382 results about "Automated technique" patented technology

The invention relates to the technical field of operation and maintenance automation, and provides an operation and maintenance field professional question and answer and diagnosis Agent design method and system, and the method comprises the steps: receiving and structurally analyzing an original query request of a user, carrying out the parameter validity check and safety verification, and extracting the query content and a session identifier; identifying task types through an intention classification algorithm based on the pre-training language model and performing content risk assessment; performing semantic extension on the query to generate an extended query word, performing similarity matching in the operation and maintenance knowledge base by using a hybrid retrieval algorithm, and fusing related knowledge fragments; inputting the enhanced query information and the task type into an inference engine for intelligent inference to obtain a diagnosis result; the reasoning result is stored in a historical memory library, and session context state information is updated; and performing formatting processing and security check on the reasoning result, packaging the result and context information, and outputting a standard response result. According to the method, the accuracy and the intelligent level of operation and maintenance professional question answering and diagnosis are improved.

The invention discloses a method for identifying an engineering drawing detail table and generating a BOM table, and belongs to the crossing field of automation technology and image processing, and the method comprises the steps: obtaining a scanning or electronic image of an engineering drawing; through preset datum line positioning, recursively detecting a nested rectangular region conforming to an area difference threshold value, and determining a title bar, a detail list region coordinate and a table image; identifying lines and cross points, analyzing the line and column boundaries of the table, and constructing a topological structure; performing character recognition by adopting multi-engine OCR integration; the characters and the cells are associated, a header is recognized through semantics, and analysis data subjected to integrity verification are generated; and automatically generating a structured BOM table in a preset standard format based on the data, and outputting an editable file. According to the method, full-process automation is achieved, manual intervention is not needed, and manual input cost and personal errors are greatly reduced.

The invention discloses a PCB component layout method, device and equipment based on a multi-modal large model, and relates to the technical field of electronic design automation, the method comprises the following steps: carrying out quality screening on a plurality of PCB design files which have been laid out to obtain a qualified design file set; constructing a serialized training sample set based on the qualified design file set; each training sample sequence comprises a plurality of training samples arranged according to a layout logic sequence; each training sample comprises multi-modal data representing a current layout state and a real position coordinate of a next component to be laid out; based on the serialized training sample set, training the open-source multi-modal large model to obtain a PCB component layout model; and iteratively generating a layout file of the target PCB based on the netlist file of the target PCB and the PCB component layout model. The method is high in generalization capability and low in cost based on the PCB component layout model trained by the layout data, and can realize rapid layout of components of a new PCB.

The invention discloses a government affair complaint dispatching system and method based on a dynamic knowledge graph and a decision engine, and relates to the technical field of government affair automation. The government affair complaint dispatching system and method based on the dynamic knowledge graph and the decision engine comprises the following steps: S1, collecting complaint work order monitoring data, and preprocessing the complaint work order monitoring data; s2, constructing an initial graph structure, calculating weight data of each semantic relation edge according to a period, updating the initial graph structure, and constructing a dynamic knowledge graph; s3, evaluating the risk emergency degree of each work order, and generating an emergency work order identifier based on an evaluation result; and S4, extracting all the emergency work orders, executing scheduling evaluation calculation on the current undertaking department, and judging whether the execution department distributes the work orders again or not based on an evaluation result so as to realize order distribution execution and dynamic scheduling closed loop. The problem that high-risk complaints cannot be recognized and scheduled in time due to the fact that an order dispatching strategy cannot be adjusted in real time according to work order complexity and department bearing capacity in the prior art is solved.

The invention discloses a mechanical arm simulation system supporting industrial quality inspection, which relates to the technical field of industrial automation and comprises a multi-physics field simulation engine module, a digital twin interface module, a defect sample library module and a cooperative control module. According to the method, traditional entity mechanical arm debugging is replaced by rigid body dynamics simulation based on a physical engine, loss and production line shutdown caused by repeated trial and error of equipment are avoided, rapid construction of the digital twin environment of the production line is achieved by means of an efficient CAD model conversion process and a lightweight loading technology, and high-fidelity optical simulation is achieved through a parameterized defect model library and high-fidelity optical simulation. Various common industrial defects and complex optical effects are covered, the modeling bottleneck of a quality inspection scene is broken through, real-time closed-loop interaction of visual inspection and motion control is realized by using thread separation and an efficient communication technology, and the recognition robustness of a visual algorithm to tiny defects is guaranteed; the reliability of algorithm verification is improved through the quantitative output of algorithm performance indexes and the comprehensive test of extreme working conditions by the simulation system.

