73 results about "Hazard analysis" patented technology

The invention relates to the technical field of path planning, in particular to a water conservancy unmanned aerial vehicle inspection process control system and method based on big data analysis. Performing path risk assessment based on a water surface anomaly prediction result and a weather anomaly analysis result, performing unmanned aerial vehicle flight anomaly analysis based on unmanned aerial vehicle operation condition data and a historical path risk analysis result, and performing path planning selection. According to the method, the path danger is quantitatively evaluated based on the evolution condition of the weather and the wave condition on the path in the flight process of the unmanned aerial vehicle, the safety of path selection is improved, the influence of the future wind power condition on the wave danger is analyzed in the evaluation process of the wave condition, and the evaluation accuracy is improved. Therefore, the future wave danger is quantitatively predicted and evaluated, and the evaluation accuracy of the path danger is improved.

The invention provides a potential safety hazard analysis method and system based on underground cavern three-dimensional geological intelligent modeling, and the method comprises the steps: firstly, based on underground cavern three-dimensional model data, cutting the underground cavern three-dimensional model data into a plurality of sub-models according to a geological condition segmentation rule, and enabling the geological condition segmentation rule to dynamically adjust the cutting spacing according to the gradient change characteristics of a rock stratum; performing gradient analysis on the longitudinal and axial rock stratum attributes of each sub-model to generate rock stratum transition characteristic data containing the adjacent rock stratum attribute change rate and the transition area space distribution, and dynamically identifying the surrounding rock type of the sub-model according to the rock stratum transition characteristic data; and mapping and matching the surrounding rock identification result with a preset protected object space coordinate, collecting a sub-model geological parameter set in real time, finally triggering a safety early warning signal according to a geological parameter set numerical value interval, and generating an emergency disposal scheme set associated with the safety early warning signal, so that the potential safety hazard of the underground cavern can be effectively analyzed.

The invention provides an intelligent launching pad management system based on AI visual auxiliary supervision. The system carries out target identification through a YOLO model, carries out behavior sequence analysis in combination with an LSTM model, and carries out cross-modal dynamic feature fusion through spatio-temporal feature alignment, time sequence and spatial feature enhancement and a graph convolution network and graph attention mechanism to generate globally optimized feature representation. And further utilizing a knowledge reasoning engine to combine with the case database and the equipment knowledge graph to generate an intelligent emergency processing scheme. And finally, generating a preliminary potential safety hazard analysis report based on a Transform technology, and performing semantic calibration in combination with the central control module and the domain knowledge base to generate an accurate and normalized alarm analysis report. The system also has the functions of adaptive algorithm optimization, multi-modal data fusion processing and real-time alarm and feedback, realizes the intelligent and automatic management of the launching pad, improves the safety supervision efficiency and fault processing capability, and effectively improves the intelligent level of the safety management of the launching pad.

A method for selecting near-source strong motion records considering fling-step effects includes the following steps: introducing a permanent displacement as a conditional parameter into ground motion selection based on generalized conditional intensity measures, and giving a target permanent displacement by extended probabilistic fault displacement hazard analysis; characterizing a frequency content component of a ground motion with a spectral displacement instead of spectral acceleration in a target ground motion intensity measure set; further calculating an empirical correlation coefficient suitable for near-source strong motion records with permanent displacement, constructing a corresponding target conditional distribution, and finally obtaining a data set of near-source strong motion records with permanent displacement most consistent with a target conditional distribution by optimizing selection from a near-source strong motion database. A reasonable ground motion selection method is provided for seismic response analysis of near-source engineering structures under a strong motion-fault dislocation coupled effect.

The invention belongs to the technical field of multi-level RCM, and discloses a multi-level RCM analysis and reliability structure construction method and a related device. The multi-level RCM analysis and reliability structure construction method comprises the following steps: establishing a unit system function model after constructing a unit system database, performing multi-level classification on equipment of a unit system in combination with a fuzzy clustering algorithm, and then determining levels and weights of various types of equipment in the unit system function model, analyzing a failure mode of each type of equipment after multi-level classification through a harmfulness analysis method in combination with a fault tree analysis technology, establishing a correlation model between the equipment failure mode and a unit system function, determining an influence weight of the equipment failure mode on the reliability of the unit system, and establishing a unit system reliability model; inputting the unit system database into the unit system reliability model to obtain a unit system maintenance strategy library; the analysis result accuracy and the system reliability can be greatly improved.

