308 results about "Active control" patented technology

Systems, methods, apparatuses, and computer program products for enhancing dynamic CORESET adaptation with limited or no control channel overhead. One method may include receiving, by a UE, a plurality of PDCCH CORESET configurations associated with at least one SS; determining, by the UE, at least one of the PDCCH CORESET configurations is associated with a symbol or slot format from a corresponding set of symbols; and performing, by the UE, PDCCH monitoring on an active control resource set configuration associated with the set of determined slots or symbols.

The invention discloses an intelligent network connection automobile active safety teaching control method based on digital twinning. The method comprises the steps that S1, multi-source sensor data are collected and preprocessed to generate a driving state data set; s2, inputting the state data into a digital twin model to drive a traffic scene and outputting a synchronous state; s3, based on Dueling-DDQN, executing strategy learning to generate an active safety control instruction; s4, the instruction response effect is simulated and verified in the virtual environment; s5, collecting driver operation behaviors, inputting the improved MHA-BiLSTM model to extract time sequence features, and outputting behavior features; and S6, comparing the driving behavior with a standard instruction item by item, calculating an operation deviation and a response difference, and generating a personalized active safety teaching task. According to the invention, efficient comparison and teaching feedback of the driving behavior and the active control strategy can be realized, and the intelligent level of driving training is improved.

The invention discloses an anti-settlement method and system for a conjoined building with asynchronous foundation construction. The method comprises the following steps: step 1, establishing a multi-stage coupling settlement prediction finite element model of the conjoined building; 2, a settlement active control system composed of a central control unit, a distributed sensor network and a servo hydraulic actuator array is arranged at the structure connection interface of the asynchronous construction areas of the connected building; 3, in the whole construction process, relative settlement data of all the areas are continuously monitored in real time; 4, comparing the real-time settlement data with the prediction model data, and calculating a deviation value; and 5, according to the deviation value, the needed active supporting force is calculated, the servo hydraulic actuator array is instructed to adjust the output force of the servo hydraulic actuator array in real time, and therefore differential settlement in the construction process is actively controlled within the preset minimum threshold value range. According to the invention, the internal stress of the structure is greatly reduced, and a long waiting period required by technologies such as post-cast strips is canceled.

The invention relates to the technical field of underground engineering construction monitoring and control, and discloses a multi-source monitoring data-based settlement risk early warning system for shield wall grinding undercrossing of a station, and the system comprises a data collection module which obtains shield and structure response data; the preprocessing module executes space-time correction to generate a synchronous data stream; the spectrum energy analysis module solves a mechanical-structural impedance coupling index; the rigidity inversion module uses the index to correct the specific energy and invert the residual thickness of the wall body; the active control module updates the kinetic model based on the thickness to calculate a frequency detuning factor; the decision module constructs a multi-dimensional feature vector, calculates a dynamic time warping distance, generates a control instruction according to a detuning factor, and achieves the active closed-loop control of the wall grinding risk. According to the method, a spectrum energy coupling analysis and dynamic stiffness inversion mechanism is introduced, and the apparent mechanical specific energy is corrected by using the mechanical-structural impedance coupling index, so that the accurate identification of the real physical state of the cutting medium and the real-time inversion of the wall residual thickness are realized.

The invention discloses a hydroelectric generating set power active control method, system and device based on frequency prediction and a medium, and belongs to the technical field of power control, and the method comprises the steps: collecting basic operation data of a hydroelectric generating set adjusting system in real time, and carrying out the preprocessing of the basic operation data; time sequence characteristics of the power grid frequency data are extracted, and a neural network is adopted to generate a power grid frequency prediction sequence in a future time window; the power grid frequency prediction sequence is converted into a dynamic power feed-forward compensation amount, feed-forward compensation amount optimization calculation is carried out, the feed-forward compensation amount is superposed to the output end of a feedback controller, and a composite power instruction input value hydroelectric generating set is formed; and updating a neural network input sequence in each control period by adopting a rolling time domain prediction strategy, dynamically correcting a future prediction result, and realizing controlled quantity updating based on actual frequency deviation. According to the method, the compensation weight is dynamically updated by using the online adaptive algorithm, the prediction error and the system performance target are considered, and the compensation amount distribution is optimized.

