4064 results about "Mirror image" patented technology

The invention belongs to the field of data analysis, and discloses a data analysis method for engineering consultation digital intelligent management, which comprises the following steps: mapping multi-project heterogeneous data to a unified three-dimensional space-time grid through space-time grid division to form a grid mapping data set; detecting data format and attribute conflicts based on neighborhood correlation analysis, and distributing calibration data through dynamic weight; missing values and abnormal fluctuations are processed by using a time sequence autoregression model and a smoothing technology, and a complete data set with continuous time is constructed by combining linear interpolation and multi-dimensional data fusion; key indexes are extracted to construct a digital mirror image containing spatial positions, time sequences and attribute association, real-time data are synchronized, and outlier grid points are corrected; and multi-scene operation conditions are constructed based on the mirror image data, and a dynamic adjustment scheme is realized. According to the method, heterogeneous data are integrated through space-time grids, digital twinning and multi-scene simulation technologies are combined, and full-period management and risk intelligent decision-making of engineering data are achieved.

The invention discloses a network attack active trapping method based on intelligent scheduling, and the method comprises the steps: constructing a dynamic honeypot environment according to a real business system mirror image, simulating the interaction logic and data characteristics of a real business system, and generating a honeypot system; analyzing a network equipment log of an access source according to the security situation awareness platform, and capturing multi-dimensional features to identify attack traffic; dynamically generating a drainage strategy according to an identification result of the security situation awareness platform, and seamlessly switching attack traffic to a honeypot system through load balancing equipment; and recording an attack behavior chain in the honeypot system, extracting an attack tool fingerprint and tracking an attacker identity. Through dynamic simulation environment construction, intelligent traffic scheduling, full-chain traceability and intelligent resource management, high-simulation trapping, accurate attack shunting, credible electronic evidence chain generation and efficient resource utilization are realized, and the active defense efficiency is remarkably improved.

The omitted right view is a mirror image of the left view; the broken lines shown in the reproductions depict portions of the indoor air conditioning control unit and form no part of the claimed design.

The invention discloses an SSD testing method, system, device and equipment and a storage medium, and relates to the technical field of solid state disk testing, and the method comprises the steps that firstly, a test request is responded, and a standardized test environment is constructed by deploying a test environment mirror image; and then an iterative testing process is executed on the SSD to be tested in the environment. The key of the iterative test process is that the real-time performance of the SSD to be tested in each round of test can be obtained, and the performance is compared with a preset performance standard. When a comparison result meets a specific condition, the system automatically adjusts and optimizes execution parameters used in the next round of test. According to the method and the device, the dynamic association between the performance indexes and the subsequent test parameters is established, so that the test process can be self-adjusted according to the actual performance of the SSD to be tested, and the limitation caused by the fact that the test parameters are fixed in the prior art is overcome.

The present application belongs to the technical field of material processing, and relates to a mold-free mirror image filament laying method and a mold-free mirror image filament laying system. The method lays a filament ribbon in a mirror image symmetry, without a mold, thereby improving production flexibility and efficiency. The method acquires the temperature and pressure of the filament ribbon in real time, calculates the output power of a heater and the modification value of a filament laying end motion mechanism path by using temperature and pressure differences, and optimizes controller parameters through reinforcement learning, so as to realize stable control of the temperature and pressure. The system comprises a hardware part and a control system. The hardware part includes pressure and heat source components. The control system adjusts through real-time feedback to ensure the quality of filament laying. The present application solves the problem that the temperature and pressure are difficult to accurately control in the process of mold-free mirror image filament laying, and improves the performance of composite products.

The invention relates to an ERP non-core service migration method based on K8s dynamic resource scheduling, and belongs to the technical field of cloud computing containerization and ERP system optimization. The method comprises the following steps: identifying a non-core module based on business criticality, and generating a migration list; an internal interface is transformed into a standard API gateway route, and strong dependency communication is asynchronously decoupled through a message queue. Historical resource load data is collected, a periodic rule is extracted by using a time sequence decomposition model, a reference value is set, and a K8s scheduling parameter is generated. Adopting multi-stage construction to separate compilation and operation environments, and generating a lightweight mirror image; and implementing security reinforcement, and dynamically updating the health examination probe and configuration. Selecting a controller according to stateless and persistent requirements; the locality of NUMA domain resources is optimized through topology awareness scheduling; dynamic storage binds a persistent volume according to QoS; the network policy implements container-level traffic isolation. And dynamically adjusting the resource quota and the number of copies. The efficient and safe migration of the ERP non-core business in the K8s environment is realized.

