28results about How to "Efficient operation and maintenance" patented technology

The invention provides a self-organizing closed-loop feedback driven iterative optimization power exception processing method and system, and relates to the technical field of power exception processing. Comprising the steps of inputting modal data into a hybrid expert model, and obtaining comprehensive features of the multi-modal data through a weighted fusion method; based on the comprehensive characteristics, detecting the abnormality of the power system; adopting a reinforcement learning method to generate a plurality of processing suggestions for the power system abnormity; obtaining feedback information of a user on various processing suggestions, inputting the feedback information into the self-organizing mapping model for clustering, and dynamically adjusting the weight of each modal data in the hybrid expert model based on a clustering result; the feedback information serves as a reward for generating multiple processing suggestions in reinforcement learning, and generation of the multiple processing suggestions in the next round is optimized; and iteration is carried out until an optimal processing suggestion is obtained. According to the method, the accuracy, the real-time performance and the individuation degree of anomaly detection and processing can be effectively improved.

The invention discloses an operation and maintenance control system for automatic intelligent equipment, and the system comprises an equipment monitoring and data collection module which is used for carrying out the real-time monitoring, data transmission and data storage of the automatic intelligent equipment; the data analysis and anomaly detection module is used for carrying out data preprocessing, data analysis and anomaly detection on the monitored data; the fault diagnosis and positioning module is used for performing fault diagnosis and fault positioning; the maintenance decision and execution module is used for making a maintenance decision and executing the maintenance decision according to the fault diagnosis and positioning result; and the feedback and optimization module is used for recording the maintenance process and optimizing the operation and maintenance control flow according to the maintenance feedback and the data analysis result. According to the invention, intelligent and comprehensive automatic intelligent equipment operation and maintenance control can be carried out.

The invention belongs to the technical field of data processing, particularly relates to a BIM-based intelligent medical building design optimization method and system, and aims to solve the problems of high error rate and low optimization efficiency when real-time data is processed by a BIM model. The method comprises the following steps: acquiring a BIM model of a medical building, construction data and user input, establishing a mirror image model, detecting and correcting real-time data, processing the corrected data, detecting the real-time data by using a dynamic data detection model, correcting the data according to an error result, and optimizing the BIM model in combination with historical data. According to the method, the accuracy and optimization efficiency of the BIM model are improved, and efficient design, operation and maintenance of an intelligent medical building are supported.

The invention relates to a novel industrial cloudization controller undisturbed upgrading method and system and a medium, and the method comprises the steps: creating a cloudization controller; the uploaded cloud controller software mirror image is received and uploaded to the private cloud platform, and mirror image preheating is carried out after verification; in response to the upgrade request, identifying and selecting a standby controller to upgrade by referring to the preheated mirror image, and controlling the standby controller to obtain and update a configuration preheating memory in the corresponding main controller; and switching the upgraded standby controller into the main controller for pilot run, switching the main controller into the standby controller, and continuing to upgrade the original main controller or rolling the upgraded standby controller back to the version before upgrading according to the running state of the current control service in the pilot run. According to the method, the hardware controller is clouded, active and standby undisturbed upgrading and flexible resource management are realized, the system flexibility is improved through an intelligent process, the maintenance cost is reduced, and powerful support is provided for efficient operation and maintenance of the industrial internet.

The invention relates to the technical field of rail transit monitoring, in particular to a rail transit tunnel monitoring and operation and maintenance method and system based on an autonomous robot, and the system comprises the autonomous robot, a sensor network, a data processing center and an operation and maintenance management platform. According to the rail transit tunnel monitoring and operation and maintenance method and system based on the autonomous robot, all-around monitoring including crack detection, leakage monitoring, temperature and humidity measurement, harmful gas detection and the like can be carried out on the structure, environment, equipment and the like in the tunnel, and the functions of autonomous navigation, obstacle avoidance, environment perception and the like are achieved; the system can freely move in a tunnel and carry out various monitoring and operation and maintenance operations, optimizes daily manual inspection, improves the inspection efficiency and safety index, reduces the danger and burden of manual inspection, improves the monitoring reliability and inspection efficiency through big data analysis, reduces the operation and maintenance cost, and is suitable for popularization and application. And tunnel management is promoted to develop towards a more intelligent and unmanned direction.

