375 results about "It equipment" patented technology

The invention discloses an intelligent management method and system for IT equipment asset maintenance, and relates to the technical field of intelligent management. During system operation, multi-dimensional parameters of IT equipment are collected in real time and transmitted to a data processing module, the collected data are preprocessed, the current state of the equipment is comprehensively analyzed, and the health state coefficient Hstate of the equipment is calculated; the method comprises the following steps: acquiring a current equipment operation state, performing baseline establishment on historical operation data of the equipment, comparing the current state with the historical data, analyzing the performance trend and change of the equipment, calculating to obtain a trend analysis coefficient Ttend, and identifying potential problems and performance reduction trend of the equipment through long-term data accumulation. And calculating a final fault prediction probability index Pfault, comparing the final fault prediction probability index Pfault with a set threshold value, obtaining a grade prediction scheme, generating early warning information, prompting a system administrator to sort and distribute according to the urgency and priority of tasks, automatically generating a comprehensive report by the system, and providing decision support for the administrator.

The invention is suitable for the technical field of machine rooms, and provides a machine room environment management and control method based on a digital twinning technology, which comprises the following steps: constructing a digital twinning machine room model based on a three-dimensional structure of a machine room and a machine room equipment layout; real-time load data of each IT device, real-time power data of each cooling device and environmental parameter data of each type of sensor are obtained, thermal load distribution of the machine room is predicted, a preset environmental control strategy is combined, corresponding working conditions are simulated and generated for the machine room in a digital twin machine room model, PUE values of the machine room under the working conditions are obtained through calculation, and the PUE values of the machine room under the working conditions are obtained. Dynamically adjusting an environment control strategy; running state parameters of the IT equipment and video image data in the machine room are obtained in real time, the running state parameters and the video image data are analyzed, and potential abnormal equipment and abnormal areas are determined in the digital twin machine room model. According to the invention, comprehensive optimization of machine room energy efficiency, operation and maintenance efficiency and environment resource configuration is realized, and the intelligent level of machine room management and control is improved.

An information technology equipment enclosure comprises a plurality of IT components, cold plates disposed over at least two of the IT components, and a cooling fluid manifold disposed within the IT equipment enclosure. The coolant liquid manifold has multiple input connectors and multiple output connectors. Each of the cold plates are coupled to the cooling fluid manifold using a coolant line attached to one of the input connectors and a coolant line attached to one of the output connectors. An input cooling liquid line couples the coolant liquid manifold to an output of an external liquid cooling system, and an output liquid line couples the coolant liquid manifold to an input of the external liquid cooling system. The coolant liquid manifold is configured to receive cooling fluid from the external liquid cooling system and to distribute the cooling fluid to all of the cold plates via the input connectors.

The invention provides a cooling liquid flow regulation and control method and system for an immersed liquid cooling system, and the method comprises the steps: obtaining a set temperature of the liquid cooling system, obtaining a power interval of a liquid cooling distribution unit and a rotating speed interval of a cooling water pump based on the set temperature of the liquid cooling system, defining a first random process based on a Monte Carlo algorithm, and obtaining a first random liquid cooling sample; defining a second random process based on a random forest algorithm and obtaining a second random liquid cooling sample, executing a particle swarm optimization algorithm on the first random liquid cooling sample to obtain a first optimized liquid cooling regulation and control parameter, executing the random forest algorithm on the second random liquid cooling sample to obtain a second optimized liquid cooling regulation and control parameter, based on the root locus diagram of the liquid cooling second-order transfer function, stability judgment is carried out, and optimized liquid cooling regulation and control parameters or fused liquid cooling regulation and control parameters are obtained; and importing the optimized liquid cooling regulation and control parameters or the fused liquid cooling regulation and control parameters into a liquid cooling regulation and control module, thereby improving the cooling effect of the immersed liquid cooling system on a server or IT equipment.