The invention relates to the technical field of forklift safety analysis, in particular to a forklift safety analysis system fusing multi-modal data, which comprises a multi-modal data acquisition module, an environment-level safety analysis module, a vehicle-level safety analysis module, a behavior-level safety analysis module, a dynamic decision engine, a safety intervention module and a model optimization module. By collecting multi-modal data, constructing a dynamic environment risk model, a forklift comprehensive performance model and a sub-scene safety evaluation model and fusing multi-dimensional analysis results to generate a multi-level instruction, early warning and active control are achieved, and robustness is improved through self-optimization. The problems that a traditional technology depends on single data, a fixed threshold value fails, and closed-loop intervention is lacked are solved, and the forklift operation safety and efficiency can be comprehensively improved.

The invention discloses a network construction type energy storage transient stability optimization control method and system considering reactive power degradation, and belongs to the field of power system transient stability control. According to the method, a network construction type energy storage grid-connected system model is constructed, a reactive power degradation effect dynamically triggered by a reactive power control loop is analyzed, and an active power loop optimization control equation is established according to the reactive power degradation effect. On the basis, a self-adaptive torque adjusting module is embedded in an active control module, and when it is monitored that the internal voltage of the inverter is reduced to 50% of a rated value, the reference torque is automatically and dynamically corrected so as to improve the power angle transient stability margin of the system. Simulation results show that the method can effectively restrain the instability of the network construction type energy storage power angle, obviously enhance the transient stability of the system, and guarantee the safe and reliable operation of the power grid.

The invention relates to a self-adaptive drilling method and system based on hole wall stability and deep learning, and belongs to the technical field of coal mine underground drilling. Aiming at the technical problems that the drilling efficiency is low and the construction safety risk is high due to the fact that an existing drilling control method is difficult to effectively predict and avoid hole wall instability, the method adopts the core technical scheme that a drilling parameter sequence is collected in real time through an orifice sensor; calculating a hole wall instability risk probability in real time by using a pre-trained lightweight hole wall instability prediction network; further, the scheme evaluation network predicts future multi-target performance based on the current state and the candidate control set; and finally, constructing a scoring function by taking the hole wall stability as a primary constraint, preferentially generating a control instruction and issuing the control instruction to a drilling machine for execution. According to the method, intelligent prediction and active control over the stability of the hole wall are achieved, the safety and reliability of drilling construction are remarkably improved, meanwhile, the drilling efficiency and the hole forming quality are both considered, the system calculation load is low, and on-site deployment and application are easy.

The invention discloses an anti-overturning active control method and device for a single-column pier bridge and a medium. The method comprises the steps that a thundersight displacement monitoring system and a hydraulic driving system are deployed; leighting multi-mode fusion data are obtained, and the transverse overturning angle of a beam body is calculated; constructing a digital twinborn body for predicting the overturning state of the bridge structure, and predicting the overturning states of the bridge at multiple moments in the future; and constructing an intelligent agent, and controlling the hydraulic driving system to execute an anti-overturning action based on the predicted bridge overturning state. The device and the medium are both used for implementing the method. The beneficial effects of the invention are that the structure displacement monitoring method based on Reighting heterogeneous fusion is provided for a traditional mode of a single structure displacement detection means, interference factor identification and weighted fusion in different environments are realized, and the reliability of monitored structure displacement data is ensured.

The invention relates to an exoskeleton safety redundancy strategy and switching method based on anomaly detection, and the method comprises the steps: collecting a tension state between the active control intention of a user and the response execution of an exoskeleton system, defining as a potential anomaly when continuous asynchronous tension exists between the expected control direction of the user and the inertial behavior of the system; a redundancy strategy triggering precondition is adopted; after abnormal triggering, the system outputs a control suggestion, and whether the control right should be taken over by a redundancy strategy or not is judged by combining user reverse force application and posture deviation trend behavior performance, and master control continues to be maintained or a forced freezing state is entered; the intervention level of a redundancy control strategy is dynamically adjusted, and continuous control evolution from low intrusion to high takeover is achieved; if it is detected that an irreconcilable confrontation trend exists between continuous reverse intention input of the user and control output of the system in the control evolution process, and intervention ratio unbalance of the system is continuously expanded, the system enters a soft freezing or conservative attitude mode; and in the freezing state, judging whether the man-machine trust relationship is reconstructed or not.

