90results about How to "Improve fitting accuracy" patented technology

A broadband voltage transformer error compensation method is proposed. First, a broadband test platform is constructed using a signal generator, power amplifier, standard voltage transformer, and high-bandwidth data acquisition system. The ratio and phase errors of the transformer at multiple frequency points are acquired through primary-side excitation and secondary-side synchronous acquisition. Based on the slope, first derivative, and second derivative characteristics of the error curve, the entire frequency band is adaptively divided into segments. Within each segment, multiple candidate models are fitted using a polynomial or exponential-linear combination model. The optimal model is selected based on the coefficient of determination, mean absolute error, and root mean square error. Ratio and phase error compensators are constructed based on the fitting functions of each segment, and error compensation is achieved using a feedforward approach. This method can significantly reduce amplitude and phase errors over a wide frequency range, improving the dynamic measurement accuracy of the voltage transformer.

This application relates to the field of gas sensor packaging technology, specifically to an automated packaging method, system, and packaging device for gas sensors. The method includes: pre-establishing a packaging process parameter-gas-sensitive channel adaptation model; calculating the actual coaxiality deviation and correcting the sealing pressure reference value based on the gas-sensitive channel aperture; starting the integrated packaging unit, applying pre-pressure according to the corrected sealing pressure, and simultaneously collecting the temperature of the sealing area through an infrared temperature measurement module to determine whether dynamic adjustment of the welding temperature is needed; after welding, maintaining the corrected sealing pressure, and dynamically adjusting the pressure holding time based on the gas-sensitive channel length and the creep coefficient of the sealing material to complete the sealing process. This application achieves a precise balance between sealing performance and conduction efficiency by establishing a dynamic adaptation model of process parameters and gas-sensitive channel structure, overcoming the coupling imbalance bottleneck of existing technologies.

The present application relates to the technical field of magnetic element modeling and control, and particularly relates to a multi-factor magnetic core loss prediction method based on machine learning. The method first acquires the magnetic flux density data of the magnetic element, extracts its distribution characteristics and shape characteristics, and realizes excitation waveform recognition by constructing a classification model; secondly, a temperature index correction term is introduced based on the Steinmetz equation to establish a temperature-sensitive loss model; further, the entropy weight method and statistical analysis are used to evaluate the importance of multiple factors; an integrated learning model of random forest and LightGBM is used to construct a magnetic core loss prediction model; and a single-objective optimization model is established by combining differential evolution and simulated annealing algorithm with the objectives of minimum loss and maximum magnetic energy transmission. The method improves the generalization ability and prediction accuracy of the model, can adapt to the modeling needs of magnetic core loss under multiple material, multiple waveform and multiple working condition conditions, and is suitable for application scenarios such as high-frequency magnetic element design and power electronic system optimization.

The invention relates to a one-dimensional function fitting method and system based on input dimension expansion, and the method comprises the steps: firstly obtaining a target function and a training sample thereof, carrying out the dimension expansion of each input scalar according to an odd-dimension central symmetry rule: placing the scalar at the center of an expansion vector, and filling the two sides with the same constant related to a domain of definition; and constructing a neural network taking the extended vector as input, and adjusting the width of the hidden layer to enable the deviation between the total parameter number and the reference model not to exceed a set value, thereby realizing parameter redistribution. Then, a second-order optimization algorithm is used to train the network. During prediction, new input is input into the trained model after dimension expansion according to the same rule, and a predicted value is obtained. According to the method, parameter arrangement symmetry is actively broken, and the loss function landscape is remarkably improved.

The invention relates to the technical field of high-strength steel production, in particular to an ultrahigh-strength steel cold-rolled material constitutive hardening model construction method. Simulating rolling; measuring mechanical properties; data processing and drawing; and performing linear fitting. The method has the advantages that based on the idea of combining physical experiments and mathematical modeling, a constitutive model is established through the systematized process of'simulated rolling + mechanical property measurement + double logarithmic linear fitting ', data processing software is adopted for data processing and linear regression, a power function hardening model is obtained, and the method has the advantages of being simple in structure, convenient to operate and high in practicability. The method shows excellent fitting precision in 980MPa and 1180MPa ultrahigh strength steel, the model has clear statistical support, and the prediction accuracy and reliability of the material hardening behavior are remarkably improved; the whole modeling process is clear in step and conventional in equipment, only a conventional two-roller cold rolling mill, a universal tensile testing machine, a wire cutting machine and general data processing software are needed to complete the modeling process, and the whole process from sample preparation to model output is high in standardization degree.

