4930results about How to "Reduce loss" patented technology

The invention relates to the technical field of drying equipment, in particular to clothing cloth drying equipment. The clothing cloth drying equipment comprises a box body, a discharging shaft for discharging cloths, a drying module, an ironing module, an air-drying module, a rolling shaft for rolling the cloths and a controller. The top of the left side of the box body is provided with a storinghole for storing the cloths, a damping piece mounted at the bottom of the box body is arranged under the storing hole, and the discharging shaft is vertically mounted on the damping piece. The dryingmodule is used for drying the cloths, the ironing module is used for ironing the cloths, and the air-drying module is used for air-drying the ironed cloths. The rolling shaft is located on the rightside of the air-drying module, a material taking hole for taking out the cloths is formed in the top of the box body over the rolling shaft, the rolling shaft is driven through a rolling motor, and the rolling motor is electrically connected with the controller. The clothing cloth drying equipment is mainly suitable for being used in a clothing manufacturing shop and has the characteristics that the size is small, the weight is small, the price is low, and energy consumption is little.

The invention relates to the field of transformer parameter regulation and control, in particular to a parameter optimization method and device for a coupling type transformer. The method comprises the following steps: acquiring multi-dimensional real-time working monitoring parameters and real-time working environment state parameters of the coupling type transformer; performing nonlinear dynamic analysis and global state sensing modeling on the multi-dimensional real-time working monitoring parameters so as to construct a transformer global state sensing model; performing multi-parameter combination definition on the multi-dimensional real-time working monitoring parameters, performing dynamic operation simulation based on a transformer global state sensing model, and collecting operation simulation response data of a plurality of schemes; performing multi-target dynamic balance analysis on the operation simulation response data of the plurality of schemes to obtain an optimal transformer working parameter combination; and carrying out environment dynamic parameter change analysis on the real-time working environment state parameters, and constructing a real-time environment condition distribution field. According to the invention, efficient and self-adaptive adjustment transformer parameter optimization is realized.

The invention relates to the technical field of ozone concentration prediction, in particular to an ozone concentration prediction method, device, equipment and medium based on a space-time diagram convolutional network model.The method comprises the steps that historical ozone concentration and meteorological data of a target area are obtained, and training and prediction samples are constructed after standardization; a space diagram structure is established, nodes represent monitoring points, and edges represent the monitoring points with correlation exceeding a threshold value; extracting a spatial dependency relationship by adopting GCN and GAT, and generating time sequence data; tCN or RNN is adopted to extract time-dependent features, and spatial-temporal feature comprehensive representation is obtained; training a model by utilizing the training sample and the spatial-temporal characteristics, adopting MSE (mean square error) as a loss function, adjusting parameters by an Adam optimizer, and optimizing hyper-parameters to minimize errors; newest meteorological and historical data are input, future ozone concentration is predicted, GNN extracts spatial features, RNN processes a time sequence, time sequence data can be processed in parallel through convolution operation, and high calculation efficiency is achieved.

The invention relates to a transformer area self-healing optimization control method and system based on flexible interconnection. The method comprises the following steps: S1, constructing an operation monitoring network based on equipment ledgers in a transformer area; s2, deploying flexible interconnection equipment at key nodes of a transformer area to realize fault isolation and power failure transfer, dynamic load transfer and voltage regulation, and flexible cooperative control of a distributed power supply and energy storage equipment; s3, introducing an equipment state evaluation model based on the transformer area operation data obtained by the operation monitoring network, and obtaining state evaluation and risk early warning of each equipment in the transformer area; s4, constructing a flexible interconnection dynamic topology management mechanism between the stations, and dynamically adjusting the interconnection topology between the stations according to the load transmission demand and the power supply condition; and S5, based on state evaluation and risk early warning of each device, performing load regulation and control and fault recovery according to a dynamic topology management mechanism of flexible interconnection. According to the invention, efficient and intelligent transformer area operation and power supply reliability improvement are realized.

