1450results about How to "Improve quality and efficiency" patented technology

The invention provides an intranet service quality optimization method and system based on deep reinforcement learning, and relates to the technical field of artificial intelligence, and the method comprises the steps: collecting multi-dimensional performance index data, carrying out the preprocessing, constructing an analytic hierarchy model, outputting the performance score of each layer, integrating the performance score of each layer, and outputting an intranet service quality score. Constructing a simulation environment, adjusting hyper-parameters of the adaptive deep reinforcement learning model, continuously learning in an actual intranet environment, determining multi-dimensional rewards, performing multi-target optimization, and generating a multi-target optimization result; and setting a hierarchical performance index threshold, if a hierarchical optimization strategy is triggered, adjusting a network topology structure, adjusting resource allocation and service configuration, adjusting weights of different indexes in the service quality evaluation model, updating a reward function, solving an optimal service decision, generating an optimal service decision sequence, and executing the optimal service decision sequence.

The present disclosure provides a control system, method, apparatus, medium and program product for a welding process. The control system comprises a sensor module configured to collect data in the welding process; the data analysis module is configured to pre-process data in the welding process, extract key features from the pre-processed data, perform weighted fusion processing on the key features to obtain comprehensive features, and perform defect identification through a machine learning model based on the comprehensive features to identify defect features; the knowledge graph module is configured to obtain a repair strategy corresponding to the defect characteristics according to the defect characteristics and by utilizing a knowledge graph; the control module is configured to transmit the data received from the sensor module in the welding process to the data analysis module, receive the repair strategy and generate a repair instruction based on the repair strategy; and the repairing module is configured to automatically adjust welding parameters or control an executing mechanism to conduct repairing operation based on the repairing instruction.

The invention provides a manufacturing-oriented test process digital twinning and dynamic optimization management method, which relates to the technical field of testing, and comprises the following steps of: acquiring real-time test data through a multi-source data acquisition device, and establishing a test process digital model; constructing a test process digital twin system; establishing a test process prediction model by using a deep learning algorithm; comparing and analyzing the real-time data and the prediction result, and identifying abnormity and optimization opportunities; generating and implementing a test process optimization scheme; and closed-loop optimization management is realized through feedback control. According to the method, the efficiency and quality of the test process are improved.

The invention provides a rapid construction and reuse method and system for an application framework, and relates to the technical field of application framework construction, and the method comprises the following steps: mapping code snippets to a high-dimensional tensor space, extracting multi-level code features, and constructing a code association graph and a deep semantic network; constructing a hierarchical Bayesian network based on the spatial-temporal feature map, executing variational reasoning and adaptive particle filtering, and generating a reconstruction code; driving a multi-level generation network by using a dual-dimension discriminator, optimizing a code structure and a dependency relationship, and generating a final optimization code through program slicing and incremental synthesis; according to the method, rapid construction and reuse of the application framework are realized, and the code quality and the execution efficiency are improved.

The invention discloses a laser cutting parameter adjusting system based on machine learning, and relates to the technical field of laser cutting. According to the method, multiple laser cutting parameters in the laser cutting process are collected, a short-term state index and a long-term state index are calculated based on the cutting parameters, and a laser cutting instant index and a laser cutting long-term index are generated respectively; based on the laser cutting instant index and the laser cutting long-term index, optimized laser cutting parameters are generated, and working parameters of the laser cutting machine are adjusted in real time; the adjustment result and the related data are sent back to the data storage module for updating the historical database; a real-time distribution curve is generated and compared with a target distribution curve, deviation is calculated, and a parameter optimization target curve is generated; and according to the optimized sub-targets, laser cutting parameters are adjusted in real time, and the stability and high efficiency of the laser cutting process are ensured. According to the system, accurate control over the laser cutting path is achieved through multi-layer and non-uniform control unit division and time-space correlation model construction.

The invention relates to the technical field of numerical simulation, in particular to a grid model generation method for the fluid displacement process of well cementation engineering. The method comprises the following steps: acquiring geological data of a well cementation project area, and constructing an initial geological model; well cementation engineering design data are obtained, well cementation engineering topological structure modeling is carried out, and a well cementation engineering topological structure model is obtained; according to the initial geologic model and the well cementation engineering topological structure model, fluid dynamic simulation is carried out, and a fluid characteristic matrix is obtained; performing fluid displacement process simulation according to the fluid characteristic matrix to obtain fluid displacement process data; performing fluid displacement process optimization on the well cementation engineering design data based on the fluid displacement process data to obtain optimized fluid displacement process data, and performing resource allocation redistribution on the well cementation engineering design data according to the optimized fluid displacement process data to obtain optimized well cementation engineering design data. According to the invention, the accuracy of fluid displacement simulation can be improved.

