981 results about "Data recording" patented technology

The invention relates to the technical field of network communication, and discloses a vehicle-mounted edge computing data recording system and method based on protocol adaptive analysis, and the system comprises a multi-protocol network access controller which is used for capturing an original data frame and extracting a physical feature triple; the identification analysis engine is used for executing hash operation on the triple to generate a physical feature code and retrieving a physical logic address mapping table; the direct memory access controller is used for responding to a target memory address pointer hit by retrieval and directly writing a data load into an input buffer area of the functional operation module, and by constructing a direct addressing mechanism based on Hash mapping, thorough decoupling of vehicle-mounted heterogeneous network physical topology and edge computing logic is achieved.

The invention provides a converter station in-station equipment energy consumption analysis model and method. Belongs to the field of converter station equipment energy consumption analysis. According to the method, a three-dimensional data acquisition system covering equipment in the whole station is established, electrical measurement data of the equipment is obtained in real time through a monitoring system, and meanwhile, a converter valve trigger pulse, a cooling water pump rotating speed adjusting signal and a circuit breaker opening and closing state are captured through an equipment digital twin interface. And carrying out real-time feature extraction by means of an edge computing node, and triggering high-speed data recording for a commutation failure event. And correcting abnormal data by combining a sliding window dynamic cleaning mechanism with a wavelet threshold denoising algorithm, and extracting a current harmonic distortion rate, a voltage fluctuation coefficient and equipment vibration spectrum characteristics. And further establishing a multi-dimensional characteristic matrix containing equipment operation conditions, environmental parameters and power grid interaction characteristics, performing energy consumption prediction by using a hybrid model, and generating a dynamic energy efficiency evaluation index which is applied to energy saving strategy optimization.

The invention discloses a wiring harness dynamic load and electromagnetic interference coupling test method, and relates to the technical field of wiring harness testing, and the method comprises the steps: S1, defining a plurality of environment parameter groups, and constructing a test platform; s2, dynamic current pulse and multi-axis vibration excitation are synchronously loaded; s3, applying broadband electromagnetic interference signals and monitoring signal crosstalk amplitude and bit error rate changes; s4, the sensor nodes are dynamically configured according to the topological structure of the wire harness; s5, generating a feature vector; s6, outputting a wire harness performance index; s7, outputting a wire harness fault probability prediction value; s8, obtaining prediction data; s9, triggering a high-speed data recording mode, and storing original sensor data 60 seconds before the fault; and dynamically adjusting the gradient step length and the loading sequence in the environment parameter group. Performance evaluation, fault prediction and service life management can be carried out on the wire harness under complex working conditions, and the reliability and safety of an automobile electrical system are improved.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a multi-modal content compliance auditing method, device, equipment and medium, and the method comprises the steps: receiving a multi-modal content set, and generating to-be-audited content; converting the multi-source content into unified semantic representation through an analysis unit; calling the judgment model based on the auditing strategy library and the configured auditing engine to perform semantic comparison, and generating an auditing processing result; outputting an abnormal level result according to the processing result; a rectification suggestion is generated and pushed based on the abnormal level result, and feedback data is received at the same time; recording feedback data and auditing tracking records, and generating a compliance data view and an auditing conclusion; and updating the auditing strategy library and the configured auditing engine according to the feedback data. According to the method, cross-modal check is realized through unified semantic representation, the check flexibility is improved in combination with a strategy library and a configuration engine, rectification and feedback are driven by using an abnormal level result, and the accuracy and efficiency of compliance check are improved.

The invention provides an electromechanical pipeline conflict detection and adjustment method and system based on a BIM model, and belongs to the field of electromechanical installation. According to the technical scheme, the method comprises the steps that geometric parameters of a BIM model generation component are analyzed, and electromechanical pipeline conflict data are generated; conflict types are automatically classified according to the electromechanical pipeline conflict data, and electromechanical pipeline conflict sorting data are calculated; calling a knowledge rule engine according to the electromechanical pipeline conflict type and the electromechanical pipeline conflict sorting data, and matching a conflict adjustment strategy; executing a pipeline position adjustment action, and synchronously updating BIM model data; and recording the adjusted conflict processing result to a case library, and carrying out strategy optimization updating on the knowledge rule engine based on case library data. The method has the beneficial effects that an automatic and intelligent processing process of electromechanical pipeline conflicts from identification to adjustment is realized by constructing a conflict detection and adjustment full-process mechanism based on the BIM model, the manual intervention frequency is effectively reduced, and the constructability and the cooperation efficiency of the BIM model are improved.

