781 results about "Systems design" patented technology

The invention discloses an electromechanical system fault pre-diagnosis method and system based on digital twinning. The method comprises the following steps of obtaining multi-source data in an electromechanical system operation process; preprocessing the acquired multi-source data, wherein the preprocessing comprises data cleaning, normalization processing and feature extraction; and on the basis of the preprocessed multi-source data, an electromechanical system design drawing, a three-dimensional geometric model, material attributes and a kinetic equation are fused, and a digital twin model is constructed. According to the invention, through a digital twin model dynamic calibration and prediction algorithm, early abnormity of the equipment is identified in advance, the fault probability and the residual life are output, and non-planned shutdown is reduced; by constructing a cross-physical domain fault feature system and fusing model simulation and actual measurement data, the potential fault identification accuracy is improved, and the missed diagnosis rate is reduced; by calibrating parameters of the digital twin model in real time, the method adapts to nonlinear changes of equipment, ensures high-fidelity mapping of the model, and improves fault prediction precision.

The invention discloses an automatic scheduling method and system for ship unloading equipment, and relates to the technical field of port automation. According to the method, a high-precision digital twinborn model for ship unloading operation is constructed, physical equipment is abstracted into a digital intelligent agent with an autonomous decision-making capability, real-time multi-dimensional data and historical data are utilized to perform deep fusion to drive system synchronization, and a future multi-step scheduling strategy is deduced in a parallel simulation manner in a virtual space based on rolling time domain control, so that the real-time multi-dimensional data and historical data are subjected to real-time multi-dimensional data synchronization driving system synchronization is realized. Dynamic evaluation and optimization are carried out by adopting a multi-objective evolutionary algorithm combined with a cooperative game mechanism, and conflicts and cooperation among equipment are effectively coordinated by defining an individual utility function and introducing cooperative game negotiation and a meta-controller to dynamically adjust target weights, so that system-level global optimal scheduling is realized under multiple objectives of efficiency, energy consumption, safety and the like, and the scheduling efficiency is improved. The intellectualization, the self-adaptability and the comprehensive operation benefit of port ship unloading operation are comprehensively improved.

The invention relates to the technical field of injection molding process control, and discloses an injection molding parameter self-learning collaborative regulation and control system which is characterized in that multi-source parameters such as temperature and pressure are acquired in real time through a data acquisition module, and the multi-source parameters are mapped to a low-dimensional manifold space through a dynamic manifold construction module to decouple a nonlinear coupling relationship; the chaos synchronization control module suppresses external disturbance based on master-slave system design, and the distributed optimization module realizes multi-target real-time decision by adopting a split Bregman algorithm; the execution module converts the optimization instruction into a control signal and triggers closed-loop feedback; and the federated learning architecture realizes cross-device strategy migration by extracting continuous homology features of a manifold space and combining a Hausdorff distance and homeomorphic mapping, and drives a global model to update. According to the invention, the technical problems of difficult dynamic regulation and control of nonlinear parameters, insufficient real-time performance of multi-constraint optimization, low cross-scene repeated parameter adjustment efficiency and lack of self-adaptability of long-term process drift in the injection molding process are solved.

The invention provides a ground source heat pump buried pipe system design method based on building load change, comprising the following steps: S1, acquiring geological survey data, meteorological data and building load data, and presetting buried pipe heat exchange system parameters; s2, establishing a multi-physics field coupling numerical model; s3, transient simulation is carried out through a multi-physics field coupling numerical model, and system short-term thermal response characteristic data corresponding to each candidate length are acquired and stored; s4, constructing and training a long-term dynamic performance prediction model through the long and short-term memory network model; and S5, based on a multi-objective optimization algorithm, solving a multi-objective optimization problem, obtaining a group of Pareto optimal buried pipe total length solution sets, and selecting a final buried pipe optimal total length from the optimal solution sets. According to the method, the design precision of the ground source heat pump buried pipe can be remarkably improved, the long-term dynamic prediction capacity is achieved, the reliability, economical efficiency and environment friendliness of long-term operation of a ground source heat pump system can be guaranteed, and the design efficiency and reliability are improved.