The invention discloses a multi-axis linkage machining precision optimization control method adopting real-time detection driving, and relates to the technical field of machining intelligent control. The method comprises the following steps: establishing a multi-source real-time detection system comprising a laser displacement sensor, a force sensor and an industrial camera, and collecting multi-source data; performing time-space synchronization calibration on multi-source data, and improving a fusion vector of a feature by borrowing an attention mechanism convolutional neural network; constructing a machining precision dynamic compensation model by combining the kinematics forward and inverse solution sub-model and the tool thermal deformation compensation sub-model, and iteratively optimizing parameters by adopting an improved particle swarm optimization algorithm; the compensation amount is converted into a numerical control instruction through a data conversion module; and after compensation, data feedback updates the feature vector, and compensation parameters are dynamically adjusted until machining is finished. According to the invention, an active control system of multi-source detection, intelligent analysis, dynamic compensation and dynamic feedback is constructed, precise control of the whole processing flow is realized, and a general solution is provided for precision upgrading in the field of high-end equipment manufacturing.

The invention discloses a fault diagnosis and self-healing control method, system, equipment and medium for a flexible interconnection device of a power distribution network, and belongs to the technical field of fault diagnosis and control of the power distribution network, and the method comprises the steps: building a system state vector, collecting operation parameters of the power distribution network, and carrying out the weighted fusion; performing quality inspection on the original data based on the acquired operation parameters, and dynamically adjusting model parameters through digital twin synchronization and model parameter updating; deep learning is carried out to carry out multi-level fault feature extraction, and multi-scale feature fusion is carried out; a fault mode identification module is started, and fault probability is calculated for fault classification; evaluating the severity of the fault according to a fault diagnosis result, selecting an optimal control strategy, and carrying out self-healing control; and fault early warning is started to estimate a future fault occurrence probability, and early warning information of different levels is issued to perform preventive maintenance. According to the invention, full-process automation and intelligentization from data perception and intelligent diagnosis to active control and prospective maintenance are realized.

The invention discloses an intelligent shock absorption and noise reduction control method for rail transit, and belongs to the technical field of rail transit noise and vibration control. The method aims at solving the problems that traditional passive control measures are poor in adaptive capacity and limited in frequency band, and effective prospective offset is difficult to achieve due to system delay and inaccurate reference signals in existing active control. The method comprises the following steps: synchronously acquiring vibration and noise signals through a sensor array; calculating the contribution weight of vibration to noise by using a cross-domain modal correlation module based on an attention mechanism, and fusing the features; predicting an evolution sequence of vibration and noise in a specific time period in the future by adopting a long-short-term memory network model; synthesizing a target reference signal according to the prediction sequence, and generating an anti-phase control signal through an adaptive filtering algorithm; finally, it is ensured that the total delay of the system is smaller than the feedforward advance time, and an actuator is driven to achieve accurate foresight counteracting. The method is mainly used for improving the self-adaptive capacity and the control effect of the rail transit damping and noise reduction system.

The invention discloses an active control method and system for suppressing torsional vibration of a permanent magnet synchronous wind driven generator, and the method comprises the steps: building a dual mass-rigidity-damping model through a lumped mass method based on transmission chain parameters and pneumatic torque, and obtaining a transmission chain dynamic equation; performing torsional vibration characteristic analysis on the natural wind speed, the pneumatic torque and the transmission chain dynamic equation to obtain a torsion angle, an eigenfrequency, a damping ratio equation and electromagnetic torque influence evaluation; and controller design is carried out on the torsional vibration mathematical model and the active disturbance rejection controller parameters to obtain an electromagnetic torque compensation amount, and active suppression of torsional vibration is realized. According to the invention, through cooperation of a physical model and intelligent control, a sensing-analysis-compensation closed loop is formed; a high-precision mathematical model is constructed, and a wind-machine-electricity coupling effect is captured; the ADRC regards unknown parameters and external disturbance as total disturbance, real-time estimation and compensation are carried out through a tracking differentiator, and an accurate system model is not needed; torsional vibration is restrained, and adaptability is enhanced.

