1008 results about "Processing Instruction" patented technology

The invention discloses a machine tool control method and system based on mechatronics, and the method comprises the steps: outputting an optimal cutting track sequence according to the three-dimensional model features and material attribute parameters of a machined workpiece; based on the optimal cutting track sequence, motion interference among shafts of the machine tool is eliminated through dynamic weight distribution, and an anti-interference optimization machining instruction is generated; constructing a nonlinear vibration wave propagation model according to the coupling relation between the spindle rotating speed and the feeding speed, and generating a steady speed regulation and control signal; generating an energy efficiency optimal parameter set including motor torque, cooling power and lubricating frequency based on the energy consumption efficiency constraint condition and the steady speed regulation and control signal; and outputting a closed-loop control signal and synchronously updating the three-dimensional machining precision thermodynamic diagram according to the real-time data in the machining process and the predicted deviation of the digital twin model. According to the embodiment of the invention, global optimization, dynamic adaptation and efficient operation of the machine tool can be realized, and technical support is provided for intelligent upgrading of the modern manufacturing industry.

According to the instruction processing system, method and device provided by the invention, the instructions can be efficiently and smoothly distributed and run through the at least one processing module of the processor, and different instruction distribution logics are adopted based on different types of business processing instructions through two-stage instruction distribution, so that the service processing efficiency is improved. The business processing instructions are stored in the target storage area and then scheduled to the instruction execution module, so that quick distribution and hardware support of different types of business processing instructions are realized, the instruction distribution efficiency is greatly improved, complex calculation tasks can be flexibly and efficiently processed, instruction scheduling can be performed according to the priorities of the business processing instructions, and the service processing efficiency is improved. The key business operation is ensured to be responded and processed in time, and the overall performance and the operation efficiency of the database processor are effectively improved. The technical effect of flexibly and efficiently processing the database acceleration task is achieved.

The invention discloses a spacecraft intelligent design method and system capable of autonomously learning, and belongs to the technical field of spacecraft design and simulation. The problems that in spacecraft design, natural language requirements are fuzzy and difficult to process, instruction generation is prone to ambiguity, linkage between simulation and design is not smooth, a design scheme lacks an effective iterative optimization mechanism, and traditional design is low in efficiency are solved. The method comprises the following steps: firstly, receiving a natural language demand, extracting key parameters to generate prompt words, inputting the prompt words into Design.AI, and generating a simulation instruction sequence; simulation is started through MCP Server conversion, if the result does not reach the standard, feedback correction is carried out, and iterative optimization is carried out. And repeating the steps until a design target is met, and generating a design report containing multiple items of content. Through natural language processing, real-time simulation, iterative optimization, knowledge accumulation and other technologies, the spacecraft design efficiency is greatly improved, the accuracy is enhanced, the threshold is lowered, and the flexibility is improved.

The invention discloses a private network data security detection method based on big data, and belongs to the field of security detection, and the method comprises the steps: obtaining a real-time data packet from private network traffic, encoding the data packet through a forward error correction code technology, generating redundancy check information, and obtaining an encoded data packet; if a bit error is detected in the transmission process of the coded data packet, requesting a sending end to retransmit a damaged data packet through an automatic retransmission request mechanism to obtain a retransmitted data packet; adjusting the redundancy of a forward error correction code and a trigger threshold of an automatic retransmission request according to the adaptive error correction parameter, generating an optimized error correction scheme, and obtaining a repaired data packet; and aiming at the alarm processing instruction, automatically adjusting a network flow control strategy, limiting the transmission bandwidth of an abnormal destination, updating the sensitive data fingerprint database, and obtaining optimized protection configuration.

