92results about How to "Reduce storage" patented technology

The invention belongs to the technical field of artificial intelligence and information retrieval, and provides a multi-modal retrieval method and system based on a lightweight knowledge graph and an index table, and the method comprises the steps: obtaining multi-modal source data, and extracting a structured semantic tag set; constructing a lightweight knowledge graph and a metadata index table; analyzing a natural language query input by a user to obtain a semantic query vector and a keyword set, executing semantic retrieval in the knowledge graph to obtain a text candidate result, and executing keyword matching in the metadata index table to obtain a non-text candidate result; for each non-text meta record, fusing the cross-modal similarity between the non-text meta record and the text candidate result, performing index matching on an original score and a graph semantic evidence score, calculating a comprehensive correlation score, and performing reordering; and generating a natural language answer containing a non-text record link according to a reordering result. The method is suitable for efficient cross-modal knowledge retrieval in a high-security and low-resource scene.

The invention provides an Internet of Things data acquisition and abnormity early warning method and system, and relates to the technical field of Internet of Things data processing, and the method comprises the steps: constructing a digital twin model for a physical entity at a cloud end, and issuing prediction data to an edge node; acquiring sensor data by an edge computing node at a basic frequency, and computing a residual error between real-time data and predicted data and an information entropy of a residual error sequence; dynamically adjusting the data acquisition frequency of the edge node based on a two-dimensional decision space formed by the residual error and the information entropy; and when the residual error and the information entropy both exceed the threshold values, potential abnormity is judged, an edge side abnormity analysis program is triggered, and abnormal event information is uploaded. According to the invention, through cloud edge cooperation and intelligent decision making, the acquisition frequency is reduced in a stationary period, resources are saved, the frequency is improved when an abnormal symptom appears, monitoring is enhanced, and optimal balance between resource consumption and monitoring precision is realized; double criteria are adopted to effectively filter noise interference, and the false alarm rate and the missing report rate are reduced.

The invention relates to the field of numerical control machining and computer-aided manufacturing software, and particularly discloses a honeycomb core six-axis ultrasonic cutting track digital control and interpolation optimization system which comprises a track preprocessing module, a parameterized spline interpolation module, a six-axis linkage inverse solution module, a dynamic feed-forward compensation module, an ultrasonic energy adaptive control module and a multi-source information fusion and decision module. By the adoption of the technical scheme, smooth and efficient interpolation of a track, dynamic feed-forward compensation of motion errors and self-adaptive adjustment of cutting energy can be achieved, and therefore the machining precision, the surface quality and the system stability are improved. According to the invention, ultrasonic energy control is originally incorporated into an overall trajectory control closed loop, and real-time accurate regulation and control of cutting energy are realized through the ultrasonic energy adaptive control module. The module is based on force, amplitude, temperature and other multi-sensor information, adopts fuzzy reasoning to intelligently decide output power, and ensures that cutting energy is constant and optimal under different processing conditions.

A data quantization method and device, a computer readable storage medium and a chip, the data quantization method comprising: obtaining a data block to be quantized, dividing the data block to be quantized into one or more data groups to be quantized according to a preset grouping method; performing quantization calculation on each data group to be quantized according to a target quantization format, to obtain quantization data corresponding to data in each data group to be quantized and quantization metadata corresponding to each data group to be quantized, wherein the quantization metadata is used for dequantization of the quantization data; and storing the quantization metadata corresponding to the data block to be quantized and the quantization data as a continuous data structure.

This invention relates to the field of photovoltaic monitoring technology, and discloses a photovoltaic monitoring adaptive sampling method, system, device, and medium based on multi-parameter coupled decision-making. The method includes: constructing a multi-dimensional environmental feature vector; dynamically setting a sampling threshold; determining the current operating mode and the corresponding baseline sampling period; introducing a hysteresis comparison mechanism and a delay confirmation mechanism to optimize the switching control of the operating mode; and introducing a correction coefficient to correct the baseline sampling period to obtain the final sampling period; performing mixed verification on the collected data and outputting data confidence labels; monitoring the operating status in real time; and judging and handling real-time operating faults based on the data verification results. This invention, by constructing a multi-dimensional environmental state vector, performing adaptive sampling based on the environmental state vector, and calculating the sampling period in real time, can output a clean dataset with confidence labels and back-optimize the threshold parameters of the decision layer.