The invention discloses a cave depot type data center based on underground river construction and a construction method and an operation method thereof, and belongs to the technical field of cave depot type data center construction. The data center comprises a mountain body, an underground river is developed in the mountain body, the underground river flows through a karst cave in the mountain body, a plurality of equipment storage tunnels are arranged on one side or two sides of the underground river in the mountain body, and the equipment storage tunnels are communicated with the karst cave through slope connecting tunnels. An equipment cabinet and a liquid heat exchanger are arranged in the equipment storage tunnel, a river water conveying assembly is connected to the liquid heat exchanger, and the end, away from the liquid heat exchanger, of the river water conveying assembly penetrates through the slope connection tunnel and extends into the underground river. The liquid cooling mode is adopted for cooling and heat dissipation of the equipment cabinet, the direct temperature control mode remarkably improves the heat dissipation and cooling effects of the IT equipment cabinet, meanwhile, the heat exchange efficiency is high, and the operation energy consumption of a data center can be reduced.

The invention relates to the technical field, in particular to a credit-based IT equipment lease management system, which comprises a credit state recognition module, an equipment matching and screening module, a lease term behavior monitoring module, an equipment state rechecking module and a lease permission backtracking module. According to the method, the dynamic credit label is formed by extracting the credit score change trend of the service party and combining the task emergency degree, intelligent judgment on resource priority configuration is achieved, and in the equipment screening link, a scheduling combination is accurately constructed through purpose consistency comparison and historical adaptation data screening, the matching efficiency is improved, and the matching efficiency is improved. In the operation process, multi-dimensional behavior data is collected and equipment self-inspection information is combined to realize joint identification of abnormal use, interface response analysis is used to guide servicing task assignment, and a closed-loop treatment system of pre-rental evaluation, in-rental monitoring and post-rental management and control is constructed by combining service party score fluctuation and equipment credit bearing limit.

The invention relates to a virtual power plant optimization operation method and system based on data center shared energy storage and load space-time migration, and the method comprises the steps: quantifying the electric energy utilization efficiency of a data center according to the power consumption of IT equipment, the power consumption of refrigeration equipment and the power consumption of other auxiliary equipment in a data center power consumption model; in the load space-time migration model, delay processing time calculation is carried out on batch processing loads, and the load migration amount across the data centers is calculated among the data centers; dynamically distributing the energy storage capacity of each data center in the shared energy storage model, and sharing the energy storage investment cost by adopting a Shapley value; in the double-layer optimization model, the upper-layer model generates an electricity price signal and a demand response instruction according to the wind and light output prediction data, the real-time electricity price of the power grid and the initial load demand of each data center, and transmits the electricity price signal and the demand response instruction to the lower-layer model; and the lower-layer model feeds back the obtained data center response and the electrical load to the upper-layer model. Compared with the prior art, the method has the advantages of high collaboration, high efficiency, high consumption and the like.

The invention discloses a server and an equipment monitoring system and method thereof, and relates to the technical field of servers, the server comprises a first controller and a second controller, the first controller in an interconnection resource module interacts with firmware of an exchange component connected with an acceleration card in the interconnection resource module, and the first controller is connected with the second controller. The method comprises the following steps: acquiring identification information of acceleration cards connected under a plurality of switching ports of a switching component by a second controller, and determining monitoring modes of all local acceleration cards in a first computing resource module where the second controller is located by the second controller according to the identification information of all acceleration cards acquired by the first controller, the local acceleration cards are respectively monitored according to the corresponding monitoring modes, so that the technical problems that the undistributed acceleration cards cannot be identified by the system and the monitoring link cannot be established are solved; the technical effects of dynamically identifying the types of the acceleration cards under different heterogeneous acceleration card resource pool configurations and adopting corresponding monitoring logic to realize out-of-band monitoring are achieved.

The invention discloses an energy-saving economic dispatching method for a data center energy system based on a prediction model. The method comprises the following steps: establishing a digital twinborn model of the data center energy system; dividing the data center into a plurality of energy consumption partitions, and installing a temperature acquisition device in each energy consumption partition; after a cooling capacity demand prediction model of the data center under each time period partition is established, target combination parameters and target energy efficiency indexes PUE of the chilled water temperature and the air supply temperature of a refrigeration subsystem under each time period are obtained through calculation; establishing a data center energy efficiency index PUE prediction model, and establishing an upper-layer refrigeration subsystem optimization scheduling model by taking the minimum deviation between an energy efficiency index PUE prediction value and a target energy efficiency index PUE, the minimum deviation between actual combined parameters of chilled water temperature and air supply temperature and target combined parameters and the minimum cold capacity supply and demand deviation of each partition as targets; and establishing a lower-layer data center optimization scheduling model by taking the minimum power utilization operation cost of the system and the minimum load migration cost of the IT equipment as a target.