The invention provides a direct disturbance suppression method for a vibration isolation system based on driving force feedforward and linear active disturbance rejection control, and belongs to the technical field of active vibration isolation. The problems that existing active control methods such as feed-forward control and iterative learning control are limited by model dependence, nonlinear adaptation is poor, and aperiodic disturbance processing capacity is weak are solved. The method comprises the steps that a dynamic model of a vibration isolation system is established, the vibration isolation system comprises a vibration isolation platform and a motion platform, and the dynamic model is used for quantifying direct disturbance force caused by motion of the motion platform; a feedforward compensator is designed, and feedforward compensation force is generated in real time according to a motion instruction of the motion platform; introducing a linear active disturbance rejection controller; and superposing the feed-forward compensation force with a compensation force generated by the linear active disturbance rejection controller to obtain a total compensation force, and applying the total compensation force to the vibration isolation system to realize disturbance suppression. The method is mainly used in the field of precision manufacturing and measurement.

The invention discloses a dynamic inertia evaluation method for an active control type energy storage converter, and aims to solve the problem that the service life of system equipment is affected due to insufficient precision and real-time performance and insufficient coupling relation coordination between SOC and output power in a traditional inertia evaluation method. According to the method, a lightweight multilayer perceptron neural network is adopted, firstly, multi-scale feature extraction is carried out on active power and frequency variation of a power grid, then inertia real-time evaluation and trend prediction are realized through a hidden layer with residual connection and neuron adaptive adjustment, and then through an output layer. And outputting an additional power regulation instruction in combination with virtual inertia control, and outputting an optimized final additional power regulation instruction through an SOC-power-life collaborative model and an efficiency-life balance mechanism. The inertia evaluation precision and the response speed are improved, dynamic cooperation of inertia support and the energy storage state is achieved, and the operation safety and the service life of the energy storage system are guaranteed while inertia support is provided.

The invention relates to the technical field of ship hoisting control, in particular to a ship hoisting heaving active control system based on hydraulic compensation, and adopts the technical scheme as follows: precise advanced prediction of heaving motion of a ship in future 2-5 seconds is realized by integrating a motion sensing and prediction module and adopting a time sequence prediction model based on a long short-term memory network; a core control decision module adopts a model prediction control strategy fused with multi-source data to uniformly optimize multiple targets such as load stability, energy consumption and equipment wear; internal and external state changes of the system are sensed in real time through a system state monitoring and self-adaption module, control parameters are adjusted on line based on a fuzzy rule base, and the system is endowed with self-adaption capacity for coping with load changes, sea condition fluctuation and component performance degradation in the whole life cycle; a closed volume control scheme that a servo motor directly drives a two-way metering pump is adopted in the hydraulic execution and compensation module, throttling loss in a traditional valve control system is abandoned, and efficient conversion between hydraulic energy and mechanical energy is achieved.

The invention relates to the technical field of glass production process intelligent control, in particular to a glass production process intelligent control system based on a PLC. The system comprises a data acquisition module, a first processing module, a second processing module, a damage evaluation module, a state determination module and a parameter adjustment module. The system predicts a temperature field in the kiln and calculates thermal stress by collecting PLC and sensor data and using a reduced order model; the core is to track the historical fluctuation of thermal stress and determine the accumulated fatigue damage degree based on the fatigue accumulation theory; converting the temperature into the kiln health degree to determine a health perception regulation factor and a control mode; when the health degree is reduced, the system adaptively adjusts the control parameters of the PLC, so that the control response tends to be gentle and conservative; according to the invention, health perception adjustment of the control strategy is realized, and excessive active control behaviors causing physical damage can be actively avoided.

The application provides a fluid pulsation control method, device and system based on a time delay parameter model. The method comprises the following steps: obtaining a hysteresis phase parameter of a control valve at a target frequency of fluid pulsation based on the target frequency; determining a model parameter of a secondary channel estimation model based on the hysteresis phase parameter of the control valve at the target frequency and a basic delay of the secondary channel; obtaining a reference signal based on the target frequency of the fluid pulsation, inputting the reference signal into the secondary channel estimation model, and obtaining a reference signal filtered by the secondary channel estimation model; and adjusting an adaptive parameter based on a reference control error of the fluid pulsation and the reference signal filtered by the secondary channel estimation model, and realizing active control. The method can ensure that an adaptive fluid pulsation control algorithm is applicable to stable control in a time-varying scene.

