178results about How to "Exact fit" patented technology

The invention discloses a manipulator for carrying automobile sheet metal parts, and relates to the technical field of manipulators, the manipulator comprises a supporting base, a mechanical arm and a plurality of suckers, the mechanical arm is mounted at the top of the supporting base, a U-shaped plate is mounted at the end, away from the supporting base, of the mechanical arm, and a supporting plate is fixedly connected to the lower end of the U-shaped plate; the supporting plate is provided with an adjusting assembly for automatically adjusting the height of the suction cups according to the automobile door frame, the adjusting assembly comprises limiting springs arranged on the outer surfaces of the suction cups in a sleeving mode, the middle of the U-shaped plate is hollow, and adjustment can be rapidly conducted according to the concave-convex condition of the door frame through the suction cups capable of being adjusted up and down; the time for manual intervention or readjustment due to the fact that the suction cups are not matched with the automobile door frame is shortened, the situation that adsorption is not stable due to the fact that the suction cups do not effectively make contact with the automobile door frame is avoided, and the phenomenon that abrasion occurs due to too large pressure when only a small number of suction cups are matched with clamping jaws to grab the automobile door frame is avoided; and the universality and the application range of the sucker type manipulator are improved.

The invention discloses a lithium battery state estimation method based on relaxation time scale modeling, and the method comprises the steps: 1, carrying out a sudden pulse charging test on a lithium battery, collecting voltage and current data, and calculating the open-circuit voltage, direct-current internal resistance and a time-domain impedance sequence of the lithium battery; and 2, converting the time domain impedance sequence of the lithium battery into a frequency domain impedance sequence after discrete Fourier transform, establishing a fitting equation set of a distribution function of the relaxation time scale DRT of the lithium battery and the frequency domain impedance sequence, and solving by adopting a regularized least square method. And 3, taking the solved DRT model distribution function as the input of a neural network, taking the state parameters of the lithium battery as the output of the neural network, and establishing a prediction model of the state parameters of the lithium battery. According to the method, EIS test required by traditional relaxation time scale modeling is avoided, the control complexity and design cost of test acquisition equipment are effectively reduced, and the method can be effectively applied to occasions such as battery life prediction, battery classification and screening, battery echelon utilization and the like.

The invention relates to the technical field of semiconductor device parameter extraction, in particular to a semiconductor device parameter extraction method based on a reinforcement learning enhanced equalization optimizer, and the method comprises the steps: constructing a semiconductor device model, and determining input, output and optimization targets based on the semiconductor device model; and starting a parameter extraction algorithm based on the input, the output and the optimization target, and obtaining the optimal parameter of the semiconductor device, the parameter extraction algorithm being constructed by combining reinforcement learning with an equalization optimizer. According to the method, the efficiency and the precision of MOSFET parameter extraction can be improved by adaptively adjusting the iteration parameters of the optimization algorithm.

The invention provides a camera offset detection method and system based on image segmentation, and belongs to the technical field of image processing, and the method comprises the steps: inputting a to-be-detected railway image into an image segmentation model, and obtaining a plurality of rail region contours; a target contour is determined from all the rail area contours, and the target contour is divided into a plurality of convex areas in the preset direction when it is judged that concave points exist in the target contour; determining a target area from all the convex areas, and performing straight line fitting on contour points in the target area to obtain a straight line to be detected; and when it is determined that the camera deviates based on a comparison result of the to-be-detected straight line and the reference straight line, alarm information of camera deviation is generated. According to the invention, through image segmentation and contour analysis, the rail boundary is accurately extracted and the camera offset is detected, so that the accuracy of camera offset detection is effectively improved.

The invention relates to a high-precision calibration method and system for a digital sinusoidal signal generator. According to the method, an ideal sine array is generated through a script program to serve as DAC input; the Raspberry Pi 4B and the DA-AD board form a sinusoidal signal error extraction module, a DA-AD conversion process is executed, and an actual output array is obtained at an ADC output position and used for extracting errors; calculating to obtain a DAC error curve according to the actual output array and the ideal input array, and performing polynomial type fitting and trigonometric function type fitting on the error curve by adopting a least square method and a particle swarm algorithm respectively; and compensating an error fitting result to DAC input, running DA-AD conversion again to obtain an output array, and calculating a compensated DAC output error to represent the precision of the sinusoidal signal. According to the method, the error curve in the sine function form can be accurately fitted, the consumed time is short, and the error fitting in the sine function form better conforms to the theoretical error rule when the DAC is used for generating the sine signal.

