452 results about "Storage efficiency" patented technology

The invention discloses a power system data integrity verification system based on a dynamic data block division mechanism and a block chain. The system comprises a data preprocessing module, a hash generation module, a block chain storage module and a verification processing module. The data preprocessing module divides original data into data blocks with dynamically adjustable sizes; the Hash generation module adopts an iterative Hash algorithm to generate a chain Hash structure and an integrity Hash abstract; the block chain storage module uploads the hash data to a block chain network through a smart contract; and the verification processing module outputs a verification result by recalculating and comparing the hash values. The system realizes efficient and reliable data integrity verification, and has the advantages of high storage efficiency, good verification precision and low system load.

The invention discloses a key value storage system indexing method oriented to an NVM-NVMe SSD (Non-Volatile Memory-Non-Volatile Memory Express Solid State Disk) hybrid architecture, which comprises the following steps of: constructing a heterogeneous storage architecture taking cold and hot data perception as a core driving mechanism, coordinating and managing two types of storage media, namely a non-volatile memory NVM and a solid state disk NVMe SSD, and realizing efficient identification, layered writing and dynamic migration of cold and hot data. According to the method, the characteristics of low delay, durability and byte addressing of the NVM are utilized, the frequency and I / O overhead of Flush and Compaction operations are reduced in a data write-in path, meanwhile, the problem of mixed storage of cold and hot data is avoided, and therefore the overall performance and storage efficiency of a system are remarkably improved. In addition, by introducing an asynchronous migration module, the method can dynamically adapt to the change of data popularity along with time evolution, and effectively support high performance and high availability of the key value system in long-term operation.

The invention provides a hierarchical storage method for multi-source data, a storage medium, a program product and electronic equipment, and the method comprises the steps: obtaining the multi-source data of a service, and converting the format of the multi-source data into a column storage format; performing embedded space pre-regularization processing on the multi-source data after format conversion to construct an n-dimensional simplex geometric constraint space of the multi-source data, and according to the n-dimensional simplex geometric constraint space, generating a multi-layer composite label, at least comprising a business semantic label and a cold and hot aging label, of the multi-source data; dividing the multi-source data into hot data, temperature data and cold data according to the cold and hot aging labels; the hot data, the temperature data and the cold data are stored in different storage layers respectively; and obtaining a data query request, and routing the data query request to one of the three storage layers according to the service semantic tag. The problems of semantic confusion, low storage efficiency and low access efficiency of bank data lakes in multi-source heterogeneous data fusion in the prior art are solved.

The invention relates to the field of coal mine safety and mine system intellectualization, in particular to a multi-source information fusion supervision method for an underground coal mine drilling process, which comprises the following steps: S1, acquiring continuous synthesized monitoring pictures in the underground coal mine drilling process to form a supervision video stream; s2, performing region segmentation on each frame of synthesized monitoring picture in the supervision video stream to obtain a corresponding static UI region, a dynamic data region and a real-time video region; s3, compressing a static UI region, a dynamic data region and a real-time video region of each frame of synthesized monitoring picture in the supervision video stream by adopting corresponding compression strategies to obtain corresponding compressed data; s4, fusing the compressed data of the static UI area, the dynamic data area and the real-time video area to generate a regional compression supervision video stream; and S5, storing the regional compression supervision video stream to realize subsequent inspection and supervision. According to the invention, the storage efficiency of supervision videos and the efficiency and accuracy of coal mine underground drilling process supervision can be improved.

The invention discloses a method and a system for improving carbon dioxide mineralization and storage efficiency. The method comprises the following steps: building a microfluidic experiment platform integrated with an online CO2 mineralization and storage monitoring system; on a microfluidic experimental platform, simulating a formation temperature and pressure condition to carry out a CO2 mineralization corrosion experiment to obtain pore scale reaction kinetic parameters and a pore structure evolution rule; macromineralization efficiency data are obtained through an indoor physical simulation mineralization reaction experiment of the core scale; a CCM-GEM reaction flow numerical model is constructed; determining a Pareto optimal solution set by using a CMG-GEM reaction flow numerical model; and based on the pore scale reaction kinetic parameters, the pore structure evolution law, the macromineralization efficiency data and the Pareto optimal solution set, determining a CO2 mineralization storage efficiency improvement path of the target rock sample. According to the method, global sensitivity analysis and automatic optimization of multiple parameters are rapidly completed, the research and development period is shortened, the economic cost and the time cost are reduced, and the research efficiency is improved.

