160 results about "Accident analysis" patented technology

The invention discloses an SCL field safety accident analysis and early warning method and system, a medium and a program product, and the method comprises the steps: carrying out the distributed cleaning and feature extraction of multi-source heterogeneous monitoring data, and obtaining a multi-dimensional time sequence feature flow; constructing a dynamic association network of a security state; identifying a key influence factor chain, and establishing a semantic analysis model; constructing a safety threshold system; evaluating the multi-dimensional time sequence characteristic flow by using a safety threshold system; when the multi-dimensional time sequence characteristic flow triggers early warning, performing tracing analysis by using a semantic analysis model to obtain a root event triggering the early warning, and simulating the development trend of the root event based on a preset evolution model; determining a predicted risk range and a risk type according to the tracing cause analysis result and the accident development trend; and the corresponding accident early warning scheme is matched in the preset database according to the risk range and the risk type, and the accident early warning scheme is sent to the monitoring terminal, so that the accuracy of judgment and classified early warning of different types of safety accidents is improved.

The invention relates to the technical field of computer vision and automatic driving, in particular to a natural driving accident scene key element extraction method based on a visual large model. Comprising the steps of data collection and preprocessing, accident data cue word design, ontology-based accident scene description and data annotation, pre-training model fine tuning and optimization, key element identification and post-processing and the like, the efficiency of natural driving accident analysis is remarkably improved, and the time and cost of manual examination are reduced. Through an ontology-based accident scene description method, dynamic feature extraction based on an optical flow method and more accurate cue word design, the recognition accuracy of the model on key elements is improved. Through a data enhancement technology and reasonable loss function design, the robustness and generalization ability of the model in different scenes are improved. The method is not only suitable for analysis of natural driving accidents, but also can be expanded to other scenes, and a high-efficiency scene understanding method is provided for management of intelligent traffic, smart cities and safe cities.

The invention relates to the technical field of hazardous chemical substance production, and provides a hazardous chemical substance safety production management and control system, in the aspect of data acquisition, all-around acquisition of equipment operation, environment and personnel operation data is realized, a high-precision sensor ensures data accuracy and far exceeds traditional finite dimension and precision acquisition, and during data analysis and processing, edge calculation is combined with deep learning, so that the safety production management and control of hazardous chemical substances is realized. A risk assessment model is dynamically adjusted, the limitation of a traditional fixed model is broken through, production change and risk early warning can be adapted in real time, risk levels are dynamically adjusted, multi-element early warning and visual display are achieved, compared with single early warning and simple display, risk perception is more timely and accurate, accurate reasons are found through a unique accident analysis model, and the risk assessment efficiency is improved. According to the method, the production management and operation improvement can be promoted, each module of the system can be optimized, a closed-loop lifting mechanism is formed, the safety production management and control level of the hazardous chemical substances is comprehensively improved from data acquisition, analysis, early warning and optimization, the safety risk is greatly reduced, and the production safety and stability are guaranteed.

The invention relates to the field of nuclear power unit accident analysis, in particular to a coupling method of a VVER unit system program and a neutron dynamics program. The method comprises the following steps: adding an interface function in a reactor core three-dimensional neutron dynamics program, compiling the reactor core three-dimensional neutron dynamics program into a dynamic link library, and accessing and calling the dynamic link library by a reactor system program in a plug-in manner; establishing a neutronics physical model of a specific loading scheme of the VVER type reactor; establishing an accident analysis system simulation model of the VVER type pressurized water reactor; establishing control logic of main systems and equipment of a primary loop and a secondary loop in the VVER type reactor; establishing control logic and conservative condition settings for specific accidents; executing coupling calculation of a reactor system program and reactor core three-dimensional neutron dynamics; and obtaining key safety parameters of the VVER type reactor in a specific accident based on a coupling calculation result. According to the invention, simulation of changes of physical and thermal parameters in a primary loop system and a secondary loop system and action response of a main system after a reactor has an accident can be realized, and efficient and reliable accident analysis can be conveniently carried out on a VVER type nuclear power unit.