The invention discloses a high-precision multi-modal twin model assembly method based on a large language model and a multiple docking optimization mechanism. The whole system framework is composed of three modules: a database, an interaction system and human factors. Wherein the database module integrates a model library module, a user interaction data recording module and a temporary data recording module, and is used for storing and managing various data information required for constructing a virtual scene; the interactive system module is used as a core part, integrates a model dynamic loading module, a model accurate positioning module and a model adaptive assembly module, realizes instruction analysis and model generation by relying on a large language model, and combines a multi-docking optimization mechanism of eye movement tracking, gesture recognition, automatic docking and logic rule binding to realize multi-docking. Efficient and accurate interaction between the user and the database is effectively guaranteed; the method not only provides a solid foundation for virtual experiments and virtual-real symbiosis, but also significantly improves the construction efficiency and precision of digital twin model assembly.

The invention relates to the technical field of data recording, in particular to a data recording system for an automatic driving vehicle, and the system comprises a multi-source signal synchronization module, a behavior stage recognition module, a track abnormity elimination module, a dynamic compression adjustment module and a segmented index marking module. According to the method, a unified time alignment mechanism is constructed in a signal synchronization processing link, a strict corresponding relation between acquisition sequences is ensured, key time sequence characteristics of driving behavior switching are extracted by adopting a multi-behavior parameter comprehensive judgment method, segmented expression of a complex driving process is realized, and the accuracy of driving behavior switching is improved. According to track anomaly identification, through collaborative screening of inertial data and a positioning track, abnormal fragments which do not conform to physical rules are effectively eliminated, data compression dynamically sets interval length according to a parameter combined fluctuation trend, the fidelity of a key period is remarkably improved, non-key data redundancy is inhibited, and after a segmented index structure is established, the data compression efficiency is improved. And the data retrieval process is clearer.

The invention relates to the technical field of self-adaptive starting, and discloses a self-adaptive starting method and system based on voltage and current monitoring, and the method comprises the steps that an MCU (Microprogrammed Control Unit) triggers an auxiliary silicon controlled rectifier and a main silicon controlled rectifier through preset starting logic to start a motor, and carries out the high-frequency sampling of current and voltage data in real time; once starting failure is detected, short-time voltage sequences and short-time current sequences before and after a failure occurrence point can be automatically captured and stored. Then, key features are extracted from the sequences, and failure causes are determined through decision tree model analysis. And based on the analysis result and the current retry times, the MCU outputs a corresponding retry strategy to ensure that the motor can be successfully started or enter a safety mode. Thus, the reliability of motor starting is improved, subsequent fault diagnosis is supported through detailed data recording, and the maintainability and safety of the system are greatly improved.

The invention discloses a man-machine cooperation degree modeling and evaluation system and method based on multi-modal perception, and aims to realize real-time quantitative evaluation and dynamic regulation and control in a man-machine cooperation process. The system comprises a multi-modal sensing module, a feature fusion and extraction module, a man-machine collaboration degree modeling module, a personalized interaction strategy feedback module and a task recording and evaluating module. The multi-mode sensing module collects the state of a user through multi-source data such as vision, voice, physiological signals and interactive actions. The feature fusion and extraction module adopts an attention mechanism to integrate multi-modal features; the man-machine collaboration degree modeling module constructs an evaluation model based on a supervised learning method, and outputs a quantitative score; a personalized interaction strategy feedback module dynamically adjusts a robot behavior strategy according to the score; and the task recording and evaluating module supports data recording, trend analysis and user portrait construction. The system can comprehensively perceive user states, evaluate cooperation quality in real time, and dynamically optimize robot behaviors.

The invention provides a containerized resource elastic scheduling method and system in a cloud computing environment, and relates to the technical field of containerized resource elastic scheduling, and the method comprises the steps: obtaining various resource contention events, and generating data which records a resource contention relationship between tenants in detail; identifying a preset high-frequency conflict mode by deeply analyzing the data, and determining a specific tenant group with a strong resource mutual exclusion effect; dynamically estimating a probability level of resource conflict between the new container and the specific tenant group in combination with historical contention information and a real-time resource load state; generating a set of dynamic isolation scheduling strategies according to the conflict risk indicated by the probability level; an independent conflict buffer resource pool is configured and adjusted for a specified key tenant, a tenant resource conflict mode can be identified, dynamic isolation scheduling and buffer resource configuration can be implemented, and the resource utilization efficiency and the system stability of a multi-tenant container in a cloud computing environment are improved.