The invention relates to the technical field of power systems and automation thereof, in particular to a generative adversarial network-based source-load joint scene generation method, which comprises the following steps of: constructing a multi-source time sequence database and extracting weather, time, space and historical state driving factors; establishing a joint probability distribution model based on a vine connection function; taking a numerical weather forecast path and a date type as conditional input, constructing a generative adversarial network embedded with a physical constraint microloss function of the power system, and forming a physical information generator; performing dependent structure fidelity verification on the generated scene by using the joint probability distribution model; generator parameters are fixed, potential space vectors are optimized through a gradient ascending method to maximize power grid risk indexes, and a high-risk source-load joint scene set is generated. According to the technical scheme, accurate generation of the source-load joint scene which is physically feasible and reasonable in statistics and focuses on the high-risk working condition is realized, and the safe operation toughness and the risk early warning capability of the novel power system are remarkably improved.

The invention relates to the technical field of computer vision and industrial automation, and particularly discloses a MARK point high-precision PCB positioning and mechanical mapping method based on multi-coordinate system fusion, which is composed of PCB positioning and mechanical mapping in a template stage and PCB positioning and mechanical mapping in a production stage. Wherein the PCB positioning and mechanical mapping in the template stage comprises the steps of coordinate system establishment and image coordinate distortion correction; the PCB positioning and mechanical mapping in the production stage comprises Mark point real-time detection and offset calculation, real-time attitude solution and dynamic matrix calculation, and mechanical coordinate calculation of any PCB point. According to the method, a three-coordinate system collaborative modeling mechanism of an image coordinate system, a PCB coordinate system and a mechanical coordinate system is introduced, so that board attitude change and equipment fixing errors are separated, and the system robustness and the mapping precision are greatly improved; rigid body affine transformation is constructed by adopting double Mark points, the rotation angle, the proportion and the translation amount are solved in real time through two-point geometric constraint, and self-adaptive compensation of the posture change of the PCB is achieved.

The invention relates to the technical field of automation, in particular to a real-time multi-target visual positioning and mechanical arm cooperation system for intelligent material sorting, which comprises a visual perception and information acquisition module, a data processing and path planning module, a mechanical arm execution module and a man-machine interaction module. By combining the 2D camera and the 3D camera, 360-degree full-view-angle material sensing can be achieved, and the possibility of repeated grabbing errors of the mechanical arm can be reduced through the design of judging whether grabbing succeeds or not after the mechanical arm is controlled to execute the grabbing step every time.

The invention provides a task processing method and device based on an industrial large model, a medium and a product, and relates to the technical field of industrial automation. The method comprises the following steps: constructing a multi-source data set based on an industrial scene, and training a plurality of adapters corresponding to the multi-source data set by adopting an adaptive low-rank adaptation algorithm; according to the learnable weight, fusing the plurality of adapters to obtain a fine-tuned industrial large model; and inputting an operation and maintenance task of the intelligent equipment in the industrial scene into the fine-tuned industrial large model, outputting an operation and maintenance strategy of the intelligent equipment, and controlling the intelligent equipment in the industrial scene to execute the operation and maintenance strategy. According to the method, efficient fine tuning and capability integration of an industrial large model in a multi-source heterogeneous data scene are achieved by introducing a self-adaptive low-rank adaptation algorithm and a multi-task adapter fusion framework, the fusion conflict problem of multi-source heterogeneous data is solved, efficient reasoning of full-process intelligent interaction of the air compressor is achieved, and the intelligent interaction of the air compressor is achieved. And the stability and the precision of the large industrial model in a complex industrial task are improved.

The invention discloses a paper product counting method based on machine vision, and relates to the technical field of image processing and industrial automation. The method is used for solving the problem of low technical accuracy of paper products in complex industrial environments. The method comprises the following steps of: quantitatively recording inherent interference characteristics of a counting area by constructing an interference baseline library capable of being dynamically updated; performing real-time anomaly detection and positioning, acquiring images through a multispectral camera, comparing baseline features, and generating a difference thermodynamic diagram to position a paper candidate area; performing multi-modal counting, adopting track coding counting logic for a dynamic transmission scene, and adopting thickness gradient counting logic for a static stacking scene; counting results are subjected to cross check, dynamic and static counting results are compared, and accuracy is ensured through confidence evaluation; and the accuracy and the reliability of a paper product technology are obviously improved.

