51results about How to "Realize intelligent operation and maintenance" patented technology

The invention discloses a heterogeneous network operation and maintenance management method based on user perception. The method comprises the steps that 1, heterogeneous network operation and maintenance data are collected by a base station and a network monitoring node; 2, the obtained heterogeneous network operation and maintenance data are processed in a unified mode, and a unified operation and maintenance data model is built; 3, correlation analysis is carried out on the heterogeneous network operation and maintenance data and network faults according to the built operation and maintenance data model to achieve network fault positioning; 4, the network node independently analyzes the positioned faults, adjusts corresponding operation and maintenance data and achieves fault self recovering and network optimization. After network operation and maintenance data excavation analysis and network fault positioning, network self recovering is achieved by optimizing network parameters, user experience is improved, and network intelligent operation and maintenance are achieved.

The invention belongs to the technical field of robot design, and particularly relates to a rail-hanging fire-fighting inspection robot. The robot comprises a rail module, symmetrical driven wheel mechanisms are arranged on the side wall of the rail module in a sliding mode, a walking mechanism frame is jointly and fixedly arranged at the lower ends of the two driven wheel mechanisms, and a sliding rail line current collector and a pressure wheel are fixedly arranged at the front end of the upper side wall of the walking mechanism frame and are in sliding connection with the front side wall of the rail module. According to the rail-hanging fire-fighting inspection robot, mobile inspection and fire extinguishment can be realized in a pipe gallery and a tunnel, traditional fixed-point installation of fire extinguishment equipment is changed, and dozens of or even hundreds of fixed fire extinguishment devices are replaced with one robot, so that the construction cost of municipal facilities is greatly reduced; robot control, a body mechanism, an environment detection module and a fire extinguishing module are integrated into the intelligent rail-hanging fire-fighting inspection robot, and intelligent operation and maintenance of the pipe gallery and the tunnel are achieved.

The invention discloses a data processing method, a data processing terminal, a photovoltaic cloud server and a system, which are applied to the data processing terminal, the method comprises the following steps: collecting operation data of a photovoltaic power station; transmitting the operation data to a photovoltaic cloud server so that the photovoltaic cloud server generates a photovoltaic power station operation and maintenance instruction according to the operation data; receiving the photovoltaic power station operation and maintenance instruction from the photovoltaic cloud server; and according to the photovoltaic power station operation and maintenance instruction, generating operation and maintenance operation data corresponding to the photovoltaic power station operation and maintenance instruction, and transmitting the operation and maintenance operation data to a photovoltaic power station. The data processing terminal collects the operation data of the photovoltaic power station, transmits the operation data to the photovoltaic cloud server, receives the operation and maintenance instruction of the photovoltaic power station from the photovoltaic cloud server, generates operation and maintenance operation data according to the operation and maintenance instruction of the photovoltaic power station, and transmits the operation and maintenance operation data to the photovoltaic power station. Therefore, intelligent operation of operation and maintenance of the photovoltaic power station is realized through the data processing terminal and the photovoltaic cloud server.

The invention discloses an intelligent operation and maintenance method for a photovoltaic power generation system. The method comprises steps that photovoltaic module electronic equipment is used forcollecting generating capacity data of a photovoltaic assembly and receiving the generating capacity data sent by a communicator connected with the photovoltaic module electronic equipment, and the photovoltaic module electronic equipment comprises any one or a combination of any more of a micro inverter, an optimizer, a turn-off device and a monitor; the power generating capacity data is analyzed, and a photovoltaic power generation system with abnormal power generating capacity data is screened out; the screened generating capacity data of the photovoltaic power generation system is diagnosed, and the abnormal condition of the photovoltaic power generation system is determined; an operation and maintenance work order corresponding to the abnormal condition is generated, and the operation and maintenance work order is assigned to a client so that the client overhauls the photovoltaic power generation system according to the operation and maintenance work order. The method is advantaged in that intelligent and automatic operation and maintenance of the photovoltaic power generation system are realized, so operation and maintenance efficiency of the photovoltaic power generation system can be improved, and operation and maintenance cost of the photovoltaic power generation system is reduced.