The invention discloses a data processing system and method for three-dimensional real estate surveying and mapping, and relates to the technical field of intelligent surveying and mapping, and the system comprises a multi-source data fusion module, a model generation module, a spatial relationship analysis module, an efficient rendering module and a data security module. The multi-source data fusion module converts the original surveying and mapping data in different formats into a unified three-dimensional point cloud data set; the model generation module generates a parameterized three-dimensional building model based on the point cloud data; the spatial relation analysis module constructs a relation graph of the building model and generates a surveying and mapping index report; the efficient rendering module processes large-scale three-dimensional data and generates an interactive three-dimensional scene; and the data security module controls the data access authority and generates an operation log. According to the method, the processing efficiency and precision of the three-dimensional real estate surveying and mapping data are improved, efficient analysis and visualization of large-scale three-dimensional data are realized, the security of sensitive data is ensured, and advanced technical support is provided for modern city planning, real estate management and real estate development.

The invention provides an ink quality online monitoring method and system based on multi-sensor fusion, and relates to the technical field of printers, and the method comprises the steps: obtaining the temperature, humidity, pH value, viscosity, particle thickness, flow velocity and other data collected by a plurality of sensors in the production process of water-based ink, and employing a multi-sensor data fusion algorithm of adaptive weight, calculating a sensing weight corresponding to the sensor data, and combining the sensor data to obtain fused water-based ink quality characteristic data; establishing a water-based ink quality prediction model by adopting a support vector machine algorithm, and inputting the fused water-based ink quality feature data into the trained water-based ink quality prediction model to obtain a water-based ink quality prediction result; and if the water-based ink quality prediction result does not meet the preset condition, judging that the water-based ink quality is unqualified, sending a feedback signal in a preset format to water-based ink production equipment, and adjusting water-based ink production parameters through a PID controller of the water-based ink production equipment. According to the method, the related parameters of the ink can be monitored and reflected in real time, and the possible problem of artificial false description is solved.

The invention provides a multi-modal data management system and method, equipment and a medium, and the system comprises a multi-modal data quality index creation module which is used for creating at least one multi-modal data quality index for multi-modal data; the multi-modal data quality detection task creation module is used for creating a multi-modal data quality detection task for the multi-modal data according to the at least one multi-modal data quality index and distributing the multi-modal data quality detection task to the multi-modal data detection module; the multi-modal data detection module is used for executing a multi-modal data quality detection task so as to carry out quality detection on the multi-modal data; and the multi-modal data detection result generation module is used for generating and displaying a multi-modal data quality detection report according to the execution result of the multi-modal data quality detection task, and the quality and management efficiency of the multi-modal data can be remarkably improved.

The embodiment of the invention relates to a processing method and device for carrying out structure optimization on electrolyte formula components. The method comprises the following steps: constructing a structure optimization model; constructing a first data set and a second data set; performing pre-training based on the first data set, and performing tuning based on the second data set; after the optimization is finished, taking an electrolyte formula input by a user as a current electrolyte formula, performing corresponding three-dimensional molecular structure modeling according to each component molecular sequence of the current electrolyte formula, and performing three-dimensional structure optimization on each component modeling structure based on a structure optimization model; forming a corresponding formula component structure optimization record by each component molecular sequence, the corresponding component type and the component optimization structure; and forming a corresponding formula structure optimization report by all the obtained formula component structure optimization records, and feeding back the report to a user. According to the method, the influence of human factors on the molecular structure modeling quality can be reduced, and the modeling quality and the modeling efficiency are improved.

The invention relates to the technical field of communication, and discloses a network optimization method and device based on multi-orbit satellite access, equipment and a medium, and the method comprises the steps: obtaining satellite orbit information from a network data analysis function module in response to an access request of user equipment; selecting a target orbit satellite from the multi-orbit satellites according to parameter requirements in the access request and satellite orbit information, and accessing the user equipment to the target orbit satellite; obtaining a Qos strategy based on the access request of the user equipment and the current network state of each orbital satellite, and configuring a network slice; and based on the Qos strategy and the network slice, constructing a data transmission session to enable the user equipment to perform data transmission with the user plane function module through the target orbit satellite. The optimal satellite orbit and the optimal network slice are intelligently selected by monitoring user requirements and network states in real time, dynamic flow routing and Qos configuration are achieved, and therefore it is ensured that a user obtains stable service quality in different scenes.

