1310results about How to "Flexible configuration" patented technology

The invention relates to a real-time fault detection and automatic repair system for a power grid. The real-time fault detection and automatic repair system comprises a multi-level sensing module, a data processing module, an automatic repair module and a monitoring and logging module. The multi-level sensing module collects data such as voltage, current, frequency and temperature in operation of a power grid by deploying multiple types of sensors, and sends the data to the data processing module. And the data processing module analyzes the collected data through an embedded intelligent algorithm, identifies potential faults and generates fault diagnosis results. And the automatic repair module executes repair operations of isolating a fault area, reconstructing a power grid topological structure and recovering normal power supply according to a fault diagnosis result. The monitoring and log module records the operation state of the power grid and the fault diagnosis and repair process, and provides fault analysis and performance evaluation functions through a user interface. According to the system, real-time detection, accurate positioning and automatic repair of power grid faults and comprehensive monitoring of operation data are realized, and the safety and reliability of power grid operation are remarkably improved.

The invention relates to the field of low-altitude economy, in particular to a server communication optimization method and system based on low-altitude economy. The method comprises the following steps: monitoring an unmanned aerial vehicle communication relay node in a low-altitude field; carrying out node space position positioning calculation on the unmanned aerial vehicle communication relay nodes one by one, carrying out distributed relay topology fitting, and constructing a low-altitude relay communication network; collecting low-altitude real-time interaction information based on a low-altitude relay communication network; performing communication link bandwidth calculation on the low-altitude real-time interaction information, performing dynamic communication protocol modulation, and constructing a dynamic low-altitude adaptive communication protocol; identifying real-time communication state parameters of the relay nodes based on the low-altitude relay communication network; performing inter-node communication channel identification on the real-time communication state parameters of the relay nodes, performing optimal channel scheduling decision, and constructing an optimal channel scheduling strategy; current user communication data of the ground server is monitored. According to the invention, low-delay and high-efficiency server communication optimization is realized.

The invention discloses a large language model reasoning optimization method and device, electronic equipment and a storage medium, which are used for solving the problem of how to reduce huge resources needed during large model reasoning due to the fact that model reasoning has a large demand on calculation and storage resources due to huge parameter quantity in the prior art. The method comprises the following steps: acquiring configuration parameter data and computing resource data of a large language model during model reasoning in real time; performing static optimization analysis on the configuration parameter data, and outputting a configuration analysis result; performing automatic configuration parameter tuning based on reinforcement learning in combination with the configuration parameter data and the configuration analysis result to obtain optimal parameter configuration; performing dynamic optimization processing on the computing resource data based on an unloading strategy to obtain optimal resource configuration; and according to the optimal parameter configuration and the optimal resource configuration, dynamically optimizing parameter configuration and resource allocation of the large language model during model reasoning.

The invention discloses a remote Internet of Things control management system and method based on fire fighting, and belongs to the technical field of Internet of Things. The system comprises an image recognition module which obtains a video stream of a fire scene through a monitoring camera, and carries out the real-time analysis and recognition of an image through image processing and a deep convolutional neural network; the gas recognition module is used for monitoring the gas concentration of a fire scene in real time and recognizing gas components by using a gas recognition algorithm; the data fusion analysis module is used for carrying out feature fusion on the data acquired by the image recognition module and the gas recognition module, and carrying out analysis and modeling on the fused data; the decision support module is used for performing fire risk assessment according to an analysis result of the data fusion analysis module; based on historical data and the scene model, performing simulation and prediction of a fire development trend; and the remote internet-of-things control module is used for providing data for checking fire scene conditions in real time, so that a user can remotely control all equipment and devices of the fire extinguishing system.

The invention discloses a high-precision three-degree-of-freedom attitude adjustment platform for a spectrometer, which is based on a simplified design of a Stewart platform and comprises a movable platform, a static platform and a three-degree-of-freedom driving mechanism connected between the movable platform and the static platform. The driving mechanism is composed of three sets of servo electric cylinders, telescopic rods and servo motors and is driven by a ball screw, and posture adjustment of the platform is achieved. According to the platform, a laser interferometer is adopted as a high-precision sensor, a closed-loop feedback control system is combined, and submicron displacement measurement and attitude control are achieved. The platform can achieve translation in the Z-axis direction and rotation around the X axis and the Y axis, the rotation angle can reach + / -15 degrees, and the precision can reach 0.02 mm. According to the invention, the device ensures high precision and stability in a complex working environment, has the characteristics of stable movement, quick response, easy maintenance and the like, and is suitable for the fields of optical experiments, spectral analysis and attitude adjustment and error compensation of precise instruments.