The present invention discloses a grid-connected cabinet with intelligent monitoring function, including primary circuit components, a multifunctional intelligent instrument monitoring part, a photovoltaic meter CF metering circuit, a status indication part and a data acquisition analysis and visualization display part, wherein the primary circuit components include an incoming circuit breaker (QF1-1-4), a surge circuit breaker (QFS), a surge protector (SPD), an anti-islanding device (QF1), an isolating switch (GS) and a connecting copper busbar and a busbar, and the multifunctional intelligent instrument monitoring part includes a current transformer (TC, TB, TA), a multifunctional meter (MPU), a fuse (Fua, Fub, Fuc, Fu1) and a connecting line. The present invention is provided with primary circuit components, a multifunctional intelligent instrument monitoring part, a photovoltaic meter CF metering circuit, a status indication part and a data acquisition analysis and visualization display part, which can enable the grid-connected cabinet to have the ability of intelligent monitoring, thereby effectively improving its use effect.

The present invention discloses a health analysis open service system and method. The system includes: a labeling subsystem, which is configured to label sample images and generate multiple data sets based on preset labeling rules, and convert the data sets into data sets that can be understood by deep learning algorithms; an algorithm subsystem, which is configured to provide an online programming environment, and generate one or more health deep learning models based on the converted data sets and the online programming environment; a health business subsystem, which is configured to use one or more of the health deep learning models to analyze the received images to be analyzed, and generate health analysis results. The present invention solves the technical problem that the health analysis efficiency and quality provided by the existing health analysis system are not high enough.

The present invention discloses a business system development and management system based on big data analysis, which specifically relates to the field of business system development, including a data collection time determination module, a development data entry module, a development data analysis module, an abnormality analysis module, and a management module. The present invention significantly improves the efficiency and accuracy of business system development management by integrating big data analysis technology. The various modules of the present invention work together to achieve a closed loop of data collection, analysis, abnormality detection, and automated management, ensuring that business data is comprehensive, real-time, and accurate, and a comprehensive abnormality index model scientifically evaluates the system status, timely discovers and warns of potential problems, and provides strong support for management decisions. At the same time, the emergency response mechanism ensures that the system can be quickly restored when abnormal, ensuring business continuity. Overall, the present invention greatly enhances the controllability and stability of business system development.

The utility model discloses an integrated motorized intelligent guarantee platform. The system comprises a superior station room power supply module, a platform core module, a tail end guarantee module, an emergency power supply module and a full-link sensing module, and the output end of the superior station room power supply module is connected with the input end of the platform core module and the input end of the emergency power supply module. The power output ends of the platform core module and the emergency power supply module are connected with one end of the tail end guarantee module, the data output ends of the platform core module, the tail end guarantee module and the emergency power supply module are connected with the data input end of the full-link sensing module, and the other end of the tail end guarantee module is used for being connected with electric equipment. And the control end of the full-link sensing module is connected with the control end of the tail-end guarantee module. According to the utility model, high-efficiency operation maintenance of the power supply system under the change of the energy supply mode is realized.

The invention discloses a multivariate data fusion-based engine oil abnormal consumption diagnosis method, which adopts an innovative diagnosis scheme of multivariate data fusion, dynamic model and multistage judgment, and comprises the following steps of: generating a dynamic reference model of engine oil consumption through a neural network model through fusion analysis of working condition parameters and engine oil consumption data; according to the system and the method, engine oil abnormal consumption can be accurately detected in real time in advance, the abnormal judgment of the liquid level-oil consumption change ratio is calculated, a matched intelligent diagnosis system is synchronously developed, and the intelligent diagnosis system comprises a data acquisition module, a sensor, an edge gateway, a visual instrument terminal and a cloud platform. And efficient technical support is provided for engine operation and maintenance.