The invention relates to the technical field of land pollution treatment, solves the problem that in the prior art, when a large-area medium polluted by hexavalent chromium is treated, the addition amount of ferrous sulfide is prone to being inaccurate, and consequently the remediation effect is not ideal, and provides ferrous sulfide particles with shells and a preparation method and application of the ferrous sulfide particles. The prepared ferrous sulfide particles with the shells can keep efficient removal of chromium within the pH value range of 5-9, the problem that the adsorption behavior of a traditional model in a low-chromium-concentration area is difficult to predict is effectively solved by means of a correction adsorption model with higher fitting precision, and therefore the actual demand quantity of target repairing liquid can be accurately predicted, and the application prospect is wide. The target repairing liquid can be injected more accurately, and excessive or insufficient injection is avoided. After hexavalent chromium is reduced into trivalent chromium by ferrous sulfide, the trivalent chromium and carboxymethyl cellulose can form a stable chelate, and zero-valent sulfur can also form a compact passivation layer on the surface of a polluted medium, so that the trivalent chromium is prevented from being reoxidized, and long-term stable repair of hexavalent chromium is realized.

The application provides an SDA spectrum design automation method, comprising: setting a database, the database storing curve data and radiation flux parameters of standard lamps, and importing corresponding target curves; generating a plurality of formula groups according to the target curves, each formula group containing at least one setting parameter of a standard lamp, the setting parameter comprising a lamp name, a current value and an occupancy ratio; performing curve fitting calculation on each formula group to generate a fitting curve, respectively acquiring an absolute amplitude curve of each group of standard lamps, and performing area integral superposition on all absolute amplitude curves participating in fitting to obtain the fitting curve; verifying the fitting curve through a multi-dimensional verification strategy to obtain a score result, selecting a formula group with the highest score as an optimal formula group, and judging whether the optimal formula group meets an expectation; if the optimal formula group meets the expectation, outputting the optimal formula group; if the optimal formula group does not meet the expectation, initializing a formula and regenerating a new formula group.

The present application relates to the technical field of strain sensor detection calibration, and particularly relates to a sub-micron FBG strain sensor calibration device and a calibration method. In terms of the calibration device, the first guiding clamping mechanism and the second guiding clamping mechanism realize synchronous displacement movement by relying on the guiding action of the first force bearing plate and the second force bearing plate respectively, the micro-displacement required for calibration operation is generated by changing the clamping interval of the first guiding clamping mechanism and the second guiding clamping mechanism, and combining the geometric constraint relationship of the first force bearing plate and the second force bearing plate fixed at a preset angle. During the calibration operation, the displacement detection mechanism collects real clamping interval change data of the first guiding clamping mechanism and the second guiding clamping mechanism in real time, the control mechanism dynamically corrects the output parameters of the micro-displacement driving part according to the real-time displacement feedback signal, realizes the sub-micron high-precision closed-loop control of the calibration displacement, and is beneficial to greatly improving the fitting accuracy of the wavelength parameters and the strain response parameters of the FBG strain sensor.

The invention relates to the technical field of battery sealing nail welding, and provides a battery sealing nail welding defect repairing method. The repairing method comprises the following steps: acquiring an aluminum wafer of which the diameter is greater than that of a liquid injection hole of the battery top cover; removing the sealing nail at the liquid injection hole of the top cover of the battery; cleaning a liquid injection hole area; carrying out penetration type stitch welding by taking the wafer as an upper layer and the battery top cover as a lower layer to form a welding seam for melting the wafer and the battery top cover into a whole; and treating the welding seam and the wafer, enabling the outer surface of the wafer to be flush with the outer surface of the battery top cover, and enabling the liquid injection hole area not to be visually recognized. According to the repairing method, the aluminum wafer and the battery top cover are subjected to penetration stitch welding, and the welding seam and the surface of the wafer are treated, so that the welding defect of the sealing nail is repaired, the situation that the battery is degraded and scrapped due to poor welding or appearance defect of the sealing nail is avoided, and the quality requirement of the battery is met.