The application discloses a kind of arbitrary pulsating wind field active control wind tunnel physical simulation method and system, comprising: establishing generalized pulsating wind field spectrum model, it has 6 controllable pulsating wind spectrum in the energy distribution model parameter of frequency domain;Based on generalized pulsating wind field spectrum model, inter-spectrum matrix is calculated using coherence function;Based on harmonic superposition method, inter-spectrum matrix is converted into pulsating wind field space-time information;Pulsating wind field space-time information is introduced into the control program of active control wind tunnel, through real-time monitoring and iterative adjustment model parameter, until the target wind field generated reaches expectation.The application can simulate wind field with arbitrary frequency energy distribution by generalized pulsating wind field spectrum model with 6 model parameters, combined with iterative closed-loop control, significantly improve the simulation accuracy and adaptability of complex wind field such as mountain valley wind, typhoon.

The invention provides an energy storage type double-fed phase modifier transient synchronous supporting method and device and a medium, and relates to the technical field of electric power. The method comprises the following steps: when voltage drop and frequency disturbance occur in a power system, determining an adaptive reactive current proportionality coefficient according to a voltage deviation normalized value, a frequency deviation normalized value and a frequency change rate normalized value of a machine end of the energy storage type doubly-fed phase modifier by adopting a control strategy of reactive power priority and active power amplitude limiting by the energy storage type doubly-fed phase modifier; determining a target reactive current according to the adaptive reactive current proportionality coefficient so as to carry out reactive control on the energy storage type double-fed phase modifier; and in combination with the amplitude limiting effect of the virtual inertia control and the adaptive reactive current proportionality coefficient on the active current, obtaining a target active current so as to carry out active control on the energy storage type double-fed phase modifier. According to the invention, when voltage drop and frequency disturbance occur in a power system, the active and reactive output proportion can be dynamically adjusted, and the overall stability of voltage and frequency is improved.

This invention relates to a multi-mode vortex-induced vibration control method for long-span bridges based on multiple SATMDI (Self-Active Capacitive Tuned Mass Damper) dampers, belonging to the field of structural vibration control. The invention addresses the problem of insufficient optimization in existing semi-active controlled SATMDI settings. The method comprises the following steps: Step 1: Establishing a finite element model of the bridge and extracting modal information for each order; Step 2: Screening the bridge modes, retaining modes with natural frequencies lower than the highest vortex shedding frequency; Step 3: Determining the vortex-induced vibration amplitude limits [A] for each mode requiring control. n ], and then obtain the allowable value of the peak value of the dynamic amplification coefficient of each mode of the bridge; Step 4, divide the retained modes into G groups, and obtain the sum of the minimum additional mass required for each group of modes; Repeat step 4 P times, regrouping each time, and obtain P results; Step 5, take the grouping strategy with the minimum value among the P results as the optimal grouping strategy, and obtain the minimum additional mass required to control all modes and the corresponding optimal SATMDI deployment position.

This application discloses a method, device, medium, and product for active control of aerodynamic noise in the target area during tiltrotor transition flight, relating to the field of noise control. The method includes: during tilt transition conditions, constructing a target noise control area within a set region based on flight mission and environmental requirements, discretizing it into multiple spatial observation points and assigning weights; parameterizing the controllable aerodynamic loads on the blades to obtain control load variables, establishing the relationship between the control load variables and the acoustic response of the target noise control area, determining unknowns, and establishing a global acoustic optimization objective function; using the DDQN algorithm as a solver, optimizing the global acoustic optimization objective function under the premise of satisfying actuator physical constraints to obtain the optimal control law, performing feedforward execution and feedback correction to achieve active control of aerodynamic noise in the target area. This application can solve the main shortcomings and derived problems caused by focusing on single-point noise control.

An experiment-in-the-loop system for determining one or more control parameters for an active controller includes a first processor and a second processor. The first processor determines one or more parameters for a first control algorithm during a series of experiments, where one or more external stimuli are applied to a device under test (DUT). The second processor derives a cost of a physical response to the one or more external stimuli based on measurements from one or more sensors. In response to an option parameter received by the second processor, a switch can select a first, second, or third controller to connect to the DUT. The first, second, or third controller produces an actuation voltage that is routed to a first stimulator device. The first stimulator device applies a first external stimulus to the DUT.

