1989 results about "System structure" patented technology

The invention relates to the technical field of data security management, and discloses a blockchain-based forestry data security management system and method, and the system comprises a data collection unit which is used for comprehensively obtaining a multi-dimensional information flow of forest ecology and resource states; the data processing unit is used for carrying out deep cleaning, standardized regulation and feature value extraction on the originally collected mass heterogeneous data; the block chain storage unit is used for constructing a permanent, tamper-proof and distributed secure storage infrastructure platform of the forestry core data; a verification unit; the safety control unit is used for constructing a covering data transmission, storage and access full-chain depth defense system structure model; a user interface unit; an auditing unit; and a network communication unit. The method is reasonable in design, and the intelligent analysis module is used for processing to form a forest interannual growth trend prediction function distribution map state visual output result set.

The invention discloses a high-temperature airflow two-dimensional temperature field and velocity field synchronous measurement system and method based on laser-induced phosphorescence, and the system comprises phosphorescence particles, a low-frequency double-pulse laser, an image collection device, a synchronous controller, and an image processing device. The image processing device analyzes the gray intensity ratio of different wave band images acquired by the two PIV cameras at the same time, and combines a temperature response function calibrated by an experiment to realize inversion of a temperature field; meanwhile, a double-frame time-resolved image acquired by any PIV camera is subjected to cross-correlation calculation, particle displacement is extracted, and then a velocity field is reconstructed. According to the invention, synchronous acquisition of temperature and speed based on the same data source is realized, and the system has the remarkable advantages of simple structure, high measurement precision and wide application environment.

The invention provides an anti-condensation temperature and humidity regulation and control system and method for remote deep learning prediction aided decision making, and the method is characterized in that a field controller is connected with a temperature and humidity collection device, obtains the environment temperature and humidity, calculates the dew point temperature, obtains the surface temperature of a protected part, and starts and stops a heating and / or dehumidification device by comparing the difference between the two values with a preset threshold value; the temperature and humidity acquisition device acquires field environment temperature and humidity data for the field controller to calculate the dew point temperature, and the temperature and humidity acquisition device is also used for acquiring the surface temperature of the protected part; the heating device is used for raising environment temperature; the dehumidification device is used for reducing the environment humidity; the communication module is used for data transmission between the field controller and the remote prediction terminal, sending field data and receiving prediction information; the remote prediction terminal obtains field data through the communication module; an anti-condensation system structure combining local autonomous control and remote prediction assistance is established, and redundancy fault-tolerant capability is achieved; even if the remote prediction function fails, the field control can still operate independently and reliably.

The invention discloses a short message template intelligent identification method and system based on semantic similarity calculation, relates to the technical field of information and communication, and realizes automatic matching of a request short message and a template library through semantic vectorization and similarity calculation; semantic extension, structural constraint and a dynamic feedback mechanism are combined, so that the matching accuracy and robustness are improved; an optimization process driven by a multi-level model and category features is introduced, and an identification-feedback-optimization closed-loop system is formed; the system structurally comprises a semantic modeling module, a similarity calculation module, a dynamic feedback module and a template optimization module, automatic and efficient short message template recognition and updating can be achieved, and the requirements for real-time performance and accuracy in a large-scale application scene are met.

The invention provides a computer hardware performance evaluation method and system based on an analogue simulation model, and relates to the technical field of computer performance evaluation. According to the method, hardware component models such as a processor, a memory and I / O are constructed by analyzing a system structure description file, semantic analysis is performed on an instruction stream or a parallel computing graph of a to-be-evaluated application, and a task load model is formed. The model is input into an event-driven scheduling module, simulation is executed on the hardware component model, task-resource mapping is generated, and task time delay, communication traffic and power consumption are recorded. And calculating average response time delay, data bandwidth and unit energy consumption according to the simulation data, and outputting an evaluation report compared with the performance baseline. According to the method, real load-oriented multi-dimensional performance prediction can be realized, and the method can be used for architecture optimization and scheme selection.

