231results about How to "Improve dynamic response performance" patented technology

The invention relates to the technical field of numerical control machine tools, and discloses a five-axis high-precision numerical control machine tool control method, device and equipment and a storage medium, and the method comprises the steps: collecting temperature data and displacement data of a five-axis high-precision numerical control machine tool, and carrying out state space modeling to obtain a machine tool motion state model; stress data and thermal error influence factors of the feed shaft are calculated; feeding shaft stress data and the thermal error influence factors are input into the compensation model, real-time compensation parameters are calculated, compensation control is conducted on the machine tool feeding shaft, and a compensation control result is obtained; according to the compensation control result, an initial machining track optimization model is constructed, and optimized machining parameters are generated; performing segmented machining control based on the optimized machining parameters to obtain real-time machining data; the initial machining track optimization model is optimized based on the real-time machining data, a target machining track optimization model is obtained, and the dynamic response performance and the control precision of the five-axis high-precision numerical control machine tool are improved through the method.

The invention discloses a central air conditioner energy-saving optimization system based on load prediction, and relates to the technical field of air conditioner energy saving.According to the central air conditioner energy-saving optimization system based on load prediction, a VMDTransformerGRU hybrid deep learning model is introduced, through multi-source data fusion, the precision of cold load prediction is remarkably improved, and the prediction model can recognize the load change trend in advance. According to the improvement, the dynamic response capacity of the system is effectively enhanced, pre-regulation and control can be carried out before load changes, energy waste is reduced, a water chilling unit, a cooling tower and a pump are modeled to be independent intelligent agents, multi-agent deep reinforcement learning (MADRL) is adopted, and all the intelligent agents can autonomously learn and optimize control strategies of the intelligent agents. The intelligent agents cooperate with one another, efficient operation of the whole system is achieved through autonomous decision, and operation conflicts between devices are avoided. In this way, dynamic coordination and joint optimization among all the devices are achieved, invalid energy consumption is reduced, and the overall energy-saving effect and operation stability of the system are remarkably improved.

The invention relates to the technical field of flexible screens, and discloses a flexible screen brightness control method and device based on region segmentation, and the method comprises the steps: carrying out the multi-view image collection of a plurality of bending regions of a flexible display screen, obtaining target image data, and calculating the deformation compensation partition data of the flexible display screen; gridding brightness sampling is carried out on the deformation compensation partition data to generate brightness uniformity characteristic data, LED driving parameter calculation is carried out based on the brightness uniformity characteristic data, and a driving compensation matrix is output; inputting the driving compensation matrix into a second-order state observer for real-time current estimation and temperature feedback, and generating a partition driving control signal; and performing multi-region collaborative optimization on the partition driving control signal to realize brightness uniformity control of the flexible display screen in different bending states. According to the method, the influence of temperature drift on the display uniformity is eliminated, the stability of the driving current is improved, and the display deviation caused by temperature change is remarkably reduced.

The invention relates to a switching power supply control method, system and device and a storage medium, and the method comprises the steps: monitoring the voltage and current of the output end of a switching power supply, and the rate and amplitude of load change, and obtaining the real-time data of the load change; according to the real-time data of the load change, the change of the current load is identified, and a load change mode is obtained; dynamically adjusting operation parameters of the controller according to the load change mode; based on the real-time data of the load change, predicting the load change trend of the switching power supply in real time by using a pre-trained load prediction model to obtain a prediction result, and generating a disturbance compensation signal based on the prediction result; and adjusting the switching state of a switching circuit of the switching power supply according to the control parameter adjusted by the controller and the disturbance compensation signal. The switching power supply has the effect of improving the stability of the switching power supply.