The invention relates to the technical field of user portrait information processing, and particularly provides a user real-time portrait updating method and system, and the method comprises the steps: collecting a time sequence interaction track sequence generated by a user in a current interaction scene in real time, and constructing a heterogeneous behavior data flow based on a cross-modal behavior synchronous collection technology; detecting the deviation degree of the historical behavior sequence in the unified feature space, and generating a conflict state mode label; analyzing a behavior evolution path by applying a time sequence self-attention model, and outputting multi-intention probability distribution; dynamically adjusting a confidence coefficient threshold value based on a conflict state and filtering out a noise portrait label; and triggering cross-modal joint recoding and intention re-reasoning for a prediction deviation time period, and locally updating the portrait through a feedback closed loop. Static portrait updating lag limitation is broken through, second-level intention tracking and dynamic behavior mode capturing are achieved, and portrait adaptability and storage efficiency in a high-noise scene are remarkably improved.

The invention provides a structured memory data processing method and system oriented to long time sequence interaction, and is applied to the technical field of natural language processing and artificial intelligence memory modeling. The method comprises the following steps: acquiring a real-time interaction data stream, partitioning the real-time interaction data stream into dialogue data blocks, loading a hierarchical attribute mode and a previous time step attribute tree instance, inputting serialized texts of the hierarchical attribute mode and the previous time step attribute tree instance into a generative model, generating a writing, rewriting, deleting or null operation instruction aiming at a leaf node path, analyzing, updating, generating a current attribute tree instance, and storing the current attribute tree instance; by means of the scheme, lossy compression and structured evolution of the infinite long dialogue stream can be achieved, memory forgetting is relieved on the premise that a context window is not expanded, and long-time-sequence information retrieval precision and storage efficiency are improved.

The embodiment of the invention provides a storage strategy optimization method and device based on data popularity and data consanguinity, and dynamic optimization of a storage strategy is realized through innovatively designing a multi-dimensional popularity calculation model and through node attribute analysis and a graph attention network. A directed graph structure is constructed, and a reliable dependency relationship management system is established in combination with blood relationship analysis. A hierarchical storage strategy is introduced, and the storage efficiency is ensured through heat division and dependency relationship optimization. According to the method, the defects of the traditional technology in the aspects of popularity evaluation, blood relationship analysis, storage optimization and the like are effectively overcome, and a technical guarantee is provided for software system storage management.

The invention discloses a lightweight spliced bridge vibration monitoring system for cooperative work performance intelligent perception, and belongs to the technical field of bridge structure health monitoring, and the lightweight spliced bridge vibration monitoring system comprises a lightweight targeted sensing subsystem which comprises a plurality of perception assemblies arranged in a targeted manner; the intelligent edge acquisition and transmission subsystem has an independent addressing function and a time synchronization function and is used for preprocessing and lightweight processing; the cloud edge collaborative storage management subsystem performs hierarchical storage, security control and efficient retrieval on the data to form monitoring data; and the cooperative performance perception early warning subsystem realizes state evaluation and graded early warning of the cooperative work performance of the spliced bridge through multi-index fusion. By adopting the lightweight spliced bridge vibration monitoring system for cooperative work performance intelligent perception, the problems of insufficient lightweight and targeting performance, low data processing, transmission and storage efficiency, and inaccurate cooperative performance evaluation, damage positioning and early warning of traditional spliced bridge vibration monitoring are solved.

The invention provides a program tracking method and device and computing device.The program tracking method comprises the steps that target program tracking information of a target program is obtained, and the target program tracking information comprises target static tracking information and target dynamic tracking information; determining target static tracking compression information corresponding to the target static tracking information based on a preset mapping relationship; compressing the target dynamic tracking information to generate target dynamic tracking compressed information; and integrating the target static tracking compression information and the target dynamic tracking compression information to generate a program tracking record of the target program. By applying the embodiment of the invention, the resource competition between the compression operation and the target program can be reduced, the time sequence stability of the key execution time period of the target program is ensured, and the transmission and storage efficiency of the tracking information is improved.