The invention discloses a feeder automation test method and system, and relates to the technical field of distribution network automation, and the method comprises the steps: building a qualitative simulation model according to the physical parameters of a power distribution network; performing fault simulation on the power distribution network through the qualitative simulation model to obtain operation states and parameters at different operation moments, and taking the operation states and parameters as typical section sequences; performing fault transient simulation on the power distribution network according to the typical section sequence to obtain a transient simulation result; matching the transient simulation result with a preset strategy library to obtain an optimal processing strategy; and collecting actual action data of feeder automation in a fault scene in real time, and performing consistency comparison on the actual action and the optimal processing strategy to obtain a feeder automation test result. By adopting the embodiment of the invention, the limitation of the traditional simulation step length can be broken through, efficient technical support is provided for logic verification of a feeder automation system in a millisecond response scene, and the test capability of power distribution network fault processing is remarkably improved.

The invention relates to a robot intelligent control method integrating visual guidance and digital twinning technologies, and belongs to the technical field of industrial automation. The method comprises the following steps: acquiring multi-source attribute data of a robot to construct a robot control digital twin architecture, and acquiring a point cloud of a to-be-operated workpiece to position a key point location; self-adaptive noise reduction and completion are carried out on the point cloud, a to-be-operated workpiece model is constructed, features are extracted, and a feature change trend pre-judgment model is established; transmitting data by utilizing an edge computing-cloud collaborative architecture, carrying out multi-dimensional comparison in a robot control digital twin architecture, constructing a dynamic weight path planning function, solving an optimal path by adopting a genetic algorithm, and then carrying out virtual-real interaction fault simulation to optimize the path; a double-end state comparison matrix is constructed for real-time monitoring, a multi-source fusion strategy is adopted for adjustment when deviation occurs, and a linkage mechanism is triggered to suspend operation and give an alarm when the deviation exceeds a threshold value. According to the method, high-precision, self-adaptive and reliable intelligent control of the robot is realized.

The invention relates to the technical field of industrial automation, in particular to an inspection path generation method and device, a storage medium and computer equipment, when an inspection path is generated, time-space synchronization can be carried out on data collected by different sensors, geometric and physical consistency of a motion track is ensured, the dynamic positioning precision is further improved, and the accuracy of the inspection path is improved. Moreover, when part of the sensors fail, the robustness of the system can be effectively enhanced through a synchronized redundant data maintenance function, and the data processing delay can be reduced through time-space synchronization, so that the real-time control requirement of a dynamic scene is met, and a map can be updated in real time according to the current environment to improve the accuracy of navigation and positioning. The method adapts to complex environments; in addition, the current positioning error can be corrected according to the target point cloud data and the target image data so as to further improve the positioning accuracy, and the relatively accurate inspection path and control instruction can be generated based on the corrected positioning result and the target map.

The invention particularly relates to an intelligent garbage classifying and sorting system based on machine vision, and relates to the technical field of intelligent garbage classification and industrial automation. A digital twin construction module; an adaptive control and optimization module; and a predictive maintenance and health management module. According to the method, vision-touch-acoustics multi-mode perception is deeply fused, so that the identification limitation of a traditional single vision sorting system is solved; after the visual identification and the tactile feature are subjected to weighted fusion, the material classification accuracy is improved, and the problems of misjudgment and missed judgment under the scenes of oil contamination, light reflection, form deformation and the like are effectively avoided.

The invention relates to the technical field of electronic manufacturing automation, in particular to an SMT equipment multi-machine cooperative control system based on the Internet of Things, which comprises a data acquisition and digital twinning module, a multi-agent reinforcement learning scheduling module, a knowledge graph diagnosis module and a central cooperative controller. The data acquisition and digital twinning module constructs a digital mirror image of a production line, a basis is provided for prediction and simulation, and the problem of data islands is solved; the multi-agent reinforcement learning scheduling module realizes self-adaptive scheduling of dynamic events of a production line based on a real-time state and a simulation environment provided by digital twinning, and solves the problem of production scheduling rigidity; the knowledge graph diagnosis module realizes deep root cause positioning of complex defects by utilizing domain knowledge and graph reasoning, and solves the problem of difficult diagnosis; and the central cooperative controller feeds a diagnosis conclusion back to the first two modules to form a complete intelligent closed loop of perception-analysis-decision-execution-learning.