The invention belongs to the technical field of energy storage, and particularly relates to a vertical circulation type gravity energy storage system based on a linear motor, the vertical circulation type gravity energy storage system comprises a circulation shaft, a carrying platform system and an energy storage system, the circulation shaft comprises a heavy object shaft, a no-load shaft and a horizontal channel, and a secondary switching disc is arranged at the joint of the heavy object shaft and the horizontal channel and the joint of the no-load shaft and the horizontal channel; the heavy well, the no-load well, the horizontal channel and the secondary switching disc are each provided with a secondary driving side, and each secondary driving side comprises a first rail set and a linear motor secondary; the platform deck system comprises a plurality of platform decks, the platform decks are used for bearing heavy objects, primary switching discs are arranged on the side faces of the platform decks, primary driving sides are arranged on the platform decks and the primary switching discs, and each primary driving side comprises a second track set and a linear motor primary; the energy storage system includes an upper storage bin, a lower storage bin, and a loading and unloading zone. The energy storage capacity expansion mode is simple, the expansion cost is low, the energy storage capacity configuration is flexible, and the energy storage efficiency is high.

The invention discloses a computing power aware routing distribution method and system based on SRV6, and the method comprises the steps: constructing a network topology undirected graph based on a target distributed cluster; in response to the service request, obtaining real-time resource state data of each node in the target distributed cluster, and analyzing the service request to obtain resource request data; matching each node in the network topology undirected graph with the resource request data to obtain a target node; calculating an optimal path from the source node to the target node in the network topology undirected graph by using an improved Di jkstra algorithm; and according to the optimal path, configuring a corresponding routing rule in the target distributed cluster through an SRV6 network programming technology. According to the method provided by the invention, the problem of insufficient computing power resource routing distribution flexibility is solved.

The invention relates to the technical field of big data and data security, in particular to a cloud-edge collaboration and AI fusion data classification and grading method and system and a storage medium, cloud computing and edge computing are combined, the AI technology is used for data classification and grading, and rapid processing and efficient analysis of data are achieved; for structured data and unstructured data, different recognition and processing methods are adopted, including regular expression, keyword matching, dictionary matching, neural network, natural language processing and other algorithm models; particularly, a neural network and a natural language processing technology are combined with an unsupervised learning method and a semi-supervised learning method to realize an automatic classification and grading method of unstructured data in stages, rapid data processing and response can be carried out on an edge layer through a cloud edge collaboration mechanism, and the efficiency is improved. And deep analysis and model training are carried out by using the powerful computing power of the cloud layer.

The invention provides an alarm method of a register chip, a storage medium and an electronic device. According to the alarm method of the register chip, each bit of the register chip corresponds to one kind of alarm information, a to-be-detected target bit can be determined according to to-be-detected information corresponding to the current register chip; therefore, the alarm operation can be executed according to the alarm information corresponding to the target bit under the condition that the target bit is detected to be abnormal. Therefore, the alarm information of the register chip can be flexibly configured through the target bit, all possible conditions can be covered as much as possible, the problem of flexibly configuring the alarm information of the register chip can be solved, the effect of improving the detection accuracy and flexibility of the register chip is achieved, the chip fault detection rate is increased, and the detection efficiency is improved. And the operation stability and accuracy are ensured.

The invention discloses a transformer intelligent temperature monitoring device based on a monitoring technology, which relates to the technical field of transformer intelligent temperature monitoring and comprises a temperature sensing module, a data processing module, a fault diagnosis module, a data transmission module and a remote monitoring module. And the temperature sensing module is used for acquiring temperature information of each key part of the transformer in real time. According to the invention, high-precision temperature monitoring is realized through the fiber grating sensor, the anti-interference capability is enhanced, and accurate fault diagnosis is realized through the GRU neural network and the fuzzy logic algorithm. And a dual-channel redundancy communication mechanism is adopted to ensure the stability and safety of data transmission. A Web-based remote monitoring platform improves the operation convenience, and a multi-level alarm function ensures safe operation. The system integration module realizes seamless connection with the existing power monitoring platform, has high adaptability and expansibility, reduces the deployment cost, and improves the equipment management efficiency.