The invention belongs to the technical field of virtual machine mirror image static scanning, and particularly relates to a virtual machine mirror image static scanning method and system based on a hyper-fusion platform, and the method comprises the steps: creating a to-be-scanned mirror image storage snapshot, employing an index and retrieval algorithm, obtaining a static virtual machine mirror image file, extracting and recording metadata information of the static virtual machine mirror image file, and then carrying out integrity verification; collecting all-around resource data of the hyper-fusion platform in real time, and distributing corresponding resource quotas for scanning tasks by using a preset algorithm; multi-stage deep scanning is carried out, file fingerprints and feature matching are firstly used for preliminary screening, then misjudgment is eliminated through version intelligent comparison, potential high-risk vulnerabilities are deeply excavated for key complex components by adopting static code analysis, and configuration files in mirror images are comprehensively examined through rapid screening and positioning of known malicious software; and a preset algorithm is used for carrying out deep classification arrangement, correlation analysis and summary statistics on various types of result data, so that virtual machine mirror image scanning in a large-scale hyper-fusion cluster is completed in a relatively short time.

The invention discloses a visual combined infrared precast beam appearance defect detection method, and relates to the technical field of civil engineering structure detection and nondestructive testing, and the method comprises the following steps: establishing an illumination time sequence observation layer, collecting multi-dimensional optical parameters aiming at the surface of a precast beam, and generating a dynamic reflection fingerprint baseline; and performing coherent phase decomposition based on the dynamic reflection fingerprint baseline, separating the specular reflection signal from the material texture signal, and calibrating light spot track and intensity evolution data in the unified baseline. According to the method, an illumination time sequence observation layer is constructed to generate reflection fingerprints, coherent phase decomposition and anti-fact playback are combined, reflection interference is stripped, and crack boundaries are recovered; time coordinates are reconstructed through double-mirror-image anchor points, and crack evolution is accurately recovered; phase conjugate projection and light field traction are combined, a dynamic threshold optical fence is established, the exposure rhythm is controlled in a closed-loop mode, and precise detection of the defects of the precast beam is achieved.

The invention provides an intelligent inspection and diagnosis system, method and device for a photovoltaic power station unmanned aerial vehicle and a medium, and the system comprises a heterogeneous perception fusion module which is used for constructing digital mirror image mapping of a power station global physical field through multi-mode sensor space-time coding and electromagnetic fingerprint matching; the group intelligent decision module is used for realizing autonomous task negotiation and anti-fragile path evolution of a multi-unmanned aerial vehicle cluster based on a dynamic Bayesian game model; the embedded diagnostic kernel module is used for running a quantization feature extraction algorithm at an edge computing node to realize component-level defect subsurface-level diagnostic reasoning; the superbody self-evolution module is used for continuously reconstructing a diagnostic knowledge graph by means of a genetic programming framework to realize Darwin asymptotic optimization of a system cognitive architecture; the problems that in unmanned aerial vehicle inspection, fault type judgment and accurate geographic positioning cannot be conducted online, photovoltaic array arrangement changes and sudden shielding scenes cannot be self-adapted, and transmission bandwidth limitation and analysis lag are likely to happen in a 5G weak coverage area are solved.

The invention relates to the technical field of medical rehabilitation training, in particular to an intelligent hand training method and system, electronic equipment and a storage medium, and the method comprises the steps: receiving a training mode instruction selected by a user; real-time biomechanical data of the affected side hand are collected through a multi-source sensor array, the real-time biomechanical data comprise finger joint angles, electromyographic signal intensity and a touch pressure distribution matrix, and when the affected side hand is in a mirror image training mode, the six-degree-of-freedom motion trail of the uninjured side hand is synchronously collected; calling a corresponding algorithm model for processing based on the training mode, and generating a control instruction set containing pneumatic pressure parameters, electrical stimulation waveforms and virtual interaction instructions; the control instruction set is sent to a server side, a mechanical glove arranged on the hand of the affected side in a sleeving mode executes corresponding pneumatic-electric combined driving operation, and multi-sense feedback is synchronously presented. According to the application, the composite requirements of patients in different rehabilitation stages on training mode diversity, control accuracy and interactive immersion can be met.

