47 results about "Potential accident" patented technology

The invention relates to an alarm information processing system and method for a technological process, and the system comprises a data collection module which is used for collecting the real-time parameter data of each equipment node in the technological process; the knowledge base module is used for storing a risk knowledge graph of the technological process, and the risk knowledge graph comprises a plurality of accident chains representing abnormal propagation paths and alarm signals among equipment nodes; the risk diagnosis module is used for positioning a potential accident chain from a risk knowledge graph according to the received alarm signal and the real-time parameter data; and the alarm deduction module is used for deducing the potential influence of the alarm signal on the technological process according to the potential accident chain. According to the method and the device, the potential influence possibly caused by the alarm event can be automatically deduced, the severity and the influence range of the accident consequence can be effectively pre-judged, a scientific basis is provided for emergency decision making, and the problem of how to improve the safety of the technological process in industrial production in related technologies is at least solved.

The invention discloses a mass concrete temperature monitoring method. The method comprises the following specific steps: step 1, planning a monitoring point position; step 2, selecting and installing equipment; step 3, installing and pre-burying a measuring point, step 4, installing and pre-burying an optical fiber, step 5, laying temperature measurement layers, step 6, collecting and monitoring data, and step 7, ending data analysis. According to the invention, through a mode of combining a wireless temperature measurement process and manual measurement, the frequency of manual point measurement can be reduced, manpower consumption is reduced, the comprehensiveness of monitoring data is improved, the monitoring blind area of a traditional point type sensor is avoided, and the possible equipment fault problem of a temperature measurement system is avoided; and data comparison of manual monitoring and wireless monitoring is adopted, so that the reliability of temperature measurement data can be determined, and accident hidden dangers are reduced.

The invention discloses an operation real-time monitoring system based on risk factor dynamic assessment, and relates to the technical field of desilting operation risk assessment, the system can comprehensively assess various potential risks in the desilting operation process through multi-dimensional environmental data acquisition and real-time monitoring, and the risk factor dynamic assessment is realized. Comprise dam instability, water flow shearing force, sediment disturbance, soft foundation stability and the like. The system calculates comprehensive risk factors according to the data, timely identifies risks and triggers early warning, and ensures the safety of an operation area. The system can dynamically evaluate the soil liquefaction risk by monitoring the soil liquefaction factor and the volume change of the workboat in real time, and prevents the workboat from inclining or sinking. In addition, the system generates and implements specific emergency strategies according to different early warning instructions, and takes effective protective measures to deal with sudden risks. The safety and efficiency of the dredging operation are improved, the potential accident risk is reduced, and the sustainability of the dredging operation is guaranteed.

The invention provides a construction safety early warning method for a construction site, a terminal and a storage medium. The method comprises the following steps: constructing a physical model of an obstacle in a construction site based on a physical engine simulation algorithm; based on the physical model of the construction site and the state information of all obstacles in the construction site at the current moment, performing mixed collision detection, determining a target obstacle, screening out obstacles which do not collide, and reducing the calculation amount; physical motion simulation is carried out on the target obstacles to obtain state information of each target obstacle in a future time period; further collision prediction is carried out on the target obstacle based on the state information of the target obstacle in the future period, and a collision detection score is determined; and performing safety early warning on the construction site based on the collision detection scores of any two target obstacles in the future time period. According to the method, early warning can be carried out on possible accidents in advance, so that the occurrence of safety accidents is reduced, and the safety warning effect of a construction site is improved.

Smart vehicle-to-everything (V2X) preemptive connections for emergency and / or potential accident scenarios. A V2X-enabled vehicle may determine a current route of the vehicle and high-risk areas through which the vehicle may travel (e.g., a hospital zone, high pedestrian traffic area, etc.). The vehicle may determine a distance (d) from a beginning of the high-risk area and begin establishing a V2X connection upon reaching the determined distance. The V2X-enabled vehicle may also, or alternatively, pre-emptively establish a V2X connection upon detecting an event initiative of an emergency, a hazardous situation, or a potential emergency. Examples of such events may include a sharp turn, a vehicle speed exceeding a speed threshold, a sudden acceleration or declaration, etc. A preemptive V2X connection may, for example, enable vehicles to begin communicating with one another faster in case of a threat, emergency, or unsafe conditions for vehicles in the area.