The invention discloses an abnormal event early warning method for an urban underground comprehensive pipe gallery. The method comprises the following steps: acquiring target attribute data through pipe gallery sensing equipment; performing data-level fusion on the data of the homogeneous data sensor by using Kalman filtering; the future pipe gallery data is predicted through an improved and trained TS-Transform model by means of the result of the data level fusion; using a D-S evidence theory to perform decision-level fusion on a data-level fusion result and predicted data; and real-time detection and early warning analysis are realized in parallel by utilizing a decision-making level fusion result. The proposed secondary data fusion model can effectively reduce the redundancy and uncertainty of the pipe gallery data; the provided prediction model solves the problem that a traditional RNN-based time sequence prediction model cannot be trained in parallel and is difficult to process long-term time dependence. According to the abnormal event early warning method, whether the abnormal event occurs in the pipe gallery or not can be detected in real time, possible accidents can be warned in advance, the major accident risk of the pipe gallery is effectively reduced, and economic losses are reduced.

The invention provides an intelligent maintenance analysis system for a ballast track bed. The system comprises a ballast bed state data acquisition module and a ballast bed state intelligent analysismodule, wherein the ballast bed state data acquisition module is used for acquiring state parameters of a ballast bed through acquisition equipment; wherein the ballast bed state intelligent analysismodule is used for formulating ballast bed state information parameters and parameters in tamping operation and optimizing a tamping scheme, and the ballast bed state data acquisition module transmits the ballast bed state information parameters to the ballast bed state analysis module for processing. According to the invention, the tamping operation parameters and schemes based on the ballast bed state are customized through the tamping operation parameter analysis module; a digital health record of the ballast bed state is established, so that scientific maintenance and repair of the ballast bed state and intelligent operation and maintenance of the ballast track are realized; the optimal tamping opportunity can be accurately judged according to a rail inspection data change rule analysis result.

The invention discloses a BIM-based building full-life-cycle dynamic intelligent management system and method. The BIM-based building full-life-cycle dynamic intelligent management system comprises a decision module, a management module, an operation module, an operation and maintenance module and a cloud platform module; the system also comprises an offline decision module and an online updating module. The offline decision module comprises a first cache module and a second cache module, the first cache module is arranged between the decision module and the management module, and the second cache module is arranged between the management module and the operation module. And the online updating module is arranged between the decision module and the cloud platform module. The off-line decision module is an expert database which is preset in a software platform of the cloud platform module. According to the invention, based on the characteristics of planning, design, construction, operation and maintenance links and the like of the whole life cycle of the building, the BIM technology, the Internet of Things, cloud computing and the like are integrated to realize the digital intercommunication of the whole life cycle of the building and the dynamic intelligent management of the process, the integrated collaborative management of the project is realized, and the operation and maintenance cost is reduced.

The invention discloses an intelligent operation and maintenance terminal of a transformer substation video and environment monitoring station end system, which is provided with a transformer substation video monitoring system, a comprehensive data network, a transformer substation operation and maintenance terminal, an intelligent electric box control system and an intelligent platform, the integrated data network performs data transmission; the substation operation and maintenance terminal carries out station-end network diagnosis, station-end data flow monitoring, station-end equipment operation monitoring, network management direct-current power supply monitoring, video image abnormity diagnosis and RPU video integrity diagnosis; the intelligent electric box control system controls the restart of the transformer substation video monitoring system; the intelligent platform displays the processing data of the substation operation and maintenance terminal and collects the operation and maintenance condition of the intelligent electric box control system. Real-time monitoring and intelligent operation and maintenance of the transformer substation video monitoring system are realized, the stability of the transformer substation video monitoring system is improved, the skill requirements of maintenance personnel are reduced, the power transformation video maintenance efficiency is improved, and the operation and maintenance investment is reduced.