The invention belongs to the field of tailing pond safety risk identification and accident analysis, and discloses a tailing dam accident path identification method based on a mixed causal knowledge graph and a related device, and the method comprises the steps: building a mixed causal logic model through employing an obtained tailing dam accident initial hazard source; solving a set of accident cause links of the tailing dam by utilizing the mixed causal logic model; in the set of the tailing dam accident cause links, the logic relation of the tailing dam accident and the accident cause links are used as nodes and edges of a knowledge graph respectively, and a Python + Neo4j method is used for constructing a tailing dam accident knowledge graph; and coding and classifying the tailing dam accident knowledge graph by using a BERT-GCN-SVM model to realize tailing dam accident path identification. The mine tailing dam accident path identification method is improved and optimized based on the thought of the knowledge graph, a set of mine tailing dam accident chain identification method is formed, and the mine tailing dam accident path identification method can be used as a new tool for mine tailing dam accident directional control and disaster situation deduction.

The invention relates to a traffic accident data analysis and visualization processing method and system for an automatic driving vehicle, and the method comprises the steps: collecting the related original data of a vehicle traffic accident, and carrying out the standardized integration of the original data; performing cleaning and verification processing, time calibration and synchronous processing on the data after the standardized integration to obtain processed data; acquiring a collision time point according to the speed and the path of the accident vehicle; according to the processed data and the collision time point, a collision moment driving mode, vehicle steering before collision, vehicle pedals before collision, vehicle accessories before collision, vehicle faults before collision, traffic signals before collision, road marking before collision and a vehicle state after collision are analyzed, and a key time point is obtained; and according to the processed data and the key time point, carrying out visual display on an analysis result. According to the invention, key time point marking can be realized, and a scientific and standardized accident analysis report can be automatically generated and stored.

The invention relates to the technical field of accident responsibility judgment, solves the problem that intelligent driving accident analysis and real-time responsibility judgment cannot be carried out in the prior art, and provides an accident responsibility judgment method, device and equipment in an intelligent driving scene and a storage medium. The method comprises the following steps: analyzing related parameters of an accident in an intelligent driving scene, and determining a plurality of key variables in the related parameters and a causal network corresponding to each key variable; according to a pre-collected traffic database and the causal network, the occurrence probability of each key variable is quantified, and a prior knowledge base related to an intelligent driving accident is determined; and according to the real-time data of the intelligent driving accident and the prior knowledge base, in combination with the Bayesian theorem, accident causes are analyzed, and an accident responsible party is determined. According to the method, man-machine responsibility division of the intelligent driving accident can be realized, and the emergency processing capability and the judgment efficiency of the intelligent driving system after the accident are remarkably improved.

The invention discloses a dangerous chemical accident analysis system and analysis method based on digital twinning. The method comprises the following steps: establishing a jet fire accident consequence model of a fire spread analysis unit; establishing a toxic gas leakage accident consequence model; establishing a pool fire accident consequence model; establishing a steam cloud explosion accident consequence model; setting coordinates, proportion and position attributes of the model in the process of importing the three-dimensional data of the chemical industry park; sensor real-time monitoring data are accessed through a data interface and serve as input parameters, and dynamic updating and visual effect display are achieved. Three-dimensional scene restoration under high resolution is realized through a digital twin technology, model influence parameters are interactively set in combination with a Web end interface, physical states and environmental factors of hazardous chemicals are monitored in real time, and dynamic simulation and analysis are performed through a digital twin model, so that early recognition and early warning of accident risks are realized. And the prevention and coping capability of dangerous chemical accidents is improved.

The invention discloses an accident analysis and intelligent intervention method and system based on an intelligent networked automobile, and particularly relates to the technical field of accident analysis, which comprises the following steps: when the intelligent networked automobile approaches an accident-prone place, extracting important features from historical traffic data in the accident-prone place of the intelligent networked automobile by using a t-SNE dimension reduction method; acquiring real-time traffic data of the intelligent networked automobile, and determining similar information of the traffic data of the intelligent networked automobile; bayesian inference is carried out based on historical traffic data in an accident-prone place of the intelligent networked automobile and real-time traffic data of the intelligent networked automobile, and probability information of the traffic data of the intelligent networked automobile is determined by analyzing statistical data and constructing a machine learning mode; through comprehensive analysis of the similar information and the probability information of the traffic data, the risk that the intelligent networked automobile enters the accident-prone place is evaluated, the road traffic safety can be improved, and the accident occurrence rate is reduced.