The present application relates to a data replay method, a data processing unit, a network interface card, a device, and a storage medium. The method comprises: when a storage stack is restarted, acquiring a replay-pending request queue from a persistent memory, the replay-pending request queue being a queue obtained by mapping a transmission buffer area into the persistent memory, and the transmission buffer area being used for receiving a request from a host side; on the basis of the replay-pending request queue, acquiring a replay-pending request from the persistent memory; and resending the replay-pending request to a target acceleration component directed to a storage device, so as to instruct the storage device to store target data which resides in the persistent memory and corresponds to the replay-pending request. In the method, a request queue, a request, and data corresponding to the request are stored in the persistent memory in advance, and if the storage stack is restarted, the replay-pending request is recovered from the persistent memory, eliminating the need for DMA and encryption / decryption techniques, and shortening an interruption duration of a storage data path, thereby improving data storage efficiency on the host side.

The invention relates to the technical field of data storage, and discloses a numerical data variable-length coding storage method, device, equipment and medium, which comprises the following steps: converting target numerical data into fixed-length binary representation according to definition precision, executing filling removal interception processing on an integer part, executing digital-level packet compression coding on a decimal part, and performing variable-length coding on the target numerical data; and generating a variable-length binary sequence containing length information and symbol information, and writing the sequence into a storage medium to realize compact storage of numerical data. According to the method, redundant filling bytes are eliminated from an integer part, compressed encoding is performed on a decimal part according to effective digits, and unified processing of sign bits is combined, so that a storage space dynamically changes along with actual numerical digits on the premise of keeping numerical precision and analyzability, space waste of fixed-length numerical types is reduced, and the method is suitable for large-scale popularization and application. Meanwhile, the precision error of the floating-point number is avoided, and the storage efficiency and the data reliability are improved.

The embodiment of the invention discloses a coding and decoding method, system and related device, relates to the technical field of media, and is used for improving the transmission efficiency and / or storage efficiency of a basic three-dimensional grid sequence. The method comprises the steps of obtaining a second basic three-dimensional grid sequence and conversion information based on a first basic three-dimensional grid sequence, the first basic three-dimensional grid sequence being used for generating at least one first synthetic three-dimensional grid, the quasi-coding length of the second basic three-dimensional grid sequence is smaller than the quasi-coding length of the first basic three-dimensional grid sequence, and the conversion information indicates how to obtain the first basic three-dimensional grid sequence based on the second basic three-dimensional grid sequence. And encoding the second basic three-dimensional grid sequence and the conversion information into a code stream.

The invention discloses an AI Agent-assisted enterprise data analysis method and system, and relates to the technical field of data analysis, and the method comprises the steps: connecting an enterprise network switch, deploying an RS-485 management network, and deploying at least two AI Agent computing nodes at the edge side of the enterprise network switch; carrying out storage redundancy analysis to obtain a redundancy label matrix; establishing a distribution relationship; issuing a redundancy processing task according to the distribution relationship, and performing data processing to obtain a plurality of return data sets; and performing overlay storage on a metadatabase of the enterprise storage management center according to the plurality of return data sets. The technical problems that in the prior art, storage redundancy of an enterprise meta-database is difficult to recognize accurately, storage optimization after data processing is insufficient, and consequently enterprise data storage efficiency is low are solved, efficient redundancy processing and optimized storage of the meta-database of the enterprise storage management center are achieved, and the enterprise data storage efficiency is improved. And the technical effect of enterprise data storage efficiency is improved.

The present disclosure provides a data storage method, device, electronic equipment and storage medium. The data storage method comprises: in response to a file storage request for a first target data file, obtaining the first target data file to be stored in a target storage system, the target storage system being configured with table metadata, the table metadata indicating storage branch information corresponding to the target storage system, the storage branch information comprising a main branch and at least one experimental branch, the main branch being used to mount data files that have been used for model training and the training results of which meet preset requirements, and the experimental branch being used to mount data files that have not been used for model training; based on the table metadata, determining a first target experimental branch corresponding to the file storage request, and newly creating a first target snapshot corresponding to the first target experimental branch; and based on the first target snapshot, storing the first target data file to a corresponding storage location in the target storage system. The embodiments of the present application can improve the data storage efficiency.