The invention discloses a parking lot accident cause determination method, and relates to the technical field of parking lot safety management, and the method comprises the following steps: a data collection step: obtaining multi-dimensional data in real time through a sensor network deployed in a parking lot, the multi-dimensional data including human behavior data, environment state data, engineering compliance data and equipment operation data; and a parameter calculation step based on human behavior data. According to the invention, the multi-dimensional data sensing network covering people, vehicles, roads, environment and equipment is constructed, real-time risk assessment and accurate cause positioning are carried out based on the dynamic weight and interaction item analysis model, advanced early warning and active prevention and control of potential accidents in the parking lot are finally realized, the safety management level of the parking lot can be significantly improved, and the safety of the parking lot is improved. The traditional passive post-event disposal is converted into active pre-event prevention, and the method is particularly suitable for high-end parking lot scenes with extreme requirements for safety, privacy and asset protection.

A method for a motor vehicle for controlling an occupant protection component of the motor vehicle, the method comprising: detecting a potential accident opponent of the motor vehicle; detecting accident opponent data relating to the potential accident opponent and motor vehicle data relating to the motor vehicle; determining, based on the accident opponent data and the motor vehicle data, acceleration information relating to a possible accident between the potential accident opponent and the motor vehicle, wherein the acceleration information characterizes an acceleration of the motor vehicle during the possible accident; and outputting a control signal for controlling the occupant protection component of the motor vehicle taking into account the acceleration information.

The application discloses a kind of method and system of active identification traffic accident based on Internet of Vehicles, it is related to accident identification technical field.By confirming and testing current vehicle operating state gradually, the accuracy and reliability of traffic accident detection can be significantly improved.Real-time acquisition vehicle operating state data and preliminary abnormality judgment based on preset basic threshold, by combining historical operating state data to calculate trend difference, and set standard threshold to further verify the authenticity of preliminary abnormality event, significant test is carried out on trend difference, its statistical significance is evaluated by error probability, ensure that only truly meaningful abnormal event is marked as potential accident, to avoid misjudgment caused by random noise or short-term fluctuations.Integrated analysis trend difference and operating state data using machine learning model, output specific traffic accident type, so that the system can not only confirm abnormal state, but also accurately classify different types of traffic accident.

The invention relates to an input parameter influence analysis method and system for nuclear power plant accident consequence evaluation, a medium and equipment. The method comprises the following steps: acquiring parameters required for evaluation; screening and setting parameters required by evaluation to generate a parameter information table; performing random sampling based on the input parameters to generate a random sampling matrix; calculating by using a random sampling matrix to obtain an accident consequence evaluation result; analyzing uncertainty and sensitivity based on the accident consequence evaluation result, and obtaining an uncertainty analysis result and a sensitivity analysis result of the input parameter; performing comprehensive analysis based on the uncertainty analysis result and the sensitivity analysis result to obtain a comprehensive analysis result; and determining an influence result of the input parameters according to the comprehensive analysis result. The uncertainty and sensitivity of the input parameters are analyzed, the influence degree of each parameter on the accident consequence evaluation result is effectively quantified, it is ensured that the nuclear power plant can make an accurate decision in time when a potential accident occurs, and the public and environment safety is effectively protected.