The invention relates to the technical field of self-adaptive control laser cutting, in particular to a self-adaptive laser cutting method and system based on characteristic parameters of sheet metal parts. Firstly, by establishing a space coordinate system and obtaining a top view image of a cutting platform, contour deviation is calculated, a correction initial position is generated, and then a cutting path is optimized. And the laser cutting head moves to the corrected initial position according to the path and performs a cutting task. In addition, the method further comprises the steps that the to-be-processed sheet metal part image is segmented into a plurality of sub-images, and a sub-image cross list is established to describe the connection relation of the sub-images. And extracting a subimage feature vector through a feature learning model, and adjusting a control parameter by using cutting simulation information to compensate an error. And for each sub-image, based on the cutting result and the connection relationship, adaptive adjustment of control parameters is carried out, and the precision of the subsequent cutting step is ensured. And finally, a complete cutting task is realized by updating the cutting mark and merging the sub-images.

The invention relates to a network abnormal behavior detection method based on dynamic data balance and generation, and the method comprises the steps: obtaining original network flow data, inputting the original network flow data into a dynamic abnormal data balance model, and obtaining an enhanced data set; the method comprises the steps of marking original network flow data based on an abnormal data balance model, performing selective undersampling on marked data, adjusting a ratio of normal data to abnormal data, obtaining a balance data set, generating new abnormal data according to the balance data set, and merging the new abnormal data with the balance data set to obtain an enhanced data set; and inputting the enhanced data set into a TimeDiT noise reduction model for denoising to obtain a target data set after noise reduction, inputting the target data set into an LSTM-Transform weighted training model for network abnormal behavior detection, and weighting abnormal data in the target data set in combination with a weighted loss function to obtain a detection result. According to the invention, the network traffic abnormal behavior detection efficiency and accuracy can be improved.

The invention provides a neodymium-iron-boron magnet surface treatment method and a neodymium-iron-boron magnet, and belongs to the technical field of rare earth permanent magnet material preparation. The surface treatment method comprises the steps that a to-be-electroplated magnet with the clean and rough surface is prepared; connecting with a power supply, soaking in a plating solution, and forming a corrosion-resistant plating layer on the surface of the to-be-electroplated magnet through an ion exchange electrodeposition method; wherein the ion exchange electrodeposition method comprises a first stage of synchronously applying a constant magnetic field and a variable-frequency electric field and a second stage of synchronously applying a rotating magnetic field and a variable-frequency electric field, the intensity of the constant magnetic field and the rotating magnetic field is 1000-3000 gs, and the rotating speed of the rotating magnetic field is 20-100 rpm / min. According to the neodymium-iron-boron magnet surface treatment method provided by the invention, a variable-frequency electric field and magnetic field synergistic enhanced ion exchange deposition technology is adopted to improve the deposition efficiency and corrosion resistance of a plating layer, and the neodymium-iron-boron magnet with an excellent corrosion resistance effect is efficiently prepared.

The invention discloses an X-band weather radar reflectivity data quality control method based on deep learning, and belongs to the technical field of meteorological data processing. The deep learning technology is introduced, the convolutional neural network is used for extracting the space and time characteristics of the original reflectivity data, high-precision data quality evaluation and classification are achieved, noise, low-quality and high-quality data can be efficiently recognized under the complex meteorological condition, and through real-time monitoring and a periodic optimization mechanism, the real-time performance of the system is improved. Model parameters are dynamically adjusted to adapt to data input changing in real time, the accuracy and reliability of data processing are guaranteed, through modular integration of a deep learning model, the deep learning model can be embedded into an existing meteorological system, automatic and intelligent application of data quality control is achieved, the data processing efficiency and quality control precision are remarkably improved, and the data processing efficiency is improved. And technical support is provided for the fields of weather prediction, climate research, disaster early warning and the like.

The invention provides a temperature control method and system for an organic fertilizer fermentation bin and a medium, and relates to the technical field of temperature control, and the method specifically comprises the steps: obtaining the environmental parameters and corresponding control parameters of the fermentation bin at a plurality of historical moments, obtaining the environmental parameters of the fermentation bin at the current moment, and calculating the comprehensive gas concentration and environmental state index; setting a target temperature, calculating the deviation between the current temperature and the target temperature, analyzing the correlation among a temperature deviation value, an environment state index and a control parameter by using a Pearson's correlation coefficient, and calculating the control parameter; and adjusting the heater and the ventilation equipment according to the control parameters. By obtaining and analyzing various key parameters in the fermentation bin in real time, comprehensive evaluation of the environment state is achieved, the accuracy of temperature control is improved, correlation analysis among temperature deviation, environment state indexes and control parameters is effectively integrated, operation of heating and ventilation equipment is dynamically adjusted in combination with a phase change material, and the temperature control accuracy is improved. The stability of the fermentation process is improved.