The invention relates to multi-mode signal processing, and provides a signal processing method of a computer system. The method comprises the following steps: acquiring different modal signal data by using a plurality of sensors and performing timestamp synchronization; a depth time sequence alignment network and a multi-layer dynamic time warping algorithm are utilized to ensure signal time consistency; multi-modal signal features are extracted and fused through a multi-stream depth feature extraction network and a cross-modal attention mechanism; the system adopts a dynamic convolution kernel generation and meta-learning technology to carry out adaptive signal processing; noise suppression and signal optimization are carried out by using a multi-mode noise reduction auto-encoder and a generative adversarial network, and parameters are optimized and processed through closed-loop feedback control and reinforcement learning strategies. According to the method, synchronization, fusion, adaptive processing, noise suppression and real-time feedback control of multi-mode signals are realized, and the method has the advantages of high precision, high robustness and real-time performance.

The invention discloses a detail level rendering method based on Gaussian splash, which can dynamically change the detail level of a model according to the actual needs of a user in an interaction process, realize high-fidelity and low-resource-loss rendering based on Gaussian splash, and reduce the loss required by rendering. The technical scheme of the invention comprises a preparation stage and a real-time rendering stage. In the preparation stage, a multi-view image is acquired, a corresponding three-dimensional model or four-dimensional model is constructed according to the multi-view image, and Gaussian splash models with different detail levels are generated. And in the real-time rendering stage, the Gaussian splash models of different detail levels are selected for real-time rendering according to the real-time data of the user by using the Gaussian splash models of different detail levels.

The invention provides a gravity energy storage device with a function of uninterruptible loading and unloading of weight blocks, the gravity energy storage device comprises a transportation module and a loading and unloading module, the transportation module comprises a rotating wheel part, a chain part and a bearing mechanism, the bearing mechanism is arranged on the chain part, the rotating wheel part is arranged at the end part of the transportation module, and the chain part moves around the rotating wheel part; the loading and unloading module comprises a conveying channel, a supporting mechanism and a weight block body, the supporting mechanism is arranged on the conveying channel, the weight block body is arranged on the supporting mechanism through driving of the conveying channel, and the supporting mechanism and the bearing mechanism can be coupled or decoupled to drive the weight block body to be separated from or connected with the supporting mechanism. According to the gravity energy storage device with the function of uninterruptible loading and unloading of the weight block, stable and continuous electric energy can be generated during power generation and energy storage under the condition that the device is uninterruptible when the weight block body is loaded and unloaded and the transportation module generates power, and under the condition that equipment does not need to be added, the power generation power and the operation efficiency are improved, and the cost is reduced.

The invention relates to the field of voltage regulation and control, in particular to a real-time voltage regulation method for a new energy automobile. Initializing a power distribution network voltage measurement module, and collecting voltage data of each node of the power distribution network; setting a voltage deviation threshold value, and judging whether the voltage is in a normal range or not; collected voltage is compared with a set voltage deviation threshold value, a result obtained after preliminary voltage regulation of an on-load voltage regulation transformer is compared with the set voltage deviation threshold value, and a result obtained after cooperative voltage regulation of an electric vehicle charging pile is compared with the set voltage deviation threshold value. According to a comparison result, tap adjustment of an on-load voltage regulation transformer, cooperative voltage regulation of an electric vehicle charging pile and voltage regulation participated by a distributed photovoltaic system are carried out in sequence; and formulating an optimization strategy based on historical data and results of three times of voltage regulation. By means of cooperative voltage regulation, optimal control, intelligent management and the like, the voltage stability is effectively improved, and the adaptability and flexibility of the system are enhanced.

The invention provides an Al-Mg alloy negative electrode current collector, a preparation method thereof and a negative-electrode-free sodium metal battery, and relates to the field of batteries. The preparation method of the Al-Mg alloy negative electrode current collector comprises the following steps: sputtering magnesium on the surface of an aluminum foil by adopting a magnetron sputtering mode, and forming a magnesium coating on the aluminum foil; and calcining the aluminum foil with the magnesium plating layer to obtain the Al-Mg alloy negative electrode current collector, and the Al-Mg alloy negative electrode current collector comprises an aluminum substrate layer and an Al-Mg alloy layer located on the aluminum substrate layer. According to the present invention, the Al-Mg alloy with characteristics of high sodium affinity and stable three-dimensional structure is introduced into the negative electrode current collector so as to induce the uniform deposition of sodium, inhibit the growth of sodium dendrites, reduce the loss of active sodium, and prolong the cycle life of the battery; the negative electrode current collector can be used in a sodium metal battery without a negative electrode. In addition, the method has the advantages of being easy to operate and low in raw material cost, and large-scale application and popularization are facilitated.

