69results about How to "Realize refined management" patented technology

The invention relates to a multi-channel firmware upgrading method and system supporting breakpoint resume, and the method comprises the steps: segmenting a firmware file into a plurality of firmware data blocks, and generating a unique identifier and a checksum for each firmware data block; acquiring a network transmission channel, performing task matching with the network transmission channel according to the unique identifier to obtain a corresponding distribution transmission task, and establishing a corresponding initial record document; transmitting the firmware data block through the network transmission channel according to the distribution transmission task, monitoring the transmission state in real time, and carrying out breakpoint record updating on the initial record document to obtain a corresponding updated document; when it is detected that transmission is completed, verifying the firmware data block according to the checksum, and recombining the firmware data block to obtain the firmware file; and generating a corresponding upgrading report based on the updating document and the upgrading information. The upgrading strategy can be continuously optimized, and the system management efficiency can be improved.

The invention discloses a life cycle visual management method based on data, and relates to the technical field of data management. The method comprises the following steps: 1, data acquisition and identification; 2, classifying and dividing data life cycle stages; 3, data state monitoring and updating; 4, recording and associating data operation; step 5, constructing a data life cycle visual framework; step 6, data life cycle decision analysis optimization; 7, performing data archiving and deletion management; according to the invention, fine management of the whole life cycle of the data is realized, and the systematic method not only improves the efficiency of data processing, but also enhances the transparency of data management, so that managers can monitor the data state in real time, quickly respond to the data problem, optimize the data circulation process and improve the overall operation efficiency. Through application of a data visualization technology, complex data information is displayed in a visual and understandable form, and managers are helped to better understand data dynamics.

The invention provides a bidirectional parallel storage battery capacity checking system and method, and relates to the field of battery capacity checking, and the system comprises a station control system, a plurality of direct current buses, an alternating current bus, a plurality of storage battery packs, a battery optimizer and a bidirectional charging and discharging module, and is used for realizing storage, charging and discharging management and online capacity checking of storage batteries. The storage battery pack comprises a plurality of battery modules connected in parallel, and each battery module comprises storage batteries managed in pairs and a charging and discharging control circuit and is used for managing the charging and discharging states of the storage batteries. According to the capacity checking system and method provided by the invention, capacity checking is allowed to be carried out on a single battery pack, the storage batteries needing capacity checking can exit independently, and other battery packs continue to supply power normally under the condition that the overall power supply is not influenced, so that the parallel connection mode not only avoids power interruption and resource waste, but also realizes fine management of the battery packs, and the power supply efficiency is improved. The service life of the storage battery is prolonged, and the continuity and the stability of a power system are ensured.

The invention discloses a point shopping mall service method and system based on user behaviors, and relates to the technical field of point shopping malls. Comprising the steps of collecting behavior data of a user in real time and generating a behavior feature vector; on the basis of the behavior feature vector and the life cycle stage of the user, personalized integral commodities and activities are recommended; user integral history is analyzed, an integral strategy is dynamically adjusted, and customized incentives are provided for different types of users; automatically managing the period of validity of the points, reminding the user of the points to be expired, and guiding the user to consume the points in time in combination with the personalized point commodities and activities; the integral strategy is updated regularly, the excitation mode is optimized according to the user behavior change, and the adaptability and the user experience are improved. According to the invention, by dynamically adjusting the point strategy and combining point validity period management, the user is helped to timely consume points about to be expired, and point loss is reduced.

The invention provides an intelligent fault diagnosis and early warning system for digital mechanical equipment. The system comprises a data acquisition module, a feature extraction module, an optimization training module and a diagnosis and early warning module. The data acquisition module collects historical operation data such as equipment state parameters and fault characteristic parameters. The feature extraction module inputs historical data to a network, outputs equipment state features and fault features, and further obtains a fault diagnosis probability, an evaluation value, an early warning level and an evaluation value. And the optimization training module optimizes the network based on the evaluation value and the probability until a preset number of iterations is reached, and a trained diagnosis decision network is obtained. And the diagnosis and early warning module inputs the current equipment operation data into the network to realize fault diagnosis and early warning. According to the invention, accurate diagnosis and real-time early warning of mechanical equipment faults can be realized, the reliability and maintenance efficiency of equipment operation are improved, and the downtime and maintenance cost of faults are reduced.