The invention relates to the technical field of motor control, and discloses a hybrid excitation synchronous motor control strategy optimization method and device. The method comprises the following steps: performing mathematical modeling on permanent magnet flux linkage, exciting current and rotor parameters of the hybrid excitation synchronous motor to obtain a state observer equation; collecting current parameters and position parameters, and performing filtering processing to obtain motor operation state parameters; inputting a five-layer deep neural network for current and rotating speed parameter prediction to obtain an optimal current parameter and an optimal rotating speed prediction parameter; constructing a multi-objective function, and solving to obtain a current reference value; inputting the current reference value into a cascade PI controller, and performing voltage regulation through feedforward decoupling control and a space vector pulse width modulation technology to obtain a control voltage signal; and performing performance calculation control parameter optimization on the control voltage signal to obtain a target control parameter, thereby improving the control precision of the hybrid excitation synchronous motor.

The invention discloses a real-time monitoring and early warning method for the leakage state of a long-line type public facility, and relates to the technical field of monitoring and early warning of the leakage state of the long-line type public facility, and the method specifically comprises the following steps: analyzing environment dynamic response information stored in a central monitoring system; respectively generating a soil humidity change coefficient, an environment pressure response index and a temperature influence compensation coefficient; constructing a leakage risk assessment model for the generated soil humidity change coefficient, the environment pressure response index and the temperature influence compensation coefficient, and generating a leakage risk coefficient; and determining a preset leakage risk coefficient threshold value, comparing the determined leakage risk coefficient threshold value with the generated leakage risk coefficient, evaluating whether a leakage risk exists in the pipe gallery area close to the earth surface, and respectively generating a normal signal and an abnormal signal according to an evaluation result. According to the invention, the problem of underground pipe gallery leakage monitoring is solved, abnormal signals are accurately distinguished, and the monitoring accuracy and safety are improved.

The invention relates to the technical field of subsynchronous oscillation suppression, in particular to a system for suppressing subsynchronous oscillation of a doubly-fed grid-connected system, and the system comprises a doubly-fed generator module which is used for converting wind power into electric energy; the subsynchronous oscillation spectrum disturbance module specifically comprises a current disturbance generation unit and a phase decoupling optimization unit; and the multi-frequency domain decomposition and absorption module specifically comprises a frequency spectrum decomposition unit and a self-adaptive absorption unit. According to the invention, the current disturbance generation unit actively injects a low-power and non-linearly distributed current disturbance signal, dynamically destroys the coherence of the subsynchronous oscillation signal, and combines the spectrum decomposition unit to accurately identify the subsynchronous oscillation dominant frequency and the harmonic component thereof, thereby refining the distribution analysis of the oscillation energy, and improving the accuracy of the subsynchronous oscillation. The high-precision target positioning capability is provided for the oscillation suppression strategy, the multi-level oscillation suppression from active disturbance to precise control is realized through the cooperative operation of the two, and the stability and adaptability of the system under the complex power grid condition are effectively improved.

The invention relates to the technical field of battery management, in particular to a new energy vehicle battery data analysis method and system, and the method comprises the following steps: merging a state feature set of a battery based on the charging and discharging period and use environment data of the new energy vehicle battery, extracting the voltage, current and temperature features of the state, and obtaining a state feature set; and carrying out feature combination on the battery degradation state, classifying and associating feature items and temperature features in the feature combination, and obtaining a state feature merging result. According to the method, through merging the new energy vehicle battery charging and discharging period and the use environment data, the battery state characteristics are accurately extracted, refined classification and correlation analysis are realized, the discrimination capability and adaptability of the state data are improved, and the state transition trend is flexibly captured based on the linkage trend of the state transition frequency and the current observation data; and dynamic evaluation is realized through correlation of periodic temperature and current, an accurate and reliable state change evaluation scheme is provided, and the dynamic response of battery management and the full-life periodic performance regulation and control quality are optimized.

