibility discrimination function of polarization course measurement based on course angle innovation, and designing a combined navigation mode switching and thrust coefficient error feedback strategy; a Kalman filtering method is used for estimating system state quantities, namely an inertial navigation attitude misalignment angle, a speed error and a position error, and an attitude error angle, a speed error, a position error and a thrust coefficient error of an unmanned aerial vehicle dynamic model, so that correction of the attitude and the position of the unmanned aerial vehicle is realized.

The invention relates to a high-temporal-spatial-resolution weather radar beam propagation path inversion method, which belongs to the field of radar detection, and designs a more accurate temporal-spatial matching strategy by taking meteorological element data output by WRF as a background field and combining high-frequency radio sounding data. A neural network model capable of fully mining local and global spatial features of data is constructed, a long-time and short-time feature extraction and fusion model is constructed, efficient and accurate extraction of time and spatial features of different scales of meteorological elements is realized, an input data set time and spatial complexity calculation method is further designed, and the calculation efficiency is improved. The adaptive optimization selection of the convolution kernel is realized, the real-time performance of outputting high-temporal-spatial-resolution meteorological data based on the 3D temporal-spatial convolution model is greatly improved, the atmospheric refractive index model and the electromagnetic wave propagation path calculation model are introduced, and the inversion of the high-temporal-spatial-resolution and accurate weather radar beam propagation path is realized.

The invention discloses an electromagnetic wire self-adhesion performance data acquisition and intelligent analysis method, and relates to the technical field of data analysis. Multi-source data such as turn-to-turn gap, paint layer residual thickness, tension fluctuation and conduction state are synchronously acquired in the winding process; and analysis mechanisms such as a gap reduction rate, paint layer thinning distribution, a synchronous evolution track and a gap strength response curve are introduced, so that continuous modeling and quantitative characterization of the autohension performance evolution process are realized. Compared with the prior art which only depends on a single gap threshold value or a post mechanical test to judge the bonding performance, the method can be started from a complete physical chain from gap change to paint layer extrusion to metal contact to bonding failure, and the change trend of the bonding performance under different gap levels can be accurately revealed; and tension output is corrected in real time through a self-adaptive algorithm, closed-loop optimization of the bonding quality is achieved, and the product percent of pass and the production efficiency are improved.

The invention discloses a data safety analysis system and method applied to low-altitude flight, and relates to the technical field of data safety analysis, and the method comprises the steps: obtaining a depth image of a low-altitude aircraft in a flight process, and carrying out the judgment and extraction of feature points in the depth image; obtaining a positioning path of the low-altitude aircraft in the flight process, and obtaining a normal positioning point and an abnormal positioning point in the positioning path; obtaining a feature distance between each positioning point and each feature point, and obtaining an incidence relation expression between the feature distance and a pixel value according to the pixel value of the feature point in the depth image; and correcting each abnormal positioning point in the positioning path according to the incidence relation expression and the geographic position coordinate of each feature point. Visual positioning assistance is carried out by using the depth image to determine the position of the unmanned aerial vehicle, correction of the positioning point is realized, errors generated during positioning of the unmanned aerial vehicle are reduced, the positioning precision of the unmanned aerial vehicle is improved, and the task execution efficiency is guaranteed.

The invention belongs to the field of structural health monitoring and data processing, and aims to solve the problem that manual intervention is always needed in the aspects of abnormal segment detection and elimination in traditional data restoration. The invention provides a deep learning method for structural health monitoring acceleration data restoration, and the method comprises a structural health monitoring acceleration abnormal data set simulation method and a deep learning method for health monitoring abnormal data restoration. Wherein the structural health monitoring acceleration abnormal data simulation method is used for manually adding various types of abnormal signals and making a data set of a deep learning model, and the health monitoring abnormal data restoration deep learning method is used for restoring various types of actually measured abnormal data into normal data. According to the invention, various types of abnormal features of the health monitoring acceleration data can be learned, the data directly collected by the acceleration sensor is used as the input of the network, and the repaired data is directly output without manual intervention in the use stage.