The invention belongs to a blade unbalance fault monitoring method, and aims to solve the technical problems that a vibration sensor needs to be installed for collection of vibration signals during blade unbalance fault monitoring at present, and time and labor are consumed due to the fact that an existing blade balance monitoring method needs to carry out manual monitoring and manual adjustment on the basis of a large amount of manual labor. According to the wind turbine generator blade unbalance fault monitoring method based on the vehicle-mounted device, the vehicle-mounted device serves as a platform, vehicle-mounted automatic inspection and fan maintenance are achieved, the deep learning technology serves as basic technical support, and video data collected by the vehicle-mounted device are correspondingly monitored and processed. A wind turbine generator blade unbalance fault monitoring method is researched, adjustment parameters of a fan are analyzed and given, the parameters can be issued to a fan console, the balance angle of the blade is corrected, and intelligent operation and maintenance of a fan field are achieved. The vehicle-mounted device is used for carrying out itinerant monitoring on numerous fans, and the defect that a traditional manual monitoring method is time-consuming and labor-consuming is avoided.

The invention discloses a magnetic levitation track state comprehensive detection device, and belongs to the field of track measurement. The device comprises a vehicle body connecting seat arranged above a magnetic suspension track, a tool frame arranged on the bottom side of the vehicle body connecting seat and located between the vehicle body connecting seat and the magnetic suspension track, and a measuring set arranged on the tool frame. The measuring set comprises an F rail profile measuring sensor arranged on the tool frame and located over the F rail, a vehicle body posture measuring sensor arranged on the tool frame and located below the vehicle body connecting base, and a plurality of sleeper irregularity measuring sensors arranged on the tool frame and located above the sleepers.According to the invention, the function of quickly and comprehensively detecting the magnetic levitation track and the auxiliary power supply facilities is realized, and meanwhile, the digital laserdetection technology and equipment with accuracy, reliability, safety and high efficiency are adopted, so that the system has the advantages of high accuracy, high reliability, interference resistance, all-weather operation and the like.

The invention belongs to the technical field of services of web servers, and discloses a service system and a service method based on a multi-web server, and a storage medium. The service system comprises a data communication module, a parameter configuration module, a main control module, a data updating module, a resource balancing module, a database module and a test module. According to the service system provided by the invention, under the condition that no additional load balancing device is deployed, a Web application system achieves the load balancing through the resource balancing module, thereby reducing the complexity of deployment and maintenance; meanwhile, the test personnel does not need to manually construct a test script according to a Web element identifier and other information through the test module; and a connection can also be established with the Web server to be tested through a Telnet protocol to test the Web server to be tested, so that the time used by thetest personnel for manually testing the Web server by using a browser can be saved. Therefore, the test efficiency of the Web server can be improved by the service system provided by the invention.

The invention provides an AIOps intelligent operation and maintenance system based on an artificial intelligence technology. The AIOps intelligent operation and maintenance system comprises an AIOps intelligent operation and maintenance center system, a data middle station system, an AI middle station system, a technology middle station system, a service middle station system and a service application system. The intelligent operation and maintenance center system additionally comprises a system health degree scoring module, a root cause analysis module, a fault prediction module, a capacity evaluation module and an intelligent alarm convergence and noise reduction module. Monitoring operation and maintenance of'one center and four middle stations' and five-layer architecture are switched on, log, monitoring, performance and other data related to operation and maintenance are collected in various forms, operation and maintenance interfaces of a front stage, a middle stage and a back stage are switched on, and centralized management of operation and maintenance of a unified portal is achieved; tenant mode docking capability with group unified AI is reasonably constructed, an AI model and algorithm are reasonably introduced, computing resources are combined with local operation and maintenance data, an AIOps scene model and a centralized AI platform are carried out to complete training framework and standard compatibility, and sharing and multiplexing of model services are achieved.

The embodiment of the invention provides a fault processing method and system, a device and a computer readable storage medium. The method comprises the following steps: acquiring basic data and real-time service data, counting the service data to obtain historical data, and storing the basic data, the service data and the historical data into a preset database according to a preset data rule; responding to a service request operation of a user in the network management system, the conference management system or the geographic information system, and obtaining response data corresponding to the service request operation from the database according to the service request operation; and analyzing the response data, and carrying out fault processing according to an analysis result and the basic data. According to the embodiment of the invention, the fault of each service platform can be automatically processed, intelligent operation and maintenance are realized, the labor cost is saved,the operation and maintenance pressure caused by video networking service expansion is reduced, and the fault processing efficiency is improved.