This invention discloses a continuous synthesis apparatus and process for nitrobenzene. The synthesis apparatus includes a mixed acid preparation system, a continuous benzene nitration system, an organic phase continuous stratification system, and a continuous water washing-alkali washing-water washing system. The process includes: concentrated sulfuric acid and concentrated nitric acid are pumped into the mixing module of the mixed acid preparation system to obtain a mixed acid solution; benzene and the mixed acid solution are pumped into the microchannel reactor of the continuous benzene nitration system; the nitrated material is cooled and then pumped into the continuous organic phase stratification system; the resulting intermediate organic phase nitrate enters the next processing unit; the organic phase nitrate and water enter the continuous water washing-alkali washing-water washing system for washing to obtain the final product, nitrobenzene. The synthesis apparatus and process of this invention achieve continuous production of nitrobenzene throughout the entire process, realizing continuous and automated operation from raw material benzene to the final product, nitrobenzene.

The present application relates to the technical field of transport box, and discloses a transport box for egg circulation, which comprises a box body, a bottom plate arranged under the box body and used for supporting egg trays, a locking member movably arranged on the bottom plate and having a locking state and an unlocking state, a pushing assembly in transmission connection with the locking member, and a driving assembly used for driving the pushing assembly to move and switch the locking member between the locking state and the unlocking state. When the locking member is in the locking state, the box body is fixed relative to the bottom plate. When the locking member is in the unlocking state, the box body can be separated from the bottom plate. The transport box for egg circulation can realize overall loading and unloading through the separable design of the bottom plate and the box body. When loading, all the trays can be stacked on the bottom plate, and then the box body is buckled. When unloading, the box body can be lifted to expose the trays integrally, so that the loading and unloading time is greatly shortened, and the transport box is suitable for cooperation with automatic handling equipment and can realize rapid and batch circulation.

The application discloses a kind of slimming traditional Chinese medicine composition and preparation method thereof, it is related to slimming traditional Chinese medicine technical field.Slimming traditional Chinese medicine composition includes the following weight parts of Chinese medicinal materials: 30-45 parts of raw astragalus, 10-15 parts of prepared atractylodes rhizome, 15-23 parts of cassia bark, 20-30 parts of dried tangerine or orange peel, 30-45 parts of lotus leaf, 20-30 parts of raw hawthorn, 15-23 parts of kelp, 10-15 parts of turmeric, 10-15 parts of fried Semen Raphani, 10-15 parts of raw safflower stigma.The preparation method includes the following steps: the weight parts of the above-mentioned Chinese medicinal materials are extracted by water decocting.The traditional Chinese medicine composition of the application has the effects of benefiting qi and invigorating the spleen, resolving phlegm and eliminating dampness, and is also compatible with drugs for warming kidney and assisting yang, eliminating phlegm and resolving mass, and has the combined effects of treating both symptoms and root causes, tonifying deficiency and eliminating excess, which can increase energy consumption of the body, reduce fat generation and storage to achieve the effect of weight loss.The traditional Chinese medicine composition of the application is mainly composed of food-medicines, and can be taken for a long time.

The application provides an interaction method, device, electronic equipment and storage medium, candidate interaction content is selected from an interaction content set based on current time and triggerable time of each interaction content in the interaction content set; human-computer interaction is performed based on the candidate interaction content; the each interaction content is obtained by content classification on historical interaction data, the interaction content set is maintained based on a memory period of the each interaction content, and the memory period and the triggerable time of the each interaction content are determined based on an interaction category to which the each interaction content belongs. The method, device, electronic equipment and storage medium provided by the application reduce terminal data storage, reduce terminal calculation, and thus improve the response speed of the terminal during interaction. Meanwhile, the candidate interaction content is selected from the interaction content set, human-computer interaction is performed, appropriate and close-to-user historical interaction data human-computer interaction is provided, and the experience of the user is improved.

This invention discloses a lightweight few-shot incremental learning method for power line defects. The method includes: first, constructing an inspection image dataset containing basic and incremental categories, and designing a lightweight feature extraction network; training the network using the basic category data to generate prototype vectors for each category, forming an initial prototype classification model; in the incremental stage, constructing incremental prototypes for a small number of samples of the new category, and introducing a prototype transfer mechanism based on inter-class tension, adaptively adjusting the new prototype based on the geometric similarity and discrimination conflict strength between the new and existing prototypes to alleviate category conflicts; simultaneously, introducing an adaptive feature fusion mechanism that perceives discrimination uncertainty, dynamically fusing the discrimination results of the main and auxiliary branches to improve recognition stability. This invention, employing the above-mentioned lightweight few-shot incremental learning method for power line defects, can achieve efficient and stable power line defect recognition in scenarios with few samples and continuously expanding categories.

