408 results about "Fingerprint" patented technology

The invention discloses a tough city resource allocation method and system based on a block chain and edge computing, and relates to the technical field of city resource allocation, a federal protocol is utilized to exchange and shear a gradient abstract synchronization model version, then a prediction abstract containing fingerprints is written into a permission chain, and a time sequence is solidified through Byzantine consensus; an on-chain smart contract executes adaptive threshold evaluation based on sliding window prediction to generate a deployment intention with a verifiable path, the intention is sent to an execution subsystem through a side chain message bus in a low-delay mode, and cross-department resource rearrangement is completed through rolling optimization of an adaptive decision driver; an execution receipt is mapped into an incremental patch and written back to a local state tensor, a node trust weight is dynamically adjusted, and when the coverage degree and the weight rising range meet a triggering strategy, differential shearing training is started, and a new structure fingerprint and a model signature are generated; and efficient, credible and dynamic allocation and sustainable learning synchronous evolution of urban public resources in an emergency scene can be ensured.

The invention relates to the technical field of ecological environment monitoring, in particular to a multi-dimensional data analysis-based water body pollution monitoring and processing system, which comprises a dynamic data cube construction module, a pollution event slice extraction module, a multi-dimensional feature fingerprint coupling module, a pollution source reverse traceability module and a self-adaptive early warning trigger module. The method comprises the following steps: receiving water quality parameters of an internet of things sensor, meteorological data of a meteorological hydrological station and satellite remote sensing spectral data, and constructing a dynamic data cube of unified space-time coordinates and feature axes; identifying pollution event slices by using entropy change analysis and a self-adaptive threshold method; carrying out characteristic coupling analysis on the pollution event, and fusing a spectrum fluctuation mode, a physicochemical gradient and toxicity response to generate a pollution characteristic fingerprint; pollution source positioning and contribution weight estimation are realized by adopting a dynamic time warping algorithm, and corresponding disposal equipment is driven to start based on an early warning level, so that intelligent closed-loop control of pollution identification, source tracing and treatment is realized.

The invention relates to the technical field of textile informatization and block chain encryption traceability, in particular to a textile quality block chain encryption traceability method, which comprises the following steps of: implanting quantum dot-nucleic acid mixed fingerprints into yarns in a spinning stage and generating distributed identities; in the production link, process data are collected in a trusted execution environment, and are packaged into an encrypted packet by using homomorphic encryption, zero-knowledge proof and threshold signature; and after a batch threshold value is reached, calculating a batch commitment and a fragmentation commitment, fragmenting through erasure coding, writing the commitment and the proof into the directed acyclic graph according to a fixed field, and confirming through a Byzantine fault-tolerant consensus. Consumer off-line fingerprint comparison and homomorphic verification can realize authenticity identification, and after networking, batch certification is verified and credits are pledged. And when the time lock expires, the historical quality data is decrypted by multiple subjects in a combined manner, and maintenance suggestion hash is generated and written into subsequent transactions, closed-loop tracing from production to maintenance is realized, and anti-counterfeiting, privacy protection and quality improvement are realized at the same time.

The invention discloses a dynamic tracking method for an air pollution source, which relates to the technical field of pollution source tracking and comprises the following steps of: acquiring a pollution concentration raster data set, a UAV sniffing set and a meteorological field data set, reconstructing a wind field and predicting pollution transportation, generating a candidate source hypothesis, matching fingerprints and calculating weights, adaptively scheduling sensors, and performing Bayesian inversion fusion and result output. Unified pollution concentration and meteorological data are generated through multi-source data collection and three-dimensional flow field reconstruction, second-level wind field calculation is achieved through a dimensionality reduction CFD model, candidate source hypotheses are generated in combination with Lagrange backtracking and Euler transport, and a weight matrix is formed through UAV mass spectrum fingerprint bidirectional matching. Secondary cruise of the unmanned aerial vehicle and densification sampling of ground nodes are driven through confidence ranking, and sampling density is adaptively optimized. Bayesian joint likelihood and Markov chain are adopted to fuse multi-source data, dynamic source coordinates and emission rate are output, and a closed-loop iterative air pollution source tracking system is realized.