The invention relates to the technical field of network communication, and discloses an intelligent control method and system of a switch. The method comprises the following steps: receiving a heterogeneous data stream in a target network domain; performing data processing by using a preset flow feature aggregation model, and generating a flow dynamic pressure field distribution diagram and a protocol priority mapping matrix; constructing an adaptive scheduling threshold model, and generating a multi-target flow control instruction set; a cascade effect is simulated based on a network congestion chained conduction model, and collaborative routing parameters are optimized; and iteratively optimizing through a mixed integer programming framework, and outputting a network scheduling action sequence to a switch control engine. The system correspondingly comprises a data receiving module, a data processing module, an instruction generation module, a simulation optimization module and an instruction output module. According to the method, heterogeneous data can be effectively processed, congestion can be accurately predicted, flow control can be optimized, the overall performance of the network can be improved, and communication requirements in a complex network environment can be met.

One aspect of the instant disclosure may provide a system and method for processing scatter-gather direct memory access (S-G DMA) instructions. During operation, the system may receive an S-G DMA instruction associated with a message and gather instruction context for the S-G DMA instruction. An S-G DMA processor may process the S-G DMA instruction based on the gathered instruction context and determine whether there exists a pending S-G DMA instruction associated with the message. In response to the presence of the pending S-G DMA instruction, the system stores the instruction context in a hot context cache at an address corresponding to the pending S-G DMA instruction. In response to the absence of the pending S-G DMA instruction, the system stores the instruction context in a cold context cache.

The embodiment of the invention provides an instruction processing method and device, a storage medium and an electronic device.The method comprises the steps that a first type of to-be-processed instructions are determined from multiple to-be-processed instructions according to preset instruction codes, and a first vector parameter is updated into a second vector parameter in an updating mode corresponding to the first type of to-be-processed instructions; and splitting a long vector instruction in other to-be-processed instructions into a plurality of micro-operations based on the second vector parameter, and renaming the other to-be-processed instructions according to the plurality of micro-operations, the other to-be-processed instructions being instructions except the first type of to-be-processed instructions in the plurality of to-be-processed instructions. According to the method and the device, the problem that an execution part circuit in a processor is too complex and too large in area and power consumption due to the appearance of a long vector in a vector instruction in the related technology is solved, and the effects of reducing the design complexity of the execution part circuit and realizing better processing frequency in a limited area are achieved.

A computer-implemented system for automated document generation receives user input and processes it through artificial intelligence models to create professional documents. The system combines user-provided information with specialized knowledge databases containing domain-specific requirements and formatting standards to generate enhanced processing instructions. Trained machine learning models process these instructions to produce contextually appropriate content that addresses specific technical and legal requirements. The generated content is formatted using configurable templates to create completed documents that meet professional standards. The system provides adaptive user interfaces that adjust functionality based on user expertise levels, supports multiple operational modes including guided and automated generation, learns from example documents to improve output quality, and enables comprehensive workflow management through network-accessible services. Applications include patent applications, legal responses, technical documentation, and other specialized professional documents requiring domain expertise and regulatory compliance.

The invention relates to the technical field of highway management, in particular to a highway electromechanical equipment fault early warning and intelligent regulation and control system which comprises a fault feature extraction and trend modeling module, a multi-source information fusion and fault diagnosis module, a fault processing strategy generation module and a closed-loop feedback and emergency processing module. The system constructs a fault development trend model through data acquisition, feature extraction and clustering analysis, carries out fault diagnosis by fusing multi-source information, generates a fault processing instruction, realizes closed-loop feedback and emergency processing, realizes the conversion from passive maintenance to active prevention, and realizes fault diagnosis through fault trend prediction and evolution rule modeling. Potential risks can be identified in the fault germination stage, preventive measures are taken in advance, and sudden faults of equipment are remarkably reduced.