The utility model discloses a material stripping module. The material stripping module comprises two supporting seats, and a first compression roller assembly, a second compression roller assembly and a stripping knife assembly which are connected between the two supporting seats, the second compression roller assembly is located on one side of the first compression roller assembly. The stripping knife assembly is located on one side of the second compression roller assembly. A sliding driving device capable of driving the stripping knife assembly is further arranged on the supporting seats, and the stripping knife assembly is arranged on the two supporting seats; a material belt sequentially passes through the first pressing roller assembly, the stripping knife assembly and the second pressing roller assembly, and a product on the material belt is stripped from the material belt at the stripping knife assembly. The stripping module has the beneficial effects that in the advancing process of the material belt, the first pressing roller assembly and the second pressing roller assembly are matched to fix the material belt, the stability of the stripping module in the stripping process is improved, and semi-finished glue can be effectively prevented from accidentally falling off in the stripping process.

The invention discloses a method for measuring a magnetic field of an inertial measurement system, which realizes accurate reconstruction of a global magnetic field vector field by planning a discrete point test layout, synchronously acquiring multi-dimensional data and constructing a magnetic field vector fitting model. The method comprises the steps of test area division and discrete point layout, multi-source data synchronous acquisition, data preprocessing and abnormal value elimination, global magnetic field vector field fitting modeling, and fitting result verification and optimization. According to the method, a discrete point layering layout strategy is adopted, a multivariable fitting algorithm is combined, magnetic field space change characteristics can be effectively captured, global magnetic field vector field fitting errors are controlled, and the method is suitable for inertial measurement system magnetic field performance detection and optimization design and has the advantages of being high in measurement speed, high in representation precision and high in practicability.

This invention relates to the field of lithium battery asset management and value assessment technology, particularly a lithium battery asset lifecycle health management and value assessment system. The system comprises a physical asset access layer, a digital twin construction and assessment layer, an economic value mapping and calculation layer, and a strategy generation and closed-loop optimization layer forming a two-way data closed loop, all connected sequentially. The system accesses multi-source heterogeneous time-series data throughout the lithium battery lifecycle, constructs a digital twin coupling an electrochemical degradation mechanism model and a data-driven model, calculates the real-time dynamic economic value vector of the lithium battery, generates operational optimization strategies with the goal of maximizing the asset value throughout the lifecycle, and iteratively optimizes the model through feedback on execution results. This invention achieves deep integration of lithium battery health management and asset value management, and can be widely adapted to the refined management needs of lithium batteries throughout their entire lifecycle in various scenarios.

This utility model relates to a labeling device, including a labeling table for fixing a paper roll, a label dispenser for horizontally dispensing labels from its dispensing port to a labeling head, and a labeling head for vacuum-fetching labels from the label dispenser and applying them to the paper roll. The labeling table has a paper roll fixing structure and also includes a robotic arm for moving the labeling head outside the dispensing port to vacuum-fetch labels, moving the labeling head with the labels above the paper roll, and lowering it to apply the labels to the paper roll. The labeling head includes a fixing frame, a linear guide rail, a vacuum plate for upward suction or downward blowing, and a limiting pin. This utility model expands the application range, improves the bonding accuracy, prevents label wrinkles, bubbles, and product damage, and is suitable for automated labeling of various product specifications.