The invention discloses an energy planning method for a low-carbon economic comprehensive energy system based on multi-agent deep reinforcement learning. The method comprises the following steps: constructing a comprehensive energy system structure including multiple energy forms such as wind power, photovoltaic, electricity-to-gas, combined heat and power generation, energy storage and the like; establishing a carbon emission intensity model of each subsystem based on an energy input and output relationship, and constructing a segmented carbon tax function to quantify the carbon cost; a double-layer two-stage Nash optimization model is designed, and the game relationship between collaboration between subsystems and external energy interaction is considered; the optimization problem is converted into a Markov decision process, and a state, an action and a reward function are defined; a multi-agent TD3 algorithm model is constructed and trained, and strategy stability and robustness are improved through a differential evolution mechanism; and deploying the trained strategy model in an actual system to realize self-adaptive energy planning and scheduling for the carbon economic target. The method has the characteristics of high adaptability, high carbon benefit and excellent intelligent cooperation capability.

The invention discloses a hydrogen-lithium dual-power system structure optimization design and integrated control method applied to an unmanned aerial vehicle. The method comprises the following steps: constructing a hydrogen-lithium dual-power system of the unmanned aerial vehicle; setting an integrated control strategy according to the hydrogen-lithium dual-power system; the integrated control strategy comprises an energy management strategy and a life and safety management strategy; the energy management strategy comprises a rule-based strategy, a power following strategy and a self-adaptive optimization strategy; the service life and safety management strategy comprises a hydrogen fuel cell protection strategy, a lithium battery health management strategy, a thermal management strategy, a dual-power coupling safety management strategy and a redundancy and fault processing strategy. By optimizing the power system design and the energy management strategy, the mass of the unmanned aerial vehicle device is reduced, the cruising ability, the load capacity and the environmental adaptability of the unmanned aerial vehicle are improved, and optimization processing of the control strategy is achieved.

The invention discloses a remote disturbance test system and method in primary frequency modulation, and relates to the technical field of power system control, and the method comprises the steps: obtaining a primary frequency modulation intelligent control system, and configuring a master-slave redundancy control device; generating and verifying a primary frequency modulation test disturbance signal, and triggering a remote disturbance test according to a verification result; the master and slave control devices respectively respond to the test and collect the power grid state signal flow, and analyze and generate a master and slave frequency modulation load instruction; evaluating and screening the master-slave load instructions by using a hardware high-selection module, and determining a target frequency modulation load instruction; and sending the target instruction to the DCS and the DEH for test recording and performance evaluation, and optimizing a frequency modulation strategy according to a test result. The technical problems of low test efficiency and insufficient accuracy caused by system complexity in an existing primary frequency modulation remote disturbance test system are solved, and the technical effects of simplifying the system structure, improving the test efficiency and remarkably enhancing the test accuracy are achieved.

The invention discloses a visual setting calculation system and method, and relates to the technical field of power grid setting calculation, and the method comprises the following steps: obtaining operation data of a target system, extracting feature data, and constructing a knowledge graph of entities and relationships, the feature data including control data; constructing a system structure diagram, and generating a semantic enhancement diagram in combination with semantic information in the knowledge graph; inputting the semantic enhancement graph into a pre-trained graph neural network model, performing node feature aggregation and edge weight learning in combination with a prior rule of a knowledge graph, and outputting sensitivity scores of all control data nodes on performance indexes; according to the sensitivity score, constructing a boundary constraint condition, and generating a control data setting candidate solution based on a CSP solver; performing parameter response simulation verification on the control data setting candidate solution, and screening out an optimal control data setting candidate solution; according to the application, accurate sensitivity scoring can be realized by fusing the knowledge graph, the semantic enhancement graph and the graph neural network.