The invention provides a motor stator vibration suppression method and system based on an electromagnetic pad and deep learning, and relates to the field of electrical technology, and the method comprises the steps: collecting a vibration signal of a motor stator, and carrying out the preprocessing of the vibration signal; inputting the preprocessed signal into a deep learning model, and training and optimizing the deep learning model; fusing the features through a full connection layer to obtain a comprehensive feature vector; predicting the future vibration state of the motor stator by using the comprehensive feature vector; establishing an electromagnetic force model, and designing an adaptive control law based on the predicted future vibration state and the electromagnetic force model; electromagnetic force required by vibration suppression is calculated by using a self-adaptive control law and is converted into a control signal to adjust the electromagnetic pad; a multi-objective optimization algorithm is used to consider the vibration suppression effect and energy consumption at the same time, an adaptive control law is adjusted, and closed-loop feedback control is formed to continuously optimize the vibration suppression effect.

The invention discloses an LED backlight driving system. The LED backlight driving system comprises a backlight time sequence controller, at least one first LED lamp panel and at least one second LED lamp panel. The first LED lamp panel and the second LED lamp panel are each provided with a plurality of driving links, the backlight time sequence controller sends a backlight brightness driving instruction to each driving link, and the backlight brightness driving instruction further comprises a first position relation instruction or a second position relation instruction; the first position relation instruction controls the driving chip to obtain a backlight brightness data packet according to a first position corresponding relation; the second position relation instruction controls the driving chip to obtain the backlight brightness data packet according to the second position corresponding relation. According to the invention, the problem that the driving sequences of the driving chips on the lamp panels are inconsistent due to the physical position relationship between the lamp panels and the backlight time schedule controller in the practical application of multiple lamp panels is solved. Therefore, backlight sequential control and the LED lamp panel can be configured on the LED backlight panel more flexibly, and the wiring area is greatly saved.

The invention relates to a modularized segmented linkage flexible mechanical arm and a rope cluster segmented decoupling driving method. The modularized segmented linkage flexible mechanical arm comprises a driving box. The base connecting rod assembly is used for guiding a plurality of driving ropes led out from the driving box, and the base connecting rod assembly is arranged above the driving box; the arm section group comprises modular arm sections and an inter-arm-section connecting rod which are connected in sequence, and the bottom of the first modular arm section 3000 is connected with the top of the base connecting rod assembly. According to the modular segmented linkage flexible mechanical arm, the design of'rigid connecting rods, rotary joints and linkage modules' is adopted, it is ensured that when a rear-end arm section drives a rope to pass through a front-end arm section, the path length of the rear-end arm section does not change along with the joint angle of the front-end arm section, and therefore segmented driving decoupling of a rope cluster is achieved.

The invention relates to the technical field of power grid side large-scale wind and light and energy storage configuration, in particular to a wind and light storage capacity distribution robust optimization configuration method, device and equipment and a medium. Establishing a power grid side wind and light energy storage optimization configuration model considering inertia constraint; uncertain factors in the optimal configuration model are considered, and a probability distribution fuzzy set based on a mixed norm is constructed; establishing a two-stage distribution robust optimization configuration model based on data driving; converting the two-stage distribution robust optimization configuration model into a mixed integer linear programming model by using a linearization technology; and solving the mixed integer linear programming model by using a column and number generation algorithm to obtain an optimal configuration and operation scheme of each device. According to the method, the economical efficiency and load fluctuation can be balanced, and the problems of frequency instability and the like of a large-scale wind and light energy grid-connected power grid are avoided by considering inertia constraint.