The invention relates to the technical field of industrial automation, in particular to a production line exception handling method and device, computer equipment and a medium. The method comprises the following steps: in response to a production abnormal event of a production line, acquiring multi-dimensional state sensing data corresponding to the production abnormal event; according to the multi-dimensional state sensing data, constructing an exception handling decision tree corresponding to the production exception event; based on the exception processing decision tree, determining an optimal processing path for solving the production exception event; according to the method, the limitation of a traditional static mapping mechanism in coping with'same symptom and different cause 'and'multi-exception concurrence' scenes can be broken through, self-adaptive response and accurate disposal of complex exception scenes are realized, and the method is high in practicability and high in practicability. The intelligent level and response efficiency of production line exception handling are remarkably improved, and reliable guarantee is provided for stable operation of a production line.

The invention discloses a cargo self-adaptive loading and unloading system and method based on vision and machine learning, and relates to the technical field of cargo loading and unloading automation, and the method comprises the steps that an unmanned aerial vehicle receives original image information and physical characteristic attributes of to-be-loaded and unloaded cargoes, and generates an initial loading and unloading strategy; collecting air operation environment data, generating an air operation feature vector, collecting ground operation environment data, and generating a ground operation feature vector; bidirectional feature vector interaction is carried out between the unmanned aerial vehicle and the robot; based on the feature vectors after interaction, calling a transfer strategy library to jointly execute rule matching; in the execution process of the transfer strategy, the posture of the goods is monitored in real time, delivery deviation parameters are generated, and the robot obtains relative posture parameters of the goods and a receiving device of the robot in real time; and when it is monitored that the delivery has deviation within an allowable range, the robot calculates a pose compensation amount based on map data, and receives the pose through autonomous movement fine tuning.

The invention provides an efficient operation and maintenance software architecture setting method for multi-task parallel scheduling, and relates to the technical field of operation and maintenance automation. The method comprises the steps that resource state data of operation and maintenance nodes in an available area are collected in real time; dynamically calculating a comprehensive load index of each available area operation and maintenance node based on the resource state data to obtain a calculation result; according to the calculation result, identifying a high-load available area with the comprehensive load index exceeding a preset threshold value and a low-load available area with the comprehensive load index lower than the preset threshold value; and based on the high-load available area, performing priority grading on operation and maintenance tasks to be processed in the high-load available area according to task types to form a high-priority core task queue and a low-priority conventional task queue. According to the invention, accurate matching and efficient utilization of cross-regional resources are realized.

Various automated techniques are disclosed herein for monitoring and assessing real-time and future operational and health statuses of real-world assets (e.g., physical devices, components, equipment, structures, buildings, machines, infrastructure, piping systems, etc.). A monitoring system incorporates the use of intelligent Monitoring Devices for monitoring pipe systems and / or other infrastructure for leaks / issues using IoT devices and machine learning. One or more Monitoring Device(s) are attached to specific physical equipment / structure(s) to be monitored A Monitoring Device performs comprehensive field data gathering. The collected field data is used to train a customized ML model, which is stored locally in that Monitoring Device. The Monitoring Device monitors current conditions of the pipe using various sensors, and uses its locally stored customized, trained model to perform real-time, edge-based analysis of the monitored data to identify possible issues in real-time and / or to predict future maintenance / service needs without relying on continuous cloud connectivity.

The embodiment of the invention provides a special-shaped element pose estimation method fusing geometric prior and self-supervised learning and related equipment, and belongs to the technical field of computer vision and industrial automation. The method comprises the following steps: firstly, constructing an element geometric priori knowledge graph containing symmetry, boundary and key point topological information; collecting an RGB-D image, and detecting a depth failure region to generate a confidence map; rGB texture features and point cloud geometric features are extracted respectively, and adaptive fusion is carried out based on the confidence map; inputting the fusion features and geometric priori into a pose prediction network comprising a differentiable constraint module, and predicting an initial pose; training the network by adopting a two-stage strategy combining synthetic data supervised pre-training and real data self-supervised fine tuning; and finally, taking the initial pose as a starting point, fusing geometric priori to carry out iterative optimization, and outputting a refined 6D pose. According to the method, the pose estimation precision and robustness of the small-size, weak-texture and reflective special-shaped element are remarkably improved, and the dependence on labeled data is greatly reduced.