The application discloses a kind of substation battery pack operation and maintenance method and device, belong to battery technology field, method includes: according to pre-constructed battery pack health degree score matrix and single battery health degree score matrix, obtain battery pack health degree score and single battery health degree score;According to the battery pack health degree score and single battery health degree score, obtain operation and maintenance scheme;Wherein, the battery pack health degree score matrix is constructed according to pre-constructed consistency evaluation level and its corresponding consistency evaluation index acquisition, and the single battery health degree score matrix is constructed according to single battery evaluation index and its corresponding weight acquisition.The method can evaluate the health degree of battery pack, and give corresponding operation and maintenance scheme.

The application discloses a belt conveyor safety maintenance hanging card practical training system, effectively solves the problems of lacking integrated "three-party confirmation" process intelligent training system in belt conveyor equipment safety maintenance hanging card operation practical training and examination. The application sets up the operation table, power distribution cabinet and belt conveyor which are associated to constitute the belt conveyor safety maintenance hanging card practical training system, and matches the corresponding practical training method, adopts the "entity operation + virtual feedback + intelligent management and control" three-in-one mode, realizes the forced operation sequence, reduces the standardized process of human negligence, realizes the dynamic simulation of accident consequences, enhances the risk perception of safety awareness, and realizes the automatic timing of the control system and the error step judgment, saves the examination time and improves the training efficiency.

The invention discloses a method and equipment for querying an abnormal state of a battery cell in an energy storage cabinet and a storage medium, and relates to the technical field of battery cell management. The method comprises the following steps: generating a local abnormal event message containing an abnormal source identifier based on a preset local abnormal triggering condition when monitoring that any battery cell monomer in the energy storage cabinet is abnormal; broadcasting the abnormal event message to other battery cell monomer nodes in the energy storage cabinet; based on a preset aggregation triggering strategy, aggregating the state information of each cell monomer node in the abnormal and associated monitoring state at a local network level; according to the received abnormal event message, the battery cell monomers in the associated monitoring state are judged by other battery cell monomer nodes according to the association relation topology between the battery cell monomers and the abnormal source; and uploading the aggregated state abstract to a query terminal through single transaction communication. The method aims to provide technical support for safe and efficient operation and maintenance of a large-scale energy storage system.

This utility model discloses a molded case circuit breaker, including a housing and a control handle disposed on the housing panel. The housing houses a main control module, a local program upgrade module, and a remote program upgrade module. The local program upgrade module includes a Type-C interface, a voltage regulator circuit, and a first isolation circuit. The Type-C interface is located on the housing panel. The power supply terminal of the Type-C interface is connected to the power supply terminal of the main control module through the voltage regulator circuit, and the data terminal of the Type-C interface is connected to the communication terminal of the main control module through the first isolation circuit. This utility model achieves plug-and-play local offline program upgrades through the Type-C interface. Combined with the remote program upgrade module, the circuit breaker can achieve more convenient and diverse program upgrades, and the program upgrade structure has stronger anti-interference capabilities, with stable and efficient data transmission.

The invention discloses a control method and device for an intelligent integrated modular circuit breaker operating mechanism, and the method comprises the steps: collecting an external sensor signal and an internal circuit state of the operating mechanism through a signal processing module after a motor control module is electrified and initialized; the motor control module calls an internal preset safety logic algorithm and generates an operation permission instruction for indicating whether the current mechanism has an action condition or not according to a comparison result; when the verification is passed, generating a corresponding mechanism driving signal of the driving coil or the energy storage motor according to the type of the external control command; and starting a real-time sampling loop to monitor the current waveform and action duration of the driving circuit, and adjusting or interrupting the mechanism driving signal. According to the technical scheme, the problems that a traditional circuit breaker is complex in wiring and difficult to maintain can be solved, and comprehensive state monitoring, rapid fault diagnosis and safe and reliable operation are achieved.