The invention discloses an IT equipment maintenance task dynamic scheduling method fused with fault prediction, and relates to the technical field of maintenance task scheduling. The IT equipment maintenance task dynamic scheduling method fused with fault prediction comprises the following steps: constructing an equipment state spatial-temporal characteristic matrix and a historical fault frequency matrix of IT equipment, and determining an occurrence frequency matrix of each fault type of the IT equipment in combination with a working condition correction factor stored in a database; determining a fault maintenance task amount based on the number of IT devices and the occurrence frequency matrix of each fault type; according to the system and the method, the expected completion state of the fault maintenance task is determined based on the current working state of the resident maintenance personnel, and the working mode and personnel of the resident maintenance personnel are adjusted based on the expected completion state of the fault maintenance task, so that the fault quantity can be intelligently evaluated, and the manual workload distribution can be optimized to improve the fault repair efficiency. Downtime is reduced, and user experience is improved.

The invention relates to the field of power systems, and discloses a multi-agent deep reinforcement learning-based power grid power failure arrangement system, which comprises an arrangement problem conversion module and a decision solving module, the arrangement problem conversion module is used for converting a power grid power-cut plan arrangement problem into a multi-agent Markov decision process model; and the decision solving module is used for carrying out training solving on the multi-agent Markov decision process model by utilizing a multi-agent depth deterministic strategy gradient algorithm under set relevant constraints of power grid power failure arrangement to obtain a power grid power failure arrangement strategy. The scheme is inspired by a single-agent reinforcement learning thought, a power grid power-cut plan arrangement problem is converted into a multi-agent Markov decision process, power equipment is regarded as an independent agent, equipment with an intelligent power-cut plan arrangement function is trained by adopting a multi-agent depth deterministic strategy gradient algorithm, and the power-cut plan arrangement problem is solved. And an optimal power-cut plan arrangement strategy is learned, so that safe operation of a power grid and equipment thereof is ensured.

The invention discloses a root cause analysis method based on an IT operation and maintenance system, and the method comprises the steps: obtaining the physical position data and real-time environment data of IT equipment, carrying out the matrix construction through a dual topological relation based on the physical position data and the real-time environment data, and obtaining an IT equipment spatial topological matrix containing environmental impact factors. And obtaining operation state data of the IT equipment, performing spatio-temporal conjoint analysis and dimension reduction based on the operation state data and the IT equipment spatial topology matrix to obtain IT equipment dynamic prediction data, and obtaining an IT equipment state dynamic prediction curve according to the IT equipment dynamic prediction data. If the IT equipment state dynamic prediction curve monitors abnormity, a fault propagation path is generated through a reinforcement learning algorithm, and IT equipment fault root causes are determined in combination with a multivariate fault knowledge graph and a causal graph model. According to the method, the problem of early warning lag of the IT operation and maintenance system can be solved, and the problem that root cause positioning has high dependence on artificial experience is solved.

The present invention discloses a cave-type data center constructed based on an underground river, as well as its construction method and operation method, belonging to the technical field of cave-type data center construction. The data center includes a mountain body, in which an underground river is developed, and the underground river flows through a karst cave in the mountain body. On one side or both sides of the underground river in the mountain body, a number of equipment storage tunnels are provided. The number of the equipment storage tunnels are respectively connected to the karst cave through a slope connecting tunnel. An equipment cabinet and a liquid heat exchanger are arranged in the equipment storage tunnel. A river water conveying assembly is connected to the liquid heat exchanger. One end of the river water conveying assembly far away from the liquid heat exchanger passes through the slope connecting tunnel and extends into the underground river. The liquid cooling method is used to cool and dissipate heat from the equipment cabinet. This direct temperature control method significantly improves the heat dissipation and cooling effect on the IT equipment cabinet. At the same time, the heat exchange efficiency is high, and the operation energy consumption of the data center can be reduced.