This invention belongs to the field of bridge traffic risk assessment technology, and specifically relates to a method for assessing traffic risk on downhill bridge sections based on reliability analysis. The method comprises the following steps: using driving speed as a random variable, constructing a vehicle braking traffic risk function for the downhill bridge section based on the sight distance required for vehicles going downhill and the emergency stopping distance provided by the bridge deck; analyzing reliability indices and failure probabilities to determine traffic risk level classification standards; determining reliability indices based on the longitudinal force coefficient detection value of the bridge deck, thereby determining the traffic risk level of the section and assessing the risk of the downhill bridge section. This invention quantifies the impact of decreased bridge deck anti-skid performance on driving safety, predicts potential accidents from a probabilistic perspective, and thus achieves the purpose of timely risk warning and timely hazard elimination.

Disclosed are an accident detection method and apparatus, and a storage medium. The method comprises: receiving an input video; identifying a plurality of objects in the video; when a specific object from the plurality of objects complies with a predetermined rule of transitioning from a moving state to a stopped state and finally remaining in the stopped state, determining that the occurrence of a potential accident is experienced by the specific object; determining a frame image in the video where the occurrence of a potential accident is experienced by the specific object; and instructing a trained image processing model to analyze and process the frame image, so as to determine whether the occurrence of an accident is experienced by the specific object.

This invention relates to the field of bridge engineering technology, specifically disclosing a steel wedge slope adjustment device in a cap beam support system. It includes a main body comprising an upper wedge and a lower wedge; an adjusting component is provided between the upper and lower wedges; the adjusting component includes a threaded steel bar with nuts at both ends; a support plate for supporting the casting mold is provided at the end of the upper wedge away from the lower wedge, and an adjusting mechanism is provided on the support plate for adjusting the tilt angle of the support plate. This device can prevent the support plate from becoming detached from the contact area of ​​the cap beam formwork, thus preventing slippage of the casting mold during demolding and potential accidents.

The utility model relates to the technical field of AGVs (Automatic Guided Vehicles), in particular to a fork arm guide rail protection structure of an AGV, which effectively limits the movement range of a fork arm and reduces equipment damage and potential safety hazards caused by excessive stretching through the cooperative work of a limiting assembly and a guide rail assembly. And the special limiting separation blade and the guide block are adopted, so that potential accidents caused by deviation or collision in the operation process of the fork arm are avoided, and the movement safety of the whole fork arm is improved.

Disclosed in the present invention are a vehicle instrument screen operating state monitoring method, a smart cockpit, and a vehicle having same. The steps of the method comprise: using a microcontroller unit (MCU) in a cockpit-domain system controller (CSC) to periodically query an operating state of a vehicle instrument screen MFD module by means of an IIC communication protocol, and determining whether an interactive message between the MCU and the vehicle instrument screen MFD module is successful; and when it is detected that a heartbeat signal is lost, the MCU performing a hardwire reset on the vehicle instrument screen MFD module by means of a hardwire IO. In summary, according to the present invention, requirements of an automotive safety integrity level are considered, and by means of precise fault detection and timely recovery measures, the safety of the vehicle during operation is significantly improved. The present invention not only meets functional safety requirements but also provides a higher level of safety assurance for drivers and passengers by reducing potential accidents caused by instrument screen failures.

This invention proposes a method for assessing driving risks by integrating an independent climate field. The method mainly consists of three parts: First, based on a three-field model of kinetic energy field, potential energy field, and behavioral field in human-vehicle-road collaboration, an independent climate field model is innovatively defined and constructed to characterize the additional driving risks caused by abrupt changes in the environmental medium. Then, by acquiring environmental information such as road surface adhesion coefficient and rainfall intensity, the risk equivalent mass of the climate field source is calculated, and the field strength distribution and attenuation function of the climate field are established based on spatial distance. Finally, the climate field is vector-superimposed with the original three fields to calculate the total driving risk field strength across the entire region. Under the premise of ensuring driving safety, the method achieves advanced warning and risk avoidance decisions for potential accident hazards based on the dynamic change trend of the total field strength. This invention does not change the internal structure of the original three-field model, but supplements the influence of meteorological and road factors on risk characterization through the principle of physical field superposition, effectively improving the safety of intelligent vehicles in complex and extreme environments.