The invention provides a data bidirectional interaction method and system based on an upper computer and a test platform, and relates to the technical field of industrial automation, and the method comprises the steps: obtaining the capability description information of the test platform through the upper computer to construct a protocol adaptation rule, transmitting a test instruction with an identifier, receiving test data with a traceability sequence and state feedback, and transmitting the test data to the upper computer; the instruction sending frequency is dynamically adjusted according to state feedback, the dependency graph is constructed based on the traceability sequence, the weight is distributed, and the root cause node is determined through weight propagation and sub-graph matching, so that rapid positioning and optimization adjustment of test abnormity are realized, and the test efficiency and accuracy are improved.

The invention discloses a service platform for completing bidding document production based on automation technology assistance, and belongs to the technical field of bidding services, and the service platform specifically comprises the steps that a user behavior collection module collects operation behavior data of a user in the bidding document production process; the decision preference analysis module processes the operation behavior data through an analysis model to generate user decision preference parameters; the strategy generation module generates a candidate bidding strategy set based on historical cases; the scene simulation module constructs a bidding scene simulation environment and records market competition data in a strategy execution process; the strategy evaluation module calculates a strategy competitiveness index according to the market competition data; the strategy execution module screens an optimal bidding strategy and converts the optimal bidding strategy into a specific bidding file making scheme; through intelligent analysis of user behaviors and dynamic simulation of a bidding environment, the accuracy and competitiveness of bidding document production are effectively improved.

The invention relates to the technical field of software engineering automation of digital data processing, and discloses a game development automation method based on a multi-agent system. The method is used for solving the problem that a machine-readable cross-product dependence model and consistency verification are lacked in a traditional method. According to the method, based on a task list freezing project context, a constraint packet and a threshold aperture, and based on a demand account book and registration demands, constraints, codes, configuration, resources and other entry abstracts, version information and strong and weak reference relationships; the multiple agents only submit change packets in a temporary storage area by writing tokens and occupying fragmentation write-in gating, and an influence range report binding verification list is generated for each change packet; boundary compliance, reference integrity, compilation verification, determinacy operation verification and acceptance assertion verification are sequentially carried out on the temporary storage area snapshots, and when conflicts occur, rollback or confinement repair is triggered to output traceable and acceptance deliverables based on reproducible evidence judgment.

The invention belongs to the technical field of smart home and automation, and provides cleaning equipment and a repositioning method, device and equipment thereof, a medium and a product, and the cleaning equipment comprises a sensing unit which is configured to collect environment data of an area where the cleaning equipment is located in the process that the cleaning equipment executes a task; the positioning mapping unit is connected with the sensing unit and is configured to match the environment data with a current map, obtain a matching degree corresponding to the environment data and output a positioning abnormity message under the condition that the matching degree is lower than a preset threshold value; and the navigation unit is connected with the positioning mapping unit and is configured to execute a repositioning operation based on the current map under the condition that the positioning abnormity message is received. Therefore, the positioning stability and accuracy are improved.

The invention relates to the technical field of intelligent warehouse logistics and industrial automation, in particular to a multi-AGV path planning method based on regional impedance perception and space-time dynamic coordination, and the method comprises the steps: obtaining grid map information and task information of each AGV based on a warehouse environment; constructing a local observation window taking the AGV as a central node, analyzing nodes covered by corresponding grid map information, determining a region passing impedance index, and constructing an obstacle distance penalty term; dynamically adjusting a heuristic function weight in an A * algorithm by adopting a regional passage impedance index, establishing an evaluation function in combination with an obstacle distance penalty term, and generating a single-machine global path; based on the task information of the AGV, generating a time window for each node in the global path, and judging the path conflict of the current storage environment through the time window; and a task priority strategy is preset, path conflicts are eliminated, and a cooperative scheduling instruction is generated to regulate and control the operation path of the AGV. And self-adaptive adjustment is performed by sensing the environment congestion degree, so that the search efficiency is improved.