This invention provides a machine learning-based method for active shape control in laser additive manufacturing. The method includes: simulating temperature field distribution data and microstructure images perpendicular to the printing direction during the additive manufacturing process using a physical model, and preprocessing these to obtain the mechanical properties of the formed part corresponding to the microstructure images; predicting the forming quality at the next moment using a trained neural network; and when the predicted forming quality does not meet requirements, actively adjusting printing process parameters to achieve real-time active control of the macroscopic temperature field, thereby regulating the microstructure and mechanical properties of the formed part online. Compared to calculation methods that directly construct physical constitutive models, this method can significantly shorten the solution time. Furthermore, this invention establishes a temporal and spatial relationship between printing process parameters, temperature field distribution, microstructure images, and mechanical properties, which is beneficial for promoting comprehensive technological innovation in the field of additive manufacturing.

The invention discloses a dynamic evaluation and intelligent compensation system and method for contact rigidity of a machine tool joint part. The system comprises a digital twin and multi-source data interface module, a contact interface multi-scale morphology acquisition and characterization module, a joint part contact mechanical state online simulation module, a contact rigidity dynamic calculation model library, a performance evaluation and intelligent compensation decision-making unit and a compensation strategy execution and feedback module. According to the method, dynamic and high-precision contact stiffness analysis is achieved, the problem that a traditional static model is insufficient in precision is solved by deeply fusing microstructure measured data, a macrostructure model and a dynamic working condition load, and the time-varying characteristic of the joint part under the complex working condition can be reflected more truly. A perception-evaluation-compensation active control closed loop is constructed, and the digitization level of machine tool design and operation is improved. According to the method, the contact state of the joint part is actively optimized, so that the dynamic and static performance and machining quality of the machine tool are improved.

The application discloses a wind power plant control method and device considering rotor speed dynamic constraint, and the method comprises the following steps: obtaining the operation parameters of synchronous units in a power grid; constructing an additional active control model of the wind power plant containing power optimization control; linearizing the power grid frequency and the synchronous unit output power according to the operation parameters and the additional active control model combined with the piecewise function principle to obtain a total power increment piecewise linear expression of the wind power plant; performing piecewise fitting according to the wind power coefficient and the rotor speed to obtain a first equation; obtaining a rotor speed piecewise expression according to the wind power plant rotor motion equation, the first equation and the total power increment piecewise linear expression; adjusting the control parameters of the wind power plant in each speed section according to the rotor speed piecewise expression; the control parameters at least include primary frequency modulation parameters; and controlling the wind power plant according to the control parameters.

The invention relates to the technical field of high and low temperature all-in-one machines, in particular to a high and low temperature all-in-one machine safety control method and system. Firstly, operation parameters of the high and low temperature all-in-one machine are collected in real time through a multi-mode sensor system; performing time synchronization and data fusion on the acquired operation parameters to generate a multi-dimensional time sequence fusion data sequence; calculating a real-time parameter boundary of the dynamic security domain model based on a current set working condition; inputting the multi-dimensional time sequence fusion data sequence and the real-time parameter boundary into a risk assessment engine, and calculating a comprehensive risk score; and finally executing a hierarchical active control strategy according to the comprehensive risk score. According to the method, a complete technical closed loop from multi-source data fusion, dynamic risk assessment to intelligent hierarchical control is realized, and the safety and reliability of equipment are remarkably improved.

An orientation fault detection system is configured to detect improper installation of the dynamic active control system (DACS) controller / software module by receiving data output from a plurality of sensors to determine whether an orientation fault is detected corresponding to an improper installation of the controller / software module. Such determination is made based upon sensor data when corresponding environmental and operational conditions are met, so the orientation fault detection system is further configured to determine whether the requisite conditions are met for orientation fault detection based upon the sensor data. If an orientation fault is detected, the orientation fault detection system initiates a safe state protocol that renders the vessel safe to operate.

The present application relates to worm grinding wheel gear grinding surface texture active regulation method based on micro pulse grinding. It includes the following steps: using white light interferometer to measure the surface morphology of the gear generated under the conventional grinding mode, and obtaining the accurate information of the texture ditch height; the height of the texture ditch is used as a reference to determine the micro pulse amplitude, and the pulse frequency is set to generate the micro pulse grinding program; the changed NC program is copied to the designated folder of the numerical control gear grinding machine numerical control system and replaces the original program, and the micro pulse grinding is carried out. The micro pulse grinding processing mode proposed in the present application can generate the network texture along the contact trace direction and along the direction of the tooth, which changes the single regular texture along the direction of the tooth under the conventional grinding mode, so as to help to improve the performance of the gear, reduce the surface defects, improve the surface quality, and help to reduce the meshing impact and reduce the noise.