This patent discloses a computer system for humanoid robot control system design and implementation, featuring a digital humanoid robot with dynamical models and a set of single-input-single-output (SISO) and multi-input-multi-output (MIMO) controllers. The system comprises a main software program, a generative Al humanoid robot intelligence engine, a robot motion path planner module, and a control system simulation engine. It enables efficient design, testing, validation, and implementation of robot control systems, significantly reducing time to market. The system supports seamless upgrades to accommodate new designs and components, enhancing applications in industrial automation, healthcare, public safety, and more, aligning with the goals of the 4th Industrial Revolution.

The invention discloses a wafer level chip system design space construction and rapid parameter search method. The method comprises the steps of task graph definition, prefabricated member parameter quantification, joint model construction based on task graph features and prefabricated member features, and Bayesian optimization implementation strategy. According to the technical scheme, construction and search of the design space can be guided, so that the number of times of calling a simulator is reduced, and construction of the design space of the wafer-level chip system architecture, efficient parameter search and performance evaluation are achieved. The method can be used for agile design and hardware implementation of a multi-chip integrated wafer-level chip system architecture.

The invention relates to a clean room airflow simulation modeling method and system fused with process layout optimization, belongs to the technical field of simulation modeling, and solves the problem that process layout and airflow cannot be optimized at the same time in existing simulation modeling. Comprising the steps of obtaining a process layout model, and constructing a label database according to a design general drawing, an architectural drawing and the process layout model; designing the purification air-conditioning system according to the process layout model and the label database, and determining design parameters; importing the process layout model and the design parameters into CFD pretreatment software to generate an initial model of the clean room, and arranging an air return passageway, a fan filter unit, a dry coil and a raised floor in the initial model according to the label database and the design parameters to obtain a fusion model; and grid division is performed on the fusion model to obtain a clean room airflow simulation model, then the clean room airflow simulation model is imported into CFD software for fluid simulation, and a process layout model of the clean room is optimized according to a fluid simulation result. And iterative optimization of the process and the airflow is realized.

The invention provides an arc resistance characteristic-based segmented modeling method of a fuse for a direct current networking system, and relates to the technical field of common direct current bus system design, and the method comprises the steps: calculating the real-time arc resistance data of the fuse according to the continuously collected short-circuit voltage and short-circuit current at the two sides of the fuse in a short-circuit test process, and forming an arc resistance curve; intercepting an arc resistance curve from the peak moment of the short-circuit current to the slope descending moment of the arc resistance curve to obtain an arc starting stage arc resistance curve, and intercepting an arc resistance curve from the slope descending moment to the moment when the short-circuit current is zero to obtain an arc burning stage arc resistance curve; respectively carrying out data fitting according to the arc starting stage arc resistance curve and the arcing stage arc resistance curve to obtain a sectional arc resistance curve equation; and taking the arc resistance curve equation as a control signal to build and obtain a fuse simulation model based on the controlled resistor. The method has the advantages that the arc resistance curve is divided into two sections, the corresponding arc resistance curve equation is designed, the simulation precision is higher, and the method can be better suitable for different working conditions.

A self-optimizing and self-programming computing system (SOSPCS) design framework that achieves both programmability and flexibility and exploits computing heterogeneity [e.g., CPUs, GPUs, and hardware accelerators (HWAs)] is provided. First, at compile time, a task pool consisting of hybrid tasks with different processing element (PE) affinities according to target applications is formed. Tasks preferred to be executed on GPUs or accelerators are detected from target applications by neural networks. Tasks suitable to run on CPUs are formed by community detection to minimize data movement overhead. Next, a distributed reinforcement learning-based approach is used at runtime to allow agents to map the tasks onto the network-on-chip-based heterogeneous PEs by learning an optimal policy based on Q values in the environment.

The invention discloses a finger-storage-multiply-accumulate three-stacked floating-point number in-memory computing system, and belongs to the field of application-specific integrated circuit design. According to the system, a three-stack type floating-point number calculation framework is designed, a pointing shift and mantissa multiply-accumulate module is designed, and floating-point number multiply-accumulate calculation of global pointing is supported. Compared with a traditional parallel floating-point multiply-accumulate circuit, the parallel floating-point multiply-accumulate circuit has the advantages that a calculation process of global alignment shifting and mantissa multiply-accumulate in sequence and a three-stack type calculation framework are adopted, similar calculation precision is achieved with smaller hardware overhead, low hardware overhead and high calculation precision are both considered, and the comprehensive performance of the calculation framework and the circuit is improved.