The present invention discloses an online mapping method and system for health monitoring data of a cable-stayed bridge, and belongs to the technical field of cable-stayed bridge monitoring. A parametric BIM model of a cable-stayed bridge is established, and the BIM model is lightweight processed based on GLTF; the monitoring page is integrated based on Vue and BIMface, and a complex monitoring page is developed in a component-based manner and bound to the BIM model; the API is called to arrange monitoring points; the sensor and the monitoring point are responsively coupled, and the monitoring data is converted from high-dimensional data to low-dimensional data based on PCA, while retaining the characteristics of the monitoring data, realizing dimensionality reduction processing, and displaying it in the form of a chart; the data exceeding the threshold is intuitively displayed in the form of a dynamic line chart and a table, and the components exceeding the threshold are warned and prompted through component color changes and email notification mechanisms. Through the above-mentioned method and system, the present invention opens up the process of data collection, data processing to data visualization management in the health monitoring process of the cable-stayed bridge, and realizes the online mapping of the health monitoring data of the cable-stayed bridge.

The invention relates to the field of photovoltaic insulation monitoring, and discloses a photovoltaic power station equipment insulation monitoring system for a non-uniform foundation, and the system comprises an insulation monitoring terminal which is used for collecting, processing and analyzing the voltage and leakage current data of photovoltaic power station equipment, and achieves the fault detection and warning. The invention also discloses a photovoltaic power station equipment insulation monitoring method for the non-uniform foundation, and the method comprises the following steps: S1, after the system is started, the fling-cut switches K1 and K2 are initialized, and the collection module carries out the signal conditioning and sampling of the high voltage of the DC bus. Through combination of a bridge detection method and a differential current detection method, the problems of switching switch loss and accident potential caused by frequent resistance switching in a single bridge method are solved, real-time fault early warning and fault position display are realized by using a high-sensitivity non-contact direct current leakage current sensor, and meanwhile, a power line communication technology is adopted, so that the fault detection accuracy is improved. Electric leakage data transmission of the distributed photovoltaic power generation system is realized, and a communication channel does not need to be specially erected.

The invention discloses a method for effectively solving non-stop capacity expansion of containerized RabbitMQ. The method comprises the following steps: S1, starting a mirror image strategy and setting an existing queue as a mirror image queue; s2, starting a mirror image queue priority mode and a message priority mechanism; s3, verifying the state of the mirror image queue; and S4, carrying out capacity expansion on the RabbitMQ and rebalancing the distribution of the main node. According to the method, the RabbitMQ middleware in a single-point and cluster mode can be subjected to non-stop capacity expansion, the problem that restarting is needed when the RabbitMQ service deployed in a containerization mode modifies resource configuration and operating parameters is solved through a mirror image mode, and particularly for a production environment, the phenomenon that the service is influenced by stop is avoided.

This invention discloses an AI-driven big data fusion-based anti-misoperation interlocking system for wind farm booster stations, relating to the field of anti-misoperation interlocking technology for wind farm booster stations. It includes a data acquisition module that collects real-time electrical parameters, operating status, and environmental parameters of the equipment, and uploads them after preprocessing; a big data fusion storage module that categorizes and stores multiple types of data according to a hierarchical strategy, optimizing access and retrieval; an AI intelligent analysis and decision-making module that integrates multi-source data to generate precise interlocking strategies; an anti-misoperation interlocking execution module that executes interlocking in a three-level mode and provides status feedback; a communication interaction module that achieves internal and external data interaction through a dual-mode architecture; a status monitoring module that monitors the operating status of each module and identifies faults; and an emergency handling module that initiates a response mechanism and restores operation after self-checking following fault resolution. This invention relies on AI and big data fusion technology, dynamically adapting interlocking thresholds to equipment and environmental conditions; supporting unattended operation and intelligent maintenance, providing reliable assurance for the safe operation of wind farm booster stations.