The invention discloses a method for collecting orchard ecological environment information, and the method comprises the steps: collecting soil parameters, space environment parameters, insect pest parameters and fruit parameters of an orchard in real time through deploying a plurality of collection devices, and carrying out the collection to form an orchard ecological basic data set; a backstepping model is constructed to indirectly calculate key ecological parameters including soil nutrients, fruit quality and insect pest diffusion trend, and an optimization result is corrected through experimental verification and the model; comparing a backstepping result with an orchard target value to analyze a deviation source, and establishing a macroscopic cause chain through data matching and a visual tool; according to the deviation analysis and the cause chain result, determining an executable regulation and control measure matched with the regulation and control direction; and monitoring the effect after the implementation of the regulation and control measures, verifying the regulation and control effect by comparing the data before and after the implementation of the regulation and control measures, and applying feedback data to iterative optimization of the backstepping model. The method is scientific and efficient and can be used for improving orchard production benefits and ecological environment quality.

The invention relates to the technical field of high-speed motor intelligent control, and discloses a high-speed motor intelligent control method and device for a cooling fan, and the method comprises the steps: carrying out the parameter collection of a high-speed fan motor, and obtaining a motor basic parameter group; performing motor overmodulation boundary calculation to obtain a linear PWM region threshold value and an overmodulation region threshold value; performing multi-objective optimization operation on the voltage distortion degree, the current harmonic quantity and the system loss to obtain an initial control parameter group; performing current harmonic analysis to obtain a current harmonic compensation value and a system delay compensation value; performing online state evaluation operation to obtain a PWM control parameter correction value, a current controller parameter correction value and a voltage vector distribution correction value; and performing fault feature analysis on the running state of the high-speed fan motor, and outputting a fault phase isolation instruction and a fault-tolerant control instruction, thereby improving the overall running effect of the high-speed fan motor.

The invention provides a vegetation prediction model construction method, a vegetation prediction method, a vegetation prediction device and vegetation prediction equipment, and relates to the technical field of data processing. The vegetation prediction model construction method comprises the following steps: taking ecological environment data of a target area as an independent variable, taking vegetation spatial distribution data corresponding to the target area as a dependent variable, and training a first random forest model to obtain a vegetation spatial distribution prediction model; taking the output of the vegetation parameter spatial distribution prediction model and the period-by-period meteorological data as independent variables, taking the period-by-period vegetation feature change data as dependent variables, training a second random forest model, and obtaining a vegetation feature time change prediction model; and splicing the vegetation spatial distribution prediction model and the vegetation feature time change prediction model to obtain a vegetation prediction model. According to the technical scheme, the data utilization efficiency can be improved, the model training time is shortened, and meanwhile the adaptability of the vegetation prediction model and the accuracy of vegetation prediction are improved.

The invention relates to the technical field of micro switch production line intelligent scheduling methods, in particular to a micro switch production line intelligent scheduling method and system based on a graph neural network, and the method comprises the steps: obtaining an attribute set of nodes, and constructing a node graph of a production line; the dynamic representation module is used for dynamically representing real-time states of nodes; generating a multi-scale state prediction model based on the aggregation weight matrix, and obtaining a state prediction matrix for predicting the state change trend of the equipment; based on the state prediction matrix, constructing a nonlinear global optimization scheduling strategy, and further optimizing task allocation and resource allocation in the production line to obtain a global optimal scheduling scheme; constructing a layered feedback correction mechanism based on the global optimal scheduling scheme; based on a hierarchical feedback correction mechanism, an intelligent maintenance trigger signal is generated for identifying potential faults and triggering preventive maintenance, deep modeling and state prediction are performed on each node of the production line, and efficient task scheduling and equipment maintenance management are realized.

The invention provides a high-power high-frequency modular battery cluster charging and discharging test device, which is characterized by comprising an alternating current coordination controller connected with a middle computer and used for receiving an instruction transmitted by the middle computer and distributing current to a plurality of isolated ACDC modules; the input ends of the plurality of isolated ACDC modules are connected in parallel and then are connected to the AC co-controller and a three-phase mains supply, and the output ends of the plurality of isolated ACDC modules are connected in parallel and then form a DC bus for converting AC into DC and realizing voltage isolation; and a plurality of BUCK-BOOST modules, the input ends of the plurality of BUCK-BOOST modules are connected in parallel and then are connected to the DC bus, and the output ends of the plurality of BUCK-BOOST modules are connected in parallel and then are connected to a target battery cluster for testing the charging and discharging of the target battery cluster. Modular design is achieved, efficient charging and discharging capacity is achieved, the defects that a traditional scheme is large in size, high in cost, slow in dynamic response and the like are overcome, equipment efficiency and flexibility are improved, and the device is suitable for a high-power scene.