The invention discloses a three-phase permanent magnet synchronous motor full-speed-domain driving control system and a control method thereof. The system is composed of a torque limiting module, a full-speed-domain control neural network module, a current control module, a coordinate transformation module-I, a coordinate transformation module-II, a coordinate inverse transformation module, an SVPWM module, a SiC MOSFET driving module, a full-speed-domain position rotating speed observation module, a weak magnetic feedback module and a three-phase permanent magnet synchronous motor. The control method is used for driving the control system. According to the method, accurate tracing of the optimal dq-axis reference current working point is realized based on deep learning, and accurate control of three operation modes of MTPA, field weakening control and MTPV is realized; an improved mobile vision field estimation algorithm is adopted, and the rotor position and the rotor rotating speed are accurately estimated within the full-speed domain range; the SiC MOSFET is used as an inverter switching tube, and a brand new drive circuit is designed to adapt to the operation condition of the electric vehicle.

The invention provides a line loss optimization system and method based on distributed photovoltaic topology analysis, and relates to the technical field of distributed photovoltaic, and the system comprises a topology connection module which is used for carrying out the topology connection, and building a distributed photovoltaic power distribution network topology model; the prediction modeling module is used for performing prediction modeling to obtain a photovoltaic output-power grid load space-time prediction model; the access position optimization module is used for carrying out photovoltaic access position optimization and obtaining a distributed photovoltaic optimization power distribution network topology model through iteration; the strategy analysis module is used for carrying out strategy analysis and determining power distribution network line loss control strategy parameters; and the feedback optimization module is used for carrying out simulation evaluation and carrying out feedback optimization on the power distribution network line loss control strategy parameters. The technical problem that the line loss control effect is poor because the line loss control strategy of the power distribution network in the prior art is often set based on experience and is not fully combined with the dynamic characteristics of photovoltaic power generation and load for real-time adjustment is solved.

The invention discloses a server power supply system and a server, relates to the field of server power supply, and is used for solving the problem of high energy loss in a traditional alternating current power supply architecture. The power conversion module converts the power supply into high-voltage direct current with the voltage not lower than the preset voltage, the high-voltage direct current is transmitted to the power distribution board of the server through the bus copper bar, and the bus copper bar serves as a transmission medium of the high-voltage direct current and has low resistance and high current-carrying capacity. Extra loss caused by electromagnetic induction and a capacitance effect in alternating current transmission is avoided; high-voltage direct current is directly input to the power distribution board, so that multiple times of conversion in an intermediate link are avoided, and energy loss in the conversion process is reduced; and the power distribution board directly converts the high-voltage direct current into the voltage required by the load, so that the loss of multi-stage conversion in the traditional architecture is reduced. According to the invention, the power transmission efficiency is improved, the energy loss is reduced, and the requirement of a modern high-computing-power and high-energy-consumption server for efficient power supply is met.

The invention discloses a fan blade icing monitoring system and method, and relates to the technical field of wind power generation, and the system collects temperature, humidity and vibration signals in real time through a multi-sensor module installed on a fan blade, fuses multi-parameter data through an edge calculation unit, and calculates a blade icing risk factor # imgabs0 #. The risk factors are calculated by adopting a dynamic weighting model, and the icing state of the blade is accurately evaluated in combination with normalized characteristic values # imgabs1 #, # imgabs2 # and # imgabs3 #. And when the risk factor exceeds a set threshold value, the system triggers an alarm and transmits data to the cloud through the wireless communication module. The cloud platform predicts the future icing risk based on a long-short term memory (LSTM) neural network model in combination with historical data and real-time monitoring data, the accuracy and real-time performance of icing monitoring are improved, the method is suitable for operation in cold regions and high-altitude wind fields, and reliable guarantee is provided for safe and efficient operation of fans.