The embodiment of the invention discloses a traffic accident data processing and analyzing method and device and electronic equipment. The method comprises the steps of performing data fusion on traffic accident data in various data formats based on a large-model heterogeneous field mapping method to obtain an accident data set, performing data cleaning on the accident data set according to a dynamic rule engine and a correction mechanism to obtain a target data set, and storing the target data set in a database. And finally, performing hierarchical analysis on the target data set based on the multi-dimensional accident analysis model to obtain a data analysis result, and performing visual display on the data analysis result. Through multi-source data intelligent fusion, data quality control and a multi-dimensional accident analysis model, the data quality of the multi-source data is improved, the purpose of efficiently and automatically processing different data formats is achieved, a large amount of human resources are saved, and meanwhile the accuracy and reliability of a data processing analysis result are improved.

The invention discloses an automatic road traffic accident scene map making method based on a three-dimensional laser scanning technology, relates to the technical field of traffic accident processing, and solves the problem of lack of a three-dimensional laser scanner for quickly acquiring three-dimensional space information of an accident scene, generating dense point cloud data and providing a data basis for accident analysis. The technical problems that in the prior art, a high-precision three-dimensional laser scanning technology and an automatic data processing method are difficult to combine, and whole-course automatic processing from data acquisition to field map generation is difficult to achieve are solved. Encrypting the data; data transmission; integrity detection; carrying out point cloud color assignment; an orthoimage is overlooked; automatically identifying a candidate area; automatically drawing a road contour; optimizing the contour line; outputting a result; and encrypting the result. The traffic accident scene map can be quickly generated, and the accident investigation efficiency and quality are improved.

The invention discloses a data alignment method and device, and relates to the technical field of computers. A specific embodiment of the method comprises the steps of obtaining target cabin sound data and target flight data corresponding to a target flight terminal; performing parameter analysis on the target flight data to obtain a plurality of air-ground dialogue moments; sorting the plurality of air-ground dialogue moments according to time to obtain a first time sequence corresponding to the plurality of air-ground dialogue moments; cutting the target cabin sound data to obtain a second time sequence corresponding to a plurality of cabin sound moments; and determining the alignment moment of the target cabin sound data and the target flight data according to the overlapping degree of the first time sequence and the second time sequence. According to the embodiment, the alignment moment between the target cabin sound data and the target flight data can be accurately determined, so that effective alignment between the target cabin sound data and the target flight data is realized, and the accuracy of data analysis in subsequent accident analysis and flight quality evaluation is greatly improved.

The invention relates to an intelligent generation method for a subway emergency disposal scheme. The method comprises the following steps: S1, constructing an emergency plan knowledge graph; s2, performing automatic accident analysis and information extraction; and S3, generating an emergency disposal scheme. The invention further relates to a subway emergency disposal scheme intelligent generation system and a computer readable storage medium. The method has the advantages of high efficiency, accuracy, intelligence and the like, intelligent generation of the disposal scheme is realized by performing automatic analysis on accident data and combining a knowledge graph RAG technology, and the scheme generation speed is remarkably improved. The semantic reasoning ability of the knowledge graph and the deep analysis ability of the large model are utilized to ensure the high matching degree of the generation scheme and the actual event. The knowledge extraction and relation recognition technology of a large model is combined, automatic generation and logic relation reasoning of the emergency task unit are achieved, and the intelligent level is improved.

The invention relates to a gas accident analysis system and method based on a dynamic Bayesian network. The method comprises the following steps: constructing a dynamic Bayesian network model; gas equipment operation state data and environment parameters are obtained; processing data, and performing gas accident risk assessment and accident evolution path analysis by using an inference algorithm; and generating an accident analysis result and outputting the accident analysis result through a visual tool. According to the gas accident analysis system and method based on the dynamic Bayesian network, multiple risk factors of a gas accident are comprehensively analyzed through the dynamic Bayesian network technology, the possibility of accident occurrence can be effectively predicted, the severity of the accident can be effectively evaluated, and reasonable prevention and response measures are put forward. Compared with a traditional risk assessment method, the method is higher in accuracy, real-time performance and flexibility, can provide more scientific safety management decision support for gas enterprises, remarkably improves the gas accident prevention and emergency processing capability, and has a wide application prospect.

The invention discloses a method and system for testing the working voltage of a switching device based on a second-order function approximation method, and the method comprises the steps: building a basic second-order function model through querying the nominal voltage Ub of a secondary switching element; performing a function initial test, and preliminarily testing the action voltage of the switch element; through multiple approximation and voltage adjustment in the test, when it is confirmed that an error is smaller than a set range, an accurate action voltage value is finally obtained. And carrying out holding voltage test, testing the holding voltage of the secondary switch element by using a second-order function approximation method, and finally determining a holding voltage value by adjusting voltage output and gradually approximating the holding voltage. According to the method, the action threshold voltage of the secondary switch element is tested based on the second-order function approximation method, the action and reset voltage of the secondary switch element can be more accurately tested, accurate data can be provided for switch type selection and accident analysis, and the method is of great significance.