The invention relates to the technical field of robot control, in particular to a robot rescue emergency control system based on voice interaction. The system is used for performing control voice signal acquisition and rescue emergency voice control task structured analysis by using a built-in voice receiving function of a robot, and generating rescue emergency voice control task structured data; acquiring panoramic image data, environment sensing data and long-distance laser radar data monitored by the robot; the method comprises the following steps: performing global image point cloud model construction and multi-level environment change collaborative optimization processing based on panoramic image data, environment perception data and long-distance laser radar data monitored by a robot, and generating an optimized global image perception model; and performing rescue emergency intelligent control operation on the robot based on the rescue emergency voice control task structured data and the optimized global image perception model. According to the invention, the voice instruction is received through the voice interaction function, so that automatic and efficient robot rescue emergency control is realized.

The invention belongs to the technical field of power electronics, and relates to a hybrid device common bridge arm three-level split output inverter modulation method and system, and the method comprises the steps: obtaining a mapping phase angle, a modulation degree and a region number according to a reference voltage vector generated by a three-phase original modulation wave; mapping the phase angle, the modulation degree and the switching period according to the size of the modulation degree to obtain two kinds of vector action time; generating two modulation waves according to the area number and the action time of the two vectors; generating a first pulse driving signal according to the area number, the first modulation wave and the forward and reverse carrier waves; generating a final carrier according to the area number and the forward and reverse carriers, and generating a second pulse driving signal according to the second modulated wave, the forward carrier, the forward carrier of the previous period and the final carrier; and selecting a driving signal from the two pulse driving signals according to the area number. The modulation degree can be maximized, driving pulses are respectively generated in different modulation degree ranges, the output current quality is high, and the total harmonic distortion rate is low.

The invention discloses a dynamic traffic distribution and signal control combined optimization method, and belongs to the field of intelligent traffic. The method specifically comprises the steps that firstly, a road section impedance function is constructed, node impedance is introduced to obtain an intersection impedance combination function, and the intersection impedance combination function is optimized through the traffic flow, density and speed relation based on dynamic adjustment parameters, vehicle type differences, weather conditions and traffic flow speed to obtain a combination optimization traffic impedance model; and solving the combinatorial optimization traffic impedance model by using a particle swarm algorithm to output a traffic distribution scheme. According to the method, dynamic traffic distribution and adaptive signal control are integrated, the road network emergency response capability is improved, traffic prediction and signal regulation and control synchronization is realized, and an accurate impedance model is introduced to dynamically adapt to driver preferences, so that congestion is relieved, and travel time and resource allocation are optimized.

The invention discloses a power supply system containing a hybrid energy storage and diesel generator two-stage emergency power supply, which relates to the technical field of power supply systems and comprises an alternating current bus, a system power supply, an energy storage device, a diesel generator, an important load and an unimportant load. The system power supply comprises a frequently-used power supply and a standby power supply which are respectively connected to the AC bus through switches; the energy storage device consists of a hybrid energy storage system, a three-phase inverter, a filtering unit and an energy storage switch, and is connected to the alternating current bus; the diesel generator is connected to the bus through the grid-connected switch; the loads are divided into important loads and unimportant loads, and the system has four switchable states of common power supply-energy storage parallel connection, standby power supply-energy storage parallel connection, energy storage power supply and diesel generator-energy storage parallel connection so as to ensure stable power supply.