The invention discloses a power transmission line foreign matter identification method and system based on an improved YOLOv10 model. Relates to the technical field of power transmission line detection. According to the method, the method is improved on the basis of the existing target detection technology in the scene of a special power transmission line, the structure of a YOLOv10 model is optimized and improved by introducing an ODConv dynamic convolution module, a CAFM hybrid convolution attention mechanism module and an NWD loss function on the basis of the YOLOv10 model, in the detection stage, foreign matters are recognized through a foreign matter detection model, and the foreign matters are recognized through a foreign matter recognition module. Inputting the image containing the foreign matter into a component detection model to determine the position of the component, and finally performing hazard assessment and making a response according to the relative position of the foreign matter and the component. The detection precision of the YOLOv10 model is effectively improved, the hazard assessment capability is improved, and the detection efficiency is improved, so that the efficiency of foreign matter removal work of the power transmission line is improved, data management can be performed, powerful support is provided for operation and maintenance of the power transmission line, and safe and stable operation of electric power is guaranteed.

The invention provides an elevation data measurement method, device and equipment for a large-fall area, and relates to the technical field of engineering survey and geological survey. The method comprises the following steps: acquiring level gauge height difference data and measurement gravity data of each measurement point in a large-fall measurement area; carrying out regional division on the large-fall measurement region to obtain measurement sub-regions, and determining a gravity interference coefficient corresponding to a measurement point according to measurement gravity data and regional environment data of the measurement sub-regions; determining corrected gravity data based on the gravity interference coefficient and the measured gravity data, and determining an elevation correction item and measured elevation data; and correcting the measured elevation data according to the elevation correction item to obtain corrected elevation data corresponding to the large-fall measurement area. According to the technical scheme, the reliability and precision of elevation data measured by the level gauge in a large-fall area can be effectively improved.

The invention relates to the technical field of lithium metal battery health monitoring, and particularly discloses a lithium metal battery pack health monitoring system and method based on thin film sensors, the system comprises a plurality of thin film sensors distributed among lithium metal battery pack cells, and each thin film sensor comprises a temperature measuring unit, a pressure measuring unit, a flexible circuit board and silica gel foam; the adapter plate is electrically connected with the plurality of thin film sensors; the signal acquisition unit is electrically connected with the adapter plate and comprises a constant current source circuit, a signal conditioning circuit, a filter circuit and an analog-to-digital conversion circuit; the input end of the data transmission unit is electrically connected with the output of the analog-to-digital conversion circuit; the input end of the digital signal processor is electrically connected with the output end of the data transmission unit; and the input end of the battery management unit is electrically connected with the output end of the digital signal processor. The mechanical information and the temperature information between the battery monomers can be monitored at the same time, the battery management can evaluate the health state of the battery more comprehensively based on the information, and the abnormal problem can be warned in advance.

The invention discloses a deepwater net cage fish feeding control method and system, and the method comprises the steps: generating a cultured fish detail list in a target deepwater region according to the fish information, and carrying out the multi-round spiced salt denoising processing of the obtained image data of the target deepwater culture region, inputting the underwater light data into the water body thermal stratification model to obtain each deepwater hierarchy and short wave radiation data corresponding to each deepwater hierarchy; and analyzing and identifying the image data through an AI graph identification algorithm to obtain fish growth data, constructing a feeding amount control model according to a cultured fish detail list, the fish growth data and the short-wave radiation data, and generating a culture visualization report to realize feeding control of fishes in the target deepwater culture area. Fish growth and health are analyzed through image data, a feeding control model is constructed and optimized according to data such as the ammonia nitrogen content, the dissolved oxygen content and short wave radiation, feeding amount control is optimized, the fish growth speed is increased, the fish growth quality is improved, and long-term sustainable breeding is achieved.

The invention discloses a positioning data intelligent management system and method applied to an Internet of Things product, and relates to the technical field of positioning data management, and the system comprises a distribution area analysis module, a distribution task distribution module, and a distribution unit management module. The distribution area analysis module is used for acquiring a distribution area image and map data, dividing a distribution area into path nodes and path units, marking the path nodes and the path units, and constructing a distribution path node graph; the distribution task distribution module analyzes the distribution exchange rate of the shortest distribution path of each distribution task, carries out the least grouping decision of each distribution task, and plans the distribution path of the distribution unit of each group. And the distribution unit management module determines the path units where the distribution units are located according to the real-time positioning data of the distribution units, and sets obstacle avoidance strategies when the distribution units advance according to the calculation results of the environment change rates of the path units.