The invention discloses an electric power knowledge graph construction method and system based on multi-head attention and a medium, and belongs to the technical field of electric power system automation. The method comprises the following steps: constructing graph structure data including power equipment, parts, defects and environment entities, and encoding node features; secondly, inputting graph data into a graph attention module, reducing storage overhead through a low-rank compression key value vector, independently performing decoupled rotation position coding on a query vector to inject hierarchy and time position information, respectively modeling an equipment hierarchy relationship and a dynamic time sequence relationship through a division-of-labor multi-head attention mechanism, and performing multi-head attention mechanism modeling on the equipment hierarchy relationship and the dynamic time sequence relationship; obtaining a node vector representation; and finally, performing hierarchical processing and dynamic updating on the node representation, and constructing and continuously updating the electric power knowledge graph through knowledge reasoning after fusion. The problems that a traditional method is low in storage efficiency, insufficient in space-time relation modeling and difficult in dynamic updating are solved, and the efficiency, precision and real-time performance of graph construction are remarkably improved.

The invention discloses a dynamic octree mapping method and system based on probability semantic fusion and a storage medium, and mainly solves the problem that a traditional octree map lacks semantic information and cannot support an advanced cognitive task. According to the implementation scheme, the method comprises the following steps: acquiring an RGB image, depth information and pose data through a sensor; extracting pixel-level semantic probability distribution by using a pre-trained semantic segmentation network; geometric information in the perception data is projected to a three-dimensional space based on the pose, and a three-dimensional observation point with semantic information is formed; performing ray projection on octree nodes, respectively updating geometric occupancy states of penetrated non-end-point nodes, and synchronously updating geometric occupancy states and semantic belief distribution of end-point surface nodes by using three-dimensional observation point data; semantic information is continuously optimized through Bayesian probability fusion, and dynamic pruning and map optimization are realized based on semantic entropy. According to the method, the map storage efficiency and the calculation speed can be remarkably improved while refined and real-time updated geometric and semantic information is given. The method can be used for map construction and storage of visual SLAM positioning, and fine three-dimensional object modeling and environment information description.

A computing system may generate, manage, and verify dynamic digital credentials recorded on a distributed ledger. The system may receive credential data from an issuer, generate a cryptographic hash representing the credential content, and record the hash on a blockchain along with issuer identifiers and version references. When a credential is updated, the system may calculate and store differential data between versions to improve storage efficiency and maintain traceability. Each version may reference the previous hash, forming an immutable version chain. Recipients may store credentials in digital wallets and share verifiable credentials containing issuer signatures and refresh links for automatic updates. Verifiers may authenticate credentials by validating issuer signatures and comparing credential hashes with corresponding blockchain records, ensuring authenticity, integrity, and version transparency across decentralized systems.

The embodiments of the present application relate to the technical field of media. Disclosed are encoding and decoding methods, a system, and a related apparatus, which are used for improving the transmission efficiency and / or storage efficiency of a basic three-dimensional mesh sequence. The encoding method comprises: on the basis of a first basic three-dimensional mesh sequence, obtaining a second basic three-dimensional mesh sequence and conversion information, wherein the first basic three-dimensional mesh sequence is used for generating at least one first synthetic three-dimensional mesh, the length to be subjected to encoding of the second basic three-dimensional mesh sequence is less than said length of the first basic three-dimensional mesh sequence, and the conversion information indicates how to obtain the first basic three-dimensional mesh sequence on the basis of the second basic three-dimensional mesh sequence; and encoding the second basic three-dimensional mesh sequence and the conversion information into a bit stream.

The invention relates to the technical field of signal acquisition, in particular to a multi-channel signal synchronous acquisition method and system based on an FPGA, and the method comprises the steps: obtaining a multi-channel signal source, connecting a device, and outputting an original analog signal; performing frequency equalization and noise suppression preprocessing on the signal; sampling and correcting a time domain and a frequency domain by using a synchronous acquisition model and an analog-to-digital converter to obtain a corrected digital signal; the storage efficiency is optimized through labeling, block compression and high-speed caching, finally, the data is written into a persistent storage module, and data analysis processing is completed based on a remote instruction. Through time reference adaptive calibration, a distributed clock architecture and a dynamic data flow management strategy, the robustness, expansibility and transmission efficiency of signal acquisition are improved, and the real-time performance and reliability requirements in a complex industrial environment are met.