The invention discloses a single-frame infrared weak and small target detection method based on multi-scale feature enhancement, and the method comprises the following steps: 1, obtaining a single-frame infrared image, constructing a single-frame infrared image data set, and dividing the single-frame infrared image data set into a training set and a test set; 2, an infrared weak and small target detection network model is constructed, the infrared weak and small target detection network takes a YOLOv5 network model as a basic network, and the YOLOv5 network model comprises a trunk feature extraction network, a feature fusion network and a detection head; a multi-scale feature enhancement module is introduced into the trunk feature extraction network, and the multi-scale feature enhancement module comprises a context feature fusion module and a feature detail enhancement module which are sequentially connected in series; 3, designing a training strategy, and training the infrared weak and small target detection network model by taking the training set as input according to the training strategy; and step 4, after training is completed, inputting a test set to test and evaluate the infrared weak and small target detection network model.

The invention relates to an MPPT (Maximum Power Point Tracking) control method based on dynamic optimization of a lightweight convolutional neural network, and belongs to the field of artificial intelligence control power tracking. The method comprises the following steps: S0, constructing a convolution-fuzzy neural network model which at least comprises an input layer, a convolution layer, a fuzzy control layer, a deep reinforcement learning layer and an output layer; s1, key parameters of photovoltaic equipment are collected in real time to serve as input data of an input layer; s2, performing convolution operation on the input data by using a convolution layer, extracting a feature vector, and transmitting the feature vector to a fuzzy control layer; s3, combining a fuzzy control layer with a deep reinforcement learning layer, and dynamically adjusting an optimization process of a fuzzy rule through a reward signal; and S4, the fuzzy control layer generates a control signal, and the control signal is transmitted to a DC / DC converter of the photovoltaic system through the output layer. The control method is suitable for a dynamic environment of a photovoltaic power generation system, can be expanded to a grid-connected system, and provides a new thought and technical support for efficient operation of photovoltaic power generation.

The invention discloses a path optimization method and system for unmanned aerial vehicle logistics distribution, and relates to the technical field of unmanned aerial vehicle logistics distribution, and the method comprises the following steps: obtaining all executable distribution paths, screening an unmanned aerial vehicle logistics distribution default execution path, obtaining unmanned aerial vehicle distribution state parameters, and analyzing unmanned aerial vehicle logistics distribution state characterization parameters. Path influence parameters of default distribution sub-paths are collected, unmanned aerial vehicle default distribution sub-path optimization label information is judged, all standby sub-paths are counted, logistics adaptation execution priority values of all the standby sub-paths are analyzed, and therefore unmanned aerial vehicle logistics distribution optimal sub-paths are screened and optimized execution is carried out. The unmanned aerial vehicle distribution efficiency and safety can be improved, complex and changeable meteorological conditions and obstacle conditions can be effectively handled, the distribution time and energy consumption are reduced, the adaptability of the unmanned aerial vehicle in a complex environment is enhanced, and smooth completion of a distribution task is ensured.

The invention relates to the technical field of air blowers, in particular to an energy-saving air blower for a roasting furnace, which comprises a shell and a driving frame rotationally arranged in the shell, a plurality of impeller blades are arranged on the driving frame, a driving disc is arranged on the driving frame, and a connecting rod assembly is arranged on the driving disc; an air inlet pipe is arranged on the shell; a fixing disc is arranged on the air inlet pipe, an adjusting mechanism is arranged on the fixing disc, the adjusting mechanism comprises a worm gear and a worm, angle adjustment is achieved on impeller blades, the air volume adjusting function is directly integrated in an impeller area, and indirect influences of adjustment of a traditional diffuser on the air volume are avoided; and the self-locking characteristic of the worm gear and the worm is utilized to ensure that the adjusted impeller blade angle does not deviate under the influence of vibration or external force, and the stability is enhanced. And the driving disc can be driven by the adjusting mechanism in the process of rotating along with the driving frame. The purposes of optimizing an airflow path, reducing energy loss and improving the overall efficiency of the air blower are achieved through angle adjustment of the impeller blades.