The invention discloses a container wharf energy digital twinning system, and a construction method of the system comprises the following steps: obtaining wharf facility information, and carrying out the three-dimensional modeling of a wharf scene and an entity according to the facility information; constructing a wharf energy digital twin platform base; according to the incidence relation between wharf operation and energy consumption, a multi-level fusion wharf whole-process correlation analysis map is formed; constructing a wharf operation and energy index system; through a three-dimensional visual index board, wharf energy and operation situations are displayed in real time. The wharf facility information comprises a wharf construction drawing and wharf entity feature attribute information. Through the digital twinning technology, intelligent management and control of energy consumption of the container terminal and fine management of energy are achieved, and digital, intelligent and green transformation and upgrading of energy management of the container terminal are promoted.

The invention discloses an attention mechanism and residual network fused industrial user carbon emission monitoring method and device. The method comprises the following steps: S01, acquiring electrical load sequence data of a to-be-detected user and state data of all corresponding key carbon emission equipment within a specified duration, and taking the data as training sample data; s02, the training sample data are input into a network model formed by fusing an attention mechanism and a residual network for training, an equipment state recognition model is obtained, and the network model is obtained by embedding a channel attention mechanism and a BAM attention module into a contraction residual network; s03, acquiring real-time data and inputting the real-time data into the equipment state recognition model to obtain a recognition result; and S04, obtaining carbon emission factors corresponding to different equipment states, and calculating real-time carbon emission according to a real-time state identification result and the corresponding carbon emission factors. The method has the advantages of being simple in implementation method, low in cost, high in efficiency and precision, high in real-time performance and robustness and the like.

The invention relates to the technical field of sensors, in particular to a multi-sensor fusion laboratory safety alarm method and system, and the method comprises the steps: setting a sensor unit, collecting space humidity, space temperature and gas concentration, building a data prediction model, carrying out the data processing to obtain corrected humidity, corrected temperature and corrected concentration, and calculating the sensing delay. If the sensing delay is greater than a delay threshold value, switching the sensing unit, carrying out delay adjustment and switching the sensing unit again, and if the sensing delay is not greater than the delay threshold value, designing a scheduling cooperation plan, operating the sensor unit, predicting to obtain predicted humidity, predicted temperature and predicted concentration, and defining a humidity grade, a temperature grade and a concentration grade; and designing an anomaly detection rule, performing level judgment to obtain a parameter level, performing evaluation based on the parameter level and the anomaly detection rule to obtain an evaluation level, and triggering an alarm system by using the evaluation level. According to the invention, the reliability and accuracy of safety early warning can be improved.

The present invention relates to the field of environmental monitoring technology, and in particular to a coal mining environment perception system based on multi-sensor fusion, comprising a coal mining environment analysis module, an environment detection module, a regional analysis module, an environment perception module and a coal mining environment early warning module; the coal mining environment analysis module determines the coal mining environment to be perceived, and determines the functional type of each perception area; the environment detection module detects the detection information of each perception area; the regional analysis module determines the type of safety hazard in each area; the environment perception module determines the environment perception strategy according to the type of safety hazard in each perception area; the coal mining environment early warning module is used to issue early warning information; the present invention divides the coal mining area into multiple functional areas, and deploys corresponding sensors according to the characteristics and safety requirements of each area, so as to ensure the relevance and accuracy of monitoring data, and improve the pertinence of data collection and the accuracy of coal mining environment perception.

The present invention discloses a data processing system and method for the Baume degree of honeycomb honey of Chinese bees based on data analysis, and relates to the field of bee breeding technology. The system includes: a workshop monitoring module, a Baume degree detection module, a Baume degree analysis module, a honeycomb honey evaluation module, a data visualization module and a storage management module; the workshop monitoring module is used to monitor and control the temperature and humidity data in the honeycomb honey maturation workshop in real time, and record the entry and exit time and storage location of each honeycomb frame; the Baume degree detection module is used to divide the honeycomb frame into multiple detection areas, and based on microwave technology, detect the water content of the honeycomb honey in each detection area; the Baume degree analysis module is used to analyze the Baume degree distribution of all positions of the honeycomb honey according to the Baume degree of the honeycomb honey in each detection area. The present invention can monitor and control the workshop environment in real time and accurately to ensure the production quality of the honeycomb honey through the intelligent and refined management of the whole process of Chinese bee honeycomb from production to evaluation.