The invention relates to the technical field of computer system structures and storage, in particular to a non-volatile memory quick recovery method based on metadata priority and on-demand loading. The method comprises the following steps: in response to a system fault signal detected by a voltage monitoring unit, freezing a processor context and traversing a page table structure to extract system configuration information; writing the system configuration information and business data codes in the volatile memory into a nonvolatile medium to generate a persistent state mirror image; analyzing the persistent state mirror image, extracting address conversion metadata, and reconstructing a mapping relation from a virtual address to a physical page frame in a volatile memory; and generating an address mapping table, wherein the physical page frame pointed by the address mapping table is set to be in an existing state but is not associated with the effective service data. According to the method, decoupling of the control flow and the data flow is realized by constructing a virtual ready state, and quick starting of the system and immediate response of key services are realized on the premise of not depending on the total capacity of a memory.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes such as financial science and technology and medical health, and discloses a root cause analysis method and device based on a space-time dependency graph, equipment and a medium. Comprising the steps of constructing a space-time dependency graph, generating a diagnosis path blueprint, identifying a fault source and a root cause entity type, generating a graph query statement, executing query and performing cause and effect verification, and outputting a root cause analysis report. And the causal reasoning and root cause positioning of the system state change are realized by fusing the graph structure information and the natural language processing capability. Through cooperative processing of a language model and a graph data structure, fault symptom information and system structured state data are deeply fused, a path is generated in the graph structure, and a causal relationship is verified, so that the ability of understanding a complex system state evolution chain is improved, and accurate identification and diagnosis of root causes are realized. And the accuracy and the automation level of root cause analysis are obviously enhanced.

The invention provides a node task migration and scheduling system based on digital twinning, and relates to the technical field of computer system structures and data processing. Computing resource interference in a multi-tenant sharing environment is quantized by sensing a cross-tenant noise coefficient and a state synchronization complexity entropy in a node micro-architecture; extracting track features of the mobile terminal, calculating spatial discrete variance, generating a self-adaptive migration decision hysteresis factor, and converting the migration decision hysteresis factor into decision damping to inhibit invalid high-frequency reciprocating migration; constructing a digital twin sandbox before physical cutover, cooperating with a chaos scene injection engine to inject a composite fault operator into a bottom layer, and performing actuarial calculation on service continuity retention after risk adjustment by using a fidelity integrator; and finally, a bottom layer controller is linked through safety baseline comparison to execute physical flow switching. According to the method, network boundary deduction is completed on the premise that physical bandwidth is not consumed, the interruption risk caused by state hard switching is avoided, and smooth transition of stateful services is effectively guaranteed.

The invention discloses a personalized semantic understanding system for assisting an autonomous mobile platform, and the system comprises a user personalized word meaning library which is used for recording the mapping relation between the user habit expression and the corresponding operation; the fuzzy semantic analysis module is used for identifying fuzzy expression in a natural language instruction of a user and generating a plurality of candidate targets or operation options of semantic generalization; the multi-round context modeling module is used for establishing a semantic context based on session history and performing disambiguation and complementation on current semantics; and the intention generation module is used for converting the processed semantic information into a structured instruction. The personalized semantic understanding system is reasonable in structural design, all the modules cooperate with one another, the effect that 1 + 1 is larger than 2 can be achieved, fuzzy semantic understanding and multi-round context modeling can be conducted, the personalized requirement of a user can be met, semantic understanding precision is high, user adaptability is good, and the personalized semantic understanding system is suitable for man-machine interaction of an autonomous mobile platform.

The invention provides a compressor and heater control integrated system and a vehicle. The control integrated system comprises a heat management controller, a compressor and a heater, the integrated controller is integrated with a compressor controller and a heater controller, and the integrated controller is in communication connection with the heat management controller; the integrated controller is in communication connection with the compressor pump body and the heater core body and used for controlling the compressor pump body and the heater core body, and the integrated controller and the compressor pump body are integrally installed to form a compressor assembly or the integrated controller and the heater core body are integrally installed to form a heater assembly. Through the innovative design of the integrated controller, centralized control over the compressor and the heater is achieved, the number of controllers and wire harness connection are reduced, the hardware cost and the system complexity are reduced, meanwhile, a software high-voltage interlocking function is adopted to replace hard wire interlocking, the system structure is further simplified, and the reliability and safety of the system are improved.