The invention discloses a directional diagram reconfigurable antenna capable of switching feed through an MEMS switch, and belongs to the field of radio frequency front-end devices. The directional diagram reconfigurable antenna is composed of a micro-strip radiation unit, a guide parasitic unit, a composite beam ohmic contact type MEMS switch, a one-to-four feed network, a direct current bias line, a test patch bonding pad, a coplanar waveguide, a gradual change micro-strip line, a dielectric substrate and a metal ground backboard. The two-stage MEMS switches are erected on the one-to-four feed network, when the two-stage switches on a certain feeder line are turned on, radio frequency current can flow to the corresponding basic radiation unit through the feeder line to generate an inclined beam facing the quadrant, and the two basic radiation units on the front side can be enabled by simultaneously turning on the four switches on the front side to generate an inclined beam facing the quadrant. And generating an inclined beam in the front side positive direction. The antenna adopts a single-layer board design, the dielectric substrate does not need to be punched, the structure is simple, manufacturing is convenient, the adopted MEMS switch is small in loss and high in isolation degree, and rapid printing and manufacturing can be achieved through the surface etching process.

The invention relates to the technical field of glass bottle defect detection, and particularly discloses glass wine bottle body defect optical detection equipment and detection method.The optical detection equipment comprises a conveying belt, and a clamping mechanism, a lifting rotating mechanism, a detection mechanism and a sorting mechanism are sequentially arranged on the conveying belt from the feeding end to the discharging end. The detection end of the detection mechanism is attached to the bottle body of the glass wine bottle for optical detection, the receiving end of the detection mechanism receives the light in the glass wine bottle, the light directly reaches the receiving end in the bottle after passing through a bottle body material, and a signal path is relatively fixed, so that the interference of ambient light or reflection of surrounding objects on an optical signal can be effectively reduced. The bottle body of the glass bottle has a certain thickness, deviation of light scattering and refraction is easy to occur when light passes through the thickness of the glass in traditional external detection, the error can be reduced by matching of an external detection end and an internal receiving end, fine defects such as bubbles, cracks or tiny scratches are helped to be captured, and the detection stability is improved.

The invention relates to a permanent magnet synchronous motor design method based on a multi-objective optimization algorithm, and the method achieves the efficient design and optimization of a permanent magnet synchronous motor through the combination of finite element simulation, multi-physical field coupling analysis, neural network performance prediction, and a hybrid optimization algorithm of a genetic algorithm and particle swarm optimization. The method comprises the following steps: determining a plurality of design targets according to an application scene of a motor, selecting key design variables, performing data cleaning and normalization processing, performing electromagnetic field, thermal field and mechanical field simulation by using a multi-physics field coupled finite element model, predicting the performance of the motor by combining LSTM and Transform neural network models, expanding a training data set through a data enhancement technology, and performing data enhancement on the motor. Finally, a hybrid optimization algorithm combining a genetic algorithm and particle swarm optimization is adopted to carry out global optimization and adaptive adjustment of design parameters, and a Pareto optimal leading edge is utilized to find out an equilibrium solution between design targets, so that the accuracy and efficiency of motor design are improved, and the method is suitable for various motor design scenes.

The invention discloses a cultural heritage digital display platform, which is mainly applied to the fields of museums, cultural heritage protection institutions, education institutions and the like, and specifically comprises a central control module, and a user interaction module, a multimedia display module, a virtual reality rendering module, a database management module and an intelligent recommendation module which are connected with the central control module. The cultural heritage digital display platform has remarkable beneficial effects in the aspects of improving cultural heritage protection and inheritance efficiency, enhancing user experience and interactivity, realizing personalized recommendation and accurate service, promoting cultural education and propagation, optimizing data management and analysis capability and the like, and is beneficial to protection and inheritance of the cultural heritage; and the cultural literacy and aesthetic level of the public can be improved, and a positive contribution is made to the development of cultural heritage.

The invention discloses a control method, device and equipment for a current loop of a permanent magnet synchronous motor and a storage medium, and relates to the technical field of electric vehicle driving motors, and the control method for the current loop of the permanent magnet synchronous motor comprises the steps: obtaining an input voltage; a current loop is controlled according to a target motor mathematical model and the input voltage, the target motor mathematical model is obtained by adjusting an initial model, and adjustment is based on the required torque, a rectangular axis open-loop transfer function and a zero-pole mutual elimination function. The initial model is constructed according to a target quadrature-axis voltage equation, a dynamic inductance parameter value, a locked-rotor test and a difference strategy, and the dynamic inductance parameter value and the target quadrature-axis voltage equation are at least calculated by three items of an initial quadrature-axis voltage equation, dynamic inductance, a quadrature-axis flux linkage equation and a back electromotive force-flux linkage relation. According to the invention, the control precision, efficiency and response speed of the permanent magnet synchronous motor are improved, and the robustness of the system is enhanced.