The invention discloses a non-contact monitoring method for the axial force of an end anchoring anchor rod, and relates to the technical field of anchor rod axial force measurement. The monitoring method comprises the steps that firstly, relevant parameters of surrounding rock, relevant parameters of an anchor rod in the anchoring process and relevant parameters of an anchoring agent are obtained; acquiring strain data of an anchor rod tray in the anchoring system by adopting a full-field strain measurement system, transmitting the strain data to a data processing module of the full-field strain measurement system, and acquiring anchor supporting force by virtue of a stress-strain relationship of the anchor rod tray; finally, a calculation analysis formula of the mechanical relation between the anchor supporting force Ft generated by the anchor rod tray and the anchor rod axial force F is constructed in a computer; and inputting the values of the related parameters obtained in the step 1 and the step 2 into a calculation analysis formula, and calculating to obtain the axial force of the end anchoring anchor rod. By means of the method, non-contact measurement of the anchor supporting force of the anchor rod can be achieved, and the integrity of an anchoring system is further protected.

The invention relates to a simulation test platform for a 1553B bus of a spacecraft, which is suitable for stand-alone test and system test of a 1553B bus interface of a satellite model, and comprises an application layer, a communication layer and a data interface connected with the application layer and the communication layer, the application layer comprises a main control module, a database module and a user interaction module; the communication layer comprises a non-periodic data communication module and a periodic data communication module. The method can be suitable for ground tests of multiple satellite models at the same time, the research and development cost is saved, great convenience is brought to the satellite ground tests, and therefore the development progress of the satellite models is effectively guaranteed.

The embodiment of the invention discloses an agent arrangement method and device, a storage medium and terminal equipment, and relates to the field of agent editing. According to the method, the intelligent agent nodes with the same function are merged into the fused intelligent agent nodes, so that the complexity of the intelligent agent flow chart is remarkably simplified. The flow chart is clearer and easier to understand, unnecessary nodes and connecting lines are reduced, and the readability and maintainability of the flow are improved. Due to the fact that the agent nodes are combined, the user does not need to process too many details when editing and managing the agent process, the operation complexity can be reduced, and the user can complete design and adjustment of the process more quickly and more accurately. Occupancy of system resources can also be reduced by combining the agent nodes. And during operation, the fusion agent node can be processed as a whole, so that the calculation overhead and the memory occupation are reduced, and the overall performance of the system is improved.

The invention relates to the technical field of projection display, in particular to a display method, display equipment, a storage medium and a vehicle. The projection area formed by the HUD display device is divided into the block display area and the extended display area, the block display area supports on-demand display of different functions in different blocks, and the extended display area can synchronously display different auxiliary contents according to the state of the block display area viewed by a user. And linkage between the block display area and the extended display area is realized. The information distribution of the projection area is flexibly configured, the auxiliary content of conventional display is expanded, and the watching experience of a user is greatly improved.

The invention provides a dangerous rock mass crack monitoring system and method based on the Zigbee technology, and belongs to the technical field of geological disaster monitoring, and the system comprises a plurality of terminal nodes, at least one coordinator node, an edge computing device and a remote monitoring center. The plurality of terminal nodes comprise a crack data acquisition module for acquiring crack data of crack widths, depths and change rates of a plurality of monitoring points of the dangerous rock mass in real time; the Zigbee wireless communication module is used for wireless transmission; the self-adaptive control module is used for adjusting the data acquisition frequency and the transmission interval according to the crack change rate of the monitoring point; the coordinator node is used for receiving crack data of a plurality of monitoring points; the edge computing device is used for analyzing a danger signal in the crack data by adopting the trained machine learning model and generating a real-time early warning signal; and the remote monitoring center is used for receiving, displaying and storing the analysis result and the early warning signal. According to the method, low-power-consumption and long-distance dangerous rock mass crack monitoring can be achieved, and long-term and stable operation is achieved.

The invention belongs to the technical field of power electronic degaussing, and particularly relates to a high-power pulse degaussing power supply circuit and system. The circuit comprises an energy storage unit, a transformer, an AC / DC converter, a four-quadrant DC / DC converter and a DC / DC converter. The direct current side of the AC / DC converter is connected with one end of the four-quadrant DC / DC converter, and the other end of the four-quadrant DC / DC converter is used for being connected with an inductive load; and the energy storage unit is connected in parallel between the direct current side of the AC / DC converter and the four-quadrant DC / DC converter through the DC / DC converter, so that the reliability of the degaussing power supply is improved, and the device size and the equipment cost are reduced.

