399 results about "Smart gateway" patented technology

The invention discloses a converter station intelligent gateway image recognition system based on a YOLOv3 target detection algorithm, and the system employs a three-stage cooperative processing architecture design, and builds seamless connection of a multispectral image collection layer, an edge calculation gateway layer, and a cloud operation and maintenance management platform layer. The invention further provides an equipment defect detection method based on the system, bimodal image data are collected through the visible light camera and the thermal infrared imager, preprocessing operation is carried out, equipment positioning and defect classification are synchronously executed by utilizing the improved YOLOv3 network, a structured detection result is output, temperature field analysis is carried out on an infrared thermal image, and the equipment defect detection result is obtained. And an abnormal heating area is identified, when defects are detected, multi-level risk response early warning is generated, and a defect diagnosis report is pushed to the cloud operation and maintenance management platform layer. Real-time image analysis of converter station equipment can be realized, the method is suitable for automatic detection of typical fault defects of the equipment, and the operation and maintenance efficiency of a power grid is improved.

The invention provides an intelligent gateway data processing method for industrial multi-protocol adaptive conversion, which aims at the current situation that various heterogeneous communication protocols exist in an industrial site and is based on a complete process of protocol feature vector extraction, machine learning automatic identification, semantic level analysis and mapping, dynamic rule configuration and protocol frame reconstruction. By constructing a protocol feature model library, semantic contents of original data frames are automatically identified and analyzed, and accurate equivalent conversion of multi-protocol data is further realized in combination with a protocol conversion rule and a unified semantic model. The reconstruction function frame realizes frame structure assembly, data coding and check calculation, and ensures that an output frame completely conforms to a target protocol specification. The method has high compatibility, high expansibility and good real-time performance, and the industrial protocol intercommunication efficiency and the automation degree are remarkably improved.

The invention discloses an equipment health management and predictive maintenance method and system based on an industrial intelligent gateway, and relates to the technical field of industrial automation and predictive maintenance, and the method comprises the steps: collecting equipment data through a multi-source sensor, and carrying out the preprocessing of the equipment data through an intelligent gateway; mapping the high-quality data to a digital twinborn model for health state evaluation; based on an evaluation result, fault prediction is carried out by adopting knowledge-driven and data-driven fused intelligent diagnosis; generating and executing a personalized maintenance strategy; according to the system and the method, the problems of insufficient multi-source data fusion, insufficient health assessment accuracy and lack of individuation of a maintenance strategy are solved, and precision, self-adaption and resource optimization of equipment health management are realized.

The invention discloses a real-time state synchronization method and system, electronic equipment and a storage medium, and belongs to the technical field of network communication.The method comprises the steps that in response to a connection request from a client side, persistent connection with the client side is established, and a state subscription relation is recorded; performing semantic analysis on the state change event from the business service layer to determine a push priority; a corresponding target intelligent gateway is found according to the target object identifier of the state change event, a pushing strategy is executed by fusing the client network condition maintained by the target intelligent gateway and the pushing priority, and the state is updated and synchronized to the related client; and monitoring the health state of the persistent connection, and when the connection is abnormal and recovered, performing state synchronization with the client by the intelligent gateway based on the stored incremental state information. According to the invention, the problems of unreliable connection, redundant pushing and poor expansibility of a traditional SSE scheme are solved, and high-reliability, high-efficiency and horizontally-expandable real-time state synchronization is realized.

The invention discloses a smart park alarm method and system based on an intelligent gateway, and the method comprises the following steps: accessing a heterogeneous terminal through a multi-protocol southbound interface, generating a standardized event set, and building a spatial topology table; performing quality evaluation on the standardized event set to form a sequential cleaning event stream; target detection is carried out based on the sequential cleaning event flow, and a semantic event flow is output; performing space-time matching on the semantic event flow to obtain a fusion event set; according to a preset grading standard, a grading warning set is generated, and a linkage instruction set is generated; scheduling and executing the execution end according to the linkage instruction set to form a processing state feedback; integrating the grading warning set and the processing state feedback into an evidence packet, and reporting the evidence packet in parallel through the main and standby reporting links; and archiving and indexing the evidence packet and the reported result, generating an auditable record, and finishing synchronous updating with an upper platform. According to the invention, the smart park alarm method and system are realized.