The invention discloses an E-SOP-based interconnected power distribution area voltage optimization regulation and control method, and the method comprises the steps: carrying out the analysis of an E-SOP-containing power distribution area interconnection system structure, and constructing an E-SOP mathematical model; establishing a voltage-power sensitivity calculation model, and determining the optimal access position of the E-SOP; an E-SOP interconnected power distribution area planning model with the lowest comprehensive cost as the target is constructed, and the optimal capacity configuration of the E-SOP is determined; establishing a multi-objective function E-SOP interconnection power distribution area operation optimization model and solving the model; and determining the optimal position, capacity and operation scheme of the E-SOP according to the solving result. According to the method, a three-terminal SOP (E-SOP) containing an energy storage system is applied to an interconnection system of a power distribution area, the flexibility and rapidity of a power distribution network can be improved from the multi-dimensional aspects of space, energy and power of a power distribution system, and voltage optimization of the power distribution area is achieved.

The invention relates to the technical field of annealing furnaces, in particular to a swirl injection type energy-saving annealing furnace. The device comprises outer shell plates and an air duct, the outer shell plates are spliced to form a hearth, the air duct is arranged in the outer shell plates to form an air path for convective circulation, the air duct is connected with a circulating fan, and air in the air duct and an inner cavity of the hearth is driven by the circulating fan to actively convectively circulate. The air direction of air convection circulation of the air channel faces the side face and the lower portion of the workpiece needing annealing, and a heat preservation layer is attached to the inner surface of the outer shell plate. The shell plate is used for supporting a main body structure of the furnace body, the air duct is used for achieving circulation convection of air flow, the annealing efficiency and the annealing quality of the metal coiled materials are improved through circulation convection of high-temperature air flow, the heat preservation layer is used for storing internal heat, reducing energy leakage and effectively reducing loss, and the circulation fan is used for providing power for circulation convection of the air flow.

The invention relates to the technical field of power maintenance, and discloses a power distribution network-oriented single-phase earth fault AI comprehensive research and judgment system, which integrates a power distribution network monitoring module, a fault diagnosis equipment module and an AI comprehensive research and judgment module. The system can accurately judge the type, position and severity of the single-phase earth fault by monitoring and collecting all-dimensional data of the power distribution network in real time and combining intelligent analysis of the AI comprehensive research and judgment module, and the accuracy of fault positioning and isolation is remarkably improved. The AI comprehensive research and judgment module adopts a Markov decision process for modeling, and a deep reinforcement learning algorithm is used for training a research and judgment model, so that rapid fault positioning, isolation and power supply recovery are realized, the fault processing efficiency and the power supply recovery speed are effectively improved, and the power failure time and the influence on users are reduced.

The invention relates to the technical field of automatic dust removal equipment, and discloses safe-filtering electrical automatic dust removal equipment which comprises a main body, a partition plate is fixedly connected to the interior of the main body, an adsorption pump is fixedly connected to the top of the partition plate, an outlet bin is fixedly connected to the bottom of the main body, and a rotating ring is arranged at the end, away from the adsorption pump, of the partition plate; the end, close to the adsorption pump, of the connecting disc is in bolted connection with the partition plate. The spiral structure in the arc-shaped vertebral plate can guide gas sprayed out through the hollow ring, so that the gas flows in a downward spiral flowing mode when being sprayed out, and dust on the surface of the filter layer is sprayed downwards to be cleaned; the dust collector has the advantages that stronger impact force and downward traction force can be generated on dust on the surface of the dust collector, so that the dust is more effectively cleaned, the dust is prevented from being accumulated on the surface of the dust collector, and a filtering layer is prevented from being blocked.