The present invention relates to a method and system for analyzing and visualizing traffic accident data for autonomous vehicles. The method comprises: collecting raw data related to vehicle traffic accidents and standardizing and integrating the raw data; cleaning and verifying the standardized and integrated data, time-calibrating, and synchronizing the data to obtain processed data; obtaining the collision time point based on the speed and path of the accident vehicle; analyzing the driving mode at the time of collision, the vehicle steering before the collision, the vehicle pedals before the collision, the vehicle accessories before the collision, the vehicle fault before the collision, the traffic signals and road markings before the collision, and the vehicle status after the collision based on the processed data and the collision time point to obtain key time points; and visually displaying the analysis results based on the processed data and the key time points. The present invention can achieve key time point marking and automatically generate and save scientific and standardized accident analysis reports.

The invention belongs to the field of accident analysis, and particularly discloses a gas pipeline third-party construction accident control defect influence analysis method and system, and the method comprises the following steps: determining a system task and safety constraints, building a hierarchical structure of an STAMP model according to a preset function demand and a safety target, and carrying out the analysis through combining a VSM model, identifying control defects; performing digital expression on the control defect obtained by analyzing the third-party construction accident of each gas pipeline, and obtaining a coefficient of the control defect of the third-party construction accident of the gas pipeline through Pearson correlation analysis; using a CRITIC weight method to process and calculate the coefficient of the third-party construction accident control defect of the gas pipeline obtained in the correlation analysis to obtain the weight of the third-party construction accident control defect of the gas pipeline; and finally, according to the hierarchical structure and the control defect weight, constructing a system dynamics model, and determining the key control defect of the third-party construction accident of the pipeline, thereby formulating targeted prevention and improvement measures.

The present invention belongs to the field of nuclear power simulation technology, and relates to a mobile equipment dispatching system under multi-unit accidents in a nuclear power plant, in which a multi-unit accident simulation unit establishes an accident model through a severe accident analysis program, simulates and calculates the initial state of each unit accident, and obtains basic parameter data, key states and index data; a mobile emergency equipment demand unit establishes mobile emergency equipment demand logic and determines the dispatching plan of mobile emergency equipment according to accident handling procedures and severe accident management guidelines; an accident mitigation simulation unit combines the dispatching demand of mobile emergency equipment on the basis of the initial state of the accident, performs accident simulation and comparative analysis through a severe accident analysis program, and evaluates the accident mitigation result; a mobile emergency equipment dispatching decision unit comprehensively determines the final dispatching decision of mobile equipment under multi-unit accidents. The present invention can avoid the adverse consequences caused by single information decision-making, and better help emergency decision-makers make more reasonable judgments.

The invention relates to the technical field of artificial intelligence, and discloses a simple traffic accident liability intelligent affirmation system and method based on an AI large model, and the method comprises the steps: collecting an accident scene image and an accident description text of a simple traffic accident scene, and carrying out the feature extraction of the accident scene image and the accident description text, obtaining accident key parameters and accident semantics; analyzing the accident space-time field quantity of the simple traffic accident scene, and constructing an accident space-time panorama by using the accident space-time field quantity; constructing an accident association map of a simple traffic accident scene, and analyzing an accident logic chain by using the accident association map; performing accident liability analysis on the simple traffic accident scene based on the accident space-time panorama and the accident logic chain to obtain an accident analysis text; and performing accident judgment optimization and intelligent conclusion calibration on the accident liability text to obtain a target accident text, and constructing an accident liability report by using the target accident text. According to the invention, the efficiency of simple traffic accident liability determination can be improved.

The invention relates to the technical field of track defect detection, in particular to a detection system for an electromagnetic track surface coating and a wear failure test analysis method. The system comprises a mobile device, a laser, a galvanometer, a temperature measurement module, an analysis module, a control module and the like, and the method comprises the steps of macroscopic inspection, parameter setting of laser defect inspection, laser defect inspection, data processing, failure form analysis and the like. The temperature measuring module measures temperature and transmits data, and the surface of the whole track is detected through laser spots and movement of the moving device. The method can solve the problem that an existing detection technology cannot rapidly and accurately detect the coating abrasion defect of the electromagnetic track, can effectively standardize the defect, failure and even accident analysis process of the coating of the electromagnetic track, and has the advantages of avoiding track failure caused by coating abrasion failure of the electromagnetic track, improving the reliability of the track and improving the reliability of the track. It is of great significance to ensure safe and stable operation.