The invention relates to a cloth setting machine energy-saving optimization method based on artificial intelligence. The method comprises the following steps: S1, collecting process operation data in a cloth setting process; s2, preprocessing the collected data, and eliminating noise and abnormity; s3, dividing the setting machine control system into a heating control subsystem, a moisture removal control subsystem and a circulating air control subsystem according to different functions; s4, according to the predicted energy consumption demand, a multi-objective optimization algorithm is used, two objectives of shaping quality and energy consumption are optimized at the same time, and an optimal temperature, humidity and airflow velocity combined curve scheme is output; and S5, introducing a deep reinforcement learning training intelligent controller, directly feeding back the working condition of the setting machine through real-time data, and dynamically adjusting the operation of each subsystem based on the optimal temperature, humidity and airflow velocity combined curve scheme. The cloth shaping quality and the energy utilization efficiency are remarkably improved.

The utility model discloses a heater with a cleaning device, the heater is provided with a heating pipe, the cleaning device comprises a dry ice spraying device, the spraying opening of the dry ice spraying device faces the heating pipe, and the dry ice spraying device is used for spraying dry ice to the heating pipe; the output end of the ultrasonic device faces the heating pipe, and the output end of the ultrasonic device transmits ultrasonic waves into the dry ice medium sprayed by the dry ice spraying device. According to the utility model, stains are cleaned in a manner of spraying dry ice and superposing ultrasonic waves, the dry ice can effectively remove oil stains and impurities at low temperature, chemical solvents are not needed, the environment is not polluted, residues are not generated after sublimation, and the cleanliness of the heater is ensured; and high-frequency vibration of the ultrasonic waves can not only vibrate out stains in gaps of the heater, but also promote the reaction between the dry ice and the stains, so that the cleaning effect of the cleaning device is further improved.

The automatic laser cutting device for tarpaulin processing comprises a workbench, a winding roller is mounted on the left side of the workbench, a plurality of mounting blocks are fixedly connected to the upper end of the workbench, and the adjacent sides of every two matched mounting blocks are jointly and rotationally connected with a pressing roller; the upper end of the workbench is fixedly connected with two fixing blocks, and the adjacent sides of the two fixing blocks are jointly and rotationally connected with a first lead screw. According to the cutting device, different laser heads can be adopted for cutting according to different layers of materials of the tarpaulin, the problems that due to cutting of a single laser head, the cutting position of the composite tarpaulin is burnt, deformed or discolored are solved, the quality of the cut tarpaulin is ensured, automatic discharging can be achieved after cutting is completed every time, and the cutting efficiency is improved. And new tarpaulin is pulled to the cutting area of the workbench, and meanwhile static electricity removing treatment is conducted on the tarpaulin before cutting, so that the situation that chippings adhere to the tarpaulin due to static electricity in the cutting process is avoided.

The invention relates to a composite sleeve lining reinforced tunnel disease structure and a construction method, a feet-lock bolt guide construction technology is adopted, the inclination angle of a drill rod is adjusted through a feet-lock bolt guide device, a feet-lock bolt is constructed through drilling of the drill rod, and the construction quality and the construction efficiency of the feet-lock bolt are improved; a shaped reinforcement cage built-in profile steel sleeve lining reinforcing technology is adopted, and the reinforcement cage for reinforcing the sleeve lining is reinforced by built-in profile steel and is welded with an anchor rod, so that the supporting capacity and stability of the secondary lining of the existing tunnel are enhanced; the steel frame beams are arranged on the upper portions of the grouting steel pipes, the grouting steel pipes are inserted into the sleeves on the lower portions of the steel cross beams to be welded and fixed, the steel frame beams form a whole, the efficiency and quality of tunnel construction are improved, and the supporting capacity and stability of a tunnel are remarkably enhanced.