The invention provides a 10kV cable accessory manufacturing quality inspection report generation method and system, and relates to the technical field of power equipment quality detection and reliability evidence storage. According to the method, original detection data is acquired and structured in multiple dimensions, and data sources, operators and equipment identifiers are bound, so that context integrity and traceability are realized; initial and enhanced data fingerprints are generated through block classification, standardization and Hash operation, and a dynamic fingerprint chain is constructed by using a chain structure, so that whole-course data has content and process dual integrity identifiers; a multi-level verification sequence is embedded in each stage of report generation, finally, a block chain is utilized to record a data packet abstract, an anchor point on the chain is bound with report metadata, a transaction ID is embedded into a report document, and a checking two-dimensional code is generated. According to the method, the non-tampering performance and the verifiability of the content and the generation process of the detection report and the traceability of the whole circulation process are improved.

The invention relates to the technical field of power equipment monitoring, in particular to a multi-mode sensor power equipment state monitoring system based on AI smell. The data acquisition module is used for acquiring multi-dimensional sensing data around the electrical equipment; the AI olfaction processing module is used for converting original sensor data into standardized odor feature fingerprints by performing spatial-temporal feature extraction and multi-modal feature fusion on the multi-dimensional perception data; the overheating state analysis module is used for generating an overheating comprehensive index and an equipment state evaluation result based on the smell characteristic fingerprints; the multi-stage early warning and response module is used for carrying out early warning grade judgment based on the overheating comprehensive index and the equipment state evaluation result and generating graded early warning information; and the storage module is used for storing historical monitoring data and early warning event records. According to the invention, through system integration of the multi-mode sensor array of the bionic olfaction mechanism, AI feature fusion processing and intelligent analysis decision, active sensing and accurate identification of the overheating state of the power equipment are realized.

The invention discloses a novel organic pollutant traceability model construction method based on multi-environment medium data, and aims to solve the problem of deformation compensation of source fingerprints in chemical conversion, interphase distribution and medium migration processes. According to the method, a constrained cost matrix is generated by constructing a micro-deformable kernel, hybrid expert gating weighting is carried out, capacity and rate constraints are injected, a shared potential source fingerprint is solved and introduced by adopting staged cascaded entropy regular optimal transmission joint, reverse optimal transmission and two-way cyclic consistency reconstruction and alignment are combined, and the optimal transmission performance is improved. The technical effects of obtaining the compensated source fingerprint and the source contribution rate and improving the cross-medium traceability accuracy and interpretability are achieved.

The invention provides a large-model-oriented heterogeneous computing power adaptive compiling method, which comprises the following steps that: a user inputs a trained large model through a system interface, and a system front-end conversion module analyzes a computational graph of the model and converts the computational graph into an intermediate representation based on a unified operator description language (UDL); the system hardware sensing module automatically detects and extracts hardware feature fingerprints of at least one piece of target hardware; based on the unified operator description language UDL intermediate representation and the hardware feature fingerprint, automatically generating an optimization adaptation rule oriented to at least one piece of target hardware; wherein the basis of parameterized filling comprises specific parameters of hardware feature fingerprints and optimized attribute tags carried in an intermediate representation of a unified operator description language (UDL); and generating and deploying multiple back-end codes. The method has the beneficial effects that intelligent compiling based on hardware features can be realized, and the deployment efficiency and the operation performance of a large model in a complex heterogeneous computing power cluster are remarkably improved.