The invention provides a non-intrusive diagnosis method for typical rotor faults of a synchronous phase modifier, and the method comprises the steps: carrying out finite element modeling and fault working condition setting, carrying out simulation to obtain magnetic field distribution data under each working condition, carrying out the extraction and feature analysis of stray magnetic field signals, extracting time domain and frequency domain signals of a stray magnetic field under healthy and various fault working conditions, and carrying out the diagnosis of the typical rotor faults of the synchronous phase modifier. Fundamental wave, odd-even harmonic components and signal change trends are compared and analyzed, stray magnetic field characteristics corresponding to faults are extracted and recognized, diagnosis criterion establishment and fault recognition are carried out, diagnosis criteria and threshold values of rotor turn-to-turn short circuit, dynamic eccentricity and shaft-diameter composite eccentricity faults are established according to the stray magnetic field characteristics, and the fault diagnosis accuracy is improved. And when the specific harmonic amplitude or change characteristic of the stray magnetic field signal exceeds the criterion threshold, determining the rotor fault of the corresponding type and degree. Equipment dismounting or structure reconstruction is not needed, the detection system is simple in structure, internal fault characteristics of the phase modifier can be reflected in real time, and high sensitivity and practicability are achieved.

The invention relates to a self-adaptive visual training method based on eye features, and belongs to the technical field of visual health and artificial intelligence. In order to solve the problems that traditional visual training equipment is heavy in structure, single in training mode and lack of personalized regulation and control and concentration state monitoring, the visual training equipment obtains eye images of a user in real time through an image acquisition module, adopts visual intelligent analysis, extracts double features of eye contours and pupil positions, calculates the visual concentration degree, and improves the visual training efficiency. And a concentration state is judged by combining a dynamic self-adaptive threshold value. When the concentration degree is insufficient, the control module triggers intervention mechanisms such as prompt or training pause and the like, and the remote interaction module uploads data to the cloud platform to generate a personalized training scheme. Intelligent and personalized regulation and control of the training process are achieved, the training effect and compliance are improved, the system is compact in structure and suitable for various scenes, and an efficient solution is provided for vision health.

The invention relates to the technical field of processing equipment, in particular to an intelligent conveying and overturning system which comprises a feeding conveying belt, a discharging conveying belt, an interval conveying belt, an overturning mechanism and a control module. The feeding conveying belt, the discharging conveying belt and the interval conveying belt are located on the same straight line and move in the same direction. The interval conveying belt is located on the front side of the discharging conveying belt, and the turnover mechanism is located between the tail end of the feeding conveying belt and the starting end of the interval conveying belt. According to the invention, the system structure is simplified, the equipment complexity is reduced, and the production takt is improved.

The invention provides a system reliability modeling method based on multi-source data fusion. The method comprises the following steps: collecting data in a ship complex system; preprocessing the collected data to obtain multi-source data; performing reliability modeling based on the multi-source data to obtain a basic model; performing simulation on the basis of the multi-source data and the data of the basic model to evaluate the reliability level of the system, and performing statistical analysis on the data obtained by system failure simulation to obtain a system reliability evaluation index; the reliability evaluation indexes comprise the reliability and the average life of the system. According to the method, data processing in each stage is developed and developed according to reliability test identification requirements of a complex system, on this basis, a system reliability model is constructed and fault and failure characteristics of the system are analyzed by combining the structure and functional characteristics of the system, and reliability simulation evaluation of typical application scenarios is developed.