The invention discloses an intelligent operation and maintenance early warning method and device for IT equipment and a medium, and the method comprises the steps: collecting multi-dimensional perception data corresponding to the IT equipment through a pre-deployed distributed probe, so as to construct a multi-dimensional real-time perception data set corresponding to the IT equipment, the method comprises the steps of obtaining current equipment attribute information of IT equipment, determining a dynamic confidence interval corresponding to the IT equipment based on the current equipment attribute information and a pre-constructed equipment health baseline model, and when it is monitored that operation of the IT equipment is abnormal based on the dynamic confidence interval and a multi-dimensional real-time perception data set, determining whether the IT equipment is abnormal or not based on a pre-constructed equipment association map. Predicting a propagation path corresponding to the IT equipment, determining a fault propagation path corresponding to the IT equipment, carrying out the impact degree evaluation of the impact equipment according to the fault propagation path and the equipment service information of a plurality of impact equipment, and determining a fault risk index corresponding to each impact equipment, so as to carry out the fault risk early warning.

The invention relates to the technical field of construction site monitoring, in particular to a construction site monitoring system and equipment based on a remote sensing image technology, and the system comprises a remote sensing image collection module, an unmanned aerial vehicle platform, a low-orbit satellite platform and a ground mobile platform which all acquire remote sensing images of a construction site through sensors; the multi-modal fusion module is used for performing data fusion processing according to the remote sensing image to obtain multi-modal data; when the system is used, the unmanned aerial vehicle platform, the low-orbit satellite platform and the ground mobile platform are used for collecting remote sensing image data, various targets on a construction site are conveniently and accurately recognized, misrecognition is reduced, and the system is beneficial for images under complex environments such as different illumination and weather conditions and images under the complex background of urban buildings. The construction site target is identified and positioned, and in a data-deficient and new construction site environment, the self-supervised learning and transfer learning technology can effectively improve the learning ability of the model, reduce the dependence on annotated data, and quickly adapt to new task requirements.

The invention relates to a data center equipment type selection method based on electrical and heating ventilation load linkage, and belongs to the technical field of data center infrastructure design. The model selection method comprises the steps of setting basic data, obtaining the number of machine rooms and the number of IT devices in a single machine room, obtaining the total power of the IT devices, setting an energy efficiency index set value, obtaining the project power consumption scale, obtaining the total cooling load, selecting models of air conditioners at the tail ends of the machine rooms and substations, selecting models of water chilling units, selecting models of heat exchangers, selecting models of cooling water pumps and chilled water pumps and selecting models of cooling towers. And obtaining the total power of the air conditioner, obtaining an energy efficiency index accounting value, and carrying out PUE verification. According to the method, through closed-loop iteration of electrical load-heating and ventilation load-PUE, model selection and quantity selection of all key equipment are completed at a time; professional splitting, repeated adjustment and modification and capacity redundancy caused by traditional serial design are avoided, the design period is remarkably shortened, and initial investment is reduced.

Data center assemblies include first and second arrays of information technology (IT) equipment cabinets defining a hot aisle. The data center assemblies also include an air containment assembly fluidly coupled to the hot aisle, at least one air-cooling unit fluidically coupled the air containment assembly, and / or at least one liquid-cooling system fluidically coupled to at least a portion of the IT equipment cabinets. The at least one fluid-cooling system includes a heat exchanger fluidically coupled to a cooling liquid loop and a fluid pump fluidly coupled to the heat exchanger and the at least a portion of the IT equipment cabinets. The air-cooling units and liquid-cooling systems may be designed to be interchangeable, allowing for seamless adaptation to changes in the number and types of IT equipment cabinets in a data center pod. The types of IT equipment cabinets may include air-cooled and liquid-cooled IT equipment cabinets.