The invention discloses a lithium hexafluorophosphate production control system and a method thereof, and relates to the technical field of lithium hexafluorophosphate production, and the method specifically comprises the following steps: obtaining crystallization dynamic information of each area in a reaction kettle in a lithium hexafluorophosphate crystallization process in real time, and analyzing after obtaining to obtain a crystallization dynamic result; respectively generating a crystal growth driving force coefficient and a particle uniform distribution index of each region; constructing a particle size distribution evaluation model for the generated crystal growth driving force coefficient and particle uniform distribution index of each region, generating a particle size distribution coefficient of each region, and performing comprehensive analysis after generation to generate an evaluation coefficient; and analyzing the generated evaluation coefficient, and evaluating the uniformity degree of particle size distribution in the reaction kettle in the lithium hexafluorophosphate crystallization process. The problem of uneven particle size distribution in the lithium hexafluorophosphate crystallization process is solved, and the effect of improving the particle size uniformity and the product quality stability is achieved.

The invention relates to the technical field of additive manufacturing digital twinning, solves the technical problems of large calculation amount and long rendering time of a traditional 3D printing simulation method, and particularly relates to a 3D simulation system for quickly realizing additive manufacturing, which comprises the steps of loading and processing a model file, loading and processing a slice file and loading 3D model section data. According to the method, the cutting plane information of a target renderer or a material is dynamically set, the display and progress of a 3D printing model are controlled and managed, user interaction is controlled through a scroll bar, and through the operation, parts in the additive manufacturing printing process can be rapidly achieved on a Unity platform. According to the method, a vivid 3D printing simulation effect is quickly generated by utilizing a simplified geometric model, material attributes and an efficient rendering algorithm, and the whole printing process is simulated, so that a user can obtain visual preview of a printing object in a short time and can watch the whole printing process, and printing parameters can be better evaluated and adjusted.

The invention discloses a distributed screen projection method and system based on GPU rendering, and the method comprises the steps: calling a window management interface and a graphic interface, and creating a virtual screen; setting one or more surface layers on the virtual screen, and drawing image data on the surface layers; and completing the synthesis of the image data on the surface layer by using a graphics processing unit (GPU), encoding the synthesized image data through a multimedia encoding and decoding service, and sending the encoded image data to a receiving end in a distributed manner for screen projection display. According to the method, the virtual screen is created by calling the window management interface and the graphic interface, image data synthesis is completed by utilizing the GPU, efficient coding is performed through the multimedia coding and decoding service, and finally the image data are sent to the receiving end in a distributed manner for screen projection display, so that low-delay and high-resolution compatible distributed screen projection is realized.

The invention relates to the technical field of intelligent positioning, in particular to an intelligent positioning system and positioning method applied to a spraying robot, and the positioning system comprises a light field data acquisition module, a particle tracking calculation module, a sound wave precision distance measurement module and a dynamic verification execution module. According to the method, the operation environment of the spraying robot is sensed in an all-around mode through synthesis of a multi-sensing technology, the accurate position of the spraying head is updated through a strategy of capturing light field data in real time and accurately calculating particle dynamics, the spraying precision is ensured, the real-time response capacity to environment changes and the dynamic adjusting capacity of the spraying process can be greatly improved, and the spraying quality is improved. The material waste is reduced, the coating quality and the production efficiency are improved, sound wave precise distance measurement is added, the robustness and reliability of the system in a complex industrial environment are enhanced through sound wave and light field information fusion, precise tracking is combined with real-time position adjustment, and it is ensured that the spraying quality reaches the optimal quality every time.

The invention provides a batch machining method and system for precision parts with multi-axis linkage, and relates to the technical field of part machining, and the batch machining method comprises the steps that information of products to be machined is obtained, and multi-axis linkage process fitting is carried out; the multi-axis linkage machining scheme is analyzed, and inter-axis cooperation is established; abrasion analysis is conducted on the machining tool, and calibration tool compensation is configured; when batch machining is executed, machining control is conducted based on the multi-axis linkage machining scheme and calibration tool compensation, and error collection is executed after execution of each machining axis is completed; and multi-axis linkage compensation is generated based on inter-axis cooperation and error collection results, and machining control is conducted based on the multi-axis linkage compensation. By means of the method and device, the technical problems that in the prior art, due to error accumulation in the batch machining process, the machining precision is reduced, and the product quality is affected can be solved, accumulation of machining errors is reduced through multi-axis linkage compensation and establishment of the tool balanced abrasion result, and the product quality of batch machining is improved.