The utility model discloses a self-adaptive tension transferring and pasting roller set structure suitable for a circular knife machine. The self-adaptive tension transferring and pasting roller set structure comprises a supporting frame, an upper roller set, a lower roller set, an eccentric bearing, an elastic adjusting assembly, a limiting assembly, a pressure sensing assembly, a fine adjustment mechanism, a control module, a proportional pressure valve and a return spring. The elastic adjusting assembly is composed of a spring set and a damping air cylinder and provides basic pressing and buffering adjusting functions. The pressure sensing assembly detects the tension of a membrane material through a tension detection wheel, and a signal adjusts the pressure of a damping cylinder through a proportional pressure valve via a control module to form closed-loop adjustment of the pressure between rollers; the eccentric bearing is matched with the return spring to ensure that the upper roller group swings and resets stably; the fine adjustment mechanism is used for setting a roller gap initial value. The structure can dynamically adjust the pressure between the rollers according to the tension change, improves the laminating stability, and is suitable for a high-speed film material transferring and laminating process.

The invention discloses a high-precision full-elevation sky-ground radiation signal correction method and device, and belongs to the technical field of radiation signal processing, and the method comprises the steps: carrying out the preprocessing of a to-be-processed sky-ground radiation signal, and obtaining a zero-offset sky-ground radiation signal; calculating a soft decision function transformation coefficient and a mixed function weight coefficient according to the skewness value of the zero-offset sky-earth radiation signal; substituting the soft decision function transformation coefficient and the mixed function weight coefficient into a pre-constructed mixed function transformation model, and using the mixed function transformation model to perform soft saturation transformation on the zero-offset sky-earth radiation signal to obtain a rectified sky-earth radiation signal; and fitting the rectified space-ground radiation signal to obtain a rectified space-ground radiation signal fitting curve. The method does not need to depend on a simplified mathematical model, does not need external reference information, can achieve the rectification of the space-ground radiation signal in a dynamic environment, and remarkably improves the reliability and robustness of a space-ground radiation measurement system.

The application discloses a modular quick-change module of an OMR vacuum laminating machine and a laminating device, relates to the field of vacuum laminating machines, and comprises a rack, a linear module is mounted on the inner side of the rack, an installation plate is fixedly connected to the top of the linear module, a workpiece is placed on the inner side of the installation plate, a hydraulic cylinder is mounted on the inner side of the rack, and a top seat is fixedly connected to the output end of the hydraulic cylinder; the cooperation of the rectangular plate and other parts enables the second nozzle to start from the sealed end, gradually advance to the middle area and the area close to the other end, and apply uniform pressure; this process not only continuously discharges air to the end, but also assists the close lamination of the film and the workpiece surface through uniform air flow pressure, ensures that the back glue of each area can fully contact the workpiece, reduces the air bubble hidden danger caused by local lamination from the root, and realizes the dead-angle-free air exhaust from one end of the workpiece to the other end, and further reduces the overall air bubble generation rate.

The invention provides a circuit board life prediction method and system based on mass failure welding spot data and a risk matrix, electronic equipment and a storage medium, and relates to the field of welding spot failure. The method comprises the following steps: acquiring massive invalid welding spot data, and extracting welding spot failure mechanism characteristics from the invalid welding spot data based on expert knowledge to obtain welding spot failure mechanism characteristics; based on the welding spot failure mechanism characteristics, welding spot failure characteristic factors are determined; acquiring welding spot failure characteristic factor data and circuit board data of a to-be-predicted circuit board, and determining welding spot failure data of the circuit board based on the welding spot failure characteristic factor data; and determining a welding spot failure type based on the welding spot failure data, and inputting the circuit board data and the welding spot failure type into a preset life prediction model to obtain a life prediction value. By means of the method, mass data are deeply utilized, essential reasons influencing welding spot faults are found out, and accurate evaluation and prediction of the residual life of the circuit board are achieved.