The invention discloses a method for constructing a prediction model of fluid mechanics flow field velocity. The method comprises the following steps: acquiring a large number of coronary artery CTA images of coronary heart disease patients, and respectively constructing 3D blood vessel geometric models; setting different inlet flow rates and physiological pressure boundary conditions in different 3D blood vessel geometric models, and performing CFD simulation to obtain simulation results; inputting the obtained contrast agent particle concentration 3D point cloud in the flow field, the actual flow field speed and the coronary artery model 3D point cloud into a PDMNN neural network for learning; and encoding the advection diffusion equation to a loss function, and driving the PDMNN neural network to calculate convergence by using the relationship between the contrast agent concentration and the fluid velocity to obtain a prediction model of the fluid mechanics flow field velocity. Through the prediction model constructed by the method, the prediction effect can be more accurately and quickly realized, and meanwhile, the method can face different geometric models and different boundary conditions.

The invention discloses a method and device for determining the temperature of a vehicle brake disc and electronic equipment, and relates to the technical field of vehicle control. The method comprises the steps that in the running process of a vehicle, environment information, speed information and pressure information of a brake disc of an area where the vehicle is located at a target moment are collected, and the environment information at least comprises temperature information, humidity information, wind speed information and weather information; and according to the brake disc temperature of the brake disc of the vehicle at the first moment, the environment information, the speed information of the vehicle and the pressure information of the brake disc, the temperature of the brake disc of the vehicle at the target moment is determined, and the first moment is before the target moment. The technical problem that in the prior art, the temperature of the brake disc is estimated according to heating, convection, heat conduction, heat radiation and other factors generated by friction caused by braking force, and due to the fact that the factors are not considered comprehensively, the temperature estimation error of the brake disc is large is solved.

The invention relates to a building concrete volume calculation method based on model voxelization. The method is suitable for the technical field of constructional engineering digital application. According to the technical scheme, a three-dimensional model of a building structure is obtained; generating a voxel model corresponding to the three-dimensional model; configuring a voxel attribute table for each voxel block in the voxel model; determining a material characteristic value and a material mixing characteristic value of each voxel block; determining the voxel volume sum of each material characteristic value and the voxel volume sum of the voxel model; dividing each voxel block in the voxel model into an internal voxel block and a surface voxel block; defining the internal voxel blocks meeting a preset condition as potential surface voxel blocks; voxelizing all surface voxel blocks, potential surface voxel blocks and mixed voxel blocks in the voxel model again; combining the internal voxel blocks to form a voxel model; configuring a voxel attribute table and determining contents in the voxel attribute table; and outputting the voxel volume sum of each material characteristic value and the voxel volume sum of the voxel model.

The invention discloses a Doppler velocity filtering multipath false target suppression method and device, and a medium, and belongs to the technical field of millimeter wave radar target detection. The method comprises the following steps: acquiring radar point cloud data; performing dynamic and static point cloud data separation on the radar original echo data to obtain a static point cloud set and a dynamic point cloud set; clustering the static point cloud set, and performing linear boundary fitting according to a clustering result to obtain a linear equation of a reflection boundary; doppler velocities of corresponding first-order and second-order multipath false targets are respectively estimated for trace points in the dynamic point cloud set, and corresponding Doppler velocity search intervals are obtained; traversing the dynamic point cloud set, and performing global point cloud Doppler velocity filtering on the obtained search interval to obtain a filtered dynamic point cloud set; and performing multi-dimensional information judgment on the filtered dynamic point cloud set, and identifying a multi-path false target so as to realize multi-path false target suppression. According to the method, Doppler information is effectively utilized, so that a multipath false target is effectively identified and suppressed.

The invention discloses a formation resistivity determination method and device for a post-casing transient electromagnetic logging curve, equipment and a medium, and relates to the technical field of oil exploration and development, and the formation resistivity determination method comprises the following steps: obtaining a post-casing electromagnetic logging curve, and carrying out time sequence conversion and data preprocessing to obtain time sequence data; converting the data into frequency domain data by adopting wavelet transform, and performing multi-scale refinement splitting to obtain low-frequency features and high-frequency features; fitting the low-frequency features and the high-frequency features by using a symbol regression method to obtain a nonlinear high-dimensional symbol regression formula for the low-frequency data and a nonlinear high-dimensional symbol regression formula for the high-frequency data, and generating a post-casing electromagnetic logging curve nonlinear fitting formula; the mapping relation between the post-casing transient electromagnetic curve and the formation resistivity is determined through the post-casing electromagnetic logging curve nonlinear fitting formula, the formation resistivity is obtained, the uncertainty of manual selection of model parameters is avoided, the capacity of processing nonlinear problems is improved, and the accuracy and reliability of high-dimensional relation mapping and nonlinear fitting are improved.