The invention discloses a multi-dimensional dynamic model sieve path platform construction method based on digital twinning. The method comprises the following steps: S1, constructing a multi-dimensional dynamic digital twinning model based on sieve path basic information; s2, screen channel operation data are collected in real time and mapped to the digital twinborn model to generate a dynamic twinborn mirror image; s3, based on the digital twinborn model and the screen way real-time operation data, analyzing the dynamic deviation between the digital twinborn model prediction parameters and the actual screen way operation data; s4, generating a parameter regulation and control instruction based on a dynamic deviation analysis result, adopting a closed-loop feedback mechanism to perform self-correction on parameters of the digital twin model, and synchronously optimizing operation parameters of a physical entity sieve channel to form construction of a sieve channel platform; according to the system, a closed-loop link of data acquisition, model diagnosis, parameter optimization and feedback execution is constructed, so that the problem of static parameter mismatch caused by working condition change of a traditional digital twin model is effectively solved, and the abnormal working condition identification response time is shortened.

The invention provides an asynchronous service deployment method and device for an edge cloud network, and the method comprises the steps: checking whether a current time slot meets a layer cache updating condition or not in response to a deployment request for a target micro service received in the current time slot; if not, for any deployable node, scheduling the scheduling information of any required mirror image layer and the data access rate between the nodes from any other node according to the mirror image layer required by the target micro-service, the memory space of the corresponding mirror image layer and the micro-service deployment information under the current time slot; and constructing a total layer loading time function that the target micro-service is deployed on the node and changes along with the time slot, so as to construct a service utility function that corresponds to the node and changes along with the time slot in combination with profit information and starting cost of the node, thereby determining a deployment strategy of the target micro-service, and starting the target micro-service based on a mirror image layer required by the target micro-service. The method effectively balances the service performance and the resource utilization rate.

The invention provides a data synchronization method which can be applied to the technical field of computer communication. The data synchronization method comprises the steps that a synchronization request initiated by a local server is responded, a virtual disk mirror image generated by converting a target file through the local server is received through a preset transmission channel, and the synchronization request carries an editing mode identifier of the target file; mounting the virtual disk mirror image to a serial bus control port of a remote server, so that the virtual disk mirror image can be identified as a removable storage device; if the editing mode identifier represents that the target file is in an editable state, acquiring change information generated by modifying the target file by a local server and / or a remote server by monitoring a file change event on the removable storage device in real time; and dynamically updating the virtual disk mirror image based on the change information to complete modification synchronization of the target file. The invention further provides a mirror image mounting method and device and a storage medium.

The invention relates to the technical field of metal material detection, in particular to a titanium alloy bar machining quality detection method and system, and the method specifically comprises the steps: carrying out the superpixel segmentation of the section of a titanium alloy bar, constructing a mirror image edge texture saliency value of a superpixel block based on the proportion of edge points in the superpixel block and the edge gradient, and carrying out the detection of the machining quality of the titanium alloy bar. Constructing the mirror image texture intensity of the titanium alloy bar by combining the gray level distribution concentration characteristics of the titanium alloy bar, and performing image segmentation on the section of the titanium alloy bar; and in each segmented region, based on the edge line fuzzy degree difference and the pixel gray level difference of each super-pixel block and the rest of super-pixel blocks, combining a mirror image edge texture saliency value to construct a segregation evaluation value of each super-pixel block, and based on the segregation evaluation value, carrying out titanium alloy bar segregation quality defect detection. The titanium alloy bar segregation defect identification capability is enhanced, the titanium alloy bar segregation defect detection accuracy under the titanium alloy bar mirror image scene is improved, potential problems can be found earlier, missing detection is avoided, and the defective rate is reduced.

The invention relates to the technical field of intelligent detection and identification of metal elbows based on image processing, and discloses an intelligent detection and identification method of metal elbows based on image processing. According to the method, mirror image filling 3 * 3 median filtering is carried out on an original image in a two-dimensional coordinate system of an original point of the upper left corner, and salt and pepper noise and boundary artifacts are removed; calculating horizontal and vertical gradients, amplitudes and directions by using central difference; bilinear interpolation is carried out on the positions of the sub-pixels in the smooth direction to suppress non-maximum values, and a 75% percentile threshold value is taken in a local pane to screen seed points; according to dynamic step length, forward and reverse tracking is carried out to extract a ridge line, and a complete edge is obtained by combining end point Euclidean combination and length elimination; and finally, calculating a turning angle point by point, accumulating a total bending angle, comparing the total bending angle with a single section and a total threshold value, and completing accurate anti-noise bending qualification judgment on line in real time.