The application discloses a tunnel boring machine space dynamic compensation seismic wave advanced detection method and system, comprising: receiving the reflection echo data of the current space position; compensating the reflection echo data according to the attenuation compensation factor of the current space position, wherein the attenuation compensation factor of the current space position is obtained by a trained neural network, and the prediction process comprises: after curve fitting of the attenuation compensation factor of the reflection echo data of the detected space position, the attenuation compensation factor of the next space position is predicted by using the trained neural network; the compensated reflection echo data is subjected to geological body imaging by using the equal travel time imaging method, and the geological body detection result is obtained according to the amplitude difference on the imaging profile. The space dynamic compensation algorithm of the mechanical wave attenuation is used to adaptively correct the attenuation compensation factor at the next tunneling surface, so as to compensate the received reflection echo data and enhance the identification ability of the reflection echo.

This invention discloses a multi-level index compression method, apparatus, and device for reducing image storage space, relating to the field of image processing technology. The method includes obtaining the total number of color categories of a security display icon, and calculating an index value representing each pixel in a single color based on the obtained total number of color categories and a preset encoding algorithm. The storage space occupied by the current security display icon is calculated by combining the index value with the current size of the security display icon, or by combining the index value with the current size of the security display icon and the region code of the target area, thereby achieving compression processing. This application significantly reduces the encoding bit width of pixels through multi-level encoding of image pixel data, effectively compressing the data volume of the security display icon and greatly reducing the data storage volume.

The present application relates to a kind of pneumonia detection model training method, specifically to a kind of hierarchical topology pneumonia detection model based on collaborative learning system and method.It overcomes the difficulty of existing pneumonia detection model training system, low efficiency and the problem that local detection node cannot achieve optimal detection performance.First, each node uses local pneumonia data to pre-train respective pneumonia detection model locally, then, center node is based on the feedback data of local model to build hierarchical topology collaborative learning system;After that, each cluster node and child node uses local pneumonia data to train respective pneumonia detection model locally;Finally, collaborative training is carried out, including intra-cluster collaborative training and inter-cluster collaborative training;Intra-cluster collaborative training includes cluster node aggregation training and child node random interactive training.The present application has small data transmission, storage and calculation pressure, and is easy to implement;At the same time, different client is provided with different model parameters, so that each hospital detection node achieves local detection performance maximization.

The application discloses a resonant converter control method and device based on threshold voltage control, and the method comprises the following steps: comparing an input voltage with a primary side equivalent voltage to determine whether the resonant converter is currently working in a boost mode or a buck mode; determining threshold voltages of a resonant capacitor in the boost mode and the buck mode; comparing the threshold voltages with collected resonant capacitor voltages to determine switching signals of an inverter circuit; and the threshold voltages of the resonant capacitor in the boost mode and the buck mode are calculated based on P-stage cosine response parameters and N-stage cosine response parameters of the resonant capacitor voltages. By using the above technical scheme, the resonant converter has strong voltage ripple suppression capability, effectively suppresses secondary harmonic voltage ripples from a previous stage, and the control signals are directly determined by input and output states, thereby having excellent dynamic performance.

This invention specifically relates to an information management platform based on Internet of Things (IoT) technology, specifically in the fields of IoT data security and information management technology. It includes: a source-side data entanglement generation module; an edge-side local ledger maintenance module; a business event-triggered anchoring module; and a cloud-based auditing and dispute arbitration module. In this invention, standardized data collection and lightweight chained hash entanglement calculation lock the time-series data from the physical source of data generation. A lightweight algorithm with hardware-level optimization is used, occupying only 32 bytes of volatile memory to cache the latest hash value, adapting to the low power consumption, low computational cost, and small storage characteristics of IoT terminals. The edge side is equipped with a real-time packet-by-packet chain break detection and self-healing mechanism, which can quickly detect and attempt to repair hash chain breaks, preventing tamper-proofing failure.