This utility model discloses a seismically resistant and stable oil drilling platform, relating to the field of oil extraction technology. The platform includes a support seismic-resistant component fixedly installed at its four lower corners, and anti-collision and shock-absorbing components fixedly installed on all four sides. This seismically resistant and stable oil drilling platform, through its support seismic-resistant components, can effectively cope with earthquakes, wave impacts, and vibrations generated by drilling operations in the marine environment, reducing wear and fatigue damage to the platform structure. Furthermore, the seismic-resistant frame evenly distributes the platform's weight to the connecting columns at the four corners, preventing excessive local stress that could lead to structural deformation, thus providing seismic resistance and further extending the platform's service life. The anti-collision and shock-absorbing components effectively protect against potential accidents such as ship collisions and ice floe impacts during offshore operations, reducing platform structural damage, lowering the risk of equipment failure, and ensuring personnel safety.

The invention discloses a dangerous chemical storage tank area risk assessment method and device based on comprehensive risks, and relates to the technical field of chemical accident risk analysis, and the method comprises the steps: constructing a basic database of a dangerous chemical storage tank area; performing failure probability analysis on the potential accident source according to the basic database to determine an initial accident frequency; calculating a first economic loss expectation based on the initial accident frequency; performing upgrade probability analysis on each affected device, and determining the domino accident frequency of the affected device in combination with the initial accident frequency; calculating a second economic loss expectation according to the domino accident frequency; calculating a comprehensive risk probability according to the initial accident frequency and the domino accident frequency; calculating an accumulated economic loss expectation according to the first economic loss expectation and the second economic loss expectation; and performing risk assessment according to the comprehensive risk probability and the accumulated economic loss expectation of each device. According to the scheme, the accuracy of performing economic loss and risk assessment on the dangerous chemical storage tank area can be improved.

The application belongs to the technical field of geographic information services, and discloses a mountaineer anti-lost early warning and tracking system, comprising the following modules: a map display module, an information reporting module, a data management module and a system interaction module. By constructing the four core modules of map display, information reporting, data management and system interaction, the pain points of inconvenience of carrying traditional paper maps, limited coverage and insufficient flexibility of fixed signboards can be effectively solved. The design of the information reporting module further strengthens the safety guarantee capability. When the mountaineer cannot judge the position or is in a positioning dilemma, the mountaineer can initiate help by uploading the photos of the surrounding environment to the system. In addition, if it is found that other personnel walk to a deep and undeveloped area or a high-risk area, the on-site photos can be taken and reported in time to avoid potential accidents such as getting lost or being in danger in advance, thereby playing the functions of active early warning and risk preposition intervention.

The invention relates to the technical field of constructional engineering protective sheds, and discloses a big data-based steel bar protective shed intelligent management system, which comprises a data acquisition module, a big data analysis module, an intelligent control module, an early warning module, a maintenance prediction module and a cloud platform interface, when real-time monitoring management of the steel bar protective shed is carried out, structure state data, environment data and operation data of the protective shed are collected in real time through a distributed sensor network, and a risk prediction model is established based on a big data analysis module, so that the operation state of the protective shed can be mastered, and early recognition and early warning of structure safety risks are realized; according to the system, the potential safety hazard discovery capability is improved, potential accidents caused by environmental changes and structure aging are prevented, auxiliary facilities of the protective shed are automatically adjusted through the intelligent control module according to a risk assessment result, the system can quickly respond when abnormal conditions are detected, delay and errors of manual intervention are reduced, and the system safety is improved. And the management timeliness and accuracy are improved.