The invention relates to the technical field of industrial automation, in particular to an automatic inspection method and device in a complex environment, a storage medium and related equipment, data acquired by different sensors can be subjected to space-time synchronization to improve dynamic positioning precision, and when part of the sensors fail, a function can still be maintained through synchronized redundant data, so that the reliability of the system is improved. The robustness of the system is effectively enhanced, and the data processing delay can be reduced through space-time synchronization, so that the real-time control requirement of a dynamic scene is met; locally updating the newly acquired global map according to the static characteristics and the target attitude data, thereby reducing the calculation amount, improving the accuracy of navigation positioning, and adapting to a complex environment; the current positioning error is corrected according to the target point cloud data and the target image data, so that the positioning accuracy is further improved, and the inspection path and the control instruction are generated based on the corrected positioning result and the target map, so that the operation risk is effectively reduced while automatic inspection is realized.

The invention relates to the technical field of robots and automation, and discloses a dynamic environment-oriented laser SLAM (simultaneous localization and mapping) system and an efficient loopback detection method thereof, the system comprises a data preprocessing module, a probability persistence map management module, a persistence weighted front-end odometer module, a loopback detection and state reverse correction module and a rear-end pose map optimization module, static and dynamic elements in an environment are distinguished by utilizing a probability persistent map, structural conflicts in the environment are intelligently identified by comparing the similarity of a structural anchoring descriptor synthesized by high-persistent voxels with an error of geometric verification, and when the structural conflicts are identified, a system performs reverse correction on old structural information in the map; and when the geometric verification is passed, generating a loopback constraint. According to the method, transient dynamic object interference and long-term structural change of the environment can be effectively dealt with, and the robustness, loopback detection accuracy and map long-term consistency of the SLAM system in the complex dynamic environment are improved.

The invention provides a multi-variety order dynamic scheduling management method and system for a liquid crystal display module production line, and relates to the technical field of industrial automation, and the method comprises the steps: collecting the size, resolution, interface type, batch and delivery time data of all orders, obtaining the process equipment, jig configuration, material inventory state and material supply plan data of the production line at the same time, obtaining an order data set and a resource data set; based on the order data set and the resource data set, an order and resource associated data point set is constructed, a three-dimensional virtual voxel space is defined in the virtual structure, and the order and resource associated data point set is mapped to corresponding voxels one by one; and recording the number of data points of each voxel falling into the three-dimensional virtual voxel space, the corresponding order type, the resource number and the material demand matching degree information to obtain a voxel sub-region with a data attribute mark. According to the invention, dynamic optimization of the scheduling scheme is realized.

The invention provides a manipulator AWC calibration method and system based on delay compensation, and belongs to the technical field of semiconductor manufacturing equipment automation. The method comprises the steps that when the operation speed of a manipulator is low, the position of a sensor in a robot basic coordinate system is calculated; when the operation speed of the manipulator is full speed, inversely solving the radius of the wafer according to the position of the sensor in the robot basic coordinate system and the position of the manipulator when the sensor is triggered; in the process of inversely solving the radius of the wafer, constructing a delay compensation model; and delay verification is conducted on the constructed delay compensation model, when the verification result is that calibration succeeds, the high-speed control mechanical arm stretches out of the station, and the delay compensation model is adopted for deviation correction. The problem that AWC calibration precision is reduced due to signal transmission delay under the high-speed working condition is solved, and laser sensor base coordinate calibration and wafer circle center positioning errors under high-speed movement are reduced.

The invention discloses an automatic data calculation method and system based on configuration driving, relates to the technical field of automation of configuration driving, and solves the problems that although standardized data acquisition of multi-source heterogeneous equipment is realized in the prior art, data calculation modeling depends on hard coding; the same function is difficult to reuse so that the development period is long; computational logic is embedded in a program, debugging and modification are difficult, system retransmission is needed for demand change, and the maintenance cost is high; the technical problems that a large amount of manual intervention exists in a calculation link, rules cannot be dynamically adapted according to field requirements, system universality and expandability are poor, project efficiency is restricted, and multi-scene energy data analysis requirements are difficult to meet are solved. According to the method, common model measuring point configuration is set; after common model measuring point configuration information is read, a function registration mechanism is executed; carrying out callback function binding; and setting a function operation mechanism to solve the technical problem.