The invention provides an all-dielectric film system structure with visible near-infrared high absorption, intermediate infrared selective radiation and microwave high transmission. The all-dielectric film system structure sequentially comprises a protection and antireflection layer, a visible near-infrared absorption and infrared selective radiation layer and a substrate layer from top to bottom, the protection and antireflection layer comprises a first dielectric layer and a second dielectric layer which are arranged up and down; the visible near-infrared absorption and infrared selective radiation layer comprises a plurality of third dielectric layers and fourth dielectric layers which are alternately stacked. According to the structure, high absorption can be achieved in the wave band of 380-1100 nm, high reflection (low radiation) can be kept in the wave bands of 3-5 m and 8-14 m, high transmissivity is achieved in the microwave wave band, certain radiation can be kept in the wave bands of 5-8 m and 14-25 m, and effective heat management is achieved. The all-dielectric film system structure also considers the stability of the material in a space environment, and is provided with a protection and antireflection layer, so that the potential application reliability of the film system is improved.

The invention belongs to the field of integrated circuits and computer system structures, and provides a caching method and system for a memory access unit of a superscalar processor, and the method comprises the steps: receiving a plurality of memory access instructions in the same period, and determining a corresponding Bank in a to-be-accessed cache through the memory access instructions; after the memory access instruction obtains a cache access permission, if cache line missing occurs, generating a missing request, merging all the missing requests, and performing parallel prefetching training on the merged missing requests by utilizing a mode of fusing a constant step length prefetching mode and a complex step length prefetching mode to obtain a prefetching request and a prefetching cache address corresponding to the prefetching request; requesting a missing cache line from the first-level cache to the second-level cache based on the missing queue, and writing the missing cache line back to the cache line of the corresponding data cache in the first-level cache; and storing the bus consistency request by using the sniffing queue, judging whether the data in the multi-core cache are consistent or not by using the consistency request, and performing consistency modification according to a judgment result. The cache hit rate and the bandwidth utilization rate are improved.

The invention belongs to the technical field of magnetic levitation rulers, and relates to a magnetic levitation ruler horizontal motion control method, which comprises the following steps: establishing a mathematical model of a horizontal system; according to the constructed mathematical model, estimating the position of the rotor iron core through induced electromotive force derivation to obtain the horizontal position and the deflection angle value of the rotor iron core; rotor iron core horizontal motion control based on SYSTD is carried out; and setting the parameters of the horizontal control system of the magnetic suspension ruler system. A mathematical model is established based on a magnetic circuit and a dynamics principle, the problems of nonlinearity and strong coupling of a magnetic levitation ruler horizontal displacement system are solved by applying an improved active-disturbance-rejection control algorithm, and a system structure is simplified by utilizing a position-sensorless control technology. According to the method, unknown dynamic and external disturbance is taken as total disturbance, and real-time estimation and compensation are carried out through an extended state observer; the ADRC not only can adjust errors, but also can actively process uncertain factors of the system and improve the control efficiency, does not depend on an accurate mathematical model, and is high in adaptability and robustness in a complex system.

The invention discloses an optical system design method and system based on a knowledge base retrieval enhancement large model, and belongs to the technical field of optical design and artificial intelligence. The method comprises the following steps: constructing an optical system knowledge base containing vectorized coded optical lens design data; a data pair is formed based on an optical system design requirement and a corresponding parameter list of each surface of the optical system, a training data set is constructed, the training data set is utilized and a low-rank adaptive technology is adopted to train a large language model, and then the trained large language model is combined with an optical system knowledge base through a knowledge base retrieval enhancement module to obtain an optical system knowledge base. Obtaining a knowledge base retrieval enhancement large model; and inputting the design requirement of the to-be-designed optical system into the knowledge base to retrieve the enhanced large model to obtain optical system structure parameters meeting the design requirement of the to-be-designed optical system, namely obtaining a parameter list of each surface of the optical system. The method can effectively improve the optical design efficiency, and is suitable for the design of various optical systems.