The invention discloses a perfluorohexanone fire extinguishing agent fire extinguishing method and system applied to a power switch cabinet fire, and belongs to the technical field of power system energy storage equipment.The method comprises the steps that an arc light signal is detected through an arc light detection device, and a partial discharge signal is detected through an ultrasonic partial discharge detection device; meanwhile, temperature data and smoke concentration data in the cabinet are detected through a temperature and smoke detection device; signal fusion is executed, and a comprehensive fire hazard grade judgment value is generated; comparing the comprehensive fire hazard grade judgment value with a preset fire hazard grade threshold value, and judging the fire hazard grade; and the release mechanism is controlled to release the perfluorohexanone fire extinguishing agent. According to the invention, through multi-signal fusion and a physical power model, the fire stage is dynamically discriminated, the dosage of the perfluorohexanone is adaptively controlled, the fire extinguishing accuracy and efficiency are improved, the false alarm rate is reduced, and data recording and intelligent management are supported.

The invention relates to the technical field of electronic systems of spacecrafts, and discloses a fault-tolerant method for non-redundant fault reconstruction of a spaceborne computer, which comprises the following steps of: 1, accessing a hardware state manager by a BIOS (Basic Input / Output System) after the system is started; obtaining health state data recording the health state of the local storage device, a current starting target ID used for indicating a current starting target, and a retry count value associated with the current starting target ID; a BIOS (Basic Input Output System) accesses a hardware state manager to obtain health state data and a retry count value of local storage equipment, so that normal equipment is autonomously selected for starting, and the fault-tolerant effect of dynamically avoiding a fault starting path is achieved; compared with the technical scheme in the prior art that the computer starting process highly depends on a solidified single physical storage device, the single-point fault risk of permanent paralysis of the computing system caused by damage of the single storage device is solved.

A computer system performs tasks in an access restricted environment. Data is logged in diagnostic files about logical resources in use by the computer system as the computer system attempts to perform the tasks. Occasionally, a problem may prevent the computer system from correctly performing a task. A machine authenticates a user in the access-restricted environment and receives error metadata to initiate an automated process for generating a troubleshooting signature. The automated process involves selecting a metadata extraction policy based on a category of error and using the metadata extraction policy to extract metadata from a diagnostic file. The extracted metadata is analyzed to determine troubleshooting components including the problem, a source of the problem, and / or a version of software that encountered the problem. These troubleshooting components are combined in the troubleshooting signature, which is consumed in a diagnostic tool environment that is separate from the access-restricted environment.

The invention provides a system for training consistent motion perception ability. The system comprises a training parameter setting module used for setting parameter information related to training; the training image generation module is used for generating a training image according to the training parameters; the man-machine interaction module is used for training information interaction and feedback between an individual and equipment; the equipment comprises display equipment, information input equipment, sound prompt equipment and monitoring equipment; the training process control module is used for controlling the sequence of different test times in the single training process; and the data recording and analyzing module is used for recording and analyzing training data so as to evaluate the overall training process. Through targeted visual stimulation design, rigorous training process control and synchronous combination of training auxiliary equipment, training of the consistent motion sensing ability is effectively realized, and the consistent motion sensing ability of a biological individual is improved.

The invention relates to the technical field of dynamic monitoring, in particular to a chemical production safety risk dynamic monitoring system based on the Internet of Things, and the system comprises a data collection module which receives pressure monitoring data, temperature fluctuation data and pipeline flow velocity data measured by a chemical plant sensor in real time, records the time of each data point, and transmits the data to a server; and sorting and organizing the data according to a time sequence. According to the method, by receiving and sorting the chemical plant sensor data and implementing comprehensive analysis of the multi-scale time window, the capture and analysis precision of key parameter fluctuation is remarkably improved, the scientificity of rapid identification and risk prediction of variable fluctuation in the chemical process is promoted, potential risks can be found in advance, and the risk prediction efficiency is improved. Therefore, production strategies are adjusted in real time, production safety is ensured, pre-judgment of future risks is optimized by analyzing long-term trends and periodic changes, the accuracy of risk assessment and the safety of operation are improved, the probability of accidents is reduced, and the safety of personnel and equipment is protected.