The application relates to the technical field of computer-aided design. By providing an AI all-ceramic crown bionic design and mechanical property optimization method based on deep learning, the method comprises the following steps: generating an initial crown geometric model based on crown design space constraints by using a physically embedded generative adversarial network; predicting the mechanical properties of the initial crown geometric model and outputting stress distribution data; simulating the manufacturing deformation process of the initial crown geometric model to obtain manufacturing deformation prediction data; fusing the physical field gradient of the stress distribution data and the manufacturing deformation prediction data to obtain optimization gradient data; updating the physically embedded generative adversarial network by using the optimization gradient data to obtain an optimized crown shape; and converting the optimized crown shape into an executable manufacturing instruction set, so that the technical effects of improving the anatomical shape adaptation accuracy, enhancing the mechanical property prediction accuracy and reducing the design optimization iteration number are achieved, and the clinical applicability of the crown product is improved.

The present application relates to the technical field of mine hoist protection, in particular to a heavy-load mine monorail hoist derailment prevention protection mechanism, comprising a long slide rail frame, a sliding mechanism and a heavy-load carriage, the sliding mechanism is slidingly connected to the end of the long slide rail frame, and the heavy-load carriage is movably installed at the bottom of the sliding mechanism; wherein the sliding mechanism is provided with a basic operation mechanism and a derailment prevention braking assembly, the basic operation mechanism can complete adaptive adjustment assembly according to the actual working condition of the track, and realize the front prevention and control of the derailment risk, the present application not only is provided with the basic operation mechanism to realize adaptive adjustment assembly and effectively prevent and control the front derailment risk, but also is additionally provided with the derailment prevention braking assembly, so that when the wheel encounters sudden abnormal working condition, it can quickly respond, through the rapid switching of the alternative wheel or the emergency braking operation, the stable and close contact state between the sliding mechanism and the long slide rail frame is maintained, thereby greatly improving the safety and reliability of the monorail hoist operation.

The application discloses a kind of folding screen automation processing OCA membrane laminating device, it is related to flexible screen processing field, including equipment rack, equipment rack is respectively equipped with material box feeding device, laminating device, visual alignment mechanism, film tearing mechanism, Plasma cleaning mechanism, material box feeding device is separately arranged in equipment rack front and back two sides, six-axis manipulator is equipped below laminating device, laminating device is driven transversely by X direction linear motor, visual alignment mechanism is respectively arranged below laminating device and above PET film attachment platform, visual alignment mechanism is divided into OCA visual alignment component and PET visual alignment component, film tearing mechanism includes OCA film tearing component and PET film tearing component, OCA film tearing component is installed on six-axis manipulator, PET film tearing component is installed on equipment rack and located above PET film attachment platform, the present application can overcome the industry pain points such as ultra-thin OCA film production, bubble, indentation, improve folding screen OCA membrane laminating production yield and product consistency.

This invention discloses a data-driven causal inference-based auxiliary decision-making method for low-carbon operation of power generation, comprising the following steps: (1) collecting and preprocessing data from thermal power plants; (2) constructing a causal graph reflecting the relationship between variables; (3) identifying control variables in the causal inference; (4) using a matching algorithm to calculate and filter matching values, thereby obtaining causal inference functions for intervention variables and outcome variables; and (5) evaluating the sensitivity of low-carbon operation control of thermal power plants based on the causal inference function obtained in step (4). This invention constructs a causal graph, fits the relationship between operation control quantities and carbon emissions based on data-driven causal inference, performs sensitivity analysis on carbon emission levels, and thus achieves reasonable control of carbon emissions, thereby realizing auxiliary decision-making for low-carbon operation of thermal power plants.

This utility model relates to the field of bonding equipment technology and discloses a UV laminating machine that uses photocuring technology to press and bond different materials. It includes a support cabinet assembly, which is equipped with a UV curing and control host, a bonding platform, and a pressing and limiting component. The support cabinet assembly includes a working side cabinet with a built-in chiller to reduce the internal temperature of the equipment and ensure stable operation. A movable support is located at the bottom of the working side cabinet, and casters with brakes are installed at the bottom of the working side cabinet next to the movable support. This utility model effectively solves the heat dissipation problem by using a built-in chiller in the working side cabinet, opening heat dissipation vents, and employing heat insulation materials, combined with the top heat dissipation vent of the UV curing and control host, thus extending the service life of components such as the UV light source curing lamp and improving the bonding quality.