The invention discloses an H-bridge series-parallel active support type SVG system and a control method, and relates to the technical field of active support type SVGs, the H-bridge series-parallel active support type SVG system is formed by three-phase star connection of a chain structure, each phase is formed by connecting an H-bridge power module and a super capacitor power module in series, the H-bridge power module and the super capacitor power module are both controlled by the power control module; the H-bridge power module is used for providing reactive power support for the static var generator system and maintaining the stability of the voltage of the power grid by adjusting the reactive power injected into the power grid; and the super capacitor power module is used for providing active support for the static var generator system so as to realize frequency active support of the static var generator system to a power grid. According to the invention, the configuration scheme of the active support type SVG super capacitor is simplified, the overall configuration is more flexible, and the expandability is stronger.

The invention discloses a distributed intelligent drip irrigation control system based on the Internet of Things, and belongs to the technical field of agricultural irrigation. The distributed intelligent drip irrigation control system comprises a basic water conservancy facility used for providing a water supply demand of certain water pressure for a drip irrigation system; the water tower is designed as a constant-pressure water source to ensure the water pressure uniformity of the whole irrigation area; the water and fertilizer mixing box is used for mixing fertilizer and water in proportion to form a water and fertilizer solution suitable for being absorbed by crops, the mixing proportion is determined by an algorithm # imgabs0 #, F is the fertilizer concentration, Nreq is the nutrient amount needed by the crops, and Nsoil is the current nutrient amount in soil. According to the invention, through efficient and accurate water and fertilizer resource management, the problems of unreasonable resource allocation, low utilization efficiency and the like in a traditional irrigation method are solved, and through integration of an advanced sensor technology, a wireless communication module and an intelligent control algorithm, accurate regulation and control of farmland water and fertilizer supply can be realized; and an irrigation strategy can be automatically adjusted according to real-time environment data and crop growth conditions.

The present invention relates to the field of real-time data processing technology, specifically a distributed real-time data stream processing system and method, the system includes a state mapping modeling module, a load dynamic calculation module, a node task adjustment module, and a resource scheduling execution module. In the present invention, by analyzing the data flow change sequence, identifying the frequency and trend of state switching, realizing dynamic identification and classification of flow states, improving the monitoring and understanding capabilities of real-time data, accurately quantifying node resource pressure in resource occupancy and load range analysis, enhancing the predictability of load balancing, providing a scientific basis for resource scheduling, combining task priority sorting and dynamic task adjustment, optimizing node computing resource utilization and task processing response speed, realizing flexible configuration of memory and computing resources, alleviating peak load pressure, improving data processing efficiency and system stability, and improving the system's adaptability and reliability in processing large-scale data flows.

The invention discloses a pavement compaction degree real-time monitoring system and method based on a high-precision vibration acceleration sensor, a signal processing algorithm and intelligent data analysis, and is suitable for vibratory roller operation. According to the system, fine vibration characteristics in the construction process are captured through the three-axis acceleration sensor installed on the vibration wheel, and the analysis precision of mechanical behaviors in the compaction process is improved by combining the viscoelastic-plastic performance, described by the three-degree-of-freedom two-dimensional viscoelastic-plastic block model, of the asphalt mixture. A compaction degree prediction model is constructed by adopting machine learning, a vibration signal is analyzed in real time, a compaction degree estimation value is output, a result is displayed through a user interface, and an optimization suggestion is provided according to a compaction effect. The system has an early warning function, gives an alarm when the compaction degree does not reach the standard, and guides constructors to adjust strategies in time, so that the road construction quality control level is effectively improved.

The invention discloses a vulnerability load classification method and system based on codes and semantic features, and belongs to the technical field of intrusion detection. The method comprises the following steps: encoding a vulnerability load, masking an encoding result, and obtaining a first representation of the vulnerability load through predicting a mask value; acquiring a second representation of the vulnerability load based on a TF-IDF encoder; synthesizing the first representation and the second representation to obtain a comprehensive representation of the vulnerability load; and classifying the comprehensive representation to obtain a classification result of the vulnerability load. According to the method and the device, the vulnerability detection accuracy is improved by enhancing the characterization capability of the vulnerability load.