The invention relates to the technical field of new energy, in particular to an intelligent charging gun and a charging method. An off-line adaptation algorithm unit identifies CP signal characteristics of a vehicle through a built-in standard library of a CP signal identification module and outputs a vehicle type identifier, and a protocol compatibility algorithm library matches charging protocol characteristic parameters according to the vehicle type identifier; after the protocol conversion unit receives the parameters, voltage thresholds, PWM duty ratios and communication message formats among different protocol standards are converted in real time through a preset mapping table; when the off-line adaptation fails, the system triggers the on-line auxiliary adaptation algorithm unit, and the fault detection module monitors handshake failure, identifies protocol incompatibility characteristics and outputs a fault signal; the data recording and broadcasting module records data in the charging starting process, the cloud communication module uploads the data to the algorithm repairing platform and receives an updating package, and finally the protocol compatibility algorithm library is updated. According to the invention, intelligent conversion and continuous learning of the charging protocol are realized, and charging compatibility and system adaptability are significantly improved.

The invention discloses a living body target intelligent identification method based on multi-mode heterogeneous data collaboration, and particularly relates to the technical field of target intelligent identification. Multi-mode heterogeneous data are acquired in real time by using multiple types of sensors, and high-precision timestamps of all modes are recorded to construct multi-mode asynchronous mismatch coefficients; the time sequence mismatch risk caused by collection and transmission asynchronization is dynamically recognized, a cross-modal similarity matrix is constructed, joint modeling is conducted on the cross-modal similarity matrix and a modal feature significance conflict area to calculate a cross-modal feature conflict enhancement coefficient, the enhancement effect of cross-modal feature conflicts is quantitatively evaluated from the feature level, and the time sequence mismatch risk caused by collection and transmission asynchronization is evaluated. The cross-modal feature conflict enhancement coefficient and the multi-modal asynchronous mismatch coefficient form a complementary output multi-modal fusion risk assessment index, the stability and risk level of the current multi-modal fusion state are quantified, and the potential time sequence and feature collaborative failure risk in the fusion process is accurately reflected; and dynamically adjusting the fusion weight of each mode based on a risk assessment result.

The invention discloses a training system for color resolution capability. The training system comprises a training parameter setting module, a training image generation module, a man-machine interaction module, a training process control module and a data recording and analyzing module. The training parameter setting module sets training related parameters; the training image generation module generates a color training image; the man-machine interaction module presents a training image, obtains the identification condition of the training image by a training individual, monitors the training environment and the training state of the training individual, and stimulates auxiliary training through a low-frequency modulated intermediate-frequency current; the training process control module controls a training process; the data recording and analyzing module can record and analyze training data and evaluate the overall training process. Through targeted training image design, rigorous training process control and synchronous combination of training auxiliary hardware equipment, training of the color resolution capability is effectively realized, and the color resolution capability of a biological individual is improved.

The invention discloses a geological data description data structured analysis method based on a multi-modal large model. The method comprises the following steps: acquiring multi-modal elements including texts, tables, curves and sheet symbols; dynamically generating a limit mapping matrix of a Sheaf neural network according to the geological description ontology and the multi-modal elements; splicing and consistency evolution from a local cross section to a global cross section are executed, and description field candidates are obtained; performing consistency verification on the description field candidates, and identifying fields with contradictions; calculating a corresponding minimum evidence cut set to form minimum conflict interpretation; inputting the minimum conflict interpretation as an additional loss function into a training process, and updating parameters; and outputting the optimized geological data description field result. According to the method, the consistency, interpretability and traceability of geological data multi-modal description analysis are improved through the dynamic constraint field and the minimum conflict interpretation mechanism.

The invention discloses a micro-positive pressure hydrogen environment in-situ stress-strain testing device and method. The device comprises a sealed reaction cavity which can be placed in a scanning electron microscope sample cabin; the loading device is arranged in the cavity and is used for fixing and applying a load; the atmosphere control system is communicated with the cavity and is used for introducing gas and maintaining a micro-positive pressure state; an electron transmission window arranged on the cavity, wherein an electronic transparent film packaged by the electron transmission window can maintain air tightness under micro-positive pressure and allows electron beams to penetrate through; and the heating module is arranged in the cavity. The method comprises the following steps: loading and sealing a sample, establishing a micro-positive pressure atmosphere, heating the sample, starting loading, and synchronously carrying out SEM real-time imaging and data recording. The problem that a traditional SEM in-situ device cannot work in a real micro-positive pressure hydrogen and high-temperature environment is solved, and synchronous visual in-situ observation of material microstructure evolution and macromechanical response under the gas-heat-force multi-physics field coupling condition is achieved.