The invention discloses a gene sequencing data management method for whole genome methylation sequencing, and relates to the technical field of gene sequencing data management.The method comprises the steps that original gene sequencing data are obtained and preprocessed, and a regional methylation matrix is generated; calculating a technical difference measure and a phenotype difference measure of each region unit based on the region methylation matrix and the sample metadata, identifying a technical methylation bias domain, and grading the technical methylation bias domain into a steady-state technical methylation bias domain and an event-driven technical methylation bias domain according to the occurrence frequency of the technical methylation bias domain in multiple batches; based on a linear adjacency relation and a co-bias relation, constructing a technical methylation bias super-domain and classifying the technical methylation bias super-domain; performing regional shielding on the methylation bias super-domain of the steady state technology, performing normalization correction on the methylation bias super-domain of the event-driven technology, and generating a corrected regional methylation matrix; calculating a sample quality index based on the corrected matrix and performing quality grading; according to the method, technical bias can be identified and corrected, and the methylation data quality and analysis reliability are improved.

The invention relates to the field of equipment for directly conveying liquid into soil, in particular to a water and fertilizer control device for a seedbed special for potato breeding, which comprises a movable base, a liftable base frame and a conveying control member, the conveying control member comprises N outflow holes, the opening and closing states of which can be independently controlled, the N outflow holes are detachably communicated with the seedbed through N small pipes respectively; the multi-groove bed body comprises a plurality of breeding grooves, and a detection assembly which can detect the humidity of soil in each breeding groove in at least one conveying sub-area and can stretch out and draw back is further arranged above the base frame; the detection assembly comprises N non-contact soil humidity sensors used for detecting the humidity of soil in the four breeding grooves in at least one conveying sub-area. An existing water and fertilizer control device of a seedbed special for potato breeding has the problem that water and fertilizer cannot be conveyed to each potato seed in a targeted mode, and the device can convey water and fertilizer to each potato seed in a targeted mode.

The invention discloses a video content management method based on a multi-modal model, computer equipment and a medium, and belongs to the technical field of multimedia, and the video content management method based on the multi-modal model comprises the following steps: after extracting an original key frame picture from at least one video clip, obtaining a timestamp and a time point of the original key frame picture; according to the method, repeated picture content and invalid picture content of an original key frame picture are removed, then a blank screen picture is removed, vectorization processing is carried out through a CLIP model, vectorized data are obtained, automatic voice recognition is executed, and finally video metadata is generated. According to the video content management method based on the multi-modal model, video content retrieval service based on pictures or characters can be provided, delicacy management of videos is achieved, video content retrieval based on frame levels is provided, the accuracy of video content retrieval is improved, and millisecond-level retrieval of mass video content is supported.

The invention relates to the technical field of computer communication, in particular to a multi-preferential-activity parallel method and system, and the method comprises the following steps: a commodity shopping system randomly generates a preferential-activity identifier, checks whether the preferential-activity identifier exists or not, and regenerates the preferential-activity identifier until a unique preferential-activity identifier is obtained if the preferential-activity identifier exists; secondly, setting preferential configuration for the preferential activity identifier, establishing a corresponding relation between the preferential configuration and the preferential activity identifier, and storing the corresponding relation in a Redis database; a link with preferential activity identification parameters is generated; according to the method, the effectiveness and the accuracy of the preferential activities can be ensured, various discounts are allowed to exist in different regions in the same period, the purchase process of the user is simplified, the user experience is improved, meanwhile, the workload of background management personnel is relieved, and fine management of marketing activities is achieved.

The application provides a kind of shipboard aviation equipment composite material damage D-S evidence theory nondestructive evaluation method, belongs to the field of shipboard aviation equipment nondestructive evaluation, it includes the following steps: at time, the triaxial damage area characteristics and triaxial vibration frequency characteristics of the composite material structure of shipboard aviation equipment are synchronously acquired and stored;The triaxial damage area characteristics and triaxial vibration frequency characteristics at time are compared respectively, and the corresponding triaxial damage area change degree and triaxial vibration frequency change degree are obtained;The identification framework of D-S evidence theory is established, and the triaxial mass function of the composite material structure is calculated respectively;According to the created D-S damage judgment model, the classification judgment and early warning of the composite material damage of shipboard aviation equipment are carried out.The application can realize the real-time classification evaluation of the dynamic damage of the composite material component of shipboard aviation equipment, and provide data support for the condition-based maintenance of shipboard aviation equipment.