The present invention discloses a modular joint of a collaborative robot with a compact structure, which is connected in sequence: a joint housing; a joint output flange; a low-speed wire protection tube connected to the joint output flange; a harmonic reducer connected to the joint output flange and the joint housing; a motor assembly, including a stator and a rotor; a motor shaft connected to the motor rotor, one end of which is connected to the input end of the harmonic reducer; a brake assembly, which is a magnetic friction type, locks when the power is off, and opens when the power is on, and is connected to the motor shaft. Compared with the latch-type brake, it is safer to stop in an emergency and will not bend the stop pin; a motor-end encoder assembly; and a joint-end encoder assembly. The encoder code disc at the motor end of the present invention is concentrically arranged with the encoder code disc at the joint end, and the encoder reading head at the motor end is integrated with the encoder reading head at the joint end, so that the axial space of the joint is compact, the integration is high, and the wiring space is large for easy operation. At the same time, the modular joint of the present invention also has the characteristics of high rigidity and large load-to-weight ratio.

The invention provides a multi-module drying machine cluster intelligent control system, method and device and a storage medium. The system comprises a plurality of air compressors and a plurality of drying machines. The air compressors are connected to the air inlet end of the pressure stabilizing air tank in parallel, and the air inlet ends of the dryers are connected to the air outlet end of the pressure stabilizing air tank in parallel. The air outlet ends of the dryers are connected to the air inlet end of the energy storage air tank in parallel; the air inlet end of the modular dryer cluster intelligent controller is connected to the air outlet end of the energy storage air tank, and the target operation state of at least one dryer is adjusted according to the target air parameters of compressed air of the energy storage air tank and the adsorbent filling amount of the dryers. According to the technical scheme, many-to-many parallel connection of the air compressors and the dryers can be achieved, the starting number of the dryers is dynamically adjusted on the premise that all the air compressors are maintained to operate, flexible adjustment of regeneration energy consumption of the dryers in a non-full-load state in a production area is achieved, and the energy consumption utilization rate is increased.

The invention belongs to the technical field of informatization security and secrecy, and particularly relates to an encrypted optical disc illegal external connection alarm tool which comprises a recording and printing tool recorded in an optical disc in an encrypted mode and an internet detection module. And automatically associating a specific website after the recording and printing tool is opened, and judging that the compact disc is used illegally if the association is successful. According to the invention, information security management can be enhanced, the management efficiency is improved, the information security cost is reduced, comprehensive monitoring and timely alarm of the secret-related optical disk are realized, and the security and confidentiality of the secret-related information are greatly improved.

The invention provides a cache system, a cache processing method, electronic equipment and a storage medium, the cache system comprises a plurality of processing cores and a configuration module, each processing core comprises a target storage area, the configuration module is used for determining multi-level cache configuration information of a first processing core, and according to the multi-level cache configuration information, the first processing core is configured to process a cache; first cache regions are divided from target storage regions of a plurality of processing cores, the first cache regions correspondingly divided by the plurality of processing cores form a multi-level cache system of the first processing cores, and the processing cores where the first cache regions of different levels are located are related to position information of the first processing cores. The first processing core is any one of the plurality of processing cores; and the first processing core is used for searching and acquiring data indicated in a data access request from the multi-level cache system of the first processing core when the data access request is received. In this way, the multi-level cache system of different processing cores can be flexibly configured, and the performance is improved.

The invention discloses a dynamic reconstruction method of a two-dimensional memory access controller, which belongs to the technical field of memory access controllers, and specifically comprises the following steps of: extracting the parallelism degree and the operation characteristic of a matrix algorithm, determining the partitioning mode of a storage module according to the parallelism degree and the operation characteristic, and storing matrix source data in a partitioning manner; based on the degree of parallelism, the number of enabled source data channels is determined, and efficient transmission of data from storage to calculation is achieved; according to the degree of parallelism and the operation characteristics, matrix source data are moved from the storage module to the calculation module through the source data channel, and matrix operation is executed; after the operation is finished, determining the number of enabled result data channels according to the degree of parallelism and a result, and transmitting the result back to the storage module; the configuration of each module is dynamically adjusted according to an algorithm and operation requirements, and the flexibility and efficiency of matrix operation are improved.