The invention discloses a storage and management method suitable for automatic scoring data of the Internet of Things, and the method comprises the steps: constructing a three-layer heterogeneous storage collaborative architecture fusing a relational database, a time sequence database and a graph database, and achieving the dynamic distribution and collaborative updating of data through an intelligent routing and cross-database transaction consistency mechanism; establishing a self-adaptive index system based on reinforcement learning, dynamically optimizing a multi-class index strategy and supporting low-efficiency index reconstruction; a storage strategy based on data value dynamic adjustment and AI-driven data quality closed-loop management are implemented, and rapid positioning and repairing of problem data are achieved; and elastic scheduling of storage resources is realized by utilizing containerization and Kubernetes technologies. According to the method, the comprehensive performance of the automatic scoring data of the Internet of Things in the aspects of storage efficiency, query performance, consistency, reliability and cost control is remarkably improved, and the method has important practicability and popularization value.

The utility model discloses a bird nest type rotary storage device which comprises a backboard lifting device, a backboard lifting device a and a disc storage device, the backboard lifting device and the backboard lifting device a are the same in structure, the two sides of the backboard lifting device and the backboard lifting device a are respectively provided with a front face and a back face, and the backboard lifting device and the backboard lifting device a are inserted into the disc storage device formed by stacking multiple layers of disc plates at intervals. And bracket supporting tables and double rows of bracket supporting tables are alternately arranged on the circumference of the disc plate. When the front / back surfaces of the lifting plates are opposite, double rows / single supporting tables are respectively accommodated, single and double rows of sample box access areas are formed, and the space utilization rate and the access efficiency are improved. And the backboard is bent to form an isosceles mounting opening and a limiting structure, and is matched with a wire slot for storing the disc and a storage opening to realize quick disassembly and assembly, so that the maintenance cost is reduced. Through modular design and structural optimization, the problems that the storage disk is inconvenient to disassemble, insufficient in space and the like are solved, and the storage disk has the advantages of being flexible to disassemble and assemble, low in cost, high in storage efficiency and the like.

The invention discloses an unmanned aerial vehicle fault diagnosis method and device, and particularly relates to the field of fault diagnosis. Comprising the following steps: acquiring a first video stream of a to-be-monitored component of an unmanned aerial vehicle, and storing the first video stream according to time; performing visual feature detection on the first video stream frame by frame, and outputting a semantic tag; when the semantic tag meets a first preset condition, generating a control instruction containing video parameters according to the semantic tag; acquiring a second video stream of the to-be-monitored component of the unmanned aerial vehicle according to the control instruction; the second video stream is stored according to time, and recording is completed; wherein the frame rate of the second video stream is higher than that of the first video stream. Based on the method, the storage efficiency can be improved, and the fault positioning time is shortened.

The invention discloses a sparse reasoning method, system, equipment and product for large language model reasoning, and relates to the technical field of artificial intelligence. The method comprises the following steps: firstly, acquiring a weight matrix of a large language model, and then carrying out pruning sparsification processing on the weight matrix to obtain a sparse matrix; the storage format of the sparse matrix is converted into a bitmap coding storage format which is suitable for tensor calculation core perception and adopts a multi-level block structure to respectively correspond to different calculation granularities in a GPU / NPU hardware architecture so as to obtain a sparse model, and then the sparse model is deployed to respond to a reasoning request to perform reasoning service; sparse matrix multiplication is completed through a sparse matrix multiplication kernel based on on-chip storage bitmap coding so as to perform reasoning, so that through an innovative sparse matrix storage format and calculation optimization, the storage efficiency and the calculation performance in the reasoning process are remarkably improved, and especially in a low-sparseness scene, the reasoning efficiency is greatly improved. And the performance blank of the existing sparse reasoning framework in the field is filled.

The invention discloses a high-speed multi-port cache arbiter with a variable word length. Along with the high-speed development of the modern network technology, storage management and scheduling take up most of time in the processing of data packets by network equipment, so that the low-speed caching capability of most memories becomes a bottleneck for limiting the further improvement of a network processor. Therefore, by managing the shared cache of not less than 32 blocks of 256Kbit SRAM units and supporting simultaneous cache writing of a plurality of ports through an arbitration mechanism, write scheduling and read scheduling can be realized without mutual influence, and concurrent read-write conflicts are avoided; meanwhile, each port supports eight priority queues, so that the data transmission bandwidth of each port can reach 1G bps; by processing a data packet, caching and data scheduling according to packets are supported, the length of the data packet is 64-1024 bytes variable, and the influence of the length of the data packet on memory resources can be avoided; and the purpose of storing resources can be achieved by dynamically adjusting space saving through memory recovery, and the data storage efficiency is improved.