The invention relates to a video coding method and device, electronic equipment, a computer readable storage medium, a computer program product and a method for generating a bit stream. The video coding method comprises the steps that distortion information of each block in a current frame and a first subsequent frame is determined, the first subsequent frame is at least one actually available subsequent frame after the current frame, and the distortion information of the block is used for indicating the influence of distortion of a reference block of a previous frame on distortion of the block; based on the distortion information of each block, the distortion information of each block in a second subsequent frame is predicted, and the second subsequent frame is a predetermined number of subsequent frames after the first subsequent frame; determining a quantization parameter increment of the current block on the basis of distortion information of the current block in the current frame and distortion information of predetermined blocks in the first subsequent frame and the second subsequent frame, the distortion of the predetermined blocks being affected by the distortion of the current block; and encoding the current block based on the determined quantization parameter increment.

The utility model relates to the technical field of infrared temperature measurement, in particular to an infrared temperature measurement sensor field angle testing device and a control system. The utility model provides a field angle testing device for an infrared temperature measurement sensor. The field angle testing device comprises a tested sensor, an infrared signal source, an infrared sensor testing bracket, an infrared signal source bracket and a parallel moving slide rail, the tested sensor is arranged on the infrared sensor testing bracket; the tested sensor can move up and down in the vertical direction, and the infrared sensor testing bracket can rotate circumferentially to adjust an angle formed by the infrared sensor testing bracket and the infrared signal source; the infrared signal source is arranged on the infrared signal source bracket; the infrared signal source irradiates the sensor to be tested, so that the sensor to be tested forms a feedback signal; the parallel movement sliding rail is perpendicular to the infrared sensor testing support and the infrared signal source support, and the parallel movement sliding rail enables the infrared signal source support to move in the horizontal direction.

The invention provides a hydraulic pump output flow soft measurement method considering service performance degradation. The method comprises the steps that the rotating speed, the inlet and outlet pressure difference, the oil liquid temperature and the actual flow of a hydraulic pump under different working conditions are obtained; a hydraulic pump flow prediction model is constructed, the hydraulic pump flow prediction model comprises a neural network and a parameter correction module, input parameters, corresponding to an input layer, of the neural network are the obtained rotating speed, inlet and outlet pressure difference and oil temperature of the hydraulic pump, and an output layer is predicted flow; the parameter correction module corrects the optimal weight matrix and the optimal threshold matrix of the neural network based on the rotating speed, the inlet and outlet pressure difference, the oil temperature and the actual flow of the hydraulic pump obtained when the service performance of the hydraulic pump is degraded; and on the basis of the corrected hydraulic pump flow prediction model, the flow output after the service performance degradation of the hydraulic pump is predicted. According to the method, even if the service performance of the hydraulic pump is degraded, the output flow of the hydraulic pump can be accurately predicted.

The invention discloses a correction method and device for a cabin wind speed transfer function, equipment and a storage medium. Obtaining an operation parameter interval of a target fan in the wind turbine generator, and determining a standard cabin wind speed correction set of the target fan in the operation parameter interval; according to the topographic condition of the position of the target fan, determining an actual cabin wind speed correction set of the target fan in the operation parameter interval; and according to the standard cabin wind speed correction set and the actual cabin wind speed correction set, a correction difference value set and a correction ratio set are determined, and the cabin wind speed transfer function of the target fan is corrected according to the correction difference value set and the correction ratio set. According to the method, the transfer function can be corrected in combination with the terrain condition of the position where the fan is located, and the problem that when the transfer function is used for determining the operation data of the cabin fan, large errors are generated due to different terrain distortion degrees or the wake flow phenomenon possibly generated by the upstream fan is solved.

The invention discloses a bidirectional research and judgment method for power distribution network faults in combination with an incidence matrix and dynamic Bayesian, and the method comprises the following steps: constructing the incidence matrix through an actual topological structure of a power distribution network, and constructing a fault research and judgment matrix in combination with a fault information matrix; fault criteria under the conditions of node fault information missing report and fault information false report are established respectively, so that fault feeder identification from top to bottom is realized; constructing a dynamic Bayesian network according to an actual topological structure of the power distribution network and a'station-line-transformer-household 'relationship, and reasoning the fault probability of each region; constructing a membership function and a fuzzy inference rule to obtain a fuzzy inference system for adjusting the fault probability; and finally inferring the most probable fault area, and realizing fault area research and judgment from bottom to top. According to the method, on the basis of a traditional matrix algorithm, the fault criterion is improved by constructing the causal incidence matrix, the feeder line identification problem under the conditions of fault information missing report and fault information false report is effectively solved, the calculation amount is reduced, and the fault positioning accuracy is improved.