The invention discloses a model training data construction method and device and a storage medium, and the method comprises the steps: obtaining an initial image data set comprising a plurality of initial images, and obtaining a to-be-modified region in the initial image for each initial image in the initial image data set; and for each to-be-modified area, modifying the to-be-modified area according to a preset automatic modification method to obtain a target image, and constructing training data based on the target image. The preset automatic modification method comprises at least one of text replacement, image mirroring, information erasing, cross-graph modification, noise addition and modification through a diffusion model, manual modification is not needed, and the training data construction efficiency is high. And the training data set comprises a plurality of methods for automatically modifying the image, so that the image detection model trained according to the training data set is used for detecting the image, and the accuracy of an obtained detection result that the image is tampered is relatively high.

The invention provides a notebook computer pre-installed environment simulation test method and system based on a virtualization technology, and the method comprises the steps: firstly creating a virtualization environment instance which is matched with a target notebook computer hardware architecture and comprises a pre-installed operation system and a preset software set, and then injecting a simulation user operation behavior sequence according to a predefined environment configuration strategy, the method comprises the steps of generating a dynamic test case set, executing and monitoring running state data in a virtual environment instance, generating an environment compatibility analysis report by extracting an abnormal response mode in the running state data, and finally adjusting resource configuration parameters of the virtual environment instance according to the environment compatibility analysis report. And generating the optimized pre-installed environment mirror image file, so that efficient and comprehensive simulation test on the notebook computer pre-installed environment is realized, and the test efficiency and accuracy are effectively improved.

The invention discloses a generative zero sample learning method based on two-state collaborative decoupling and semantic refining, and belongs to the field of generative zero sample learning. According to the method, static features such as a background, a structure and details of an image are decoupled, and dynamic common features are extracted by a cross-modal label generation module, so that complementary expression of the static and dynamic features is realized; the feature focus is dynamically adjusted according to different confusion types, the feature discrimination is enhanced, and cross-class interference is relieved; on the semantic level, by constructing a vision-semantic mirror image cross attention mechanism, bidirectional alignment between semantic features and visual features is achieved, and the multi-granularity capability and adaptability of semantic representation are further improved. According to the method, feature structure decoupling, confusion adaptive regulation and control and dynamic semantic alignment are taken as the core, the cross-category generalization ability and the generated sample quality are effectively improved, the performance bottleneck of traditional generative zero sample learning is broken through, and the method has high theoretical value and wide application prospects.

The invention relates to the technical field of defect detection, in particular to a bonding wire process defect detection method and system, and the method comprises the following steps: detecting coordinate positions of a bonding wire track starting point and a bonding wire track ending point, extracting and analyzing a tangential direction formed by continuous pixel line segments, determining a mirror symmetry center candidate point, and recording a direction change angle in a path segment. Bending deformation defect coordinates are positioned, cracking risk points are judged, and a bonding wire indentation type identification set is generated. According to the method, the starting point and the ending point of the bonding wire track are detected and extend to determine the symmetric offset point of the track through accurate measurement of the direction angle, so that potential tiny defects can be found earlier, the uniformity of the wire diameter is evaluated through the change of the distance between transverse and longitudinal coordinates, and the material strength is directly predicted through the change of the physical size; the product quality can be evaluated and optimized on a more microscopic level, the production efficiency and cost management are directly influenced, and meanwhile, the safety guarantee of a user is improved.

The invention discloses an intelligent power grid optimization scheduling method based on digital twinning, and relates to the technical field of power grid optimization scheduling, and the method comprises the steps: building a dynamic power grid mirror image model according to a standardized power grid data matrix, and generating an evolution trajectory prediction report through a quantum magnetic coupling mechanism; establishing a variable association network based on the evolution trajectory prediction report, and generating an optimization scheduling instruction set in combination with the standardized data matrix; executing an optimization scheduling instruction set to obtain magnetic potential gradient distribution, and generating a topology reconstruction scheme by identifying a magnetic potential change trend; and inputting the topology reconstruction scheme into the dynamic power grid mirror image model to generate an electromagnetic field evolution trajectory, and generating a safety scheduling report in combination with magnetic potential energy gradient distribution. According to the method, the power grid magnetic field data is coded into an evolution trajectory prediction report through a quantum-magnetic coupling mechanism, and high-precision risk pre-judgment is realized; a topology reconstruction scheme is dynamically generated according to the electromagnetic energy gathering trend, and the power grid optimization scheduling efficiency is improved.