The invention discloses an intelligent vehicle finite time integral sliding-mode control method based on a disturbance observer, and the method comprises the steps: inputting composite disturbance into a disturbance observer model, obtaining a disturbance observer estimation value, inputting expected input linear velocity information and expected input angular velocity information, and obtaining an estimated value of the disturbance observer; the linear velocity integral sliding mode controller and the angular velocity integral sliding mode controller act to obtain position information and a vehicle running track, and the traditional sliding mode controller controls to obtain position information and a running track under a traditional sliding mode; and comparing the moving trajectory obtained by the linear velocity integral sliding mode controller and the angular velocity integral sliding mode controller with the tracking condition of the reference trajectory and the moving trajectory under the traditional sliding mode. According to the scheme, buffeting is effectively relieved, the system robustness is enhanced, the control precision is improved, the convergence speed of the system is increased, better intelligence and adaptability are achieved, better control performance and system stability are achieved, and the method is suitable for accurate path tracking and dynamic control of the intelligent vehicle.

The invention discloses an automobile charging station load intelligent prediction method and system, and relates to the technical field of new energy, and the method comprises the steps: collecting the charging state information of each automobile charging station in a target range, so as to construct a plurality of load intensity coefficients Xfh of the automobile charging stations, and carrying out the comparison of the load intensity coefficients Xfh, marking a number group of high-load automobile charging stations, and sending a load demand prediction instruction; according to the method, charging piles in a high-load automobile charging station number group are continuously monitored, a radio frequency identification technology is combined, a load demand index Zyc is obtained through fitting, after threshold comparison is carried out on the load demand index Zyc, whether the automobile charging stations in the high-load automobile charging station number group meet the automobile charging demand of the day or not is judged, and a corresponding grade regulation and control instruction is generated and executed; according to the method, through real-time monitoring, dynamic analysis and accurate regulation and control, the resource allocation of the automobile charging station is effectively optimized, and the charging user experience is improved.

The invention relates to the technical field of wind power generation, and discloses a method for reducing damage to a yaw mechanism of a wind power generation system through pneumatic unbalance adjustment, and the method comprises the following steps: S1, arranging sensors to monitor blades, a wind field and a vibration state; s2, fusing data, and calculating pneumatic unbalance; s3, constructing a model to predict the change of the wind field; s4, adjusting the balance load of the blade load; s5, optimizing a yaw angle adjustment strategy; s6, yaw action is reduced, and operation is optimized; and S7, health state prediction faults are monitored. The pneumatic load and the pneumatic unbalance degree of the blade are monitored in real time, the micro pneumatic actuator and the dynamic balance weight module are combined, the pneumatic performance and the load distribution of the blade are dynamically adjusted, the impact load and the vibration amplitude borne by the yaw mechanism are effectively reduced, in addition, a torque limiting and intelligent damping protection mechanism is adopted, and the service life of the yaw mechanism is prolonged. The fatigue damage accumulated value and the part abrasion degree of the yaw mechanism are fundamentally reduced, and therefore the service life of the yaw mechanism is prolonged.

The invention relates to the technical field of information analysis, in particular to an information analysis method and system based on student data traceability. The method comprises the following steps: acquiring a student subject learning quality data set; performing data preprocessing on the student subject learning quality data set to generate a subject learning quality preprocessing data set; performing influence factor screening on the subject learning quality preprocessing data set according to a preset regression analysis model to generate subject influence related factors; utilizing a Fahrenheit combination interval analysis method to carry out deep interval analysis on the subject influence correlation factors, and generating a student subject learning quality strategy; therefore, through influence factor analysis and strategy adjustment of the system, the problem that a traditional education analysis method is lack of individuation and dynamic adjustment is solved, and the scientificity and the implementation effect of education decision making are improved.