This invention discloses an automated settlement system for cross-regional power trading based on smart contracts. A feature recording module records multi-dimensional settlement characteristics of settlement data packets from power generation companies. A data preparation module, responding to the power generation company's need to send settlement data packets, generates a sending request based on the multi-dimensional settlement characteristics. A sending module processes the settlement data packets based on the sending request, encapsulating the access sequence number and key segment sequence number for synchronous transmission. A verification module verifies the settlement data packets, and the verified data packets are used to generate a trading contract through a contract trading module. Based on the trading contract, a transaction fund transfer instruction is generated. This invention automates the entire power trading settlement process, reconstructs the trust system for power trading settlement, and lays a solid foundation for building a new generation of transparent, intelligent, and efficient power market operation ecosystem.

The invention relates to an application configuration method and device and computer equipment, and the method comprises the steps: carrying out the updating processing of a target protocol folder based on a temporary storage protocol folder of obtained configuration modification information, obtaining an updated target protocol folder, and then transmitting the updated target protocol folder to an application node, and sending the updated target protocol folder to the application node, so that the application node performs application configuration loading processing according to the updated target protocol folder to obtain an application configuration loading result. According to the method and the device, the target protocol folder is updated based on the configuration modification information and the temporary storage protocol folder, so that fine management and accurate updating of the target protocol file are realized. The temporary storage protocol folder can effectively record and process various kinds of information in the configuration modification process, it is ensured that when the target protocol folder is updated, various configuration parameters are accurately modified, confusion and errors possibly caused by direct modification of the target protocol file are avoided, and therefore the accuracy and reliability of configuration updating are greatly improved.

The present application provides a personalized settlement method, system and equipment, which relates to the field of information technology, including: training and generating a power consumption optimization model by combining the user's power consumption behavior portrait, the adjustable space of the equipment, the power supply plan of the non-adjustable equipment and the power price adjustment plan; using the power consumption optimization model, for each user's adjustable equipment, in different power consumption periods, determine the optimal equipment power consumption scheduling plan and differentiated power price adjustment strategy, and generate a personalized power consumption plan; continuously monitor the real-time power grid load data, and when the load data exceeds the load threshold, trigger the dynamic optimization of the personalized power consumption plan, and perform differentiated power price adjustment and equipment power consumption scheduling for each adjustable equipment according to the optimized personalized power consumption plan. Meet the personalized needs of users, effectively balance the power grid load, and realize the refined management and optimization of smart home power consumption.

The invention belongs to the technical field of electric vehicle charging, and particularly relates to an intelligent optimization method for standby power consumption of an electric vehicle charging system. In order to overcome the defect that the existing electric vehicle charging system cannot give consideration to reduction of standby power consumption and guarantee of user experience, the invention adopts the following technical scheme: the intelligent optimization method for the standby power consumption of the electric vehicle charging system comprises the following steps: establishing a multi-stage dormant state mechanism; through a data driving method, the optimal state granularity in the multi-stage dormant state is automatically determined, and a state conversion threshold value is dynamically adjusted; acquiring an environment state sensing feature vector; a standby power consumption optimization problem is converted into a sequence decision problem, the sequence decision problem is solved according to a multi-stage dormant state mechanism and an environment state sensing feature vector, and the sequence decision problem is to determine which state conversion action should be executed at what time. The method has the beneficial effect that the dynamic balance between the standby power consumption reduction and the instant response of the charging system is ensured.

This invention discloses a monitoring method for a friction pendulum seismic isolation bearing, comprising: an upper bearing plate; a lower bearing plate; a spherical cap slider disposed between the upper and lower bearing plates; PTFE friction plates disposed at the upper and lower ends of the spherical cap slider; and a sensing mechanism disposed between the lower bearing plate and the lower PTFE friction plate, or between the lower bearing plate and the lower PTFE friction plate and between the upper bearing plate and the upper PTFE friction plate. This invention has the following advantages and effects: by employing an external resistive sensing mechanism to form the sensing module of the entire friction pendulum seismic isolation bearing, it has comprehensive monitoring functions, can acquire data such as horizontal displacement and vertical pressure in real time, and can grasp the real-time displacement and compressive stress distribution of the spherical cap slider, thereby assessing the usage status of the friction pendulum seismic isolation bearing, providing dynamic monitoring support for structural safety, facilitating the determination of whether the spherical cap slider has slipped into a dangerous area, and thus achieving refined management of the structure.