The invention discloses a bearing anomaly detection method and system, and the method comprises the following steps: obtaining the historical operation data of a current motion sequence of a bearing, and constructing a first parameter trend model based on the historical operation data of the current motion sequence of the bearing; acquiring historical operation data corresponding to the bearing attitude, and constructing a second parameter trend model based on the historical operation data corresponding to the bearing attitude; acquiring first parameter prediction data according to the current time point, and acquiring second parameter prediction data according to the current bearing attitude; obtaining first difference data corresponding to the first parameter prediction data and second difference data corresponding to the second parameter prediction data; and judging whether the bearing is abnormal according to the first difference data and the second difference data. The method has the beneficial effects that the influence of space and time on the bearing operation condition can be shown through the operation data corresponding to the bearing posture change and the operation data corresponding to the bearing operation time change, and the situation that the bearing does not operate in the expected state is judged in time.

The invention discloses a fire-fighting robot track detection device and method, and relates to the field of track detection. The mobile station and the measuring station are both provided with an equipment host and a GNSS antenna which are connected with each other. An infrared distance meter is also arranged in the measuring station; the server obtains RTCM data of the base station; the mobile station obtains the position information and corrects the position information based on a preset error according to the RTCM data to obtain positioning data; the measuring station collects attitude data and determines positioning data according to the RTCM data; and the upper computer determines advancing track information according to the positioning data and the attitude data. The track detection of the fire-fighting robot can be realized.

The invention relates to a photomask pattern correction method and device, electronic equipment, a storage medium and a program product. The method for correcting the photomask pattern comprises the steps that an original photomask pattern is obtained, the original photomask pattern comprises a target area, and the target area is an area influencing photomask limitation; the original photomask pattern is subjected to optical proximity effect correction, a corrected photomask pattern is obtained, and in the corrected photomask pattern, the target area is a blank area not including the pattern. According to the technical scheme, on the basis of eliminating photomask limitation and enabling the contour of the photomask pattern to converge, effective correction of the photomask pattern can be realized.

The application belongs to the technical field of microwave radar, and particularly relates to a microwave radar data missing value classification and interpolation method and system based on reinforcement learning. The method obtains microwave radar measurement data, determines the data source of the missing item based on the variation trend of the to-be-judged parameter, and then classifies the radar parameter data into an interpolatable item or an uninterpolatable item, and removes the uninterpolatable item. The effective data segments adjacent in time of the interpolatable item are divided into multiple sub-data segments, the pre-interpolation gap of each sub-data segment is calculated, and the time interval in the adjacent data area is matched to determine the fluctuation parameter, and the interpolation compensation value is calculated by combining a preset interpolation formula. The application avoids introducing false signals into the data set, ensures the physical meaning and logical rationality of the interpolation, and improves the overall quality and reliability of the repaired data set.

The application relates to a kind of automatic cutter setting method and system based on machine vision, belong to milling cutter setting technical field.The method first locates the initial position coordinate of milling cutter, and plans the initial cutter setting path of milling cutter in combination with target cutter setting position coordinate;Then the image of milling cutter in initial cutter setting path is acquired to carry out image denoising and image deblurring processing, after obtaining second image, carry out edge detection, extract the edge profile of milling cutter, and calculate the edge point subpixel coordinates of profile to carry out parameterized fitting, obtain current milling cutter position and milling cutter attitude;And the initial cutter setting path, the wear degree of milling cutter, current milling cutter position and milling cutter attitude are input into error prediction model, and the current motion error of milling cutter is predicted;According to the current motion error of milling cutter, the path compensation amount is calculated, and the cutter setting path of milling cutter is adjusted according to the compensation amount.The application can reduce the interference of milling cutter motion blur and environmental factors, realizes the quantitative adjustment and correction of milling cutter setting.