The application discloses an edge big data-based regional terminal data security and protection management system and method, and relates to the technical field of terminal security management; the application collects behavior data and interaction data of edge terminal nodes; behavior factors are extracted according to the behavior data, and real-time state scores are analyzed; a behavior matrix of the edge terminal nodes is constructed, and the influence weights of each behavior factor are calculated; the behavior volatility of each behavior factor in a preset period is analyzed according to the state scores of the behavior factors, and the behavior abnormality degrees of each behavior factor are determined based on the analysis data; the instantaneous interaction trust degree is analyzed based on the interaction data of the edge terminal nodes at each moment, and the comprehensive interaction trust degree of the edge terminal nodes at the current moment is determined; the current risk abnormality degree of the edge terminal nodes is analyzed according to the comprehensive interaction trust degree and the behavior abnormality degrees of each behavior factor, and the abnormal edge terminal nodes are located; the application improves the accuracy and efficiency of regional terminal anomaly monitoring.

This invention relates to the field of intelligent detection technology for building materials, specifically disclosing a multimodal real-time detection method and system for the crushing value of lightweight recycled aggregate. First, a multimodal dataset is constructed: images of recycled aggregate are acquired and their precise crushing values ​​are configured; physical attribute data corresponding to the images are collected; the images are transformed; and lightweight debris occlusion areas are randomly generated. Next, single-modal base learners for both image and physical modes are constructed and trained. A dual-path cross-validation mechanism is constructed to generate initial prediction values ​​for samples by the trained base learners, and a meta-feature set is constructed with the actual crushing values ​​of the samples. Finally, a meta-learner is introduced, trained using the meta-feature set, and its output is nonlinearly combined with the base learner outputs to finally output the fused prediction result of the sample crushing values. This invention can fuse multi-source heterogeneous information, flexibly handle modality-deficient scenarios, and is suitable for mobile edge computing environments.

The invention discloses a distribution network remote operation and maintenance method and system, a storage medium and a program product, and the method comprises the steps: selecting a distribution network automation terminal, automatically recognizing the state of the distribution network automation terminal, and selecting a terminal according to the state or from a preset list; selecting and remotely calling a fault recording file, a remote control operation event and an SOE event file or upgrading software of the terminal; and displaying the calling file or the upgrading result, and downloading the file to a master station system. The device comprises a terminal selection module, a file type selection module, a file calling and software upgrading module, a result display module and a file downloading module. The technical problems that an existing operation and maintenance scheme is low in operation and maintenance efficiency, the labor intensity of operation and maintenance personnel is large, and errors are prone to occurring are solved.

The invention provides a railway bridge construction operation and maintenance method and system based on carbon emission optimization, relates to the technical field of traffic infrastructures, and aims to construct a bridge digital twin model in a construction stage to simulate and predict carbon emission dynamics. And carrying out correlation analysis on the carbon emission influence factors by using a space-time diagram network. The carbon emission is globally optimized through a quantum annealing algorithm, construction scheduling is optimized in combination with a quantum decision tree, dynamic regulation and control of the carbon emission are achieved, and meanwhile the influence on bridge material attenuation is determined. And an operation and maintenance stage: inputting the bridge structure attenuation information and the bridge structure data obtained in the operation and maintenance stage into a convolutional neural network, predicting a bridge structure state, and generating a dynamic maintenance decision according to the bridge structure state. The method can accurately monitor and optimize the carbon emission in the construction, operation and maintenance stages of the railway bridge, and provides technical support and decision basis for the industry to realize low-carbon and sustainable development targets.

The invention provides a method and system for drawing a 3D topological graph through an orthographic projection method, electronic equipment and a storage medium, and relates to the technical field of data visualization. The method comprises the following steps: firstly, automatically generating a two-dimensional top view according to network element information and a network element relationship of a CMDB module, and optimizing topology through one-key beautification or manual adjustment; the Z-axis height of the network element is modified, front-back and left-right view verification is switched, and the three-axis space position of the network element is adjusted; and finally, rendering the 3D icon, the height level and the three-dimensional connecting line dynamic effect, and generating an angle-adjustable 3D topological graph. According to the method, an orthographic projection method in engineering drawing is innovatively adopted, the 3D topological graph is efficiently constructed in a low-code mode, and the spatial position relation of each network element in the X-axis direction, the Y-axis direction and the Z-axis direction is accurately presented.