The invention relates to the technical field of power grid monitoring, and discloses a power grid power equipment anomaly prediction method, system and device, and a storage medium, which are used for solving the problem that the existing single data source and threshold alarm prediction mode cannot adapt to advanced prevention and high-precision state detection. The method comprises the following steps: acquiring real-time electrical quantity time sequence data, image data and a monitoring report of each piece of power equipment in an equipment abnormal area in a power grid through an edge intelligent gateway; respectively carrying out feature extraction on the real-time electric quantity time sequence data, the image data and the monitoring report to obtain an electric quantity feature vector, a visual feature vector and a semantic feature vector; and carrying out weight fusion on the electrical quantity feature vector, the visual feature vector and the semantic feature vector, and carrying out abnormal state prediction based on the fused feature vector and a historical feature sequence.

The invention discloses a method and a system for realizing remote operation and maintenance of equipment through cooperation of an industrial intelligent gateway and a cloud platform, and relates to the technical field of remote operation and maintenance of industrial Internet of Things, and the method comprises the following steps: the gateway collects multi-modal data of the equipment and locally preprocesses the multi-modal data to generate a structured data packet; lightweight Transform model forward propagation is executed, and an encrypted feature vector is extracted and uploaded to a cloud platform; the cloud platform adopts federated learning to update model parameters based on the feature vectors, issues the model parameters to the gateway, and synchronously constructs equipment digital twin bodies; analyzing the natural language operation and maintenance instruction through the digital twin to generate a control command; an equipment association graph is constructed, a fault propagation path is analyzed by using a graph convolutional network (GCN), and an early warning is generated; and after executing the control instruction, the gateway feeds back state data to the cloud platform, updates the digital twin and model input, and forms closed-loop control. According to the invention, collaborative optimization of data privacy protection, cross-device fault prediction and intelligent decision is realized, and the operation and maintenance efficiency and security are improved.

The invention relates to the technical field of artificial intelligence, intelligent gateways and finance, and provides a flow scheduling method, device and equipment for an intelligent gateway and a medium, and the method comprises the steps: obtaining resource monitoring data and API call chain data of each node in the intelligent gateway through a distributed service cluster grid; determining resource use trend prediction information and dynamic threshold information according to the resource monitoring data and a trained time sequence prediction model; in response to the fact that the resource use trend prediction information is abnormal, determining a fault propagation path according to the API call chain data and a pre-trained causal reasoning model; and determining a dynamic flow scheduling strategy through a multi-factor weight formula, and determining an adaptive fusing strategy according to the dynamic threshold information. Through the technical scheme, the problems of difficult fault positioning and scheduling lagging in a traditional distributed system are solved, and the stability, the anti-risk capability and the resource utilization efficiency of the intelligent gateway in a complex load scene are remarkably improved.

The invention relates to the technical field of intelligent gateways, in particular to a method and system for automatically expanding intelligent router plug-ins through LLM. The method comprises the steps that a user describes a plug-in function requirement of the intelligent router in a natural language through voice or text input equipment; and the cloud preprocessing service carries out character conversion processing on the voice data, carries out contradiction check and invalid information filtering on natural language requirements, extracts structured requirement information and inputs the structured requirement information to the cloud big language model. According to the intelligent router plug-in development method and system, the problems that in traditional intelligent router plug-in development, the manual intervention degree is high, the process is long and compatibility is insufficient are effectively solved by constructing an automatic system with the cloud large language model and the multi-service module cooperating. Through cooperation of multiple technical modules, a full-automatic process covering demand input, code generation, engineering integration, test verification and terminal deployment is constructed, and the intelligent router plug-in development efficiency and quality are remarkably improved.