The invention discloses an aircraft flight data recording system health degree evaluation method, device and equipment, a storage medium and a product, firstly, aircraft data recorded by an aircraft flight data recording system is acquired, and the aircraft data comprises an engine rotation speed initial record value; then, recording timeliness is determined according to the engine rotation speed initial recording value, and the engine rotation speed initial recording value and the recording timeliness are in a negative correlation relation; and finally, evaluating the health degree of the aircraft flight data recording system according to the recording timeliness. Therefore, according to the embodiment of the invention, the timeliness of data recording of the aircraft flight data recording system is verified by using the operation characteristics of the aircraft engine, the system health degree is reflected to a certain extent, and the data quality condition is reflected.

The invention discloses a traditional Chinese medicine data record management platform and method adopting a knowledge graph, and particularly relates to the technical field of data management. A plurality of traditional Chinese medicine clinical cases are collected, a traditional Chinese medicine image thinking feature data set is constructed, a fuzzy clustering algorithm is utilized to extract continuous image feature modes, an image feature mode library is established, and symbolic mapping is performed to form a preliminary knowledge graph. An enhanced knowledge graph is constructed through non-discretization enhancement processing, an iterative adjustment model is constructed based on mapping distortion degree analysis, optimization adjustment of the structure of the enhanced knowledge graph is achieved, finally, a traditional Chinese medicine data management knowledge graph is constructed, semantic mapping and intelligent reasoning of new patient diagnosis and treatment data can be achieved, and the diagnosis and treatment efficiency is improved. And the digital expression ability of traditional image thinking and the intelligent support level of diagnosis and treatment decision are effectively improved.

The invention relates to the technical field of exercise direction distinguishing ability training, in particular to an exercise direction distinguishing ability training system which comprises a training parameter setting module, a training image generating module, a man-machine interaction module, a training process control module and a data recording and analyzing module. The training parameter setting module sets training related parameters; the training image generation module generates a training image; the man-machine interaction module presents a training image, obtains the identification condition of a training individual on the training image, monitors a training environment and a training state, and assists training through a low-frequency modulated intermediate-frequency current; the training process control module controls a training process; the data recording and analyzing module can record and analyze training data and evaluate the overall training process. Through targeted visual stimulation design, rigorous training process control and synchronous combination of training auxiliary equipment, training of the motion direction distinguishing ability is effectively achieved, and the motion direction distinguishing ability of a biological individual is improved.

The invention discloses an agricultural product cold-chain logistics full-process interactive simulation system, and relates to the technical field of agricultural product cold-chain logistics, and the system comprises a cold-chain process module which is used for simulating logistics paths and temperature and humidity state changes of agricultural products in a plurality of links; the parameter configuration module is used for setting environment parameters, product parameters and equipment parameters for each link in the cold chain process; the logic judgment module is used for judging operation reasonability according to user configuration and built-in standard rules; the operation verification module is used for feeding back a logic judgment result and giving an operation suggestion; the data recording module is used for recording input parameters, judgment results and system responses in the whole simulation process; the visual display module is used for displaying the key indexes, the process states and the alarm events in a graphic mode; and the user interaction terminal is used for providing a user interface and performing interaction. According to the invention, the problems of scattered simulation links, lack of dynamic interaction and incomplete data tracing in the prior art are solved.

The invention provides an automatic fixed-point recording field geological sample collection system, which comprises a handheld machine, and the handheld machine comprises a sampling task generation module used for generating a sample number and a design geographic coordinate corresponding to each sampling point; the two-dimensional code generation module is used for associating the sample number with the designed geographic coordinate and generating a two-dimensional code corresponding to each sampling point; the sampling navigation module is used for automatically generating an optimal navigation path between sampling points and recording a track of a sampling person; the data recording module is used for carrying out bag opening code scanning identification on the two-dimensional code on the sampling bag, recording data information of a sampling point and carrying out bag sealing code scanning identification; the sampling quality inspection module is used for performing anti-cheating detection on bag opening code scanning identification and bag sealing code scanning identification; and the storage module is used for storing data sent by the sampling navigation module and the data recording module. According to the invention, automatic recording of the sampling data is realized, the error probability in the sampling process is reduced, and the sampling work efficiency is improved.