The invention relates to the technical field of machine learning intelligent decision, and discloses an AI intelligent decision reasoning method and system based on machine learning, and the method comprises the steps: monitoring a micro event which does not reach an alarm threshold value to open a time sequence window, coding the time sequence causal association between a plurality of sensors into a fingerprint vector which does not contain an original amplitude value in the window, according to the method, the limitation that traditional machine learning depends on static data snapshots is overcome, the hidden dynamic causal chain is directly coded into identifiable fingerprints, and therefore the recognition accuracy of the fingerprints is improved, and the recognition accuracy of the fingerprints is improved. The system can make accurate early warning in the germination period instead of the outbreak period of a systematic risk formed by accumulation of a plurality of tiny events, and the transformation from post-event diagnosis to beforehand foreseeing is realized.

The invention relates to the technical field of big data processing and analysis, in particular to a commodity traceability management method and system based on big data. The method comprises the steps of determining a data range and association logic of each type of events by constructing a semantic event system of a commodity life cycle, performing data acquisition, preprocessing and credibility evaluation at edge nodes and generating an evidence header, and further converting data into multilayer verifiable commodity fingerprints of an L1 edge abstract, L2 event level fusion and L3 full link fusion, the method comprises the following steps: realizing feature fusion and dynamic incremental updating, then performing distributed notarization and multi-party verification on fingerprints through a federated anchor point mechanism to ensure that a full link is traceable and cannot be tampered, and finally supporting full link traceability query and anomaly tracking based on a unique commodity identifier. And closed-loop traceable management is realized through visual display and multi-role authority management. According to the invention, the reliability, interpretability and cross-organization trust of commodity traceability are effectively improved.

The invention discloses a console identity recognition method based on a block chain, relates to the technical field of computer security and human-computer interaction, and realizes non-sensibility and precision of console identity recognition through fusion of behavior feature modeling and a block chain technology. In a multi-person alternate scene, an operator does not need to actively execute a biological verification action, and the system converts behavior characteristics into encrypted operation fingerprints by continuously capturing physical operation actions and graphic interaction logic and carries out uplink storage on the encrypted operation fingerprints; the block chain smart contract compares the time sequence difference between the current operation and the historical fingerprint in real time, and only when the behavior is abnormal, the biological auxiliary verification is triggered, so that the operation interruption caused by the factors such as gloves and light in the industrial environment is remarkably reduced; a dynamic permission label generation mechanism breaks through static authorization limitation; by analyzing the semantic intention of the control instruction and combining a preset equipment permission topological graph, the minimum equipment operation range is automatically delimited, and the tag validity period is set according to the instruction risk level.

The invention discloses a circuit breaker rigid regulation and control method and system based on a load monitoring terminal, and relates to the technical field of electric power automation, and the method comprises the following steps: S1, obtaining a unified nanosecond time base line, continuously collecting current signals of a plurality of loops, reconstructing a complete phase track of each loop current, generating a corresponding low-frequency lag fingerprint base line, and carrying out the collection of the low-frequency lag fingerprint base line; the reference basis is used for dynamic response correction; and S2, constructing a causal playback chain based on the low-frequency hysteresis fingerprint baseline, replaying a current transition behavior in the rigid regulation and control process of the circuit breaker, identifying a nonlinear hysteresis section, and extracting a threshold drift core parameter. According to the method, the current phase is reconstructed through the nanosecond-level time base, the lagging characteristics are extracted, the causal playback and energy coupling model is constructed, threshold double-track generation and time sequence correction are achieved, lagging energy is dissipated in combination with a phase conjugate instruction, the regulation and control precision and stability of a circuit breaker are improved, and the safety and the intelligent level of a power distribution network are enhanced.