The invention relates to the technical field of industrial intelligent gateways, in particular to an aviation plug waterproof wet plug type connector for an intelligent gateway. Comprising a connecting shell, a conductive module is arranged in the middle of the interior of the connecting shell, the conductive module is used for protecting two cable ends after butt joint is completed, symmetrically-distributed sliding rings and symmetrically-distributed limiting rings are slidably connected into the connecting shell, and the sides, close to the conductive module, of the limiting rings are in threaded connection with threaded sleeves. And wedge-shaped blocks which are distributed at equal intervals in the circumferential direction are fixedly connected to the sides, close to the conductive modules, of the limiting rings, the threaded sleeves are used for extruding the adjacent wedge-shaped blocks so as to clamp the adjacent cable ends, and springs are fixedly connected between the sliding rings and the adjacent limiting rings. According to the invention, the springs and the limiting rings drive the wedge-shaped blocks which are distributed at equal intervals in the circumferential direction, so that the two separated cable ends are close to each other, and normal transmission of current can still be ensured after the cable ends are interfered by external force.

The utility model discloses a structural settlement diagnostor which comprises an intelligent gateway, a liquid storage tank, a static level gauge a, a static level gauge b and a static level gauge c which are respectively connected in series through an air pipe, a liquid pipe and a communication bus. When the static force level gauge a, the static force level gauge b and the static force level gauge c are replaced and maintained, the connecting nut is rotated, the connector a and the connector b are separated, no pressure exists between the ejector rod and the conical round head b, under the action of resilience force of the elastic piece a and the elastic piece b, the inner taper hole round plate a makes contact with the conical round head a, the connector a is sealed, and the static force level gauge c is maintained. And an inner taper hole circular plate b is in contact with a conical round head b to seal a connector b, so that the condition of liquid leakage is avoided after the liquid pipe is detached, and the maintenance difficulty is reduced.

The invention discloses an equipment logic interlocking control method supporting edge collaboration and an intelligent gateway, and belongs to the field of industrial control and industrial Internet of Things. Reading a configuration center rule and generating a verification entry list; reading a local key value cache, sending a remote state query request and analyzing a state response message; obtaining an interlocking judgment result based on aging screening, numerical value comparison and Boolean operation of the collection timestamps; and executing physical bus message issuing or failure response output according to an interlocking judgment result. According to the method, a data access mode of combining configuration center rule management and local cache is adopted, so that the state of the dependent object can be uniformly verified, and the interlocking judgment traceability is improved.

The invention discloses a method and system for adapting an industrial intelligent gateway to multiple industrial protocols, and relates to the technical field of industrial Internet of Things edge computing, and the method comprises the steps: monitoring industrial network traffic self-learning, and constructing a protocol fingerprint database; dynamically constructing a virtual equipment twinborn body based on the fingerprint database to form a simulation environment; automatically verifying protocol configuration in a simulation environment; the application verification configuration is connected with the entity device to collect data; performing in-stream calculation processing on the data stream in real time to generate an advanced event and feature data; according to the method, automatic identification and compatibility of unknown protocols are realized, production accidents are avoided through virtual simulation verification, data value extraction is synchronously completed in the data acquisition process, and the security, reliability and data processing efficiency of protocol adaptation are effectively improved.

The invention belongs to the technical field of environment monitoring equipment, and relates to an environment monitor for a chemical plant, which comprises a stand column, a monitoring box and a sampling box, a multi-sensor fusion unit is mounted at the bottom of the monitoring box, and an edge intelligent gateway is arranged in the multi-sensor fusion unit; a detachable sampling container is arranged in the sampling box, a gas inlet joint and a gas outlet joint are arranged on the sampling container, a sampling joint is mounted at the bottom of the monitoring box, one end of the sampling joint extends out of the monitoring box, and the other end of the sampling joint is connected with the gas inlet joint through a gas conveying pipeline; an air extracting pump is installed in the sampling box, an air inlet of the air extracting pump is detachably connected with the air outlet connector, and the multi-sensor fusion unit and the air extracting pump are electrically connected with the edge intelligent gateway. The environment monitor can be arranged at a certain point position of a chemical plant and used for monitoring pollutants in ambient air, continuous real-time on-line monitoring can be carried out on the pollutants in the ambient air by using the multi-sensor fusion unit and the edge intelligent gateway, and gas samples can be automatically and manually collected.