The present application relates to the technical field of park energy data management, and particularly relates to a zero-carbon smart park comprehensive energy method and system based on big data, wherein the method comprises the following steps: S1, generating a carbon equity unit record; S2, establishing a corresponding source summary for each carbon equity unit; S3, writing the identification information corresponding to the transferred carbon equity unit into the restriction identification set corresponding to the first node; S4, generating a merged source summary; inheriting the source summary before splitting; S5, performing backflow risk verification based on the source summary attached to the to-be-transferred carbon equity unit and the identification information in the restriction identification set; S6, using the registration result for comprehensive energy scheduling and carbon accounting; the method effectively avoids the loss of source information and the risk of repeated offsetting caused by merging and splitting, and facilitates linkage with comprehensive energy scheduling and carbon accounting, thereby improving the real-time performance, implementability and system autonomy of zero-carbon smart park carbon equity management.

The invention relates to a method and system for obtaining analysis data in a semi-physical simulation process, the method is applied to a simulation computer end, and the method comprises the steps that when simulation starts, recording configuration issued by a data analysis computer is received, and the recording configuration comprises a sampling recording period, a segmented recording condition, a to-be-recorded signal set and a data recording layout; based on the to-be-recorded signal set, establishing a corresponding relationship between the record description information and the field offset and the corresponding relationship between the record signal identifier and the field length; and creating an initial segmented data recording file and writing segment header information. Segmental recording conditions are judged step by step in simulation operation, and if not, the to-be-recorded signals are read from the model according to a sampling recording period and packaged into fixed-length records according to layout, and the fixed-length records are additionally written; and when the segmentation condition is met, ending the current segmentation, generating a completion identifier, creating a new segmented file, switching and writing, and circulating until the simulation is finished.

The present application relates to a ship heave motion prediction method and system based on a lightweight context-aware network, belonging to the field of ship and ocean engineering motion control technology, including the following steps: signal acquisition and preprocessing, heave motion multi-step prediction based on LCGNet network, model training and optimization, quantization and compression of the trained LCGNet model, and deployment on a shipborne edge computing device; during system operation, historical heave data is collected in real time and input into the model, and step S2 is executed in a loop to realize continuous online prediction of future heave motion; through innovative lightweight network structure design, high-precision, multi-step heave motion real-time prediction is realized at extremely low parameter and calculation cost to meet the engineering deployment requirements of the shipborne active heave compensation system.

The application discloses a kind of energy-saving control method of frequency conversion speed regulation and energy recovery cooperation rig plunger pump, and relates to industrial control technical field.The method includes: monitoring the current working power of rig plunger pump at first working frequency, when power exceeds preset first working power interval, first working power time sequence is collected;According to the time sequence data, the geological adaptability coefficient is calculated using the pre-trained geological adaptability analyzer;Determine whether the working frequency needs to be adjusted, and determine the second working frequency and the corresponding second working power interval accordingly;Based on the second working frequency, frequency converter, energy storage device and energy recovery device are cooperatively controlled.The application realizes intelligent perception and self-adaptive adjustment to formation change, and significantly improves the energy efficiency and operation economy of rig plunger pump under complex geological conditions through the collaborative management of energy.

The utility model relates to screen test field, specifically disclose a TFT screen general test drive board, including main PCB board, power interface, core processor, image signal generating unit, multiple different types's FPC connector seat, programmable interface switching circuit, function button group and state indicating unit, multiple different types's FPC connector seat connects the TFT screen of different interface specification, programmable interface switching circuit input end connects image signal generating unit, and multiple output ends are connected to the pin of multiple FPC connector seat respectively, are used for dynamic configuration signal mapping relation, the utility model discloses through integrating multiple different types FPC connector with programmable interface switching circuit, so that single drive board can intelligent adaptation different model TFT screen, has promoted test universality and efficiency, avoided the cost and tedious of frequent replacement special drive board, reduced the storage and management expense, and the test pattern has strengthened the reliability, has expanded the application flexibility, and the comprehensive economic benefit is remarkable.