The invention discloses an on-line monitoring device for a power transmission line wire connection point temperature. The device comprises a temperature monitoring module and a signal transmission base station. A battery and a wireless transmission chip are fixedly connected to the interior of a shell; a thermistor sensor is fixedly connected with the shell and extends to the outer surface of theshell from the inside; the outer side of the shell is sleeved with a silica gel sleeve; a ribbon is arranged on the silica gel sleeve; the thermistor sensor is electrically connected with the wirelesstransmission chip; the battery is electrically connected with the thermistor sensor and the wireless transmission chip respectively; the wireless transmission chip is wirelessly connected with the signal transmission base station; the signal transmission base station is wirelessly connected with a cloud server; and the cloud server is wirelessly connected with a terminal. The device has the beneficial effects that the reliability of the device is improved; the temperature can be monitored online for 24 hours and the heating hidden danger of the device can be found in time; the practicabilityis high, the personnel cost, the time cost and the equipment cost are saved; the labor intensity of operation and maintenance personnel is greatly reduced; and the working efficiency is improved.

The invention discloses an intelligent operation and maintenance system for a BIPV roof photovoltaic power station. The system monitoring subsystem comprises: a system monitoring subsystem, the monitoring camera carries out full-area real-time video monitoring on the photovoltaic roof. The local monitoring computer locally checks, stores and processes monitoring data of the roof photovoltaic powerstation in real time, the communication management machine manages interaction and transmission of various monitoring data of the roof photovoltaic power station, and the remote monitoring mobile phone remotely checks, stores and processes various monitoring data of the roof photovoltaic power station in real time. The fault detection subsystem comprises a detection unmanned aerial vehicle and isused for carrying out conventional inspection and fixed-point detection of a specified area on the photovoltaic roof assembly so as to automatically identify and position faults of the assembly; andthe roof cleaning subsystem comprises an intelligent cleaning machine and a charging bin, the intelligent cleaning machine is used for carrying out conventional cleaning on the photovoltaic roof assembly and carrying out fixed-point cleaning and recycling on general shelters, and the charging bin is a storage place of the intelligent cleaning machine and is used for charging and protecting the intelligent cleaning machine.

The invention discloses an intelligent operation and maintenance system of a video monitoring box. The intelligent operation and maintenance system comprises a monitoring box state intelligent maintenance terminal and an Internet-of-Things platform, the monitoring box state intelligent maintenance terminal is connected with the Internet-of-Things platform; the monitoring box state intelligent maintenance terminal comprises a core controller and a communication module, and the core controller is connected with the video monitoring box; and the core controller is used for detecting the working state of the video monitoring box, judging whether the video monitoring box breaks down or not and sending the working state of the video monitoring box to the Internet-of-Things platform through the communication module. According to the method, the working state of the video monitoring box can be detected through the monitoring box state intelligent maintenance terminal, and the fault is reported to the Internet-of-Things platform when the video monitoring box sends the fault, so that intelligent operation and maintenance of the video monitoring box are realized, fault information can be accurately positioned, the labor cost is saved, the repair time is shortened, and the urban management level is improved.

The invention provides a railway power supply equipment state abnormity alarm realization method based on deep learning LSTM. The method comprises the following steps: 1, presetting a power supply equipment detection sensor, building a time sequence, and obtaining an experiment data set corresponding to each time step under the time sequence and aiming at the power supply equipment; 2, carrying out descrambling on the experimental data to obtain training data beneficial to evolutionary characteristics; 3, constructing an LSTM network model, inputting the training data as training feature information into the LSTM network model, and training to obtain a training model; and 4, carrying out model prediction on the training model, measuring the deviation of a model prediction value, and visualizing a prediction result based on a histogram. A deep network architecture is adopted for the long-short-term memory network, so that fault features can be automatically recognized from various sensor information of the transformer, the evolution trend of faults can be predicted, and the technical guarantee is provided for intelligent operation and maintenance of the transformer.