The invention discloses a multi-axis motor control system based on an ARM and an ASIC, and particularly relates to the technical field of multi-axis motor control, and the system comprises a control processing module, a real-time execution module, a state mirror image construction module and a path compensation module. The control processing module generates a target trajectory in combination with a multi-axis task and spatial constraints, and constructs a prediction model; the real-time execution module realizes multi-axis synchronous control through a hardware sequencer; the state mirror image construction module maintains a difference state of feedback and prediction in real time; the path compensation module dynamically calls candidate track fragments according to the difference vector when the path compensation module is abnormal, and path self-recovery is completed; according to the method, the multi-axis path synchronization precision is improved, the intelligent selection and space adaptation capability of path compensation is enhanced, meanwhile, a feedback anomaly recognition and fault-tolerant control mechanism in an interference state is provided, the track continuity in a cabin complex environment and the stability of a control system are ensured, and the comprehensive effects of high precision, high robustness and uninterrupted operation are achieved.

The invention relates to a digital twin simulation and optimization method for a large-scale stamping production line, and the method comprises a rapid lightweight modeling technology, a multifunctional fault indicator feedback technology, a three-dimensional dynamic real-time driving simulation technology, and a big data analysis intelligent optimization decision technology. According to the method, virtual-real fusion and a three-dimensional dynamic technology are combined, a three-dimensional visual user interface oriented to the whole manufacturing process is developed based on Unity, the whole stamping production line is simulated in real time, potential problems are predicted and solved through real-time monitoring of the stamping production line, various problems influencing the production efficiency in the production process are optimized, and the manual management and control difficulty is reduced.

The invention relates to the technical field of tool magazine control, in particular to a chain type combined tool magazine control method, which comprises the following steps: monitoring the running state parameters of each chain in a chain type combined tool magazine in real time, and generating a chain fault alarm instruction by the running state parameters in response to a preset fault judgment condition; according to the chain fault warning instruction, power isolation of a fault chain is controlled, the tool access permission of at least one standby chain is activated, and mirror image tool information mapped with a tool storage location of the fault chain is stored in the standby chain; based on the space coordinate data of the mirror image cutter information, obtaining a path planning instruction of the target cutter from the standby chain; and executing the path planning instruction to complete the cross-chain transfer operation of the target cutter, and updating the global cutter distribution information based on the execution result of the cross-chain transfer operation. According to the invention, the systematic defects of the traditional chain type tool magazine in fault response and dynamic scheduling are effectively overcome.

The invention discloses a method for preventing a PCIe switch internal link state from being recognized to be abnormal by an OS, and relates to the field of link state recognition anomalies, a high-risk link is recognized by obtaining a historical data set, configuration processing and algorithm optimization are carried out, an injection verification mirror image is obtained, and accurate link training control analysis is carried out based on the injection verification mirror image, so that the reliability of the PCIe switch internal link state is improved. Carrying out intelligent topology mapping management on the final link stability score to obtain an optimized topology; carrying out anomaly detection and hierarchical response control on the optimized topology to obtain a response action set; and carrying out repair or degradation processing on the link based on the response action set. And finally, the link state and the topological structure are updated according to the processing result to obtain a repair result and the updated topological structure, so that the high-risk link can be identified, the OS link state can be accurately judged, the system availability is improved, the misjudgment risk is reduced, and a dynamic degradation and active repair mechanism based on the actual risk levels (high, medium and low stability) of the link is provided.

The invention discloses a motion vector refinement for oversampling of time domain spread. A residual network is used to predict a set of residual motion vectors that provides additional motion data for portions of frames for which motion vectors are not provided, such as animation textures, mirrored / reflective objects, and / or moving objects without motion information.