The invention discloses a cable partial discharge analysis method and device based on oscillatory waves. The method comprises the steps that the oscillatory waves are applied to a tested cable, and low-frequency envelopes and high-frequency pulses are synchronously collected; performing structure normalization according to cable parameters; encoding the environment and working condition data into a condition vector to implement condition normalization; carrying out domain self-adaptive alignment with an ideal template clustered according to a model, a length and a joint / terminal type, and obtaining a difference feature; constructing a PRPD joint fingerprint, and counting a pulse phase, an amplitude, an envelope attenuation rate and / or an equivalent Q; outputting defect positions, types and confidence intervals based on the difference features and the joint fingerprints; and adaptively determining multi-gear upper pressure and advanced shutdown according to the information gain, and generating maintenance priority and retest interval suggestions. Through step-by-step normalization processing, domain adaptive alignment and fusion of PRPD combined fingerprint features, diagnosis stability and reproducibility are enhanced, weak discharge and early defect detection capability are enhanced, and complex working conditions and cross-trigger adaptability are enhanced.

The invention relates to the technical field of computers, and provides a cross-platform installation package automatic adaptation method and system, and the method comprises the steps: obtaining a unified description file and an operating system fingerprint of each target platform; based on the operating system fingerprints of the target platforms and the installation package adaptation parameters, matching is carried out, and dependency trees of the target platforms are generated; and generating an adaptive installation package based on the dependency tree of each target platform and the installation package adaptation parameter. According to the cross-platform installation package automatic adaptation method, specific parameters and shared parameters of the platform are managed in a centralized mode through unified description files, environment intelligent perception is achieved and the dependency tree of the platform is generated in combination with dynamically obtained operating system fingerprints, and the adaptive installation package is generated through analysis of the installation package adaptation parameters of the platform and the dependency tree. The problems of low adaptation efficiency, high configuration error rate, high maintenance cost and the like are solved; in addition, a unified construction management mechanism realizes cross-platform centralized management and control, and the accuracy and efficiency of cross-platform installation package adaptation are improved.

The invention discloses a data transmission security protection system for an edge computing server, which relates to the technical field of edge computing and network security, is deployed in an edge computing environment comprising a plurality of edge computing nodes, and comprises five modules: a behavior fingerprint construction module, a data processing module and a security protection module, dynamically updated behavior fingerprints are generated through a lightweight convolution auto-encoder; the dynamic trust chain management module constructs a dynamic trust chain network and generates a comprehensive trust score based on node historical interaction data; the collusion attack detection module identifies a collusion attack in combination with trust chain topology and node behavior consistency analysis; the self-adaptive isolation and recovery module isolates malicious nodes and migrates tasks to guarantee service continuity; according to the edge computing security protection method, protection is converted into active immunity from passive feature matching, collusion attacks are effectively defended, data transmission security is guaranteed, and the edge computing security protection method is suitable for edge computing security protection.

The invention discloses an electricity price execution and bill risk combined preposed intelligent early warning method, which relates to the technical field of electric power charging risk control, and comprises the following steps of: constructing rate digital twinning, managing atomic change according to a version directed acyclic graph, generating an explanation path of a trigger condition-calculation expression-bill line item, and mapping with a metering object, a customer object and a bill object; executability and traceability are realized. Based on layered samples and boundary samples, new and old rules are played back on double tracks of a sandbox, the bill difference, the uncertainty and the exposure degree are obtained, and differential hotspots are identified; generating a version binding scene pre-bill after a semantic structure, a coverage boundary, a performance budget and compliance consistent access control are passed, providing an alternative scene and collecting a receipt; gray level monitoring is carried out, rollback and secondary account checking are carried out according to the TariffID subgraph when triggering is carried out, and evidence fingerprints are formed; according to the scheme, aperture consistency and boundary coverage are improved, and accurate rollback and auditing verification are supported.

Disclosed is a method for providing a trained machine learning system for classifying images of fingerprints, the method comprising: providing a training data set, comprising sets of images of fingerprints, wherein each image in the training data set further comprises a binary label encoding a class designation; using the training data set to train a machine learning system, wherein the machine learning system comprises a classical machine learning model implemented on a classical processor and a quantum machine learning model implemented on a quantum processing unit (QPU); encoding the image data of each image in the training data set into a feature vector using the classical machine learning model, obtaining a family of feature vectors; using the family of feature vectors obtained from the images in the training data set to train the classical machine learning model and the quantum machine learning model, for providing the trained machine learning system, comprising a trained classical machine learning model and a trained quantum machine learning model.