The invention relates to a target detection performance curved surface progressive sampling method based on Gaussian process multi-core fusion. The invention relates to the technical field of target detection, in a target detection process, multi-level search space construction is carried out, and efficient kernel function combination and optimization are realized in a complex performance curved surface scene; a progressive sampling optimization strategy of a multi-scale collaborative adaptive kernel system is established, a kernel function combination structure and parameters are optimized step by step, and the fitting precision of a Gaussian process model to a target detection performance curved surface is improved. The method is mainly used for solving the problem of model performance evaluation under a multi-dimensional interference condition, and the performance evaluation efficiency and accuracy of the target detection model in a complex environment are improved by optimizing kernel function combination and parameter tuning.

The invention relates to the technical field of heavy metal contaminated soil remediation, in particular to a plant-microorganism-passivator synergistic remediation method for a heavy metal contaminated farmland, which comprises the following steps: step 1, constructing a soil digital twinborn model; step 2, intelligent decision making and verification of a collaborative restoration scheme; 3, soil pretreatment before remediation; step 4, hierarchical collaborative restoration and dynamic regulation and control; 5, performing long-term verification on the repair effect and performing model iteration; physical heat treatment is used as strengthening pretreatment, the occurrence form of heavy metal is changed through high temperature, biomass charcoal is generated in situ, passivation immobilization-microbial strengthening-plant extraction three-stage collaborative operation is carried out according to the time sequence, pollutants are rapidly locked through a passivating agent, rhizosphere immobilization is strengthened through functional microorganisms, plant growth is promoted, and the quality of plants is improved. And the hyperaccumulator finally removes the heavy metals from the soil, so that the unification of short-term control and long-term reduction is realized.

The invention relates to a permanent magnet synchronous motor full flux linkage model parameter identification method based on a full-connection neural network, and belongs to the technical field of permanent magnet synchronous motor control. The method comprises the following steps: deducing a discrete voltage equation of a motor voltage equation under the action of a digital controller according to a forward Euler method; obtaining a simplified discrete voltage equation under the condition that the given dq-axis current and load of the motor are maintained at stable values; according to the simplified discrete voltage equation, calculating flux linkage data corresponding to the current by changing the load torque and scanning the dq axis current; and obtaining a flux linkage value corresponding to the current through a mapping relation between the current and the flux linkage in the full-connection deep neural network flux linkage mapping model, and further obtaining the electromagnetic torque under the action of the current. According to the method, the full-connection neural network is constructed to carry out parameter learning and identification on the flux linkage, and the flux linkage-current mapping relation of the permanent magnet synchronous motor is accurately fitted.

The invention relates to the technical field of noise prediction, and discloses a shell high-frequency sound radiation forecasting method based on local optimization and deep learning, comprising: acquiring historical operation data of a shell of an underwater vehicle, the historical operation data comprising speed data, vibration data and sound radiation data; processing the historical operation data, and extracting key features; constructing a deep learning network model, and training the deep learning network model according to the key features; optimizing the deep learning network model by adopting a local optimization algorithm to obtain an optimal solution of parameters of the deep learning network model; the trained deep learning network model is endowed with the optimal solution of the parameters, and a shell high-frequency sound radiation forecasting model is obtained; and acquiring real-time operation data of the shell of the underwater vehicle, and determining a high-frequency sound radiation forecast value of the shell according to the real-time operation data based on the shell high-frequency sound radiation forecast model. According to the invention, the accuracy and efficiency of sound radiation prediction are improved, and online monitoring of shell noise is realized.

The invention relates to the technical field of remote sensing, and discloses a forestry loss value evaluation method, device and equipment and a storage medium. A second time sequence image data set and a first fitting model are combined to calculate a first difference image; and the change condition of the vegetation in the cloud-free area of the remote sensing image after typhoon disaster relative to the non-disaster state can be intuitively and quantitatively displayed. Furthermore, model training is carried out by using the environmental influence factor set and the first difference image, and a deep relationship rule of the influence of the typhoon disaster hidden behind the complex data on the forest can be mined. Furthermore, the normalized vegetation index difference value of the cloud coverage area is predicted by using the constructed model to generate a second difference value image, so that the spatial representation information of the disaster condition of the whole typhoon disaster area can be perfected. And finally, in combination with the real forestry loss value, the first difference image and the second difference image, rapid evaluation of the forestry loss value in the whole typhoon affected area can be realized.