The invention provides a shunting network simulation model construction method and system for a liquid cooling cold plate, and the method comprises the steps: S1, obtaining the distribution positions of IT equipment elements, building a two-dimensional IT simulation plane, S2, obtaining the constraint conditions of the cold plate, building a two-dimensional network simulation plane, carrying out the heat source grade marking of the two-dimensional network simulation plane, and carrying out the heat source grade marking of the two-dimensional network simulation plane. The method comprises the following steps: performing unit division on a two-dimensional network simulation plane and performing shunting network connection in a step S3 to generate a plurality of three-dimensional shunting network models, performing analogue simulation in a step S4, performing discrimination operation, executing a step S5 or a step S6 based on the discrimination operation, if the step S5 is executed, generating a plurality of improved three-dimensional shunting network models based on a shunting improved model, and if the step S5 is executed, performing shunting network connection on the improved three-dimensional shunting network models. And S4, if the step S6 is executed, sorting output is carried out on the three-dimensional shunting network model based on the judgment operation, a designer can refer to the three-dimensional shunting network model to design the shunting network of the liquid-cooling cold plate, and the research and development rate is improved.

The invention discloses a data center micromodule inter-row air conditioner joint optimization scheduling method and system, and the method comprises the steps: collecting the temperature and wind speed of an air outlet of each inter-row air conditioner at the same moment and the temperature data of a rear measurement point of each IT equipment cabinet in a single micromodule of a data center, and constructing a data set; a temperature prediction model of the incidence relation of the inter-row air conditioner air outlet temperature, the air speed and the case rear measuring point temperature is built; training a temperature prediction model by using the training set, and optimizing intermediate vector dimensions output by an LSTM layer and an Attention layer to obtain a trained temperature prediction model; the inter-row air conditioner air outlet temperature and the air speed set value are adjusted, the temperature prediction model is input, and an inter-row air conditioner joint optimization dispatching value is formed based on the inter-row air conditioner air outlet temperature and the air speed set value; according to the invention, the method of association relation mining and joint optimization scheduling is adopted, and the temperature balance of the IT equipment cabinet measuring points in the data center micro-module under the condition of load change is rapidly realized.

The invention relates to the technical field of data center management, and discloses a prefabricated cabin type data center monitoring system, which comprises a data acquisition module arranged in a prefabricated cabin and used for acquiring environment data, electric power data and IT equipment operation state data in the cabin, converting the acquired data into a standardized data format, and transmitting the standardized data format to a server through a protocol conversion interface; and uniformly converting the acquired data of different communication protocols into a preset standard data format. A data cleaning and compression mechanism is designed in an edge calculation module, collected environment data, power data and IT equipment operation state data are preprocessed in real time, abnormal data are rapidly judged based on set upper and lower limit values, the abnormal data are marked as alarm data and are preferentially transmitted to a subsequent module, transmission of invalid data is reduced, and the efficiency is improved. The network bandwidth utilization rate is improved, rapid fault detection and response are realized, and the fault diagnosis and repair time is shortened.

The invention discloses a flight data safety management method applied to low-altitude economy, and relates to the technical field of data management, and the method comprises the steps: obtaining heterogeneous monitoring data of an infrastructure and IT equipment in real time; calculating the health degree score and the fault risk probability of each logic area in the low-altitude economic flight data center in real time; based on the health degree score and the fault risk probability, root cause analysis is carried out in combination with a pre-constructed operation and maintenance knowledge graph, and an optimal operation and maintenance disposal plan is generated through matching; and converting the generated operation and maintenance disposal plan into a specific automatic instruction. The method has the advantages that through deep fusion and conjoint analysis of multi-modal data, accurate and panoramic perception of the health state of the low-altitude economic flight data center and prospective prediction of the fault risk are realized, and through automatic execution and a closed-loop feedback mechanism, the safety of the low-altitude economic flight data center is improved. A traditional operation and maintenance mode which is passive in response and highly depends on manpower is converted into a closed-loop autonomous mode which is active in early warning, intelligent in decision making and autonomous in execution.