The invention discloses a piezoelectric type macro-micro force sensing device and a measurement method, solves the problem that an existing force sensor is difficult to meet quasi-static measurement of micro force, and belongs to the technical field of macro-micro force measurement. Two force measuring units with piezoelectric ceramics as sensitive elements and a piezoelectric quartz reference unit with a piezoelectric quartz wafer as a sensitive element are used as sensors, the piezoelectric quartz reference unit is used for measuring macroscopic force, the force measuring units are used for measuring micro force, and continuous quasi-static measurement of the micro force can be realized through alternation of the two force measuring units. The resolution of the sensor is improved by utilizing the characteristic of high sensitivity of piezoelectric ceramics; and the stability of the sensor is improved by utilizing the characteristics of good linearity, high temperature stability and no hysteresis of piezoelectric quartz. Two indexes of high precision and wide range of the force sensor can be considered, multi-range quasi-static macro-micro force measurement is realized, and the force sensor has the advantages of high rigidity, high frequency response and the like.

The invention discloses a virtual synchronous generator converter model control parameter identification method and system. A traditional control parameter identification method is low in convergence speed, insufficient in precision and difficult to adapt to precise control requirements under complex working conditions. An intelligent optimization method based on a particle swarm optimization algorithm has high convergence efficiency, but is easy to fall into local optimum. The virtual synchronous generator converter model control parameter identification method comprises the following steps: an analysis control link: constructing a virtual synchronous generator converter control model suitable for a distributed power supply; selecting a to-be-identified parameter and a to-be-identified observed quantity in the control model, generating standard test data, and constructing a fitness function; and improving a particle swarm algorithm, taking the constructed fitness function as an optimization target, and performing parameter optimization by using the algorithm to complete identification. By optimizing the control parameter identification process, not only is the control precision improved, but also the problems of slow parameter convergence, insufficient precision and the like in a traditional identification method are effectively solved.

The invention discloses a time perception user portrait modeling method based on sentiment analysis, belongs to the field of user portraits and the field of recommendation systems, and constructs a new user portrait model and applies the new user portrait model to the recommendation systems for personalized recommendation. The construction process of the new user portrait model comprises the following steps: designing a data collection and preprocessing module comprising a user behavior data collector, a data cleaner and a feature extractor, wherein the data collection and preprocessing module is used for data collection and preprocessing; designing a time-aware user portrait construction module comprising a time sectionalizer, a sub-time-aware user portrait generator and a user portrait integrator, wherein the time-aware user portrait construction module is used for constructing a time-aware user portrait; a reviewer credibility and sentiment analysis module comprising a credibility calculator, a sentiment analyzer and a weighted sentiment evaluation calculator is designed and used for reviewer credibility and sentiment analysis; and the design recommendation generation and dynamic updating module is used for generating a personalized recommendation list and dynamically updating. According to the invention, the recommendation accuracy and the user experience are enhanced.

The invention discloses a harmonic suppression and dynamic reactive compensation control method for an energy router, which is suitable for a micro-grid and a distributed energy access system. According to the method, three-phase current and voltage signals of an alternating current port of the energy router are collected, five-time and seven-time main harmonic components are extracted through fast Fourier transform, harmonic compensation current instructions equal in amplitude and opposite in phase are generated and injected into an inverter to be output, and active counteracting of main harmonics is achieved. Meanwhile, the bus voltage deviation and the change rate thereof are detected, a reactive current instruction is adjusted on line by adopting a fuzzy self-adaptive PI controller, rapid and smooth dynamic reactive compensation is realized, and the bus voltage is stabilized. Decoupling control of active / reactive and harmonic components is realized in combination with Park conversion, and virtual impedance is introduced to enhance system damping and harmonic suppression capabilities. Compared with the prior art, harmonic suppression and voltage support can be simultaneously realized under a single control framework, the response speed is high, the stability is high, and the method is suitable for high-performance grid-connected operation of the multi-port energy router.