The application discloses a kind of system security analysis method, system and equipment, method includes: system task is decomposed, each subtask is determined as the functional unit of the system;The performance of each functional unit is evaluated using time and precision, the output variability score of each functional unit is obtained by introducing expert score, then the potential coupling of each functional unit performance change is analyzed, and the functional coupling variability score of each functional unit is obtained in combination with the output variability score;Threshold value of functional coupling variability score is set, when exceeding the threshold value of functional coupling variability score, system will occur functional resonance, so as to identify the key functional unit in system, and set barrier for the key functional unit to prevent potential accidents from happening.The application fuses subjective and objective factors to analyze the safety of system, solves the technical problems that cannot give quantitative analysis results due to excessive dependence on expert subjective evaluation, and lacks theory or process to construct functional resonance.

In a vehicle control device, environmental information is acquired which is information about an environment in which a vehicle is placed. The environmental information precludes an obstacle around the vehicle. A possibility is estimated for potential proximity of the vehicle to the obstacle. A behavior of a predicted target moving object including the vehicle and at least one moving object around the vehicle is predicted based on the estimated possibility. A responsibility is determined for a potential accident that is assumed in response to the vehicle traveling on a candidate route that the vehicle travels.

The present invention provides a method for detecting and warning spatial conflicts in construction scenes based on semantic networks. The method comprises the following steps: capturing construction scene images; extracting construction machinery, vehicles, and personnel from the images; extracting hazardous areas; and performing semantic reasoning. This method enables dynamic monitoring of the spatial areas of various construction elements within a construction scene and provides early warnings of potential accidents. Compared to existing technologies, the method is not limited to identifying hazardous element features after an accident has occurred; it also integrates the recognition results with natural human reasoning, avoiding the high errors and low accuracy of traditional purely machine vision detection methods.

A travel storage system includes: a target vehicle behavior determination unit that is configured to: acquire a sensor value indicative of a behavior of each of surrounding vehicles around the host vehicle; and sequentially determine a relative behavior of a target vehicle with respect to the host vehicle based on the sensor value; a rule acquisition unit that acquires an accident liability rule in a current position of the host vehicle; a potential accident liability information determination unit that sequentially determines, using liability determination information, potential accident liability information indicative of whether the host vehicle is liable for a potentially assumed accident between the target vehicle and the host vehicle; and a storage unit that stores the potential accident liability information and the liability determination information in association with each other or in associable with each other.

According to the new energy automobile risk prediction method based on the LSTM, in the constructed risk prediction model, the LSTM is utilized to extract the time sequence dependence characteristics, modeling is performed on the dynamic time sequence data so as to capture potential information and internal relations related to accident occurrence, static data are processed through an independent full-connection Dense layer, and the risk prediction accuracy is improved. Generating a fixed feature vector to quantify and capture potential accident risk characteristics of the vehicle, splicing dynamic characteristics extracted by the LSTM and static characteristics extracted by the full-connection layer to form a joint vector containing time sequence and static characteristics, further inputting the joint vector to the full-connection layer, and performing feature fusion to obtain the potential accident risk characteristics of the vehicle. And the detection head predicts the risk probability of future accidents of the vehicle.

The utility model discloses a lifting mechanism and a roller changing system, and belongs to the technical field of battery production. The lifting mechanism comprises a tray suitable for being arranged opposite to the roller in the vertical direction, and a groove used for containing the roller is formed; the hydraulic cylinder comprises a cylinder barrel, at least one stage of moving cylinder slidably mounted in the cylinder barrel and a piston rod slidably mounted in the innermost stage of moving cylinder, the cylinder barrel is suitable for being mounted on the roller press, the tray is supported on the piston rod, and every two adjacent stages of moving cylinders are in sliding fit; the hydraulic cylinder is configured to drive the moving cylinder and the piston rod to reciprocate by injecting oil into or returning oil to the cylinder barrel so as to drive the tray to ascend and descend. By means of the roller changing mode design that the hydraulic cylinder drives the tray to ascend and descend, uncertainty and potential accident risks of manual operation are reduced, safety of roller changing operation is improved, roller changing time is greatly shortened, production line rhythm and production capacity are improved, input of manpower and material resources is greatly reduced, and roller changing cost is reduced.