The invention provides a safety early warning method, system and equipment for a galvanizing process production line and a medium. The safety early warning method comprises the following steps: acquiring multi-source data of the galvanizing process production line; performing multi-modal analysis and vectorization processing on the multi-source data, constructing a galvanizing process production line knowledge graph, and storing the knowledge graph to an AI data lake; reading a knowledge graph from an AI data lake to adjust the general large model; transversely splitting the galvanization process into a plurality of process thinking chain nodes according to a process sequence; longitudinally splitting each process thinking chain node into an analysis node and an auxiliary node executed by the potential safety hazard analysis model to form a tree structure thinking chain; traversing the tree structure thinking chain based on a preset sequence, and analyzing the potential safety hazard of each process; and summarizing the potential safety hazard analysis results of all the processes, and generating a potential safety hazard report and rectification measures for safety early warning. The method helps managers to master potential safety hazards possibly existing after operation of a production line and corresponding rectification measures in the galvanization industry.

Systems and methods is provided for road hazard analysis. The method includes obtaining sensor data of a road environment including a road and observable surroundings, and applying labels to the sensor data. The method further includes training a first neural network model to identify road hazards, training a second neural network model to identify faded lane markings, and training a third neural network model to identify overhanging trees and blocking foliage. The method further includes implementing the trained neural network models to detect road hazards in a real road setting.

The application discloses a kind of control method and system of industrial park energy storage device, it is related to energy storage device control technical field.This application is based on production plan and real-time electricity price, dynamically senses load demand fluctuation, and distributes distribution unit accordingly dynamic adjustment;Further through real-time current signal analysis, actively identify potential hazards, guarantee the reliability of distribution unit hazard analysis result;While comprehensive multidimensional data assesses the overall health status of distribution unit, provides basis for maintenance and replacement decision, solves the limitations existing in current energy storage device control feasibility analysis;Once hidden danger or state anomaly occurs, immediately give early warning, improve system security and reliability;From demand calculation, resource matching and operation monitoring to abnormal early warning form complete closed loop, realize the intelligentization, safety and high efficiency management of energy storage device control.

This invention relates to the field of geological hazard analysis technology, and particularly to a geological hazard early warning method based on active detection and spectral response variation. The method includes: deploying active signal excitation devices and signal receiving sensors in the monitoring area to apply active detection signals to the geological body and collect response signals; filtering and adaptive time window segmentation of the response signals to obtain stable-period spectral data; establishing a benchmark spectral model through Fourier transform and phase spectrum analysis; periodically transmitting active signals and collecting real-time responses, calculating real-time spectral characteristic parameters, and comparing them with the benchmark spectral model to obtain spectral variability; determining an early warning threshold using a decision tree model based on historical monitoring data; and calculating the geological hazard risk level and outputting early warning information when the real-time spectral variability exceeds the threshold, combined with environmental variables.

The invention discloses an energy storage system hazard analysis method and system based on full-link fault sorting, and relates to the technical field of energy storage systems, and the method comprises the steps: defining a hazard scene of an energy storage system; establishing a safety control system of the energy storage system; taking a safety control loop of the whole link of the energy storage system as an object, performing fault sorting on the safety control system, and identifying a problem control behavior of the safety control system; and determining an energy storage system hazard scene corresponding to the problem control behavior of the safety control system. According to the method, key failure events can be identified, and harmful events possibly caused by unsafe fault protection decisions when the failure events occur can be analyzed and obtained from the perspective of component interaction. Meanwhile, safety function classification is carried out on all the components, sorting is carried out from the whole link based on the interaction relation, potential safety hazards still existing in a complex system can be avoided, and the possibility of accidents caused by decision errors is relieved from the mechanism.