The invention discloses a cold-chain pork quality dynamic evaluation method and system based on multi-source data fusion, and relates to the technical field of data processing and intelligent evaluation, and the method comprises the following steps: collecting multi-source signal information of a whole cold-chain transportation process, sorting according to a unified time sequence, continuously arranging all signals on a time axis, and carrying out data processing on all the signals; a complete dynamic record is formed; and extracting each time interval and signal amplitude change track from the formed dynamic record, analyzing a signal section with repeated wave crests in a short time, and generating a preliminary data manuscript for reflection interference judgment. According to the invention, through time sequence arrangement and dynamic association of multi-source signals, a wave crest track analysis mechanism is constructed, real-time identification and correction of reflection interference are realized, and continuity and accuracy of a gas concentration curve are ensured; and by generating a reflection source position list and adjusting numerical value distribution of repeated fragments, false fluctuation is eliminated, and the stability and reliability of cold-chain pork quality evaluation are improved.

The invention discloses a permanent magnet synchronous motor single current sensor control method based on single vector model prediction. Firstly, a current prediction model of the permanent magnet synchronous motor is analyzed and calculated, a rolling optimization principle is combined, a cost function is designed, delay time caused by actual use of a digital controller is considered, a deadbeat prediction model containing one-beat delay compensation is designed, and after problems possibly generated in three-phase current reconstruction are analyzed, a deadbeat prediction model containing one-beat delay compensation is designed; and the most / suboptimal vector is selected by setting a sinking threshold, so that the whole permanent magnet synchronous motor single-current sensor control based on single-vector model prediction is completed. According to the method, the structural complexity of a control system is effectively reduced, the dynamic response speed of a driving system is increased, the waveform quality of reconstructed three-phase current is improved, and current ripples are reduced.

The invention discloses a full-closed-loop motorized spindle ternary control method and system, a medium and application. The method comprises the following steps of: performing full-closed-loop control by adopting a combined control logic of a feedback controller, a feedforward controller, a first disturbance observer and a second disturbance observer; wherein the first disturbance observer observes the disturbance output of the motor end and outputs a first compensation value, and the second disturbance observer observes the disturbance output of the output end and outputs a second compensation value; and performing control after linear combination. In order to solve the problem that an electric spindle is greatly influenced by uncertain factors such as bearing friction and machining chatter, a double-disturbance observer is designed on the basis of feed-forward control and a feedback controller, and a three-element speed control framework of'feed-forward + feedback + double-disturbance observer 'is formed. Compared with a traditional lumped disturbance observer, the method can achieve the separated estimation and compensation of interference sources with different amplitudes and frequencies, can more accurately remove the disturbance force in the machining process of the motorized spindle, and improves the speed tracking precision and control stability of the motorized spindle.

The multimodal digital twin scene construction method and device based on image semantic fusion provided by the present invention relate to the technical field of data processing and digital twin scene. The present invention obtains image data sets and text data sets of a construction site and performs preprocessing; inputs the preprocessed image data sets and text data sets into a natural language processing model to obtain semantic description auxiliary data; inputs the preprocessed image data sets into a target detection algorithm to obtain target extraction image data containing a target detection frame; then fuses the output results of the two to obtain a fusion frame of each target; then uses a perspective projection algorithm to calculate the coordinate position of each target corresponding to the BIM to obtain a three-dimensional world coordinate; uses Dynamo to input the three-dimensional world coordinate into the BIM to realize the construction and real-time update of a multimodal digital twin scene. The present invention significantly improves the accuracy and robustness of scene recognition and solves the shortcomings of traditional methods in multimodal data processing.

The utility model provides a heat treatment annealing furnace control device for semiconductor processing and a heat treatment annealing furnace, and relates to the technical field of annealing furnace control. A temperature acquisition module is installed on each temperature heating module, the system can monitor the actual temperature of a heating area of each temperature heating module in real time, a traditional control device is adopted for temperature control for the first group of temperature heating modules, and an error amplification module and a current driving module are introduced for the subsequent temperature devices, so that the temperature of the heating area of each temperature heating module is controlled. According to the system, the temperature difference between the adjacent temperature devices is accurately controlled, the error amplification module calculates the analog output voltage difference value of the two adjacent temperature detection modules, then the working current of the corresponding temperature heating module is controlled to be directly adjusted by adopting the difference value, and the dynamic response capability of temperature control is improved.