The invention discloses a green cave depot type data center operated through hydraulic power and a construction method and an operation method of the green cave depot type data center, and belongs to the technical field of cave depot type data center construction. The data center comprises a river channel and a mountain body, a river water storage tunnel and a plurality of equipment storage tunnels are arranged in the mountain body, the river water storage tunnel is communicated with the river channel, the equipment storage tunnels are communicated with the river water storage tunnel through slope connecting tunnels, equipment cabinets and liquid heat exchangers are arranged in the equipment storage tunnels, and the equipment cabinets are communicated with the liquid heat exchangers through slope connecting tunnels. The liquid heat exchanger is connected with the equipment cabinet through a cooling liquid conveying assembly, the liquid heat exchanger is connected with a river water conveying assembly, and the end, away from the liquid heat exchanger, of the river water conveying assembly extends into the river water storage tunnel. The liquid cooling mode is adopted for cooling and heat dissipation of the equipment cabinet, the direct temperature control mode remarkably improves the heat dissipation and cooling effects of the IT equipment cabinet, meanwhile, the heat exchange efficiency is high, and the operation energy consumption of a data center can be reduced.

Data center assemblies include first and second arrays (110a, 110b) of information technology (IT) equipment cabinets (115) defining a hot aisle 112). The data center assemblies also include an air containment assembly (125) fluidly coupled to the hot aisle (112), at least one air-cooling unit (122a-122c) fluidically coupled the air containment assembly (125), and / or at least one liquid-cooling system (222, 322, 922) fluidically coupled to at least a portion of the IT equipment cabinets (115). The at least one liquid-cooling system includes a heat exchanger (1102) fluidically coupled to a cooling liquid loop and a fluid pump (1104) fluidly coupled to the heat exchanger (1102) and the at least a portion of the IT equipment cabinets (115). The air-cooling units and liquid-cooling systems may be designed to be interchangeable, allowing for seamless adaptation to changes in the number and types of IT equipment cabinets in a data center pod. The types of IT equipment cabinets may include air-cooled and liquid-cooled IT equipment cabinets.

Disclosed are a data transmission method and a data reception method of a wireless communication system and a device thereof. A terminal of the wireless communication system includes a communication module and a processor, and the processor is configured to control the communication module. The processor receives a radio resource control (RRC) signal from a base station of the wireless communication system through the communication module, and determines a time-frequency resource corresponding to at least one resource set indicated by the RRC signal. The processor receives a physical control channel from a base station through the communication module, determines a time-frequency resource domain in which a physical data channel of a terminal is scheduled to be received through the physical control channel, and receives a physical data channel based on the time-frequency resource in which the physical data channel of the terminal receives the scheduled time-frequency resource and the time-frequency resource in which at least one resource set overlaps. The resource set is a collection of time-frequency resources.

The utility model relates to a mobile cold source for an immersed liquid cooling data center, which comprises a mobile cabinet, and a high-temperature liquid cooling liquid pipeline, a liquid pump, a heat exchanger, a compression refrigerating machine, a cold storage unit and a low-temperature liquid cooling liquid pipeline which are arranged on the mobile cabinet, and high-temperature liquid cooling liquid sequentially flows through the high-temperature liquid cooling liquid pipeline, the liquid pump and the heat exchanger. The compression refrigerator is used for refrigerating the heat exchanger; a liquid cooling liquid outlet of the heat exchanger is connected to a low-temperature liquid cooling liquid pipeline through a first valve and is also connected to the low-temperature liquid cooling liquid pipeline through a cold storage unit; the movable cold source further comprises a storage battery which is used for supplying power. The movable cabinet design is adopted, so that the device is convenient to move and can directly reach an inspection and maintenance point; besides, the compression type refrigerating machine and the cold storage unit are integrated, the dual functions of double cold sources and cold storage are achieved, and the functions of non-stop on-line maintenance and on-line cold storage module replacement of IT equipment can be achieved.

The invention discloses an intelligent equipment management method and an equipment management system thereof, and relates to the technical field of equipment management.The method comprises the steps that key operation parameters of equipment are collected through multiple types of sensors, and data processing is executed; transmitting the encrypted data to a central node in real time through a communication module, and completing data cleaning and redundant backup; performing training, prediction, diagnosis and result generation on the equipment state by using a decision tree model in an artificial intelligence engine; according to the intelligent analysis result, fault warning, authority verification and control instruction issuing execution are carried out through the terminal module; and collecting execution feedback data, continuously optimizing the decision tree model, and realizing equipment management closed loop and intelligent evolution. The invention provides an intelligent equipment management method and system integrating multi-source sensing, decision tree intelligent analysis, security authentication and multi-level control, real-time monitoring, fault prediction and automatic control of the equipment state are realized, and the intelligence and reliability of equipment management are improved.