The invention relates to the technical field of rock mass analysis, in particular to a karst area limestone mechanical property degradation mechanism analysis method and system, and the method comprises the following steps: obtaining limestone of a karst area to construct a limestone test sample; testing the limestone test sample to obtain a test result; observing the limestone test sample to obtain a microscopic feature observation result of the limestone test sample; analyzing the microscopic characteristic observation result to obtain a microscopic characteristic analysis result of the limestone test sample; and analyzing the limestone mechanical property degradation mechanism by combining the test result and the microscopic characteristic analysis result. The dynamic corrosion test is constructed to more accurately fit the rock mass degradation condition in the natural environment, and the change rule of the limestone mechanical property parameters is researched based on the dynamic corrosion test, so that the mechanical property degradation mechanism of the limestone in the karst area is analyzed, and a reliable theoretical technical support is provided for engineering application.

The invention discloses a rotary blowout preventer rubber core working performance evaluation method, and relates to the field of oil and gas development, and the method comprises the steps: building a strain energy function of a rubber core material, and defining the strain energy function as a first strain energy function; establishing a rubber core material damage function based on the Mullins effect, introducing the rubber core material damage function into the first strain energy function to obtain a strain energy function considering the Mullins effect, and defining the strain energy function as a second strain energy function; preparing a sample from the rubber core material, and performing a tensile test to obtain an actual stress-strain curve; fitting the second strain energy function based on the actual stress-strain curve to obtain material parameters of the rubber core material; establishing a finite element model based on the material parameters; and analogue simulation: evaluating the working performance of the rubber core based on an analogue simulation result. The method is used for solving the problem that it is difficult to evaluate the influence of the Mullins effect on the sealing performance of the rubber core of the rotary blowout preventer through the prior art, and the purposes of evaluating the working performance of the rubber core on the premise of considering the Mullins effect and providing a more accurate evaluation method for the safety of the rotary blowout preventer are achieved.

The invention relates to the field of image processing, in particular to a video image distance measurement method based on a feature target. The method comprises the following steps: setting a feature target with a feature pattern, acquiring a field image through an industrial camera, detecting and identifying edge data of a feature point, carrying out edge fitting to obtain a detection parameter, carrying out feature matching on the detection parameter and an actual value, and determining an optimal center position of the feature point; and calculating the central point of the feature graph by using the optimal central position of the feature point, and finally calculating the included angle and distance between the feature target and the industrial camera lens. Through setting the feature target, video distance measurement can be rapidly carried out, distance measurement can be determined without obtaining excessive image detail features, the use is simple, and the measurement precision is high.

The invention provides a business process execution method and related equipment, and the method comprises the steps: carrying out the intention recognition of a business request, and obtaining a structured intention and key entity information; based on the structured intention, constructing a business process comprising a plurality of executable tasks; executing each executable task in the business process in sequence, and extracting a target cue word template matched with the structured intention from a cue word factory when a target task of a preset large model needs to be called in each executable task is executed; filling the key entity information into the target cue word template to obtain a parameterized cue word; and based on the parameterized cue word, calling a preset large model to execute the target task, and continuing to execute the remaining executable tasks in sequence after the target task is executed. In the scheme, dynamic binding of the cue word and the business scene is realized, and the accurately customized cue word can be automatically generated for different scenes, so that accurate adaptation to diversified business scenes in automatic execution of the business process is realized.

The invention relates to the technical field of marine environment numerical simulation, in particular to a near-shore typhoon wave refined simulation method based on terrain adaptive grids and parameter dynamic correction, and the method comprises the steps: obtaining basic data and simulation parameters of a target sea area, constructing a computational domain and an initial grid, and constructing a target sea area; the initial grid is an unstructured grid fused with multiple physical constraint factors; performing optimization processing on the initial grid based on a numerical stability criterion to obtain a final calculation grid meeting a calculation convergence requirement; establishing a bidirectional coupling model, and applying the final computational grid to the bidirectional coupling model; carrying out localization iteration calibration on key physical parameters of the bidirectional coupling model to obtain an optimal parameter set; and carrying out typhoon wave process simulation calculation and constructing a typhoon wave feature database by utilizing the final calculation grid and the optimal parameter set, and realizing high-precision simulation and prediction of the typhoon wave process by constructing an adaptive optimization grid, a bidirectional coupling model and a parameter localization calibration mechanism.