The invention relates to a synchronous processing method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the steps of obtaining a to-be-processed task, splitting the to-be-processed task into at least one to-be-processed instruction, and distributing the to-be-processed instructions to different thread processing units; obtaining an access sequence barrier corresponding to the to-be-processed task, and sending the access sequence barrier to each thread processing unit; when the execution of the at least one to-be-processed instruction is completed, generating access sequence barrier execution completion feedback information, and storing the access sequence barrier execution completion feedback information to a target barrier cache region corresponding to the thread processing unit; if the corresponding access sequence barrier execution completion feedback information is stored in each target barrier cache region, it is determined that the to-be-processed task is completed, and the target barrier cache regions correspond to the thread processing units. By adopting the method, the processing efficiency can be improved.

The invention discloses a cloud big data storage management method, and the method comprises the steps: carrying out the classification of multi-element access habit feature vectors of all terminal nodes through a preset classification model based on the multi-element access habit feature vectors of all terminal nodes, and obtaining a plurality of terminal node groups; based on all the terminal node groups, a first node network and a second node network are constructed, the first node network is used for carrying out distributed storage on the data, and the second node network is used for carrying out distributed backup on the data; monitoring and obtaining target data and a source tracing point thereof in real time, and generating an association processing instruction of the target data according to a preset differentiated source tracing processing decision, the association processing instruction including storage, backup and forwarding; and periodically executing the steps according to a preset time interval. Therefore, based on the dynamic node network, dynamic storage and backup of data are realized, the change of access habits of terminal nodes is adapted, failure storage of nodes in an off-line state is reduced, and the reliability of storage resources is improved.

The utility model discloses a double-station aluminum mold processing machine tool, and relates to the field of machining. The machine comprises a rack, a first workbench, a second workbench, a first spindle box, a second spindle box, a first X-axis moving assembly, a second X-axis moving assembly, a Y-axis moving assembly, a first Z-axis moving assembly and a second Z-axis moving assembly. The first X-axis moving assembly and the second X-axis moving assembly are arranged on the rack in a spaced mode. The first workbench and the second workbench are arranged on the first X-axis moving assembly and the second X-axis moving assembly respectively. The Y-axis moving assembly is arranged on the upper portion of the rack. The first Z-axis moving assembly and the second Z-axis moving assembly are arranged on the Y-axis moving assembly in a spaced mode. The first spindle box and the second spindle box are arranged on the first Z-axis moving assembly and the second Z-axis moving assembly respectively. The numerical control machine tool can run on an operation panel of the machining machine tool, two machining instruction programs can be modified, and two same products or two different products can be machined at the same time.

The invention provides a multi-source network equipment fault mode identification and positioning method and system, and relates to the technical field of computer fault diagnosis, and the method comprises the steps: collecting equipment hardware data and software data, generating a fault feature vector, collecting adjacent equipment information, and constructing a communication relation graph and a link abnormity probability distribution graph; determining fault source equipment and probability through correlation analysis; according to the method, the processing instruction is generated, and the baseline data is updated, so that the computer network fault can be accurately identified and quickly positioned, the fault processing efficiency is improved, and the network maintenance cost is reduced.

The invention relates to the technical field of data processing, in particular to a customized packaging design management system for household appliances, which comprises a dynamic feature genetic coding module, a cross-domain parameter coupling optimization engine, a double-level genetic optimization architecture, a dynamic case feature reconstruction module, a coevolution verification interface and a self-adaptive processing instruction generator. Converting the geometric features of the household appliance into a hybrid coded chromosome data stream; the cross-domain parameter coupling optimization engine integrates the logistics vibration spectrum and the material shock resistance parameters, constructs a dynamic constraint matrix and generates a multi-target non-dominated solution set; the coevolution verification interface corrects and optimizes the weight coefficient through physical simulation feedback to form a closed loop verification link; according to the method, the problems of static template adaptation lag, insufficient multi-constraint coupling and historical case feedback deficiency are solved, and the packaging design efficiency and the structural reliability are improved.