According to the rapid modeling method for the finite element of the bridge rod system unit disclosed by the invention, a clearer and more reasonable modeling method is constructed by combining rod system structure modeling and BIM modeling logic, and a user can obtain the finite element of the bridge rod system unit by modifying simple underlying data or utilizing a result formed in the method. And analysis and modeling are realized by effectively combining with other software at low cost. The method uses a Python language, and comprises the following steps of: 1, realizing attributes of editing classes by utilizing the Python language; 2, creating a material and a section instance; 3, the bridge structure is divided into different component instances corresponding to the bridge types, boundary information between different components is bound through the boundary class, and loads acting on the different components are determined through the load class; 4, packaging the axis class, and binding the component instance with the axis instance; 5, adding a calculation module, and carrying out mesh generation; 6, obtaining each subdivision point on the axis, and connecting the subdivision points to generate a corresponding unit set; and 7, establishing boundary and load examples.

The utility model relates to the field of medical instruments, in particular to a dilution system structure for hemodialysis, which comprises a front dilution loop, a rear dilution loop, a displacement liquid outlet, a dialyzer and a controller. Displacement liquid of the displacement liquid outlet flows into the dialyzer through the front dilution loop, and dialysate flowing out of the dialyzer and the displacement liquid of the displacement liquid outlet flow into a human body through the rear dilution loop; the front dilution loop comprises a front dilution displacement pump, and the rear dilution loop comprises a rear dilution displacement pump; the problems that existing hemodialysis synchronous mixing and diluting treatment effects are poor and flexibility is poor are solved. The operation modes of the front dilution replacement pump and the rear dilution replacement pump are changed through the connection mode of the front dilution loop and the rear dilution loop, and flexible adjustment of the dialysis mode is achieved; the hemodialysis treatment effect can be effectively improved by monitoring the hemodialysis process in real time and automatically adjusting the hemodialysis parameters according to the monitoring result.

The invention provides a multi-unmanned aerial vehicle airborne cooperative control method, electronic equipment and a readable storage medium, the multi-unmanned aerial vehicle airborne cooperative control method comprises the following steps: S1, dispersing control logic to each unmanned aerial vehicle through a distributed control architecture, and establishing communication connection between the unmanned aerial vehicles; s2, adopting a real-time communication mechanism to realize information exchange and collaborative decision-making among the unmanned aerial vehicles on the communication connection among the unmanned aerial vehicles; s3, according to the task demand, the information exchange result and the collaborative decision result, generating a collaborative control scheme and executing the task; s4, adjusting the structure of the unmanned aerial vehicle system through a dynamic reconstruction mechanism and the distributed execution task; and S5, state monitoring is carried out on the adjusted unmanned aerial vehicle system structure, and abnormal conditions are processed. According to the invention, the distributed control architecture and real-time communication capability of the ROS2 are utilized to realize efficient, reliable and extensible multi-unmanned aerial vehicle cooperative control.

The invention relates to an electric power multi-modal total element sample fusion labeling method and system based on Transform, and the method comprises the following steps: S1, obtaining multi-modal original data of a production operation site, and carrying out the preprocessing of the multi-modal original data, and obtaining a preprocessed multi-modal data set; s2, according to the preprocessed multi-modal data, multi-modal feature coding and Transform representation modeling are carried out, and through cross-modal feature fusion and information completion, fusion feature representation is obtained; s3, according to the fusion feature representation and a candidate tag set corresponding to the fusion feature representation, obtaining a multi-modal semantic alignment tag set through semantic consistency detection and a semantic mapping mechanism; s4, aligning the label set according to the multi-modal semantics, and constructing a label system structure tree; and S5, based on the fusion feature representation and the label system structure tree, constructing an automatic labeling module to generate a preliminary label, and directly inferring a label based on similar samples and category probabilities. According to the invention, efficient automatic label generation and sample dynamic classification are realized.