The invention discloses a shipping accident analysis method. The method comprises the following steps: constructing a shipping accident knowledge graph; inputting questions, retrieving the shipping accident knowledge graph by adopting a retrieval enhancement generation method, and generating answers; wherein the retrieval enhancement generation method is adopted to retrieve the shipping accident knowledge graph and generate the answer, and the method comprises the following steps of: analyzing a question by adopting a large language model to generate a query statement; retrieving in the shipping accident knowledge graph according to the query statement, outputting nodes and edges matched with the query statement from the shipping accident knowledge graph, and generating a Bayesian network according to the matched nodes and edges; generating a query result according to the conditional probability of a target node and a father node thereof and / or the posterior probability of a child node thereof in the Bayesian network, and inputting the query result into the large language model; and the large language model generates an answer according to the query result. The invention further discloses a shipping accident analysis device, computer equipment and a storage medium. The method comprises the following steps: extracting and storing shipping accident data by adopting a large language model in combination with a knowledge graph, and analyzing the shipping accident data in combination with a Bayesian network analysis model to obtain an occurrence probability of a complete causal chain from causes to accident results in an accident, so that objective and accurate accident causals are sorted out for complex shipping accidents, and the probability of occurrence of the complete causal chain is improved. And reliable conclusions and suggestions are provided for subsequent shipping businesses.

The present invention discloses a method and system for constructing an event-based knowledge model of power grid monitoring services based on deep learning. The method comprises: collecting alarm information data during the historical operation of the power grid, preprocessing the power grid monitoring alarm text, and constructing a power grid monitoring alarm information event-based rule set; using the event-based rule set to process the historical alarm information data to obtain a data set of various labeled monitoring alarm events; performing unsupervised pre-training on the pre-processed monitoring alarm text through a word2vec model to obtain a vectorized expression of the monitoring alarm text; offline training and online application; the system comprises a preprocessing module, a pretraining module, a testing module, and an identification module. The present invention provides timeliness guarantee for power grid fault diagnosis and accident analysis; provides support for event definition and autonomous generation of event rules, and can realize automatic expansion of the monitoring service event knowledge model.

The invention discloses an accident analysis method and system based on digital twinning, a product and a medium. The method comprises the following steps of: calculating an actual stress value and a theoretical stress value by collecting deformation data of the protective fence and a vehicle driving record; the protective fence is divided into different stress areas according to the deformation degree, and the difference value proportion of the theoretical stress value and the actual stress value of each area is calculated; the reliability index of each area is determined by combining the collision angle, the collision part and the deformation characteristic of the vehicle, and a weight coefficient table is established; and combining a difference value proportion with a reliability weight by using a regional weighted integral method, calculating a final stress compensation value, and providing a more accurate accident analysis basis. By implementing the technical scheme provided by the invention, the accuracy of road traffic guardrail accident analysis is improved.

The invention provides an ATF fuel-based pressurized water reactor break accident analysis method, which comprises the following steps: S1, checking an ATF scheme parameter demand table, and identifying important fuel parameters required in accident analysis; s2, according to important parameters of the fuel, mechanism phenomena and key model research of the ATF fuel is carried out, and distinguishing points of the ATF fuel and existing nuclear fuel are identified; s3, carrying out applicability evaluation on the first accident analysis program according to the distinguishing points; s4, if not, a fuel model in the first accident analysis program is improved, and a second accident analysis program suitable for AFT fuel is obtained; and S5, analyzing the typical crevasse accident by adopting a second accident analysis program, verifying whether the important phenomena in the step S1 and the step S2 are embodied or not, and if so, carrying out crevasse accident analysis on the pressurized water reactor based on the ATF fuel by adopting the second accident analysis program. According to the invention, qualitative and quantitative evaluation can be carried out on the nuclear power plant break accident adopting the ATF scheme.