This invention relates to the field of book digitization and copyright management technology, and discloses a method and apparatus for intelligent recognition and structured information extraction of book copyright pages. The method includes: acquiring raw image data and performing preprocessing; locating multiple key regions using a target detection model; extracting text strings and recognition confidence scores using a sequence recognition model, executing a first feedback loop; if the recognition confidence is low or the semantics are incomplete, then performing adaptive adjustment of region coordinates; for text that passes the first loop verification, performing post-processing verification based on preset rules; if the post-processing verification fails, then activating a second feedback loop, locating potential erroneous characters and performing constrained re-recognition to correct character-level recognition errors; finally, integrating and storing the corrected text that passes all verifications. This invention significantly improves the accuracy, robustness, and automation level of information extraction by setting up dual dynamic correction loops for different error types.

The invention discloses a real-time semantic segmentation method for attention-guided multi-scale information fusion, and the method comprises the following steps: 1, constructing a multi-scale feature aggregation module, and aggregating multi-scale detail information; 2, constructing an attention guiding feature correction module, and correcting information extracted by different branches to promote fusion of multi-scale information and local information; and 3, constructing an attention guiding feature reduction module, fusing feature maps extracted at different depths in the network, and making up image information lost in a feature transmission process. And 4, building an image segmentation network based on the three modules, efficiently extracting important features in the image, and accurately segmenting the complex scene image through a deep learning mode. A novel real-time scene semantic segmentation model is designed on the basis of an encoder-decoder architecture, the model precision and the model speed are better balanced, and under the conditions of low parameter and low calculation cost, accurate segmentation of image objects can be achieved, and meanwhile real-time performance is achieved.

The invention relates to the technical field of computer science, in particular to a multi-thread concurrent processing method and system based on adaptive entropy segmentation and interactive differential learning, and aims to dynamically divide preprocessed data through an adaptive entropy segmentation algorithm and optimize a data processing path by using an interactive differential learning algorithm. Finally, the system realizes the backtracking and correction of the abnormal data through a multi-level error correction backtracking mechanism, and ensures the consistency and accuracy of the final data. According to the method, the problems of non-uniform load, insufficient data processing path optimization and poor abnormal data processing in the traditional multi-thread concurrent processing are effectively solved, and the processing efficiency and data reliability of the system are greatly improved.

The invention belongs to the technical field of monitoring systems, and particularly relates to a measuring and monitoring system for high-speed construction, which comprises a walking module, and a three-dimensional scanning module, a vehicle pose monitoring module and a control module which are arranged on the walking module, the walking module, the three-dimensional scanning module and the pose monitoring module are electrically connected with the control module and controlled by the control module, and pose changes of a vehicle provided with a three-dimensional laser scanner are monitored through the pose monitoring module and transmitted to a compensation unit of the control module. And the compensation unit processes the pose change data and performs geometric transformation, so that correction of the point cloud data uploaded by the three-dimensional laser scanner is realized, point cloud data deviation caused by vehicle pose change can be effectively eliminated, and subsequent monitoring of the flatness of the asphalt pavement in construction according to the point cloud data is improved.

The present invention discloses a battery pack information acquisition system based on terminal control; the system comprises a main control module, the main control module is electrically connected to a data processing module, the data processing module is electrically connected to a BMS management system and a communication module, the BMS management system is electrically connected to a battery module, the main control module is electrically connected to an electric power device, and the communication module is communicatively connected to a remote terminal module. The present invention manages and controls the battery module through the BMS management system, and then calculates and processes the data information through the data processing module, calculates and processes the power supply mode of the battery module through a greedy algorithm to achieve a balanced and stable power supply mode, and evaluates the power supply mode through a neural network algorithm to prevent calculation errors. Finally, when errors occur in the data information, the data information is corrected and eliminated to improve the accuracy and validity of the data.

The application discloses a kind of barometric altitude dynamic correction method based on airborne data.First, the sliding window parameters are screened using recursive feature elimination method, and then the sliding window is initialized and updated;Clean the sliding window data, first determine whether the sliding window data is null, then correct;For the data fusion multiple methods to detect outliers and correct after completing null judgment and correction;Construct the LSTM model and optimize the sliding window size, select the window size of the best performance indicator, use the LSTM model to correct the barometric altitude dynamically.This method has the characteristics of high precision, strong real-time, etc., improves the deficiency that the existing method can only correct the barometric altitude at a specific location, realizes the dynamic correction of barometric altitude in the whole approach process, improves the obstacle safety under low temperature conditions, at the same time, has the ability to correct the barometric altitude under high temperature conditions, and can be widely used in flight operation using barometric vertical navigation program.