The invention discloses a high-low voltage power distribution cabinet operation monitoring management method and system based on big data analysis and electronic equipment, and relates to the technical field of intelligent operation and maintenance of high-low voltage power distribution cabinets. The method comprises the following steps: acquiring various parameters based on deployed various types of sensors, and performing protocol conversion on acquired data through an intelligent gateway; carrying out local preprocessing on the data, and generating a standardized data message; uploading the data to a cloud platform, performing association analysis on multi-source data through a big data fusion algorithm, establishing multi-baseline monitoring of an equipment operation state, performing fault mode identification on abnormal data deviating from baselines, and generating fault early warning information; and automatically generating an operation and maintenance strategy according to the fault early warning information in combination with a preset operation and maintenance rule base. According to the technical scheme, comprehensive and real-time monitoring of the operation state of the high-low voltage power distribution cabinet is achieved, multiple parameters are collected through multiple types of sensors, the big data analysis technology is combined, and the abnormal situation in the equipment operation process can be accurately captured.

The invention relates to the technical field of network scheduling, and discloses an agricultural heterogeneous perception and intelligent network scheduling method and system, and the method comprises the following steps: S01, a system initialization stage; step S02, a resource scheduling and strategy learning stage; step S03, a sensing data fusion and processing stage; s04, a security mechanism and life cycle management stage: adopting an end-to-end encryption and identity authentication mechanism in a data transmission process, and collecting feedback parameters for updating a scheduling strategy and releasing resources after a task is completed; the system comprises a multi-mode agricultural sensing terminal, intelligent gateway equipment, a 5G and LPWAN hybrid access network, a resource scheduling module and a scheduling strategy learning engine. According to the method, the multi-dimensional state characteristics such as the network congestion level, the edge node load, the data timeliness and the task priority are sensed in real time through the deep reinforcement learning model, and the optimal allocation decision of communication and computing resources is dynamically generated.

The invention provides a soft extraction paper product production control system. The hardware platform comprises a central control all-in-one machine, an intelligent gateway, a folding machine, a semi-finished product paper storage frame, a cutting machine, a single packaging machine, a finished product paper storage frame, a medium packaging machine and a box filling machine. The software platform comprises a monitoring system running on the central control all-in-one machine and is provided with an adaptive feedback learning control method based on PID; according to the intelligent monitoring system, in the normal production process of a papermaking production line, firstly, an SCADA system is responsible for carrying out data acquisition on all PLCs, execution mechanisms and sensors on the production line, a WINCC control platform is responsible for data monitoring and processing, and the adaptive feedback learning control method based on PID is implemented. The control system is convenient to set, is simple and easy to use, saves manpower, improves the productivity of a papermaking production line and the market competitiveness of products, is low in comprehensive cost, and is very suitable for monitoring and control of online papermaking production line equipment.

The invention provides a multi-working-condition fault diagnosis test platform for a hoisting mechanism of hoisting machinery, and belongs to the technical field of fault diagnosis test platforms. The system comprises a hardware device, a data sensing and collecting device and a test working condition setting device. The hardware device is mainly composed of a bottom layer truss, a walking mechanism, a hoisting mechanism and a control device. The data sensing and collecting device supports multi-sensor data to synchronously collect multi-source fault data, the sensor collected data are uploaded to the database through the data collector and the intelligent gateway, and the upper computer extracts the data from the database and diagnoses faults and is used for achieving fault type recognition and early warning; the test working condition setting comprises lifting motor fault type setting, load working condition setting and lifting motor rotation frequency setting. According to the invention, the actual working condition of the hoisting mechanism of the hoisting machine can be better simulated, the acquisition cost of fault data is reduced, the test period of multi-working-condition faults of the hoisting mechanism is shortened, and the fault identification efficiency of the hoisting mechanism of the bridge erecting machine is greatly improved.

The invention discloses an intelligent gateway control method based on edge computing, and the method comprises the steps: S1, collecting the operation state data of network nodes through a distributed sensor, carrying out the filtering, denoising and normalization processing, sorting according to a timestamp, and generating the preprocessing data containing network flow, node load and response time delay; s2, calculating the resource demand quantity of each node based on the preprocessed data, executing a dynamic resource allocation algorithm in combination with the available resource state of the node, and generating a resource allocation result containing a calculation resource quota and a task allocation relationship; s3, inputting a resource allocation result into a gateway control model, adjusting model parameters based on a real-time network state, and generating a control strategy; and S4, encoding the control strategy into an instruction sequence, encrypting the instruction sequence through a digital signature, transmitting the encrypted instruction sequence to an execution unit through a secure channel, and executing a control instruction after verifying integrity and signature validity. Therefore, dynamic resource allocation, real-time network state adjustment and security instruction transmission are realized.