The invention discloses a rail vehicle fault diagnosis information acquisition method. An important information acquisition and storage strategy is adopted. The method comprises the following steps: setting an important information acquisition starting condition of a monitoring point and a single acquisition total duration T0; meanwhile, setting a time-division frequency-division acquisition scheme in the total time period T0; the time-phased frequency-division acquisition scheme comprises the steps that the total acquisition time T0 is divided into T1, T2,..., Ti,... and TN, the sampling frequency corresponding to each time period is F1, F2,..., Fi,... and FN, and T0 is equal to T1 + T2 +... + Ti +... + TN and F1gt; f2gt; gt,... gt; figt; gt,... gt; i is greater than or equal to 1 and less than or equal to N, and N is greater than or equal to 2, namely, the acquisition frequencies in all time periods are different and are sequentially reduced. According to the invention, all effective information of railway vehicle daily fault diagnosis can be collected, invalid information is little or even no information exists, and the problems that the number of monitoring points for railway vehicle fault diagnosis is large, the information collection amount is large, and the calculation processing amount is large can be solved.

The present application relates to a kind of cylindrical electrode paste and its preparation method.A kind of cylindrical electrode paste, by mass parts, including 15-20 parts of anthracite main material, 25-40 parts of residual anode, 3-10 parts of graphite fragment, 25-35 parts of coke, 15-30 parts of organic binder, 6-18 parts of bio-based binder. Among them, organic binder includes medium temperature pitch, anthracene oil, beta resin. Among them, bio-based binder includes carbonized hydrophobic composite modified wood bamboo powder, sodium carboxymethyl cellulose. The carbonized hydrophobic composite modified wood bamboo powder of the present application and sodium carboxymethyl cellulose are compounded to form a bio-based binder, which cooperates with the organic binder to ensure the bonding strength, high temperature resistance and electrical conductivity of the cylindrical electrode paste, while realizing the green and low-carbon utilization of biomass, solving the problems of high temperature failure, moisture absorption and easy caking, and many pores of traditional bio-based binder, reducing the resistivity and production cost, and improving the structural density and use stability.

The invention discloses an automobile-oriented dynamic electronic fence generation method, which comprises the following steps of: acquiring vehicle information, denoising, mining a risk area and a resident place, and generating an initial risk area model with boundary coordinates and risk levels; then, administrative division and road vector data are fused, a three-dimensional hierarchical fence structure is constructed, and fence boundaries are optimized through a Douglas-Peucker algorithm and a cubic B-spline function; according to the real-time driving state of the vehicle, the fence radius is dynamically adjusted through a linear expansion algorithm, the alarm sensitivity is regulated and controlled in a graded mode, and dynamic fence configuration is generated; and finally, vehicle positioning is monitored based on a state machine model, fence switching and boundary jitter are processed by combining priority arbitration and a hysteresis comparison mechanism, redundant alarms are filtered through a time sliding window and behavior intention analysis, and an early warning report with a context is generated. According to the invention, dynamic and multi-level management and control of the electronic fence are realized, the accuracy and suitability of vehicle risk control monitoring are improved, and the false alarm rate is reduced.

The application discloses a kind of MIMO mobile phone antenna adaptive tuning methods based on reinforcement learning, comprising the following steps: acquisition operating parameter;Operating parameter set is fused and encoded, and the characteristic vector containing historical state and time series information is generated;According to operating parameter set, the action range boundary is calculated, and the out-of-bound detection rule and rollback trigger condition are generated;Characteristic vector and action range boundary are input into improved diffusion strategy generation model, and tuning action is generated using hierarchical policy network;According to the out-of-bound detection rule, detection is carried out and rollback is triggered when out-of-bound, to obtain stable execution state;Stability index is calculated and diversity-stability collaborative reward function is constructed, and hierarchical policy network is updated;Scene label is generated, key-value pair index is formed and stored, and lightweight strategy is constructed and solidified through network distillation method.The application realizes the adaptive tuning of MIMO mobile phone antenna.

The utility model discloses a water area salvaging device which comprises a salvaging head used for salvaging floating objects on water. The telescopic rod comprises a first hollow rod, a second hollow rod and a locking structure, a fishing head is installed at one end of the first hollow rod, the radial outer surface of the first hollow rod is matched with the inner surface of the second hollow rod, the second hollow rod and the first hollow rod can slide relatively, and the locking structure is arranged between the first hollow rod and the second hollow rod; the locking structure is used for connecting and fixing the second hollow rod and the first hollow rod; the floating body is connected to the side, away from the first hollow rod, of the fishing head, and the floating body is used for preventing the fishing head from sinking into water. According to the utility model, the problems of operation risk and storage caused by insufficient or overlong length of the traditional handheld rod are solved, and the operation difficulty is reduced.