The invention provides a number-theory transformation acceleration method based on sparse data features, and belongs to the field of accelerator system design in privacy calculation. According to the method, the number of times of multiply-add calculation in the butterfly network is reduced by utilizing the sparsity of input data in number theory transformation, and the whole process comprises four steps of bit inversion, pre-calculation, optimization calculation execution and subsequent butterfly network calculation execution. According to the data distribution type after bit inversion in the number-theory transformation, a corresponding optimization calculation method is designed, the preceding-stage calculation data flow of the butterfly network is optimized, multi-stage calculation is combined, unnecessary calculation is avoided, the multiplication and addition times needed in the number-theory transformation are greatly reduced, calculation delay is reduced, and the overall energy efficiency of privacy reasoning is improved; wide application prospects are realized.

The invention discloses a dynamic adhesion coefficient correction evaluation method and system based on multi-source data fusion, and belongs to the field of vehicle electronic control, and the method comprises the following steps: S1, carrying out the data collection of a multi-source sensor; s2, calculating a slip rate based on data collected by a wheel speed sensor, calculating a dynamic compensation factor based on data collected by a suspension load sensor, correcting a centroid offset error based on data collected by an inertial sensor, and triggering segmented compensation based on data collected by a brake disc temperature sensor; s3, calculating a basic adhesion coefficient based on the slip rate; s4, correcting the basic adhesion coefficient based on the dynamic compensation factor and the corrected centroid offset; and S5, the basic braking force and the basic torque distributed by the ESC system are corrected. By adopting the dynamic adhesion coefficient correction evaluation method and system based on multi-source data fusion, high-precision correction of the dynamic adhesion coefficient and intelligent adjustment of the braking force are realized through multi-source sensor data fusion and ESC system integrated design.

The invention provides a bidirectional level converter and electronic equipment, and relates to the technical field of analog integrated circuits, the bidirectional level converter comprises a first port, a second port and a conversion circuit arranged between the first port and the second port; the first port comprises a first input / output port and a first reference level port; the second port comprises a second input / output port and a second reference level port; the conversion circuit comprises a first Schmidt comparator, a clamping circuit, a pull-up module, a pull-down module and a second Schmidt compartment.The bidirectional level converter and the electronic equipment have the advantages that under the condition that an input signal is converted from a high signal to a low signal, driving of an input stage does not need extremely high driving capacity, input and output are in an isolated state, and the conversion efficiency is improved; and the load size of the output stage has no influence on the driving capability of the input stage, so that the integrity of signals can be maintained, the system design is more flexible, and meanwhile, the circuit can adapt to more application scenes.

The invention relates to the technical field of distributed computing, and discloses a distributed computing modeling system design method for high-dimensional discrete data, which comprises the following steps: acquiring a feature identifier access request in a high-dimensional discrete data stream, counting an access frequency, and marking a feature identifier of high-frequency access as a high-frequency access state; constructing a local parameter copy on a non-master node physical computing unit of the distributed cluster; routing gradient update data aiming at the feature identifier to a local parameter copy closest to the network and generating a local residual tensor; calculating the direction cosine similarity of the local residual tensor and the global gradient update vector; calculating a real-time access entropy based on the access source distribution and converting the real-time access entropy into a dynamic synchronous threshold value; according to the method, through a dynamic synchronization judgment mechanism based on semantic information gain, high-frequency but invalid redundant communication is effectively inhibited, and network congestion under long-tail distribution is reduced.

The invention provides a ship management system design assisting method based on a knowledge graph, which comprises the following steps of: processing scattered design documents and design criteria of enterprises by utilizing a natural language processing technology, extracting knowledge triple information in the design documents and design criteria, and on the basis of the constructed knowledge graph, further utilizing a retrieval enhancement generation (RAG) technology to generate a knowledge triple; according to the method, subjective query of design information of a graph database is achieved, analysis and proofreading of design information graph-text and document data corresponding to design drawings and models are achieved, and finally design requirement query and automatic check of the design drawings and models in the design process of aided designers are achieved. Integration and sharing of design knowledge are completed, and the design knowledge utilization rate is increased.