The invention provides a quadrant switching smooth control method, device and equipment for an electro-hydrostatic system, and relates to the technical field of electro-hydraulic compound drive control. According to the method, sensor state information is acquired, a discretization state-space equation is established, a cost function is designed, improved sequential quadratic programming is called to solve the optimal control quantity, instructions are smoothly processed through a linear tracking differentiator, a reference value is calculated through a current distribution strategy and pressure feed-forward compensation, and cooperative impact resistance control is achieved through a PI controller and SVPWM. The response speed and stability of the electro-hydraulic compound system in the quadrant switching process can be remarkably improved, the problems of impact and torque overshoot are effectively restrained, the service life of equipment is prolonged, and the electro-hydraulic compound system is suitable for high-performance requirement scenes under complex working conditions such as electric loaders, excavators and winches.

The invention provides a data processing method and device based on a nonvolatile storage space and related equipment. The method comprises the following steps: searching a target index identifier matched with a to-be-matched index identifier in the nonvolatile storage space; when the target index identifier is found, determining an index storage address and a storage address offset corresponding to the target index identifier pre-stored in a nonvolatile storage space; determining a tuple storage address of the target tuple through the storage address offset and the index storage address so as to determine a storage state set of the target tuple; if the storage state set comprises a plurality of storage states, obtaining storage timestamps corresponding to the plurality of storage states and an instruction timestamp corresponding to the data processing instruction; and when a target storage state corresponding to the target tuple is determined based on the storage timestamp and the instruction timestamp, executing an instruction operation indicated by the data processing instruction through the target storage state. By adopting the method, the tuple searching efficiency and the operation execution efficiency can be improved.

The invention relates to the technical field of Internet of Things science and technology, and discloses an intelligent processing method, device and equipment for Internet of Things data and a medium, and the method comprises the steps: obtaining initial data which are transmitted and collected by different types of equipment to a platform unified interface of an Internet of Things platform; sorting and classifying the initial data, and distributing the classified initial data to different first message queues according to classification rules of classification; after the initial data passes through the calculation engine, calculating the initial data to obtain different efficient data, and storing the different efficient data into different second message queues; and sending the efficient data conforming to the preset alarm calculation rule to a preset large model to obtain an intelligent processing instruction, and pushing the intelligent processing instruction to a task arrangement service for arrangement so as to be read and executed by a corresponding external device.

The invention relates to the technical field of machine tool machining, in particular to a method, system and equipment for reducing the tool sticking probability in numerical control machine tool machining and a medium. The method comprises the steps of firstly obtaining overall machining parameter information, dividing a machining area according to workpiece geometric information, and setting partition parameters according to the overall machining parameter information; triggering a corresponding processing instruction according to the current processing area; then monitoring the machining state in real time and calculating a tool sticking risk index; finally, when the risk index exceeds a safety threshold value, the partition machining parameters are automatically adjusted; the overall characteristics of the workpiece are considered, the machining requirement of a local area can be met, and flexible control over the machining process of the complex workpiece is achieved; the machining precision and efficiency are remarkably improved, the service life of the tool is prolonged, and meanwhile the tool sticking probability is greatly reduced.

The invention relates to the technical field of factory intelligent inspection, and discloses a distributed factory intelligent inspection path dynamic planning and fault linkage processing system. The system comprises four core modules, namely a partition monitoring module, a path planning module, a fault analysis module and a linkage execution module. The subarea monitoring module obtains current operation data of each production area and provides basic data for a subsequent process; the path planning module generates an initial inspection path, breaks through the limitation of a traditional fixed path, and optimizes the distribution of inspection resources. The fault analysis module calculates a path deviation value according to the real-time operation state data of the path nodes, and captures node state changes to identify fault risks; and the linkage execution module triggers the linkage processing instruction of the corresponding area according to the deviation value, thereby reducing information transmission links and realizing rapid fault response. The system forms a complete closed loop of data monitoring, path planning, deviation analysis and linkage processing, and ensures the production stability and safety of distributed factories.