The embodiment of the invention provides a state snapshot method of a cloud native container, a state recovery method and related equipment, and relates to the technical field of computers. The state snapshot method comprises the following steps: receiving a snapshot triggering instruction which is issued by a snapshot controller and carries a target container identifier; obtaining a writable layer path of the target container based on the target container identifier, wherein a writable layer is an Upperde layer of a basic mirror layer in the joint file system; based on a writable layer path of the target container, calling a snapshot execution component to perform persistent operation on a writable layer, generating snapshot data and associated snapshot metadata, and storing the snapshot data and the associated snapshot metadata to a persistent storage system; the snapshot metadata at least comprises a writable layer path, a basic mirror image layer identifier and a snapshot identifier, the basic mirror image layer identifier is used for uniquely identifying a basic mirror image layer on which a writable layer depends, and the snapshot identifier is used for uniquely identifying a snapshot version of the snapshot data. Therefore, the flexibility and reliability of container state management can be improved.

This invention discloses a real-time personnel recording door lock system based on door lock handle action triggering, belonging to the field of smart lock technology. It includes: an inertia spectrum acquisition module for acquiring the rate of change of the angular velocity of the handle rotation and generating an idle inertia spectrum characterizing the handle's natural rotation; an energy-addition calculation module for decomposing the handle rotation into multiple phases and calculating the energy difference between the real-time inertia value of each phase and the idle inertia spectrum, defined as the operation energy-addition; and a feature window retrieval module for opening an attention window centered on the anchor point when the curve shape of the operation energy-addition matches a predetermined feature, with the handle rotation angle reaching a predetermined critical angle as the anchor point. This invention can avoid cluttered backend ledgers, reduce the difficulty and cost of data screening for management personnel, reduce system storage and computing power consumption, improve the response speed and operational stability of the door lock system, and prevent invalid logs from masking real abnormal events such as illegal intrusions.

The application discloses a weld surface defect detection method and system, and relates to the technical field of image recognition. The method comprises the following steps: acquiring a weld image to be detected; inputting the weld image to be detected into a preset weld defect detection model to obtain a defect detection result. The preset weld defect detection model comprises a preset backbone network, a preset neck network and a preset head network. The preset backbone network and the preset neck network each comprise a plurality of lightweight C2f modules that replace C2f modules in an original YOLOv8n model. Therefore, the model parameter quantity and the calculation quantity can be reduced to reduce the storage and calculation resource requirements of the model. In addition, the lightweight C2f modules are constructed based on a lightweight convolution layer and a double-channel attention mechanism. Therefore, the model detection accuracy for small target defects can be improved, and the missed detection rate can be effectively reduced.

This invention discloses a heterogeneous dual-stream Chinese memory reasoning method based on dynamic adjustment of semantic confidence, relating to the fields of natural language processing and large model architecture optimization in artificial intelligence. This application employs a semantic mapping table and gating mechanism to dynamically adjust the weights of the glyph feature vector and the context semantic vector of each Chinese character to generate a fused representation of each Chinese character, thereby more effectively distinguishing similar-looking characters and more accurately processing abstract words. Cross-attention calculation is performed on the semantic subgraph to obtain a corrected vector representation for the target text. Since the number of nodes in the semantic subgraph is limited, this correction process significantly reduces computational consumption compared to the global attention calculation of Transformer models or static hybrid architectures such as Jamba in the same text processing scenario.

The invention discloses cryptographic module embedded software supporting an anti-quantum cryptographic algorithm and an implementation method, aiming at the problem that embedded equipment resources are limited, a layered architecture design is adopted, and threat detection, algorithm selection and a core cryptographic module are included. The method comprises the following steps: quantifying a quantum threat level (TL), combining resource states such as equipment memory, computing power, electric quantity and the like, adaptively selecting a traditional cryptographic algorithm or a PQC algorithm (CRYSTALS-Kyber, SPHINCS + variant) through a dynamic decision function, and reducing overhead by adopting technologies such as hybrid encryption, assembly optimization, sparse matrix and the like. According to the method, key generation, encryption and decryption, digital signature and algorithm seamless switching are realized, quantum attacks can be resisted, an embedded scene is adapted, an existing system is compatible, data security and service stability are guaranteed, and the method is suitable for terminal equipment which is limited in resource and needs to resist quantum threat, such as a smart power grid.