The utility model relates to the field of automatic rubberizing machines, and discloses a battery pack protective film automatic rubberizing machine which comprises a machine body, a support is fixedly connected to the side wall of the machine body, a conveying belt is arranged on the surface of the support, a containing box is fixedly connected to the outer wall of the machine body, and a gluing bin is fixedly connected to the top of the machine body. The top of the machine body is fixedly connected with a supporting frame, the top of the supporting frame is fixedly connected with a motor, the output end of the motor is fixedly connected with a rotating frame through a rotating shaft, the top of the rotating frame is fixedly connected with an air cylinder, the output end of the air cylinder is fixedly connected with a fixing frame, and the inner wall of the fixing frame is fixedly connected with a vacuum pump. According to the utility model, by arranging the supporting frame, the motor, the rotating frame and other structures, the laminating operation efficiency between the battery pack and the protective film is ensured, the risk of deviation caused by impact due to too high or too high laminating speed is avoided, and the laminating precision is improved.

The utility model relates to the technical field of optical cement lamination, in particular to a portable OCA (Optical Clear Adhesive) lamination auxiliary device which comprises a working table, a lamination mechanism, a feeding box, a first feeding mechanism, a second feeding mechanism, a third feeding mechanism, a fourth feeding mechanism, a fifth feeding mechanism, a sixth feeding mechanism, a seventh feeding mechanism, a seventh feeding mechanism, a seventh feeding mechanism, a seventh feeding mechanism and a seventh feeding mechanism. According to the portable OCA optical cement laminating auxiliary device, all parts of the device are integrated on the workbench, the structure is compact, the occupied area is small, arrangement is convenient, the space utilization rate of a production site is increased, a driving cylinder on a supporting base controls a moving frame to ascend and descend, a motor drives a rotating arm to rotate, and a laminating base is converted into a laminating state from a feeding state; and then the driving cylinder drives the moving frame and the laminating seat to move downwards, the optical cement product is laminated on the object, the laminating strength is accurately controlled, the problems of bubbles, deviation and the like when the optical cement is laminated on the object are avoided through negative pressure adsorption, the laminating precision and quality are improved, and meanwhile, the feeding speed is high, and the laminating efficiency is high.

The application discloses a kind of aircraft global time-varying aerodynamic parameter identification method, comprising: S1. establishing aircraft rigid body dynamics model, and obtaining time-varying parameter to be identified;S2. the time-varying parameter to be identified is written as polynomial form about time;S3. state sensitivity, covariance sensitivity, gain sensitivity, filter state sensitivity and covariance sensitivity are estimated;S4. according to aerodynamic parameter characteristics or time period, carry out local subarea;S5. in current interval, obtain state estimated value, estimated covariance matrix, Kalman gain, state filter value, covariance matrix by parameter value in combination with Kalman filter;S6. according to the above obtained criterion function, when criterion function is not minimum value, parameter is updated using Newton-Raphson algorithm;S7. using moving average filter to smooth all parameters, obtain a smooth global aerodynamic data curve.The application avoids the problem that fitting is not accurate when parameter variation amplitude is too large.

The application relates to the technical field of panel display, in particular to a high-precision substrate laminating device for a very warm liquid environment. The device comprises a base, a protective cover, a pressing module, a temperature control module, a lower laminating table and a visual positioning module. The base is provided with the protective cover. The pressing module is fixedly installed on the base in the protective cover and used for installing an upper substrate. The temperature control module is installed on the base in an inclined manner below the pressing module. The lower laminating table is installed in the temperature control module in an inclined manner and used for installing a lower substrate. The visual positioning module is fixedly installed on the base at one side of the temperature control module and extends into the temperature control module and is used for positioning the substrate. The application has the advantages of high laminating precision, good size adaptability, provision of a very warm working environment and reduction of bubble phenomenon, solves the problems of low laminating precision, poor size adaptability, only suitable for normal temperature use and easy bubbling of existing substrate laminating equipment, and meets the needs of substrate lamination in a very warm liquid.