The invention provides a block chain-based second-hand vehicle detection evaluation report traceability method and system, and relates to the technical field of traceability detection, and the method comprises the following steps: detecting a second-hand vehicle to obtain structured report data, the structured report data comprising a plurality of pieces of traceability information and a plurality of pieces of feature information; performing encryption processing on the structured data to generate a first verification code and a feature information set integrity check code, and generating a second verification code for each type of traceability information; storing the structured report data in a distributed storage system, and obtaining a global content addressing identifier of the structured report data in the distributed storage system; organizing the multiple key data according to a predefined sequence and format, calculating abstract fingerprints, and writing the abstract fingerprints, the structured report abstract and the multiple verification codes into blocks of the block chain; and performing traceability verification in the second-hand car exit transaction. The method has the advantages of high reliability and capability of ensuring that detection report data is real, complete and traceable.

Systems and methods are provided for attributing source code, including ingesting source code from a plurality of repositories, normalizing the ingested source code using abstract syntax trees (ASTs), and converting the normalized source code into vector embeddings that represent syntactic and semantic features of the source code. Unique fingerprints are generated from the vector embeddings, the fingerprints are compared against a vector database to identify potential matches and verify code attribution, and feedback and alternative code suggestions are provided based on the comparing the fingerprints.

The invention belongs to the field of analytical chemistry, and particularly relates to a method and a kit for identifying freshness of apple juice, and the method specifically comprises the following steps: S1, selecting apple juice prepared from known apples with different freshness, and analyzing and detecting the apple juice by using a chromatography-mass spectrometry system to obtain a corresponding fingerprint spectrum; s2, clustering and defining the fingerprints by using K-means clustering analysis and orthogonal partial least squares discriminant analysis based on peak information of the fingerprints corresponding to the apple juices with different freshness in S1 as characteristic variables, and defining the fingerprints as a fresh group or a rotten group to obtain a data set; s3, based on the data set in the S2, constructing an identification model by adopting a supervised machine learning algorithm; s4, to-be-detected unknown apple juice is taken, the fingerprint spectrum of the unknown apple juice is obtained under the same detection conditions in the step S1, and the freshness of the unknown apple juice is identified based on the identification model in the step S3. The method is high in identification accuracy.

Disclosed are methods of producing nutrient solutions having unique isotopic fingerprints; methods of producing traceable plants; and methods of identifying the source of a traceable plant that does not rely on expensive artificially separated isotopes. Plants grown with these nutrient solutions will have unique isotopic fingerprints that will be difficult or impossible to counterfeit.

The invention discloses an electric forklift gantry synchronous inclination system and an inclination system control method, and relates to the technical field of vehicle engineering and electrical control, and the method comprises the following steps: establishing a time-frequency phase-locked observation baseline, and calibrating an abnormal trigger window by collecting a pressure wave change track of the gantry synchronous inclination system under a reverse pressure bearing condition; generating a pressure wave characteristic fingerprint and a time delay matrix as dynamic references for resonance path identification; and according to the pressure wave characteristic fingerprints and the time delay matrix, inverting a hydraulic pipeline reflection topology, identifying a pressure energy concentration area, extracting a resonance source anchor point, constructing a wave energy distribution diagram, and forming a space positioning basis of the standing wave risk. According to the method, hydraulic standing wave risk modeling and boundary extraction are achieved through time-frequency observation and resonance path recognition, a standing wave damping structure is constructed in combination with the phase conjugate test and track shaping technology, steady-state damping and high-precision synchronous inclination control of the portal under reverse pressure bearing are achieved, and the system stability and operation safety are improved.