The present invention relates to the field of IT operation and maintenance technology, and in particular to an IT operation and maintenance intelligent management system, which realizes the precise positioning of equipment in an office building through an IT equipment positioning module. Each device is equipped with a Bluetooth device to synchronize the location information and operating status to a cloud management module in real time. When a device fails, the system quickly obtains the device location information through automated monitoring, which reduces the reliance on manual troubleshooting and significantly shortens the time for maintenance personnel to locate the fault. By tracking the location of maintenance personnel in real time and combining the data of faulty equipment, the optimal scheduling plan is automatically generated using a reinforcement learning model to ensure that the nearest maintenance personnel arrive at the faulty equipment in the shortest time, thereby improving operation and maintenance efficiency. Based on operation and maintenance data analysis, the optimal maintenance plan is generated using an equipment similarity algorithm, the faulty equipment is matched with historical maintenance records, and efficient maintenance methods are automatically recommended to reduce human judgment errors and further shorten fault repair time.

The invention relates to an operation and maintenance factory visualization system based on data processing, belongs to the field of data processing specially suitable for administrative, commercial, financial, management, supervision or prediction purposes, and particularly relates to the field of big data processing. Based on data processing and artificial intelligence technologies, the operation and maintenance factory visualization system is developed, intelligent analysis and prediction are carried out by collecting and analyzing the IT equipment of the IDC machine room and mass operation and maintenance data of applications in real time and utilizing an AI algorithm realized based on an intelligent analysis and prediction model, and the operation and maintenance efficiency is improved. The equipment fault information and the application fault information of the set IDC machine room in the next time segment of the current time segment are obtained, so that the equipment fault information and the application fault information are synchronously displayed when the IDC machine room operation and maintenance system carries out transparent factory type assembly line visual display on various operation and maintenance works of the set IDC machine room on a visual interface. Therefore, operation and maintenance personnel are helped to master and set the running state of the IDC machine room in time.

The invention relates to a virtual power plant-oriented data center resource scheduling method, equipment and medium, and the method comprises the steps: carrying out the multi-time scale division and dynamic characteristic decoupling of IT equipment, energy storage system and refrigeration system resources, and forming a decoupling resource model; dividing a high-collaboration resource cluster, and calibrating an elastic capacity boundary of the resource cluster; solving a multi-market collaborative optimization model in a global optimization layer at a first preset time scale according to the electric power information, the carbon information and the computing power demand information, and generating a day-ahead baseline strategy; carrying out distributed decision making by adopting a federal reinforcement learning framework at a local decision making layer based on the day-ahead baseline strategy and the real-time operation data at a second preset time scale, and generating a real-time regulation and control instruction; and when a trigger event is monitored, triggering the global optimization layer to re-plan the day-ahead baseline strategy, issuing a re-planning result to a local decision-making layer, and updating a real-time regulation and control instruction. Compared with the prior art, the method has the advantages of high reliability, collaboration, robustness and the like.

The invention discloses a group control method and device for air conditioners in a machine room, terminal equipment and a storage medium, and belongs to the field of air conditioner control. The method comprises the steps that the environment temperature of the machine room and the actual operation total power of all I T equipment are collected, and whether local hot spots exist in the machine room or not is judged; if yes, the hotspot grade corresponding to the local hotspot is judged according to the machine room environment temperature, and the air conditioner air volume of the area corresponding to the local hotspot is adjusted according to the hotspot grade; if not, the actual total operation power is larger than the first preset threshold value, the air conditioner temperature of all the areas is gradually reduced through gradient cooling, and the state of the machine room is monitored after the air conditioner temperature is reduced every time; when monitoring that the machine room state exceeds a first preset time, if the machine room state does not meet a preset state; if yes, the air conditioner air volume and the air conditioner temperature of each area are set in a rollback mode according to the recently recorded parameter snapshots. The problem of how to improve the regulation and control reaction speed while ensuring the accuracy of the group control process of the air conditioners in the machine room can be solved.