The embodiment of the invention provides a screen content generation method, a display method, equipment, a medium and a program product, and relates to the technical field of computers, the method comprises the following steps: receiving a processing instruction, the processing instruction being used for indicating a content processing demand of a target screen through a natural language; in response to the processing instruction, analyzing the content processing demand by using a preset identification model to obtain each task needing to be executed; and based on the task type to which each task belongs, calling a task execution tool corresponding to the task type to execute the corresponding task, and obtaining screen display content corresponding to the content processing demand. According to the technical scheme, the processing instruction of the target screen can be automatically analyzed, and the corresponding task execution tool can be called to process the content of the target screen, so that the labor cost and the time cost can be reduced, and the content processing requirement of the target screen can be efficiently and accurately realized.

The invention discloses a graphic processing engine development method and system based on virtual simulation, and relates to the technical field of computer graphics and virtual reality, and the method comprises the steps: collecting three-dimensional point cloud data, carrying out the convolution operation through a convolutional neural network algorithm, extracting a three-dimensional space feature matrix, and constructing a graphic recognition model. Inputting original data of a to-be-processed graph into the graph recognition model, outputting a graph parameter set, matching a virtual scene model in a preset scene library, and adjusting parameters of the model; establishing a physical coordinate system according to the adjusted model, converting a to-be-processed graph into grid units through a grid division algorithm, and calculating displacement data of the grid units; and reading displacement data, generating a graphic processing instruction sequence and sending the graphic processing instruction sequence to a graphic processor, and outputting an imaging result by superposing texture information and a ray tracing effect on the grid units. According to the method, a complete processing chain from data acquisition to rendering output is established, and the automation level and accuracy of graphic processing are improved.

The invention discloses a metadata processing method, computer equipment and a readable storage medium. The method comprises the steps of obtaining an unstructured text; according to the unstructured text and a processing instruction corresponding to metadata processing, generating a first model cue word, and inputting the first model cue word into a trained large language model; and processing the unstructured text through the large language model, and outputting metadata information of general attributes and metadata information of sensitive attributes in the unstructured text. In this way, the efficiency and the intelligent level of metadata information extraction can be improved. Moreover, besides the metadata with the general attributes, the metadata with the sensitive attributes can be extracted, and management of sensitive information is facilitated.

The embodiment of the invention provides an instruction response method, electronic equipment, a storage medium and a program product, after a to-be-processed instruction is received, a trained large language model is firstly used for prison break attack detection, and the safety of the instruction is judged. And if the instruction is safe (that is, the instruction does not contain the jail break attack behavior), a corresponding response result is generated by using the same model, so that the processing continuity and efficiency are ensured. And if the jail break attack behavior is detected, the instruction is rejected immediately, so that the potential safety risk is effectively prevented. The synchronous processing mode not only improves the safety of the model, but also ensures the timeliness of model response.

The invention relates to the technical field of system-on-chip service interrupt processing, in particular to a hardware Sequence-based SoC interrupt processing method, which comprises the following steps of: pre-programming an interrupt processing instruction sequence into an instruction random access memory (RAM), and configuring an instruction set, a sequence processor and an interrupt priority strategy of a task scheduler Sequence; receiving the interrupt signal by a task scheduler, and selecting a corresponding sequence processor according to an interrupt type; for the interrupt with low priority, the Sequencer directly executes the pre-stored instruction sequence to complete the interrupt response; and for high-priority interruption, the Sequencer caches the state of the register and sends a message packet to notify the CPU to perform cooperative processing. According to the method, interrupt autonomous response is achieved through hardware Sequence, zero CPU intervention is achieved in low-priority interrupt, a lightweight message mechanism is adopted in high-priority interrupt, and bandwidth occupation and power consumption are reduced while efficiency is improved.