The invention discloses a construction project contract dispute judgment document classification system based on natural language processing, and relates to the crossing field of project management and natural language processing. The system comprises a document receiving module used for supporting dragging, dropping and reading of judgment documents; the text preprocessing module is used for preprocessing documents and screening phrases with dispute focus key information; the dispute type classification module is used for inputting and transmitting the text into a BERT-BiLSTM-Attention classification model to obtain the dispute type of the text; the dispute focus classification module is used for transmitting the text input into a RoBERTa-TextCNN-GLU classification model to obtain a corresponding dispute focus; and the system function module is used for displaying the text content and the classification result after inputting the judgment document to obtain a dispute type and a dispute focus corresponding to the document. The purpose of system design is to realize rapid information extraction of construction project contract dispute judgment documents, so that related enterprises can rapidly understand basic conditions of the judgment documents, and the enterprises can also be helped to establish a high-quality and sound project contract risk control system.

The invention provides an undercarriage system scheme design method based on heterogeneous design simulation data management, which comprises the following steps of: firstly, analyzing, abstracting and standardizing different types of heterogeneous design and simulation data in a development process of an undercarriage system, and constructing a uniform abstract data model; secondly, according to the defined semantic rules, an undercarriage semantic ontology model is constructed, then the semantic rules are loaded through a semantic reasoning engine, and processed data are associated; according to the research and development process of the undercarriage system and the semantic association relationship between the data, data storage and display are realized; after data abstract analysis, semantic association and unified storage are completed, functional information, design information and simulation information are further derived based on an undercarriage semantic ontology and a reasoning result, so that an undercarriage system development scheme driven by requirements is constructed. According to the method, multi-source heterogeneous design and simulation data generated in the research and development process of the undercarriage system can be effectively managed, and a design scheme of the undercarriage system is constructed on the basis of the multi-source heterogeneous design and simulation data.

The invention discloses an intelligent troubleshooting method, device and equipment for vehicle function faults and a storage medium, and relates to the cross technical field of natural language processing and vehicle fault troubleshooting, and the method comprises the following steps: retrieving a knowledge base according to fault description to obtain technical data associated with the fault description, the knowledge base is constructed based on a vehicle function system design document; based on the technical data and in combination with a big language model, generating a fault reason and a fault checking strategy which corresponds to the fault reason and is used for indicating a signal needing to be detected and detection logic; and analyzing the vehicle-mounted protocol and the vehicle-mounted data to obtain a signal of a corresponding fault moment, sequentially detecting related signals according to the troubleshooting strategy, determining a fault signal, and realizing vehicle function troubleshooting. According to the invention, the efficiency and the accuracy of vehicle function troubleshooting can be effectively improved.

The invention discloses an intelligent tea withering control system based on multi-modal feature fusion and time sequence prediction. The system is composed of a multi-modal feature extraction module, a time sequence modeling module, a transfer learning module and an intelligent decision control module, a Transform attention mechanism is adopted to construct a cross-modal fusion framework, RGB images, hyperspectrum and time sequence information are fused, and accurate recognition and trend prediction of the withering state are achieved. According to the system, an adaptive attention fusion network is designed, optimal fusion of images, spectrums and grade information is realized through dynamic distribution of modal weights, and the recognition accuracy and stability are remarkably improved. The classification accuracy of 180 verification samples reaches 93.33%, and is improved by 15.93%-34.83% compared with that of a single-mode method. And cross-environment self-adaption is realized through fusion transfer learning, and the performance is improved by 6.7%-14.3%. The intelligent decision engine optimizes temperature and humidity parameters based on a multivariable coupling control theory, the control precision reaches + / -0.5 DEG C and + / -2.0%, and the response time is 2.5 seconds.

The invention provides an automatic construction method and equipment for a building electromechanical system circuit, and the method achieves the quick construction of a building electromechanical system and the efficient retrieval of key paths of equipment through abstracting the equipment attributes and the connection relation into a directed graph and automatically generating the connection relation between the equipment through a link prediction graph neural network model. The method can be used for automatically generating the mutual connection relation between the devices according to given device attributes, so that rapid construction of a building electromechanical system and efficient retrieval of key paths of the devices are achieved, and basic data are provided for the functions of device fault positioning, abnormal energy consumption analysis and the like in the building operation and maintenance stage. According to the method, the efficiency and accuracy of electromechanical system design are improved, reliable basic data support is provided for the functions of equipment fault positioning, abnormal energy consumption analysis and the like in the building operation and maintenance stage, meanwhile, a data link of electromechanical system design, construction and operation and maintenance is broken through, and technical support is provided for digital and intelligent transformation of the building industry.