The application provides a large-diameter slurry shield safety stability multi-objective online optimization method and system based on GAT-LSTM-MOMPA, and belongs to the technical field of shield tunnel construction parameter multi-objective online optimization. The method comprises the following steps: obtaining monitoring data of shield construction parameters and preprocessing, and establishing an original sample set; adopting a method combining knowledge driving and correlation analysis, input parameters and output targets of a prediction model are determined; a space-time deep learning network framework GAT-LSTM is built, the mapping relationship between the input and the output is determined, and accurate prediction of the future time step optimization value is realized; through connection with MOMPA and TOPSIS, the historical value of the model is constantly updated, and accurate and effective real-time online optimization is achieved. The GAT-LSTM-MOMPA multi-objective online optimization model established by the application effectively improves the safety and stability of the shield machine operation.

This invention relates to the field of glass production testing technology, specifically disclosing a glass cold bending ultimate failure test device and method. The device includes a worktable and four identical cold bending loading units. Each unit integrates a planar displacement structure with horizontal displacement capability, a liftable and directional adjustable support structure, and a pressure head connected by a ball joint. During testing, the planar displacement structure of each unit is first adjusted to accommodate glass specimens of different sizes. Then, the support structures of three units form an L-shaped support surface, and their pressure heads press against corresponding corner points on the upper part of the specimen to establish stable constraints. Finally, the pressure head of the fourth unit applies a concentrated load to the unconstrained corner points, while automatically monitoring the load and displacement until the specimen fails. This invention, through modular and automated design, achieves high versatility of the device, high testing accuracy, and high operational safety, effectively improving testing efficiency and data reliability.

This invention discloses a hip joint prosthesis for bone defects, comprising a crescent-shaped acetabular rim filler assembly, a bone-metal defect block, an acetabular wall defect support block, a cylindrical support block, an angle pad, a locking screw, a locking nut, an assembly screw, an acetabular sealing screw, and an acetabular support block. The crescent-shaped acetabular rim filler assembly includes two sets of crescent-shaped acetabular rim fillers, which are assembled by engaging pins through pin holes. The outer circumference of the bone-metal defect block of the acetabular support block is connected to the crescent-shaped acetabular rim filler assembly via bone cement. This hip joint prosthesis for bone defects effectively fills irregular defect areas of the acetabular rim. The various screw holes and Kirschner wire holes on its surface provide multi-dimensional fixation options. The overall structure, through the synergistic action of multiple components, achieves precise reconstruction while ensuring biomechanical performance, significantly reducing the risk of postoperative prosthesis loosening and wear.

The utility model discloses an automobile die sundry cleaning device relates to automobile die cleaning equipment technical field, and this device includes work table, support frame and sliding slot, the support frame is installed in the top of work table, the sliding slot is set up in the both sides of support frame, the inside sliding connection of sliding slot has the sliding block, and the rotatory column is rotatoryly connected between two sliding blocks, the outer wall on rotatory column both ends is fixedly connected with fixed block, and the top swing of fixed block has the die, the inside of support frame is provided with the brush, be provided with the moving assembly for moving to the brush on the support frame, and the clamping assembly for clamping the die is set up between two fixed blocks. The utility model drives first screw rod and second screw rod to rotate through two third motor respectively, realizes the movement of brush in horizontal direction and vertical direction, and then combines the vertical movement of brush in the direction of second electric push rod control, makes the brush can cover each position of die.

The present invention provides a control method and device for an environment adjustment device, and an intelligent environment adjustment system. The environment state of an entire space is accurately reflected based on environment parameters collected at limited positions, and accurate environment parameters corresponding to the positions of the plurality of users can be easily acquired, whereby an environment parameter distribution of the entire space can be acquired at a low cost and applied to many large spatial areas; a target parameter distribution of the environment adjustment device is acquired by using a first prediction model from the state parameter overall value reflecting the overall state of the plurality of users, whereby the target parameter distribution can be accurately adapted to the plurality of users as a whole; and the deviation between an actual setting and an ideal setting can be reduced while the plurality of users can all be in a comfortable state, thereby improving the performance of the device and user experience.