The invention relates to the technical field of osmotic pressure testing, and particularly discloses an optimization system for osmotic pressure testing of an ipratropium bromide solution, which comprises a data acquisition module, a data processing module and a data processing module, the data recording module records the operation state data of the conductivity acquisition instrument in the use process, and the operation state of the conductivity acquisition instrument directly affects the accuracy of the conductivity data of the standard solution, so that the operation state of the conductivity acquisition instrument can be analyzed based on the data; the conductivity data can be corrected, so that the data is closer to a true value, the reliability of a quality analysis result of a standard solution is improved, the accuracy of a precision detection result of an osmotic pressure detection instrument and an osmotic pressure detection result of an ipratropium bromide solution is further improved, and the optimization of an osmotic pressure detection method is realized.

The invention discloses a positioning end PPP-RTK real-time precision product monitoring method and device, and belongs to the technical field of satellite navigation and positioning. The method comprises the steps that a PPP-RTK positioning result and a post precision coordinate reference value are acquired in real time, ENU direction positioning deviation is calculated, three types of parameters including satellite geometric configuration, product precision and data timeliness are fused to generate a credibility index C, and an alarm threshold value is dynamically adjusted according to the credibility index C; establishing a positioning precision database to support rapid query and analysis; making a multi-level alarm rule for positioning continuity and precision overrun, and presetting a diagnosis item mapping relation; and after the alarm is triggered, data recording, root cause diagnosis and information output are automatically executed, so that full-process automation from abnormal sensing to root cause definite diagnosis is realized. According to the invention, the reliability, the stability and the operation and maintenance efficiency of the PPP-RTK positioning service are remarkably improved through an evaluation-prediction-diagnosis three-layer intelligent closed-loop system.

The invention provides a ceramic card production data state control method and system. The method comprises the following steps: obtaining production data in a ceramic card production process; by adopting the data acquisition module with a distributed architecture, sensor self-diagnosis and self-adaptive adjustment functions and dynamic self-adaptive time interval data acquisition, and combining with the preprocessing and standard storage mode of the data processing and storage module, the problems of inaccurate production data recording and transmission delay errors are solved; the data state updating module monitors in real time, updates the state based on a machine learning model, and realizes data state real-time tracking and anomaly discovery by matching with a visual platform of the data state monitoring and early warning module, dynamic threshold early warning and multi-mode early warning; a multi-dimensional analysis result is generated through a data analysis module by applying a professional tool and an algorithm, and an intelligent decision-making module constructs an intelligent decision-making model and provides an effective data state control mechanism, so that reasonable production scheduling and decision-making are performed according to a production data state.

The invention provides a data recording method for a vehicle, which is executed by a second electronic control unit of the vehicle, and comprises the following steps: during operation of the vehicle, receiving to-be-recorded data related to an intelligent driving function from a first electronic control unit through the second electronic control unit of the vehicle in real time, the to-be-recorded data is non-duplicated data of data specified to be recorded in data recording requirements of the second electronic control unit, and the second electronic control unit has redundant power supply capability; and storing the received to-be-recorded data to the nonvolatile memory through the second electronic control unit in response to meeting a preset triggering condition. The invention further provides a data recording device for the vehicle and a computer program product. The intelligent driving data and the non-repetitive data of the EDR are transmitted to the second electronic control unit with redundant power supply in real time, so that bus overload can be avoided under the condition that an existing whole vehicle power supply framework is not changed, and the power-off storage requirement is met.

The invention discloses a multi-modal security dynamic regulation and control system based on an alliance block chain technology, and the system comprises a multi-modal data collection layer which is used for collecting multi-modal data and carrying out the preliminary preprocessing of the multi-modal data; the data processing and analysis layer is used for receiving the data transmitted by the multi-modal data acquisition layer and carrying out feature extraction, correlation analysis and safety evaluation; the data processing and analysis layer is used for recording the security evaluation index, the early warning information and the regulation and control strategy data generated by the data processing and analysis layer to a block chain, and realizing automatic execution and dynamic adjustment of a regulation and control strategy by using an intelligent contract; and the security regulation and control execution layer is used for carrying out real-time regulation and control on each component and equipment of the modal data acquisition layer and feeding back a regulation and control result to the data processing and analysis layer, and the system realizes real-time monitoring, dynamic evaluation and accurate regulation and control on the security of the multi-modal system by utilizing the characteristics of the alliance block chain in the use process, so that the security of the multi-modal system is improved. And the safety and the reliability of the multi-mode system are improved.