The application belongs to the technical field of engineering cost, and relates to an AI-based engineering cost big data intelligent analysis system and method, wherein a ground pile coupling model is constructed, precipitation prediction parameters in a construction period are input as time-varying boundary conditions, transient seepage changes of foundation soil under the action of precipitation are analyzed, the distribution of pore water pressure increment in the influence domain of each supporting pile is quantified, the pile body inclination probability, embedded failure probability and soil loss probability between piles of the supporting pile are predicted based on the reduction relationship of the pore water pressure increment and the effective stress of the soil body, directional parameter adjustment is triggered according to the probability threshold value condition, a supporting pile design parameter adjustment scheme and a corresponding supporting structure incremental cost are formulated, high precipitation risk working conditions are identified in advance to output risk control supporting cost, the possibility of supporting structure failure is effectively reduced, the safety and stability of the engineering structure are enhanced, and the economic loss caused by potential accidents is reduced.

The invention belongs to the technical field of engineering cost, and relates to an AI-based engineering cost big data intelligent analysis system and method.A ground pile coupling model is constructed, rainfall prediction parameters in a construction period serve as time-varying boundary conditions to be input, and transient seepage changes of foundation soil under the rainfall effect are analyzed; the method comprises the following steps: quantifying pore water pressure increment distribution in a pile periphery influence domain of each support pile, predicting a pile body inclination probability, a build-in failure probability and an inter-pile soil loss probability of the support piles based on a reduction relation of pore water pressure increment relative to effective stress of a soil body, and triggering directional parameter adjustment according to a condition that the probability exceeds a threshold value, a support pile design parameter adjustment scheme and corresponding support structure increment cost are formulated, a high rainfall risk working condition is recognized in advance to output risk regulation support cost, the possibility of failure of the support structure is effectively reduced, the safety and stability of an engineering structure are enhanced, and then economic losses caused by potential accidents are reduced.

The invention discloses a distributed video monitoring integration method based on edge computing, and relates to the technical field of intelligent monitoring, and the method comprises the following steps: screening key nodes and related nodes, carrying out the first analysis and the second analysis, obtaining a time feature and a space feature, and further obtaining a first accident degree and an accident level; and constructing a first influence model and sending a first early warning signal. According to the invention, through two-stage topology of key nodes and related nodes mined by historical data, the AI reasoning model, the cache capacity and the communication bandwidth can be pre-deployed to a potential accident area in advance, non-differentiated redundancy calculation of the whole network and direct embedding of a mapping model from a first accident degree to an accident level into an edge ARM-NPU are avoided, local closed-loop decision is realized, and the reliability of the whole network is improved. And the edge node regularly returns a new accident sample to the center for incremental training, and the weight of the key node is dynamically updated once every 24 hours, so that the same-frequency resonance of the model and the scene is realized.

The utility model relates to fastener technical field discloses a kind of high-strength fastener for warship, including fastener nut, oil injection device is arranged in the fastener nut, stable device is arranged between the oil injection device and fastener nut, the oil injection device includes pressing column, the lower end of the pressing column is fixedly connected with connecting column, the inside of the fastener nut is fixedly sleeved with sleeve at middle part, oil storage cotton is arranged in the sleeve.In the utility model, oil injection device extrudes lubricating oil by connecting column pressing oil storage cotton, and lubricating fastener nut is transported to oil outlet by water pipe, can avoid that nut is worn due to long-term extrusion friction, prevent potential accident caused by not expected fastening effect, and at the same time, stable device is driven to move down by pressing column with the help of clamping block, clamping block is inwards retracted when contacting nut, to the clamping groove mouth is reset buckle fixed by spring elastic force, can prevent pressing column from moving out the outside of nut due to oil storage cotton self elastic force, guarantee oil injection device stable work.