The invention discloses a sea-land interaction zone underground water pollution source tracing method based on multi-pollutant fingerprints, and the method comprises the steps: constructing a fingerprint feature library of eight key pollutants including cadmium, arsenic, nitrate nitrogen, ammonium nitrogen, phosphate, total petroleum hydrocarbon, sulfamethoxazole, pH value and the like; statistical characteristic models of four pollution sources of industrial emission, agricultural non-point sources, oil exploitation and aquaculture are established, Z-Score standardization and a similarity calculation method based on a standard normal distribution probability density function are adopted, comprehensive similarity evaluation is performed in combination with a risk weight distribution mechanism, a similarity threshold value of 0.7 is set to perform pollution source identification and sorting, and the pollution sources are identified and sorted according to the similarity threshold value. And correction is performed by considering environmental factors such as tide, season and geology of a sea-land interaction zone. The method can quickly and accurately recognize the groundwater pollution source of the sea-land interaction zone, the traceability accuracy rate reaches 80% or above, and scientific and technical support is provided for prevention and control of groundwater pollution of the sea-land interaction zone and formulation of an environmental protection policy.

The invention provides a detection and pollution tracing method and device based on four-dimensional fluorescent fingerprints, and relates to the technical field of detection. The method comprises the following steps: firstly, taking an enterprise involved in a suspected pollution industry as a suspected pollution source; then, collecting a target water body section sample, a target water body upstream unpolluted section sample and a suspected pollution source sample, and testing four-dimensional fluorescent fingerprints of all the samples; performing background signal deduction on the four-dimensional fluorescent fingerprint data based on the four-dimensional fluorescent fingerprint data of the upstream unpolluted section; calculating the fluorescence integral value of each component, and rejecting component data with the fluorescence integral value lower than a threshold value according to the set threshold value to form four-dimensional fluorescence fingerprint data; and calculating weight vectors of each component of the target water body cross section and the suspected pollution source, obtaining comprehensive similarity of each pollution source, and determining the attribution of the pollution source according to the comprehensive similarity. The method can achieve the precise recognition of different pollution emission sources in the same industry, and improves the traceability accuracy.

The invention relates to a branch identification system and method of a passive optical network. The system comprises a central control unit, a light emitting module, a polarization analysis unit and a plurality of polarization control modules deployed in an optical splitter, wherein the plurality of polarization control modules are in one-to-one correspondence with a plurality of ports of the optical splitter; the optical transmitting module transmits a detection signal to the passive optical network; the polarization control module carries out modulation processing on the received detection signal according to a preset polarization state modulation rule, generates a reflection signal carrying a polarization fingerprint and transmits the reflection signal to the polarization analysis unit; the polarization analysis unit analyzes polarization fingerprints according to the reflection signals and sends the polarization fingerprints to the central control unit; and the central control unit determines a branch serial number corresponding to the reflection signal according to the polarization fingerprint, and determines a branch link identification result. By adopting the system, the identification of a plurality of branch links in the passive optical network is realized, manual intervention is not needed, normal communication service does not need to be interrupted, the network maintenance efficiency is improved, and the manpower and time cost is reduced.

The invention belongs to the technical field of data analysis, and discloses a case clue acquisition method and system based on intelligent terminal forensic data, and the method comprises the steps: collecting multi-source forensic data from intelligent terminal equipment, carrying out the time synchronization, denoising and format unification processing of the collected multi-source forensic data, and obtaining the multi-source forensic data. Extracting behavior feature vectors, mapping the behavior feature vectors to a unified feature space, and outputting a standardized feature set; the standardized feature set is combined with a corresponding time label, a tamper-proof evidence obtaining fingerprint is generated, a double-index storage structure according to time and geographic dimensions is constructed, and cross-terminal evidence retrieval, integrity verification and tracing are carried out; according to the standardized feature set and the tamper-proof evidence obtaining fingerprint, verifying cross-terminal identity and implement association through behavior signature consistency characterization; adopting a subthreshold accumulation triggering mechanism to perform accumulation evaluation on behavior characteristics of the intelligent terminal in a preset time window, and outputting an identity object consistency assertion; the case reasoning accuracy and the case clue obtaining efficiency are improved.