The invention discloses a monitoring method of a printing and dyeing intelligent manufacturing system based on a bimodal monitoring network, and the method comprises the steps: 1, data collection and preprocessing: a visual monitoring module and an auditory monitoring module work synchronously, and collect image and sound data in a cloth printing and dyeing process in real time; 2, data fusion and analysis: carrying out feature extraction on the image and sound data collected in the step 1, carrying out data fusion and comprehensive analysis, and generating a comprehensive evaluation report of the running state and the product quality of the printing and dyeing equipment; the dual-mode monitoring makes up the deficiency of single-mode monitoring, provides more comprehensive and accurate monitoring information, and improves the precision of fault detection and quality control.

The invention discloses a full-automatic forging production line for connecting rod parts. The production line comprises an automatic feeding machine, an intermediate frequency heating furnace, a roll forging machine, a first mechanical arm, a die forging press machine, a second mechanical arm, a fifth mechanical arm, a temperature control cooling line, a fourth mechanical arm, a trimming and punching press machine, a third mechanical arm, a bar positioning slide way, a descaling machine and an intermediate frequency furnace slide way. The automatic feeding machine, the intermediate frequency heating furnace, the roll forging machine and the descaling machine form a heating area. The first mechanical arm, the die forging press, the second mechanical arm, the fourth mechanical arm, the trimming and punching press, the third mechanical arm and the bar positioning slide form a forming area, the forging and pressing process is divided into four procedures of pre-forging, finish-forging, trimming and punching correction, and forgings at all stations are transferred in order through mechanical arm equipment. And the fifth manipulator and the temperature control cooling line form a heat treatment area. The full-automatic forging production line for the connecting rod type parts is reasonable in layout, high in automation degree and good in stability, the amount of labor used for forging operation is greatly reduced, the labor intensity of workers is relieved, and the product quality and the production efficiency can be improved.

The invention relates to the technical field of sludge dewatering, and discloses sludge brick production equipment for hydrolytic carbonization treatment. Comprising an equipment main body, a feeding hole formed in the surface of the front end of the equipment main body and used for feeding sludge, and two racks fixedly connected to the left and right sides of the equipment main body respectively and used for ensuring normal sludge filter pressing of the device, the pushing assembly is installed at the top of the rack and used for pushing the mud plate to move, the two driving assemblies are installed on the two sides of the interior of the equipment body and used for controlling the filter pressing force of the device, a toothed plate is arranged in the equipment body and fixedly connected to the symmetrical faces of the two driving assemblies, and a plurality of filter pressing plates are arranged on the outer surface of the toothed plate. The filter pressing plate comprises a material removing assembly which is arranged in the filter pressing plate, the material removing assembly is used for synchronously starting to assist the mud plate to fall when the filter pressing plate is moved to discharge the mud plate after filter pressing of the equipment main body is completed, and the device has the advantages that the discharging quality and the filter pressing efficiency of the device are improved, the manufacturing cost of the device is reduced, and the device is convenient to use by a user.

The invention provides an AI and VR nursing method and device integrating multiple senses, a medium and a program product, and relates to the field of intelligent medical treatment. The method comprises the steps that a first instruction for entering a virtual scene is received, and a subject enters the virtual scene to generate a virtual subject; the virtual scene comprises a foretaste area; receiving a second instruction that the virtual subject moves to the foretaste area in the virtual scene and moving the virtual subject to the foretaste area; receiving an instruction for a fake feeding object placed in the foretaste area, wherein the fake feeding object appears in the hand of the virtual subject; the category of the fake feeding object is recognized, and according to whether the distance between the fake feeding object and the mouth of the virtual subject in the virtual scene exceeds a threshold value or not or whether a feeding instruction is received or not, the smell spraying device receives a smell simulation instruction of the fake feeding object and starts the device to generate corresponding smell. A voice control module of the false feeding device is developed through AI, and a sniffing intention recognition algorithm is developed, so that accurate analysis and conversion of signals are realized, and the equipment intelligence is improved.

The invention provides a rolling mill equipment design parameter optimization method and device, equipment and a storage medium, and relates to the technical field of equipment parameter optimizing.The rolling mill equipment design parameter optimization method comprises the steps that original design data of to-be-optimized rolling mill equipment is obtained, and an equal-proportion roll changing force model is established based on the original design data; analyzing the roll changing force model to obtain key design parameters of the rolling mill equipment to be optimized; and classifying the key design parameters to obtain a plurality of classification data, and performing parameter optimization on each classification data according to a preset condition to obtain actual design parameters of the rolling mill equipment to be optimized. Through systematized data acquisition, model establishment and parameter analysis and optimization, the production requirements can be met, so that the system can operate more efficiently in the production process, the product quality and the production efficiency are improved, and meanwhile, the fault rate and the maintenance cost are reduced.