A workshop waste gas filtering absorption tower device comprises a tower body and a tower bottom, an air inlet is formed in the tower bottom, and a first filler layer, a first spraying assembly, a second filler layer, a second spraying assembly, a demisting layer and an air outlet are arranged from the bottom to the top of the tower body; the demisting layer comprises a wire mesh demister and a filler demisting part, the wire mesh demister is positioned below the filler demisting part, and an induced draft fan is arranged at an air outlet. The acid-containing and alkali-containing waste gas is fed from the bottom of the tower, is distributed by the gas distribution device, continuously passes through gaps of the filler layer in a countercurrent manner with the washing liquid, and is in close contact with the washing liquid on the surface of the filler for mass transfer, so that the equipment is very practical in effect for the acid-containing and alkali-containing waste gas and macromolecular substances which can be dissolved in water; the contact area is increased by spraying the washing liquid, the acid-containing and alkali-containing waste gas is absorbed and filtered by utilizing the characteristic that the washing liquid can be dissolved in water, the operation and maintenance are efficient, and compared with ozone filtration, infrared ultraviolet filtration, membrane permeation and other technologies, the method is simpler, more efficient and low in cost.

The wind power intelligent robot moving system comprises a battery box, a storage battery is arranged in the battery box, leg frames are installed on the four sides of the battery box through elastic supporting mechanisms, electromagnetic suction cups are arranged in the leg frames, and moving driving mechanisms are arranged on the side edges of the leg frames; an electric rotating disc is arranged at the top of the battery box, supporting top frames are mounted on rotating seats of the electric rotating disc, mounting plates are mounted at the tops of the supporting top frames, and an ultrasonic array module is arranged between the supporting top frames; a camera is mounted on one side of the bottom of the mounting plate and is used for shooting the surrounding environment of the system; a thermal infrared probe is arranged on the other side of the bottom of the mounting plate; and an analysis processing module and a driving control module are arranged in the development board. Movement in all directions on the wall of a steel tower drum with a certain radian and the wall of a steel cabin is met, and autonomous movement, intelligent monitoring and efficient operation and maintenance can be achieved.

The utility model belongs to photovoltaic equipment cleaning technical field, concretely relates to a water -saving photovoltaic panel cleaning device based on centrifugal water and sand separation, including a plurality of photovoltaic panels, the upper portion of which is provided with a spraying assembly, the lower portion of which is provided with a water receiving assembly, the water receiving assembly is connected with the water and sand separation assembly, the water and sand separation assembly is connected with the water circulation assembly, the water circulation assembly is connected with the power system, and the power system and the water circulation assembly are electrically connected with the control system; the device is integrated with the spraying assembly, the water receiving assembly, the water and sand separation assembly, the water circulation assembly, the power system and the control system, realizes the closed loop recycling of cleaning water, reduces water resource consumption, and can efficiently remove sand particles through the centrifugal water and sand separation technology, reduces the risk of nozzle blockage, simultaneously utilizes the structure of photovoltaic panel self -power supply and is applicable to the area without power grid, and the overall structure is simple and reliable, convenient to maintain, is especially suitable for the efficient operation and maintenance of photovoltaic power station in arid sand area, and gives consideration to water saving, economy and environmental adaptability.

This invention discloses a controllable intelligent photovoltaic (PV) management architecture, belonging to the field of photovoltaic energy technology. The architecture includes an edge layer, a platform layer, and an application layer. The edge layer is used to collect equipment operation data and business management data in PV management. The platform layer is used for centralized storage, processing, analysis, and application of the data collected by the edge layer. The application layer provides intelligent operation and maintenance, management decision-making, and business empowerment based on the data and analysis results from the platform layer. This invention reduces the operation and maintenance costs and difficulty of PV power plants and avoids the problem of data silos.