The invention discloses a winding forming die for a tail stay tube of an unmanned aerial vehicle. The winding forming die comprises a mandrel, a small-head yarn blocking ring, a large-head yarn blocking ring, a pressing ring, a force application ring and a clamping shaft. The mandrel is the main part of the whole die, is consistent with the tube surface of the tail boom in shape and is used for winding the tube surface of the tail boom; the small-head yarn blocking ring and the large-head yarn blocking ring are of an annular flange plate and nail-shaped structure, are fixed to the mandrel through bolts and are used for blocking yarn during winding. The pressing ring is used for pressing the flange of the small end of the tail stay tube, the force application ring and the corresponding shaft are provided with threaded holes used for applying pressure to the pressing ring, the flange of the tail stay tube is pressed by applying force through the bolt, and the forming quality of the flange of the tail stay tube is guaranteed. The clamping shaft is used for clamping the driving end of the winding machine when the tail supporting pipe is wound. The winding forming mold for the tail stay tube of the unmanned aerial vehicle can guarantee the product quality of the tail stay tube, and is reasonable in structural design, convenient to demold and convenient to use.

This invention discloses a high-precision automatic magnetizing device for high-thrust stators, relating to the field of linear motor manufacturing technology. The device includes a guide table, a magnet pushing mechanism, a pressure holding mechanism, a stator base plate loading / unloading mechanism, and a demolding mechanism. The magnet pushing mechanism is mounted on the mover of a first linear module, and the stator base plate loading / unloading mechanism is mounted on the mover of a second linear module. The first and second linear modules are parallel to each other. The guide table is supported by legs above the intersection area of ​​the two linear modules and remains stationary. The stator base plate loading / unloading mechanism achieves coarse positioning through the cooperation of a preliminary positioning rod and a clamping block. After being lifted, it disengages from the preliminary positioning rod, and a clamping cylinder pushes the stator base plate tightly against the positioning step at the bottom of the guide table for secondary fine positioning. The pressure holding mechanism uses a U-shaped pressure holding block to move horizontally along the pushing direction to overcome the repulsive force between like poles of adjacent magnets in the same slot. The demolding mechanism pushes the product downwards after all magnets are bonded to overcome the attractive force between opposite poles, achieving fully automatic high-precision magnetizing operation.

This invention discloses a method for calculating the installed capacity of distributed generation (DG) in a distribution area based on the time-series power of distribution transformers. The method includes: classifying the target distribution area by DG type; matching the DG type classification results with corresponding time period filtering principles; filtering the corresponding pure load time periods according to the time period filtering principles; obtaining pure load time period data; classifying the pure load time period data by date type; extracting the load cycle features corresponding to each date type; fitting the load cycle features using a pre-trained LSTM neural network model; outputting the load prediction value corresponding to the pure load time period; calculating the DG output at the corresponding time based on the load prediction value; filtering the maximum DG output value for the pure load time period; assigning dynamic coefficients to the maximum DG output value; and outputting the actual installed capacity of the target distribution area. This method improves the accuracy of DG installed capacity calculation, enhances data robustness, is applicable to a wider range of application scenarios, and is low-cost and easy to implement.

The invention discloses a virtual machine template library construction method and system for active medical instrument software detection, and relates to the technical field of active medical instrument software detection, a targeted classification system and a four-layer basic template frame are constructed, exclusive dependence, detection tools and compliance configuration are built in, the standard requirements are highly met, and the detection efficiency is improved. The adaptation precision of the template and medical instrument software of different types and versions is greatly improved, the consistency of the detection environment is guaranteed, and the reliability of the detection result is enhanced. Automatic template generation, a multi-dimensional retrieval interface and a full-life-cycle dynamic management mechanism replace tedious manual configuration and screening, the labor cost of environment deployment and template maintenance is remarkably reduced, and the retrieval and management efficiency is improved. The new, iteration and archiving process of the unique identification system and specification avoids the disorder and failure of the template, realizes the standardized management and control of the template library, meets the requirements of multi-scene rapid detection, and provides efficient, compliant and stable environment support for the software detection of the active medical instrument.