The invention discloses an assembly process knowledge graph construction and updating method based on graph attention network mapping, and the method mainly comprises the following steps: standardization system design construction, data collection, data classification, multi-modal data preprocessing, multi-source information extraction and graph node feature initialization. Semantic modeling and vector space mapping driven by a graph attention network, knowledge storage, construction of an assembly process knowledge graph by using stored knowledge data, and semantic complementation and dynamic updating of a process information model. Through the unique self-attention mechanism of the GAT, the weight can be dynamically distributed for the relationship among different information nodes, so that knowledge reasoning and expression are more accurately carried out, and the problems of knowledge fragmentation, management rigidity, semantic understanding deficiency, low knowledge utilization efficiency and the like in the prior art are systematically solved.

The invention discloses a protocol conversion method and device, a medium and a server system, and relates to the technical field of servers. Once an original protocol type is determined, a dynamic interface routing controller calls a corresponding conversion program stored in a mapping table; and converting the detected heterogeneous bus protocol command into a unified single-line serial bus protocol operation code. As the conversion program and the protocol characteristics are stored in the mapping table, the method has infinite protocol expansion capability, a new protocol can be supported by updating the mapping table and a detection engine without redesigning hardware or modifying codes of an editable logic device, the system design is greatly simplified, and the development cost is reduced. Therefore, the problem that the current programmable logic device can only realize single interface protocol conversion is solved.

The invention discloses a micro-seismic monitoring system based on distributed optical fiber sound wave sensing, and belongs to the technical field of seismic monitoring. The application potential and advantages of the DAS in seismology are applied to the design of the system. The process of processing the DAS signal by using the seismological method comprises the steps of firstly collecting the DAS signal by using equipment, then obtaining the DAS signal through detection and carrying out preprocessing mean removal and normalization, then carrying out picking operation on a waveform signal, carrying out event positioning after obtaining the picked signal, and finally carrying out magnitude fitting. The process of the system design comprises the following steps: in combination with a system design method, performing demand analysis on functions to be realized by the system, performing function definition, selecting a proper system architecture design according to demands and functions, performing technical model selection on the whole system and the like. And finally, a DAS method is combined with system design, and a micro-seismic monitoring system using the DAS is realized.

The invention relates to an electric control system test board for engineering equipment, which comprises a test box, a comprehensive controller, an operation control box, a closed pump control box and a computer, the test box is connected with a tested electric control system through a test cable, and the electric control system is tested by pulling a toggle switch on a panel of the test box or rotating a single-circle carbon film potentiometer. An analog switching value or an analog quantity electric signal is transmitted to a tested electric control system and processed by an electric control system controller to control a corresponding system state indicating lamp on the test box to be lighted so as to test the correctness, stability and safety of the function of the electric control system, and the system can be operated by a single person, is simple and convenient to operate, is high in test response speed, and is visual and clear in test result. Powerful support is provided for early-stage performance analysis, system design, test verification and production delivery of the electric control system of the engineering equipment, so that the production quality of the engineering equipment is continuously improved, the time, manpower and material cost is reduced, and the development and production cycle is shortened.

The invention provides a deep evidence fusion-based target detection and tracking method for an intelligent maritime investigation instrument, and belongs to the technical field of multi-modal sensor fusion. The method comprises the following steps: performing feature extraction on data of each modal by using a deep learning model, generating a corresponding evidence quality function, then correcting the weight of a sensor through context discount, and finally performing evidence fusion through a Dempster-Shafer rule to generate a global decision result. Another technical innovation point is that the system designs a mechanism for dynamically adjusting the weight of the sensor, and the fusion process is dynamically optimized according to a real-time environment and historical data so as to ensure the self-adaptability of the system in different environments. According to the invention, through combination of a real-time weight adjustment mechanism and a multi-modal fusion algorithm, the precision of sea target detection is improved, sudden environmental changes can be dealt with, and the robustness and high efficiency of the system in long-time operation are ensured.