The invention belongs to the technical field of network equipment operation and maintenance, and relates to an operation and maintenance method and system for remote management and data acquisition and analysis based on hybrid networking, and the method comprises the steps: obtaining customer information, and carrying out the preprocessing; deploying and configuring an intelligent gateway to access a client network; configuring an intelligent gateway to enable a client network to establish secure communication connection with the monitoring center through the intelligent gateway; the monitoring center inputs customer asset information in a grading manner based on the preprocessed customer information; the intelligent gateway collects state information of customer assets in a customer network according to a preset collection period and transmits the state information to the monitoring center, and the monitoring center updates the states of the customer assets based on the received state information and performs operation and maintenance based on the current states of the customer assets. The security communication between the monitoring center and the user network is realized by deploying the intelligent gateway; state information of client network equipment is collected based on an intelligent gateway to serve as an information safety buffer area of a client network and a monitoring center, and safety communication in different scenes is achieved.

The invention relates to the technical field of power distribution cabinet data interaction, in particular to an efficient data interaction method for an intelligent power distribution cabinet. The method comprises the following steps that S1, an intelligent gateway gathers multiple paths of electrical parameters in the power distribution cabinet, and standardized electrical data is generated after edge side processing; and S2, identifying an operation cooperation relationship between the power distribution cabinets, and performing dynamic networking for the corresponding intelligent gateways according to the operation cooperation relationship to form an edge cluster capable of cooperative calculation. When the intelligent gateway detects a local anomaly, the abnormal data packet is forwarded in the edge cluster instead of depending on a possibly unstable uplink of the intelligent gateway, and other intelligent gateways with healthy uplinks in the edge cluster cooperate with each other, so that on one hand, a plurality of optional routing paths are constructed, the transmission reliability is greatly improved, and on the other hand, the transmission efficiency is improved; on the other hand, redundant operation is provided for subsequent control, and the fault influence range is limited within the minimum range.

The invention discloses a method for efficiently caching off-line state data of a water affair edge intelligent gateway based on multi-modal data, which relates to the technical field of water affair edge intelligent gateways, and comprises the following steps of: under the condition of identifying that a sensor is temporarily restarted, constructing a modal acquisition reference matrix by using a multi-modal data structure of a historical sampling period; a modal difference vector is generated in combination with the actual collection content of the current period and is used for determining the modal data gap state under the condition that the sensor is temporarily restarted; and based on the determined modal data gap state, carrying out matching analysis on the image data acquisition record at the current time point and the modal data gap vector at the current time point, and identifying modal inconsistency of the image and the sensor in the same time point cache. According to the invention, the problem that the modal gap of the multi-modal data cannot be identified and marked in an offline state is solved, and modal consistency identification and structural integrity guarantee are realized.

The invention discloses a stretching equipment centralized control intelligent monitoring method, system and equipment based on a recurrent neural network and a medium, and relates to the technical field of industrial equipment intelligent monitoring, and the specific steps are as follows: setting each stretching equipment as an independent subunit, installing various sensors to collect equipment operation data, and setting the equipment operation data as an independent subunit; the method comprises the following steps: establishing an edge intelligent gateway to pre-process equipment operation data to obtain a fusion data set; setting a safety threshold to judge equipment abnormity in real time and send an alarm; establishing a core controller to coordinate other equipment to execute a linkage strategy; establishing a cloud analysis platform to store equipment operation historical data; and training the equipment life prediction model to output life prediction results of the key parts of the equipment. According to the invention, cooperative control, safety response and predictive maintenance of the distraction equipment are realized, and the method can be widely applied to the technical field of electric power engineering construction and communication facility construction.