The invention discloses a method for calculating an approximate circle diameter in a touch algorithm, which comprises the following steps of: 1, calculating a central physical coordinate according to original data obtained by touch, and taking the central physical coordinate as an expected value; step 2, calculating a covariance; step 3, constructing a covariance matrix; 4, performing eigenvalue decomposition on the constructed covariance matrix to obtain eigenvalues; step 5, calculating an initial ellipse semi-axis length through the characteristic value; step 6, calculating an equivalent diameter; step 7, simulating a curve equation by using a plurality of samples; and step 8, when actual touch occurs, obtaining the equivalent diameter through the steps 1-6, and calculating to obtain the diameter of the touch object. According to the method, eigenvalue calculation processing is carried out on the original covariance matrix, the contour of a real touch area can be accurately fitted, coordinate distribution characteristics in a theoretical model are considered, original data and physical size factors of a sensor are combined, and therefore the accuracy of touch size calculation is remarkably improved.

The damping underframe comprises an underframe body, a centrifugal machine body is fixed to the surface of the underframe body in a screwed mode, four sets of underframe damping shock-absorbing seats are evenly and fixedly arranged at the bottom of the underframe body, and meanwhile the underframe damping shock-absorbing seats are fixed to the workshop ground in a screwed mode through bottom plates at the bottoms of the underframe damping shock-absorbing seats; and the chassis damping shock-absorbing seat comprises a guide column fixedly arranged on the surface of the bottom plate, the guide column is inserted into a guide groove, and meanwhile, the guide groove is formed in a damping cylinder. According to the damping underframe for the centrifugal machine, the compression amount of the spring can be flexibly adjusted according to different application scenes and load conditions so as to better adapt to various working conditions, and more accurate adaptation can be achieved on heavy-load equipment and light-load equipment; by adjusting the compression amount of the spring, the damping performance of the damping seat can be optimized, and it is ensured that a good damping effect can be achieved under different vibration frequencies and amplitudes.

The invention relates to an electric vehicle fault current evaluation method considering the influence of the state of charge of a battery, and the method comprises the steps: calculating the critical state of charge of constant current-constant voltage charging switching of an electric vehicle, and judging whether the electric vehicle is charged at constant current or constant voltage according to the state of charge of the electric vehicle at a fault moment; and in a constant-current or constant-voltage charging state, respectively calculating a critical charge state of fault current over-damping / under-damping under constant-voltage or constant-current charging of the electric vehicle, judging whether the fault current is over-damping or under-damping according to the charge state of the electric vehicle at a fault moment, and respectively calculating the fault current of the electric vehicle by adopting a corresponding expression. The method can consider the influence of the state of charge on the fault current of the electric vehicle, accurately estimates and calculates the fault current of the electric vehicle, and provides more accurate reference data for the fault current analysis of the new energy power distribution network under the access of the electric vehicle. And therefore, accurate charging fault early warning or power distribution and power supply management of the charging management system on the new energy power distribution network can be better ensured.

The utility model discloses a filter support, including fixed frame, two active elements, two driven module and transmission part. Active element and driven module all are opposite fixed frame mobile setting, and transmission part is opposite fixed frame rotation setting. Two active elements and two driven module are along annular arrangement, and a driven module is located between two active elements. Active element and transmission part transmission connection, and driven module also with transmission part transmission connection. When active element is opposite fixed frame mobile, can drive transmission part opposite fixed frame rotation, and then promotes driven module to move to the same mobile direction with active element. The structure realizes the cooperation of active element and driven module through transmission part, improves the adjustment flexibility, can better adapt to different caliber lens, reduces the dark corner, satisfies the diversified shooting demand.

The invention discloses a variable frequency motor adaptation method and device, electronic equipment and a storage medium, and relates to the technical field of variable frequency motor adaptation. According to the technical scheme, the motor database of the on-line variable frequency motor is obtained, and the motor database is composed of corresponding motor parameters of various on-line variable frequency motors of different models; the method comprises the following steps: grouping a motor database according to a plurality of preset index entries to obtain an initial grouping result of all online variable frequency motors; updating the initial grouping result according to the control parameter of the frequency converter adapted to each online variable frequency motor to obtain a target grouping result of the online variable frequency motors; and when the variable frequency motor needs an adaptive component, searching for adaptation in the target grouping result according to the motor parameters of the to-be-adapted variable frequency motor to obtain a target adaptation result of the to-be-adapted variable frequency motor. According to the technical scheme, the adaptive efficiency and accuracy of the variable frequency motor are considered.