The invention discloses a meter-scale leveling and aligning static pressure rotary table shaft system structure expanding torque in the radial direction and a method. The meter-scale leveling and aligning static pressure rotary table shaft system structure comprises a base, a lower plate, an upper plate, a leveling structure, an aligning structure and a workbench. A lower plate is arranged on the base, an upper plate is arranged on the lower plate, the upper plate is fixedly connected with a rotor, and the rotor is directly connected with a motor rotor; the top end of the upper plate is vacant, and the bottom end of the upper plate is provided with an adsorption structure and a supporting surface and matched with the top end of the lower plate; the leveling structure and the aligning structure are both mounted on the lower plate and are arranged on the same horizontal plane; according to the rotary table shaft system structure, a torque transmission path expanding in the radial direction is adopted, the extending amount of an aligning ball head is controlled through an aligning structure, a lower plate is promoted to move in the opposite direction of the extending direction of the aligning ball head relative to an upper plate, and axial aligning of a workbench and a rotor is achieved; and the leveling structure is used for positioning the plane of the workbench through three points, so that the workpiece is leveled. According to the invention, the leveling and aligning functions of large-size high-precision rotary tables with meter-scale calibers and above can be realized, and the table-board distance of the rotary table is reduced.

The invention provides a near-infrared model cross-device application method based on multi-source fusion optimization, and aims to solve the problem that various neural network models constructed by a high-precision near-infrared spectrometer cannot be applied to portable devices when being migrated to the portable devices. And the model performance is reduced due to differences of an optical system structure, a wavelength range, a signal-to-noise ratio, an instrument response characteristic and the like. According to the method, the near infrared spectrum data and the conventional quality parameters are subjected to feature level fusion, and the cross-equipment spectrum deviation is calibrated and compensated by using the stability of the conventional quality parameters, so that efficient knowledge migration from high-precision equipment to portable equipment is realized in the fused feature space. The problem of cross-device feature dimension mismatching is solved through a stable feature importance evaluation-based wave band alignment method; a small sample optimization strategy and a hyper-parameter automatic search technology are combined, so that the transfer learning effect is improved, the performance of a portable equipment detection model is remarkably enhanced, and meanwhile, the modeling cost is greatly reduced.

The invention provides a large-opening spoke cable dome space structure system and a construction method thereof, and relates to the technical field of building structure construction.The large-opening spoke cable dome space structure system comprises a supporting column system, a ring beam, a single-layer spoke type crossed cable net, an inner ring cable and a multi-stage cable system structure; the multi-stage cable system structure comprises a first endless cable structure, a second endless cable structure, a third endless cable structure, a fourth endless cable structure, a first supporting structure, a second supporting structure, a third supporting structure, a fourth supporting structure, a first stay cable structure, a second stay cable structure, a third stay cable structure and a fourth stay cable structure. The supporting column system is fixedly connected with the ring beam, one end of the single-layer spoke type crossed cable net is hinged to the ring beam, the other end of the single-layer spoke type crossed cable net is hinged to the inner ring cable, the multi-stage cable system structure is hinged to the ring beam, one end of a first supporting structure of the multi-stage cable system structure is connected with the inner ring cable, and the other end of the first supporting structure is connected with the first ring cable structure. The overall rigidity is large, the anti-collapse capacity is good, the length of the pressing rod is effectively reduced, buckling is avoided, and the problem that arrangement of a cable truss structure is limited is solved.

The invention relates to a railway vehicle system structure modal test measuring point optimization method and a medium, and the method comprises the following steps: constructing a modal matrix of a railway vehicle system structure, extracting candidate measuring points of modal test, and forming a candidate measuring point set, the sensor comprises a three-way sensor and a one-way sensor; if a three-way sensor is selected to perform modal testing, calculating measurement values of candidate measurement points in the candidate measurement point set by adopting a multi-dimensional effective independent method based on the modal matrix, and determining final measurement points of the modal testing according to the measurement values; and if the unidirectional sensor is selected for modal testing, constructing an auxiliary matrix based on the modal matrix and the candidate test point set, and determining a final test point of the modal testing according to the auxiliary matrix. Compared with the prior art, the method has the advantages of optimizing measurement point distribution, improving the accuracy of a modal identification result and the like.