The invention provides an abnormity early warning method and system for comprehensive monitoring of a power distribution station house and an intelligent gateway. The method comprises the steps of collecting multi-parameter real-time data including electrical parameters, environmental parameters and equipment state parameters in the power distribution station house; preprocessing the multi-parameter real-time data and extracting to obtain a real-time characteristic parameter set; performing first-level early warning judgment on the real-time characteristic parameter set based on a preset multi-parameter safety threshold to obtain a first-level early warning result; inputting the multi-parameter real-time data into a pre-trained naive Bayes LSTM anomaly early warning model, and obtaining a prediction characteristic parameter set of the power distribution station house in a future set time window; performing secondary early warning judgment on the prediction characteristic parameter set based on the multi-parameter safety threshold to obtain a secondary early warning result; and outputting early warning information according to the primary early warning result and the secondary early warning result. The technical scheme of the invention can be deployed in an intelligent gateway of a power distribution station house, data acquisition is more comprehensive, early warning can be performed in advance, and response is more timely.

1. The name of the design product: intelligent gateway. 2. The use of the design product: for connecting network and Internet of Things home. 3. The design points of the design product: in shape. 4. The picture or photo that can best show the design points: perspective view 1.

The application discloses a power distribution cabinet monitoring method and system based on cloud-edge fusion technology and an intelligent power distribution cabinet, and relates to the technical field of power distribution cabinet control. The method comprises the following steps: dynamically forming an edge cluster, electing a main cooperative node and at least one backup cooperative node in the edge cluster, fragmenting, redundantly encoding and transmitting abnormal data, and the main cooperative node executing or forwarding control instructions according to the feedback state of the cloud platform. Through the dynamic election mechanism of the intelligent gateway, the cooperative responsibilities in the edge cluster can be circulated according to the instant state of each node, thereby improving or even avoiding the problem of long-term overload of individual intelligent gateways caused by uneven time and space distribution of abnormal events. Through the introduction of the fragmentation and redundancy coding technology of abnormal data, the transmission task originally concentrated on a single link is decomposed and dispersed to multiple independent nodes and links, thereby reducing the systemic risk of local surface failure caused by the single-point failure diffusion of the cooperative gateway in the traditional scheme.

1. The name of the design product: intelligent gateway (FTTR-ZB015). 2. The use of the design product: the design product is used for data communication and network connection. 3. The design points of the design product: the shape of design 1 in the design product; the combination of the shape and color of design 2 in the design product. 4. The picture or photo that best indicates the design points: design 1 perspective view 1. 5. Design 1 is designated as the basic design. 6. Other circumstances that need to be explained: the color of design 2 is required to be protected.

A device in communication with a first network associated with a building management system (BMS) includes one or more processing circuits configured to receive a virtual device corresponding to one or more physical devices or systems and provide a mapping between the virtual device and the one or more physical devices or systems. The virtual device is configured to represent the one or more physical devices or systems on the first network and one or more data points of the virtual device correspond to one or more data points of the one or more physical devices or systems. The one or more processing circuits are configured to receive data values for the one or more data points of the one or more physical devices or systems and update the one or more data points of the virtual device with the data values for the one or more data points of the one or more physical devices or systems.

1. The name of the design product: intelligent gateway. 2. The use of the design product: the design product is used for tower crane safety monitoring and network control. 3. The design points of the design product: the shape of design 1 is protected, and the combination of shape and color of design 2 is protected. 4. The picture or photo that best indicates the design points: the perspective view of design 1. 5. Design 1 is designated as the basic design. 6. Other circumstances that need to be explained: the design 2 in the design product to be protected contains color.

The utility model relates to the technical field of elevators, and particularly discloses a control system based on elevator local safety detection and intelligent presentation, which comprises a cloud platform, a local detection module, an elevator detection module, an elevator control system, a data module, a first intelligent gateway, at least one second intelligent gateway and a plurality of intelligent screens, the local detection module, the elevator detection module and the at least one second intelligent gateway are respectively connected with the data module; the intelligent screens are correspondingly connected with the data module, the first intelligent gateway and the second intelligent gateway in different areas, on one hand, the problem that local safety detection of key components of an elevator is lacked is solved, data analysis is conducted through a cloud platform self-learning data model, and detection results of various forms are intelligently generated; and on the other hand, the intelligent screen is used as a data presentation and user interaction terminal, the attribute that the elevator is only used as traditional transportation equipment is changed, the intelligent application scene of the elevator is further improved, and various intelligent requirements of special application occasions are met.