The invention relates to the technical field of electric vehicles, and discloses a low-temperature slow charging control method for a pure electric vehicle, which comprises the following steps of: in response to a low-temperature slow charging starting signal, acquiring the current charge state and the current temperature of a battery by a battery management system; if the current charge state is lower than a preset charge threshold value and the current temperature is lower than a preset temperature threshold value, the battery management system sends a maximum allowable discharge power limit value to the vehicle control unit; and the vehicle control unit receives the maximum allowable discharge power limit value, and limits the initial operation power of the battery heating device based on the maximum allowable discharge power limit value, so that the power extracted from the battery by the battery heating device does not exceed the maximum allowable discharge power limit value. According to the invention, power flow among the vehicle control unit, the battery management system, the vehicle-mounted charger and the heater can be managed cooperatively, and over-current and over-discharge faults of the battery are strictly avoided while the low-temperature heating requirement is guaranteed.

The invention discloses a traffic data processing method and device, a storage medium, equipment and a program product, which are applied to scenes of traffic data processing, directional traffic free flow and the like. The method is applied to an end-side multi-network transmission unit in a multi-network transmission system, and comprises the following steps: when a directional traffic free function is started for a service application program, obtaining configuration information containing an IP address list and CID field division information from a multi-network transmission controller; respectively establishing a first QUIC tunnel and a second QUIC tunnel with a first gateway and a second gateway in the multi-network transmission gateway according to the configuration information and a service target of the service application program; obtaining traffic data of the service application program and carrying out traffic screening to distinguish directional traffic and non-directional traffic; the non-directional traffic is sent to the first gateway for proxy forwarding through the first QUIC tunnel, and the directional traffic is sent to the second gateway for proxy forwarding through the second QUIC tunnel, so that the problem of failure of a directional traffic flow-free function in a multi-network transmission system is solved.

The present invention discloses a dynamic credit gateway for industrial terminal edge based on classification and grading and an implementation method, the implementation method includes the following steps: step 1, classify and grade industrial terminals and store them in a local cache module; step 2, collect terminal device information; step 3, obtain the classification and grading information of industrial terminal device identity, obtain the credit access to industrial cloud platform application resources, and perform synchronous access credit on the device; step 4, obtain and monitor the dynamic information of industrial terminals in real time, comprehensively assign the dynamic information of each industrial terminal device to obtain the initial comprehensive trust score, and combine the security event log to obtain the final comprehensive trust score; step 5, determine whether the real-time trust score of each terminal device is within the safe range, and send the dynamic credit result to realize edge dynamic credit control. The method realizes flexible dynamic credit for industrial edge devices by integrating static identity factors and dynamic information indicators.

The present invention discloses a sliding surface feature monitoring method and system based on acoustic emission, and relates to the technical field of landslide monitoring. The process of the present invention includes: installation of acoustic emission monitoring device; establishment of wave velocity field; division of sliding surface area; monitoring and analysis of acoustic emission signals; data processing and analysis; positioning and modeling of sliding surface; real-time monitoring and early warning. The present invention installs a highly sensitive acoustic emission monitoring device, establishes a wave velocity field, divides the sliding surface area, monitors the acoustic emission signal in real time, and accurately locates the sliding surface position through professional data processing and analysis, constructs a three-dimensional model, and realizes real-time monitoring and early warning of landslide risks. This method can effectively improve the accuracy and real-time performance of landslide monitoring, and provide strong technical support for the prevention and control of landslide disasters.

The invention relates to the technical field of data analysis, can be applied to business system platforms of financial science and technology, medical treatment and health and the like, and discloses a dynamic bandwidth adjustment method, device and equipment based on bucket-level resources and a medium. Obtaining high-priority resource buckets and common resource buckets, collecting system resource states of the resource buckets, performing health degree analysis on the high-priority resource buckets and the common resource buckets, and generating health degree scores of the resource buckets; and performing weighted averaging on the health degree score of the high-priority resource bucket and the health degree score of the common resource bucket according to a preset weight to obtain a global health degree, and performing different dynamic bandwidth allocation and dynamic speed-limiting adjustment on the high-priority resource bucket and the common resource bucket according to the global health degree to obtain a target bandwidth adjustment result. According to the invention, the differentiation and adaptive management of the bandwidth can be realized according to the service importance and the load change.