The invention provides an energy guarantee test system design method and system and a medium, and belongs to the technical field of energy guarantee test systems.The method comprises the steps that design parameters of an energy guarantee test system are determined according to basic elements of the energy guarantee test system, and the energy transmission efficiency of the energy guarantee test system serves as a target function; the design parameters are optimized through an improved litsea rotundifolia optimization algorithm, and the design parameters with the optimal fitness value are obtained; wherein a tuna swarm optimization algorithm and a mirage algorithm are introduced into an exploration stage and a development stage of the improved litsea rotundifolia optimization algorithm, and a position updating mode is improved; and determining an energy guarantee test system design scheme according to the optimal design parameters. According to the method, the optimal energy guarantee test system design scheme can be quickly generated, and the optimal transmission efficiency of the system can be achieved through the design scheme.

The invention provides an event-based flight simulator simulation method and system, a terminal and a medium, and relates to the technical field of flight simulators, the method comprises the following steps: setting components of a flight simulator, and setting public attributes and equipment attributes; describing a simulation object file; configuring an initial scene; configuring a development environment; configuring and developing a visual plug-in; configuring a virtual instrument, and defining input and output of the virtual instrument; compiling a logic processing plug-in, and executing a logic processing process based on the logic processing plug-in; the logic processing plug-in is used for setting pointers and parameters so as to process events sent by the event processor and access attributes. The design level and development efficiency of the system are improved, the reusability of the system is enhanced, the stability of the system is improved, and the user experience is also improved.

The invention belongs to the technical field of airborne radar phased-array antenna wave control system design, and particularly relates to an airborne radar phased-array antenna wave control system multi-node software online upgrading method, which comprises the following steps of: 1, synthesizing upgrading files of software needing to be upgraded into a total upgrading file; step 2, extracting a total upgrading file from the software configuration library, sending the total upgrading file to a main node of a system to be upgraded by an upper computer, and performing file verification; step 3, extracting frame header information of the total upgrade file by the master node of the system to be upgraded, comparing the information of each upgrade file with the information of each slave node software collected in real time, and judging whether to upgrade each slave node software; 4, the master node of the to-be-upgraded system disassembles the upgrade file needing software upgrade according to the upgrade file information in the total upgrade file frame header, and issues the upgrade file to the corresponding slave node; and step 5, upgrading the software by the slave nodes needing to be subjected to software upgrading according to the upgrading file.

The invention belongs to the technical field of aviation airborne system design, and provides a helicopter airborne system-oriented novel software architecture and a construction method thereof, and the architecture comprises a hardware abstraction layer, a framework resource layer, an intelligent platform service layer and an application software layer from bottom to top. And the hardware abstraction layer realizes decoupling of hardware and basic software of an operating system. The framework resource layer supports operation of a hybrid key operating system, supports and isolates tasks and application programs with different key levels, software bases and computing power requirements, and provides basic computing communication resources and AI computing power resources. The intelligent platform service layer comprises middleware, a servitization function unit and a servitization management unit, and the servitization function unit comprises atomic services and enhanced services. And the application layer interacts with the intelligent platform service layer and is decoupled from a bottom software and hardware environment. The framework is suitable for unmanned / manned helicopters, and generalization of platform support and maximum reuse of software assets are achieved.

The invention relates to a different intelligence traffic subject interaction information model construction method based on a three-dimensional digital model. The method comprises the following steps: S1, constructing a multi-level scene based on spatial levels of a road traffic system and designing functions of the multi-level scene; s2, defining autonomous levels of the traffic system, and describing the perception capability, decision logic and execution precision of each terminal device of the vehicle road cloud of each level; s3, according to different attributes of traffic entities, designing a perception-transmission-decision-control four-stage traffic information circulation process and realizing unambiguous collaboration among different intelligence subjects; and S4, converting the standardized and defined information model into a plurality of instantiation units, and deploying the instantiation units into computing entities of various end-edge-cloud traffic subjects to support actual operation of a traffic service scene. According to the method, the problems of difficult cross-domain collaboration, non-uniform information models and insufficient global optimization caused by non-uniform intelligent level of traffic subjects in the prior art are effectively solved, and methodological support is provided for design, verification and implementation of a vehicle-road cloud integrated system.