The invention provides a micro-expression recognition method and system based on a three-branch network, relates to the technical field of micro-expression recognition, and aims to solve the problems that according to an existing micro-expression recognition technology, micro-expression samples are insufficient, multi-type features are difficult to learn, and the model recognition precision is low. The method comprises the following steps: acquiring a video sequence, preprocessing the video sequence to obtain an optical flow diagram, further processing the optical flow diagram to obtain an optical strain diagram, respectively inputting the video sequence, the optical flow diagram and the optical strain diagram into a three-branch network, extracting human face features, optical flow features and optical strain features, and fusing the human face features, the optical flow features and the optical strain features to obtain a fusion result. And performing micro-expression classification on the fused features to obtain a micro-expression classification result. According to the method, the problems of insufficient micro-expression samples and the like are solved, the loss of fine face features in the recognition process can be reduced by utilizing implied different information, the model can more effectively process samples which are difficult to classify, and the micro-expression recognition accuracy is remarkably improved.

The invention relates to the technical field of data management, and discloses a method for realizing intelligent management of an all-optical network based on big data analysis, which comprises the following steps of: acquiring operation data of the all-optical network, positioning an abnormal point location of link optical power of the all-optical network, and performing data linear repair on power data corresponding to the abnormal point location to obtain target data; analyzing wavelength characteristics of the all-optical network, analyzing signal transmission stability of optical signals of the all-optical network, and analyzing optical signal characteristics of the all-optical network based on the wavelength characteristics and the signal transmission stability; analyzing equipment operation state characteristics of the all-optical network; identifying data service types of the all-optical network, analyzing flow change rules of different service types in the data service types, and analyzing service flow periodicity characteristics of the all-optical network; and performing operation anomaly analysis on the all-optical network to obtain an operation anomaly analysis result, and constructing an intelligent management strategy of the all-optical network based on the operation anomaly analysis result. According to the invention, the operation efficiency and stability of the all-optical network can be improved.

The invention relates to the technical field of chemical synthesis, and particularly provides a preparation method of a semaglutide side chain, which comprises the following steps: step S1, carrying out reaction on octadecanedioic acid mono-tert-butyl ester and trifluoroacetic acid pentafluorophenyl ester to generate a first intermediate; s2, enabling the first intermediate to react with 1-tert-butyl L-glutamic acid to generate a second intermediate; s3, enabling the second intermediate to react with pentafluorophenyl trifluoroacetate to generate a third intermediate; and S4, carrying out an amidation reaction on the third intermediate and 17-amino-10-oxo-3, 6, 12, 15-tetraoxa-9-aza-heptadecanoic acid, so as to generate a semaglutide side chain, and carrying out an amidation reaction on the third intermediate and 17-amino-10-oxo-3, 6, 12, 15-tetraoxa-9-aza-heptadecanoic acid. According to the preparation method disclosed by the embodiment of the invention, the pentafluorophenyl trifluoroacetate is used as the condensation reagent for two times to activate the carboxylic acid, and the amidation reaction is carried out for two times to construct the amido bond after each activation, so that compared with the traditional carbodiimide and urea positive ion type condensation reagent, the chiral racemization in the condensation process can be effectively avoided, and the yield of the product is improved. The condensation chiral racemization impurity can be lower than 0.3%.

The invention discloses a steel pipe forging device with a positioning mechanism, which relates to the technical field of steel pipe forging and comprises a mounting frame, a core anvil, the positioning mechanism and a pneumatic hammer. And a component force forging mechanism for changing the forging direction of the pneumatic hammer is arranged on the mounting frame. The component force forging mechanism is arranged, kinetic energy provided by the pneumatic hammer is dispersed to the forging hammer, in the kinetic energy transmission process, under the condition that kinetic energy loss is reduced to the maximum degree, forging work is achieved, the kinetic energy loss is reduced, and the forging strength and precision are guaranteed; through cooperation with the first linkage mechanism, downward force applied by the pneumatic hammer is converted into rotating force, the mounting ring is pushed to generate large torque, then large force can be provided for pushing the forging hammer to move, and the forging effect is guaranteed; and by arranging the buffering mechanism, the reverse acting force borne by the rotating rod and the second connecting rod is buffered, and the situation that the rotating rod and the second connecting rod are deformed due to stress, and the next forging work is affected is prevented.