The invention discloses a computer and large model interaction system based on an artificial dictation command, and the system comprises a control unit which is used for controlling and managing the whole information collection and conversion process; the acquisition module is responsible for capturing voice signals, recognizing the voice signals and converting the voice signals into readable text data for a computer; the analysis module is used for analyzing the text data and converting the text data into a readable instruction format for a large model; the interface module is used for receiving and processing an instruction format and realizing a corresponding function; and the feedback module is used for adjusting and optimizing the accuracy of the voice recognition system and the instruction analysis module according to the feedback result of the user. According to the method, through a deep learning algorithm based on a large model technology, commands dictated by a user are accurately recognized, texts are analyzed and key information is extracted through a large model, and the texts are converted into executable instruction formats, so that seamless joint of man-machine interaction is realized.

The invention provides a register processing method, and relates to the technical field of artificial intelligence, in particular to the technical field of chip, simultaneous multithreading and vector operation. According to the specific implementation scheme, a to-be-processed instruction is transmitted according to a first number of architecture registers required by the to-be-processed instruction and a second number of idle physical registers, the second number is determined from a plurality of physical registers shared by a plurality of threads, and the to-be-processed instruction is an instruction of a target thread in the plurality of threads; and in response to a received release instruction corresponding to the to-be-processed instruction, releasing the physical register occupied by the to-be-processed instruction. The invention further provides a register processing device, electronic equipment and a storage medium.

Systems and methods for management of user interactions in a physical facility utilizing a studio controller and user interaction configuration are provided. A physical facility can include or define a physical space in which one or more users interact with devices, objects, or services within the physical space. Various devices can capture interaction data. The facility, via the studio controller or other process, can then process the received interaction data according to a configuration or other processing instructions. The facility, through the studio controller or other process, can generate, or cause to be generated, various outputs based on the processed interaction data.

A facility for predicting on site electric power requirements for maintaining a fully electric fleet of vehicles in a mining operation to ensure sustainable electric operations, comprising a server comprising communications module configured to receive data and to transmit load management instructions; plurality of electrical charging stations; plurality of electric vehicles configured to be recharged by a selected electrical charging station; wherein the server comprises processor coupled with non-volatile memory, the non-volatile memory storing processing instructions that, when executed by the processor, causes the processor to simulate a total electrical power demand of the mine site due to the plurality of cabled mine equipment and the plurality of electric vehicles for each electric vehicle and each charging station within the facility over a prescribed period thereby to simulate and determine an energy storage capacity requirement of the charging stations of the facility through the prescribed period; thereby to forecast the electrical load management needs of the facility through the prescribed period.

The invention provides a spindle constant-temperature AI closed-loop heat engine system, and relates to the technical field of numerical control machine tool control and heat management. The invention aims to solve the problems of response lag, uncontrollable thermal stress, single heating strategy and the like of the traditional spindle heat engine method. The system comprises a multi-dimensional thermal state sensing module used for constructing a multi-node discrete temperature field representing the overall thermal distribution of the main shaft; the real-time heat balance feedback module is used for judging the cold / hot starting state of the main shaft according to the initial temperature difference and executing a differentiated feedback control strategy; and an AI prediction forward compensation module that predicts a future cutting thermal load by pre-reading a machining instruction and generates a feedforward thermal compensation instruction. According to the method, the thermal stress is controlled by introducing the radial thermal gradient index as the safety constraint, negative precooling or positive preheating is achieved in combination with the AI predictive capacity, a feedback and feedforward composite control mode is formed, and the dynamic thermal stability and the machining precision of the main shaft under the complex working condition are improved.

The invention provides a database node switching method, device and equipment based on hardware faults. Comprising the steps that node fault information of at least one node of a database is acquired, and the fault information of each node is used for indicating the hardware fault condition of the node; for each node, determining a fault type according to the node fault information of the node, and determining a fault processing instruction according to the fault type; and reporting the fault processing instruction to a database management platform. According to the technical scheme, the switching efficiency of the database fault nodes is improved, and the continuity of database services is ensured.