To provide a protection relay system capable of properly communicating electricity amount data and accident analysis data of a plurality of relay devices by using the same network.SOLUTION: A protection relay system includes: a plurality of network switches; a plurality of relay devices connected to each network switch; and an analysis device and a management device, which are connected to any one of the plurality of network switches. The management device collects reception information of data in each network switch. The analysis device transmits a first transmission request of accident analysis data with respect to the plurality of first relay devices to the management device. The management device generates a plurality of second transmission requests based on reception information in response to the first transmission request from the analysis device, and sequentially transmits the plurality of generated second transmission requests to each first relay device. Each first relay device transmits accident analysis data to the analysis device according to the received second transmission request.SELECTED DRAWING: Figure 1

The invention provides a vehicle accident data processing method and device and a storage medium, and the method comprises the steps: S1, obtaining the vehicle state information of a vehicle within a preset time range before and after the accident time according to the accident time after a triggering event of an accident is received; s2, inputting the vehicle state information into a pre-trained vehicle accident analysis model, and judging whether the vehicle has an accident or not; s3, when it is judged that the vehicle has the accident, determining the latest effective parking time point; s4, according to the effective parking time point, judging whether at least one piece of alarm data of a predetermined type exists or not; if yes, determining the time corresponding to the first piece of alarm data of the pre-type as the accident occurrence time; otherwise, determining the time corresponding to the vehicle positioning record which is closest to the effective parking time point and has the vehicle speed greater than 0 as the accident occurrence time. By means of the technical scheme, the accident occurrence time can be determined more accurately.

The present application relates to a kind of EPR nuclear power unit accident initiation event list optimization method and system, method includes: collecting the initiation event list of each nuclear power unit;Each initiation event list is compared and analyzed, and the optimization object of the accident initiation event list of EPR nuclear power unit is determined according to comparison result;Frequency analysis is carried out to the accident initiation event in optimization object;EPR accident classification standard and frequency analysis result are combined to reclassify accident;According to the classification result, optimization initiation event list is carried out;Generation optimized initiation event list.Through implementation of the present application, after the optimization of the accident initiation event list of EPR nuclear power unit, optimization EPR accident analysis and EPR nuclear power unit operation technical specification are carried out, realize unit online maintenance, further improve the economic benefit of nuclear power plant under the premise of guaranteeing safety.

The invention discloses a nuclear power plant accident analysis method and device, and relates to the technical field of nuclear power safety analysis. The method includes: responding to user triggering to perform accident analysis of a first accident type on a nuclear power plant, and acquiring a first input card and a first reference card; the first input card is used for representing an initial analysis condition corresponding to accident analysis of a first accident type of the nuclear power plant, and the first reference card is used for representing an accident verification standard of the first accident type; based on the first input card, calling a first calculation configuration template corresponding to the first accident type to perform accident calculation to obtain a first accident calculation result; the first calculation configuration template is used for representing a calculation process rule of the first accident type; and determining an accident analysis result of the nuclear power plant in the first accident type based on the first accident calculation result and the first reference card. According to the invention, the accident analysis efficiency can be improved.

The application provides a control rod uncontrolled lifting accident analysis method of a reactor, including providing a first neutron dynamics model, and setting a shutdown protection signal, the shutdown protection signal including an over-power protection signal and a period protection signal; carrying out power spectrum analysis according to the first neutron dynamics model to obtain a transient peak power; obtaining a transient MDNBR based on the transient peak power and initial thermal parameters of the reactor; comparing the transient MDNBR with a safety analysis limit value, if the transient MDNBR is less than or equal to the safety analysis limit value, then carrying out a system optimization operation and returning to carry out the power spectrum analysis until the transient MDNBR is greater than the safety analysis limit value. The application only carries out neutron dynamics calculation and does not carry out thermal flow and heat transfer calculation, the calculation process is the most conservative, for example, if the accident analysis process only carries out a first analysis stage, the analysis process is the most simple, and the work efficiency of the accident analysis can be greatly improved.

The application discloses a vehicle safety belt device and a vehicle safety system, which comprise a safety belt, a winding device and a monitoring module. The monitoring module is used for monitoring the length of the pulling-out and winding of the safety belt, so as to judge whether the wearing mode of the safety belt is correct, for example, whether a passenger wears the safety belt and whether the safety belt is correctly worn. By monitoring the pulling-out length of the safety belt, the size of the passenger's body can be judged. When a collision occurs, corresponding safety belt burst points and airbag burst points can be burst, so that better protection is provided for the passenger. By monitoring the pulling-out length of the safety belt, the current sitting posture of the passenger can be judged. When a collision occurs, the posture and displacement of the passenger can be judged by monitoring the pulling-out and winding length of the safety belt, and whether the safety belt is normally actuated can be judged, so that a basis is provided for accident analysis.