The invention relates to the technical field of industrial automation and intelligent manufacturing, and discloses an industrial big data simulation verification system based on digital twinning, and the system comprises a physical entity module which is used for deploying an industrial sensor array and collecting the real-time parameter data of production equipment; the digital twin mirror image module is linked with the physical entity module through a data mapping engine, and synchronously updates a virtual mirror image model at a millisecond level according to the parameter change of the physical entity; and the data transmission module is used for transmitting the data acquired by the physical entity module to the digital twin mirror image module and the multi-source data fusion module through a 5G or industrial Ethernet, and is used for cleaning the acquired multi-modal industrial data and eliminating noise data. Through the physical entity-digital twin mirror image real-time linkage design, the limitation that traditional simulation is disjointed with entities is broken through. The industrial sensor array is combined with the edge calculation module, so that rigid linkage of physical production equipment, a real-time database and a digital twin mirror image is realized.

The invention relates to a mirror image file processing method and device, and relates to the technical field of container mirror image generation. The method comprises the steps of obtaining target file system directory information of a target container in response to a mirror image file export request for the target container; the target file system directory information of the target container is used for representing file system directory information of a writable layer of the target container; comparing the target file system directory information of the basic mirror image with the target file system directory information of the target container to obtain a difference file of the target container relative to the basic mirror image; constructing a layer file of a new incremental layer based on the difference file; writing a layer file of the incremental layer into a mirror image layer file directory of the basic mirror image, and updating a list file and an index file of the basic mirror image to obtain a mirror image file of the target container; the manifest file comprises metadata of each mirror image layer in the basic mirror image, and the index file comprises metadata of the manifest file. By adopting the method, the export efficiency of the container mirror image file can be improved.

The invention discloses an ERP (Enterprise Resource Planning) data intelligent supervision method based on the Internet of Things, which relates to the technical field of enterprise informatization, and comprises the following steps: constructing a time sequence integrity observation layer in an Internet of Things data acquisition link, embedding a mirror image time anchor in each sensor sampling point, recording electromagnetic interference, time service offset and queuing delay, generating a phase fingerprint time baseline, and obtaining a phase fingerprint time baseline; constructing a unified time reference framework; operating a causal coherent analysis mechanism based on a unified time reference frame, comparing instantaneous offsets of a mirror time anchor and a real-time timestamp, identifying a phase inversion region, extracting information of a corresponding sampling node, a production line position and an energy consumption unit, generating a high-risk time slice list, and determining a time correction boundary. According to the method, a time sequence observation layer and a time reference frame are constructed, phase abnormity is identified, a data trend is reconstructed, a regulation and control instruction draft is generated, sampling time sequence recovery and scheduling convergence are realized through time inversion control, data consistency and decision accuracy are improved, and a closed-loop control system is constructed.

The invention discloses a continuous overturning and pouring device for saggars, which relates to the related technical field of material conveying and blanking and comprises an overturning unit, a driving unit and a cover pushing unit. The overturning unit comprises a rotating motor, a rotating roller is arranged at the output end of the rotating motor, a baffle is arranged at one end of the peripheral side of the rotating roller, a bottom supporting plate is arranged at one end of the baffle, and a top supporting plate is arranged at the other end. The driving units are arranged on the two sides of the baffle in a mirroring mode, each driving unit comprises a second linear mechanism arranged at one end of the peripheral side of the rotating roller, a vertical L-shaped plate is arranged at the output end of the first linear mechanism, a transverse L-shaped plate is arranged at the upper end of the vertical L-shaped plate, and a cover blocking block further extends from the upper end of one short side of the C-shaped clamp. The cover pushing unit is arranged below a driving unit, a transverse rod is arranged at the output end of the fourth linear mechanism, and a pair of triangular blocks with right-triangle-shaped sections is arranged on one side of the transverse rod. According to the saggar overturning and discharging device, the saggar can be automatically overturned and discharged, and the saggar can be automatically overturned and put back to the roller conveyor.

The invention relates to a method, a system and equipment for online upgrading of a storage system and a medium, and belongs to the technical field of distributed storage, and the method comprises the following steps: determining at least one node to be upgraded in the storage system; any node to be upgraded is selected as a control node to receive the mirror image file package, and a mirror image source is created based on the mirror image file package; and determining at least one node cluster according to the node cluster category to which the to-be-upgraded node belongs, determining the upgrading sequence of each node cluster according to the upgrading priority of the node cluster, and simultaneously upgrading the plurality of to-be-upgraded nodes which belong to the same node cluster and belong to the same storage pool. Through the upgrading method provided by the invention, rapid and reliable upgrading iteration can be realized on the premise of not influencing service operation.