The invention relates to the technical field of computer graphics and three-dimensional modeling optimization, in particular to a 3D model lightweight method and system based on point cloud hierarchical slicing and dynamic mapping mapping.When the 3D model lightweight method and system are used, the storage efficiency, the rendering performance and the visual fidelity are improved by establishing a point cloud and mapping bidirectional coupling mechanism, and the 3D model lightweight effect is improved. In the aspect of storage efficiency, an efficient geometric and texture association storage system is constructed by relying on a map curvature adaptive segmentation and dynamic slice binding technology, an excellent geometric and texture compression effect is realized, the storage cost of a high-precision three-dimensional model is greatly reduced, and in the aspect of real-time rendering performance, through a dynamic loading strategy during operation, the real-time rendering efficiency is improved. By combining efficient visibility screening acceleration and an intelligent resource preloading technology, the real-time scheduling efficiency of the model is greatly improved, and the working efficiency of scenes such as design iteration and model editing is remarkably improved.

The invention relates to the technical field of data management, in particular to a data management method and system.The method comprises the steps that a distributed monitoring system is used for collecting the transaction operation state of a multi-node database in real time, and dynamic visibility range calibration data is obtained; performing transaction consanguinity tracking algorithm processing on the original transaction operation state data based on the dynamic visibility range calibration data to obtain transaction consanguinity tracking data; performing cross-node data dependence path identification according to the transaction blood relationship tracking data to obtain cross-node data dependence path data; performing dirty reading risk quantitative evaluation to finally obtain a dirty reading risk quantitative evaluation value; obtaining self-adaptive transaction isolation level adjustment data; and a data basis is provided for subsequent targeted treatment. The system can realize collaborative optimization of storage efficiency, execution performance and resource utilization rate on the premise of ensuring data consistency, and provides core technical support for stable operation of a large-scale distributed database.

The invention discloses a user working environment persistent storage method based on a double-layer container. The method comprises the steps that mirror images of all public containers in mirror image private server are pulled to a shared storage space to form a hot loading area; dividing a corresponding working space from the shared storage space, querying a target storage block corresponding to a target public container mirror image from a hot loading area based on a public container mirror image identifier in a creation request from a client, copying the target storage block to the working space to serve as a system disk, and further establishing a double-layer container and starting the double-layer container; in response to a modification request of a client, performing corresponding modification operation on the initial state inner layer container to obtain a target state inner layer container, so as to run a user working environment based on the target state inner layer container to execute a computing power task; and storing a file corresponding to the modification operation in the remaining space except the system disk in the workspace to form a user mirror image layer. According to the invention, the persistent storage efficiency of the container state and the user working environment can be improved, and the rapid restarting of the container can be realized.

The invention discloses a solid state disk-based data transmission method and device, a medium and a product, and relates to the field of solid state disks. According to the method, a data layout description header is obtained from a host memory in a direct memory access mode according to a target memory initial address; analyzing the data layout description header through a flash translation layer of the solid state disk, identifying each data segment entry, and extracting length information and life cycle attribute tags of corresponding data segments from each data segment entry; based on the life cycle attribute tag, planning a corresponding physical flash memory page for each data segment as a target write address of the data segment; and based on the target write-in address, controlling the solid state disk to execute DMA operation segment by segment according to the sequence of data segment entries in the data layout description head until the write-in of the total data length is completed. By implementing the technical scheme provided by the invention, the data storage efficiency of the solid state disk is improved.

The invention discloses an automatic storage management and control method, system and device for an intelligent wafer storage cabinet, and belongs to the technical field of data processing, and the method comprises the following steps: S1, obtaining a designated storage position of a wafer box, and sending a storage instruction to a rotation supporting platform; s2, controlling a turntable storage mechanism to rotate to a specified angle, controlling a mechanical arm to store the wafer box to a specified storage position, acquiring a steady-state execution parameter of the turntable storage mechanism in real time, and analyzing to obtain an equipment adjustment instruction; s3, corresponding rotation angular velocity adjustment is carried out, and corresponding heat dissipation power adjustment is carried out; and S4, the speed of the conveying belt is increased and adjusted. Stable and efficient operation of the wafer storage process is achieved, and the problem that in the prior art, storage efficiency and equipment storage precision cannot be considered at the same time is solved.