The invention discloses a real-time energy consumption optimization control system for digital twins of a paper cup production line, and relates to the technical field of energy consumption optimization control, and the system comprises the steps: 1, collecting incoming material and environment fingerprints, carrying out the semantic alignment of an asset management shell, and building an energy consumption baseline; 2, constructing a mass-energy coupling twinborn model, and fusing infrared, vision, output intensity, risk and unit energy consumption; 3, online identification is carried out, fingerprints are mapped into process boundaries and change rates, and a process window is published; 4, joint optimization is carried out in the window, and reinforcement learning of shielding projection is used for short-time takeover during disturbance; and 5, safely issuing, storing the strategy snapshot, auditing and rectifying to form a closed loop. Multi-source connection, energy conservation, consumption reduction, quality control, peak power suppression and traceable treatment are realized; and compressed air supply-transmission and distribution-gas utilization efficiency evaluation, boundary versioning and rate limitation unified management, boundary-crossing back-off of a safety template and strategy parameter closed-loop updating are carried out.

The invention provides a mobile application security detection method and system based on multi-dimensional features and network behavior fingerprints, and relates to the technical field of network security, the method comprises the following steps: running a mobile application in a controlled environment, capturing network traffic data generated in the running process of the mobile application, extracting dynamic behavior characteristics including communication frequency, communication type and communication content from the network flow data, constructing a network behavior fingerprint based on the dynamic behavior characteristics, and performing normalization processing on the dynamic behavior characteristics to obtain normalized dynamic behavior characteristics; and in combination with a risk classification threshold and the normalized dynamic behavior characteristics, correcting a scoring result to obtain a final security score. According to the method, the static code layer features and the dynamic flow layer features are comprehensively analyzed, the mobile application type is judged, and efficient traceability is achieved.

The invention relates to the technical field of analogue simulation, in particular to a plate shape control parameter optimization method based on digital twinning, which comprises the following steps of: constructing a material microscopic performance digital twinning body, calculating the offset of a physical neutral layer through virtual straightening rehearsal, deducing a non-uniform differential curvature target, carrying out reverse iteration, and outputting a global optimal parameter of a straightening machine. And the fracture mechanical model is used for driving the digital twin to perform virtual simulation of shear crack propagation, burr and edge collapse data are calculated, and the angle and surface prestress parameters of a shear knife are adjusted. And the production line laser point cloud and the visual image are fused to construct geometric morphology digital twin bodies, a defect topology fingerprint is generated, the two digital twin bodies are coupled by running a moving target spot interception algorithm, and the optimal transverse track and the local rolling reduction of the stress release roller are planned. According to the method, through multi-physics field virtual simulation and closed loop verification, collaborative optimization of global straightening, dynamic shearing and local repairing in high-strength steel plate production is achieved.

The invention provides a certificate generation and access authentication method based on host fingerprints, and aims to improve authentication security by combining hardware fingerprints and certificate management. In the traditional EAP-TLS authentication, the user identity completely depends on a client certificate and a private key, is easy to copy or leak and has potential safety hazards, and when the private key is captured, an attacker can disguise as a user to access an intranet. According to the method, hardware fingerprints are dynamically calculated at a client side (an SHA256 Hash value is generated based on information of a network card, a hard disk, an SMBIOS, a mainboard and the like) to verify a certificate, and the certificate is sent to an authentication server. Meanwhile, on the basis of EAP-TLS bidirectional authentication, the matching condition of the certificate fingerprint and the client host is additionally checked, strong binding of the certificate and the host is achieved, and the related certificate can only be used on the corresponding host. In order to further enhance the protection of the certificate, the client stores the certificate and the private key as EFI variables. The method is widely applicable to various wireless network authentication scenes, and has wide applicability and remarkable economic benefits.