The invention discloses an unexpected electric braking fault control method and related equipment, and the method comprises the steps: determining a risk level and a fault cause corresponding to an unexpected electric braking fault of a vehicle, the unexpected electric braking fault being used for representing unexpected deceleration exceeding a quantitative safety boundary generated by the abnormal electric braking function of the vehicle, and determining the risk level and the fault cause corresponding to the unexpected electric braking fault; the quantitative safety boundary is a threshold value of unexpected deceleration and duration related to each risk level, the risk level is determined based on hazard analysis and risk assessment, and the fault cause is obtained through analysis and tracing of an architecture-level fault tree; safety requirements are determined based on the risk level and the fault reason, and the safety requirements comprise generation control of an electric braking request, execution process monitoring of the electric braking request and management and degradation when an unexpected electric braking fault occurs; an actual execution electric braking force of the vehicle is configured based on the safety demand to limit an unexpected electric braking force within a quantified safety boundary.

The invention relates to the technical field of cable management, in particular to a thermal insulation type fire-resistant cable potential safety hazard analysis sniffing method and system.The method comprises the steps that in the cable manufacturing stage, a memory metal wire is embedded in a protection sleeve on the outermost layer of a cable; constructing a cable distribution model according to the cable distribution information; real coordinates are configured for the cable distribution model, after the real coordinates are configured, the cable distribution model is amplified, and a hidden danger sniffing path is planned by applying the amplified cable distribution model; a cable surface wide image is acquired based on unmanned aerial vehicle aerial photographing equipment, and an acquisition period is synchronously set and applied; according to the invention, the memory metal wire is embedded into the outermost protection sleeve of the cable, the operation heating condition of the cable is represented, and the unmanned aerial vehicle aerial photography equipment is further matched to collect the cable surface image, so that the position of the cable surface where potential safety hazards easily exist is analyzed based on continuous cable surface image collection; and reference is provided for cable management users.

The invention relates to the field of clinical nursing equipment, in particular to a clinical nursing potential safety hazard analysis and early warning device which comprises a storage supporting box, a fixing plate is fixedly connected to the rear end of the storage supporting box, and an overall fixing supporting piece is fixedly connected to the outer side of the fixing plate through bolts. The front end of the overall fixing supporting piece is connected with a plurality of sets of hanging storage assemblies, the interior of the storage supporting box is connected with an article storage assembly, and the front end of the storage supporting box is connected with an infusion monitoring assembly. By using the infusion monitoring assembly, the situation of liquid medicine is monitored in real time, and air embolism caused by air entering blood vessels is avoided; the monitoring watch is arranged on the wrist of a patient in a sleeving mode, the body temperature, the blood pressure and the heart rate of the patient are monitored in real time, and potential safety hazards can be analyzed and early warned in time; through the design that the limiting disc is detachably connected to the outer side of the mounting block, the patient can conveniently move, and the use flexibility of the patient is improved.

The present application relates to the technical field of local structure damage detection, and particularly relates to a local structure hazard analysis method using digital twinning. The method acquires measured strain signals and vehicle parameters when a standard vehicle passes over a bridge, and extracts a normalized measured feature vector. At the same time, an isomorphic simulation feature vector is generated based on the vehicle parameters and a finite element model. An optimal transmission coupling matrix between the two is calculated using the Sinkhorn algorithm, and a distribution pattern transmission cost and an adaptive sparse weight are obtained, solving the recognition error caused by the phase shift in the waveform space. By minimizing the transmission cost and applying sparse constraints, the equivalent cross-section reduction coefficient of each unit is inverted, and the precise positioning of local stiffness damage is realized. Finally, the model material parameters are updated synchronously, and the load bearing capacity reduction rate of the structure is calculated through nonlinear whole-process analysis. The present application can accurately quantify the influence of local damage on the overall safety of the structure under the conditions of unknown vehicle weight and waveform shift.

The invention provides a construction potential safety hazard analysis system and method based on image recognition, and relates to the technical field of potential safety hazard analysis, and the method comprises the steps: obtaining an excavation video of excavated earthwork and a three-dimensional point cloud model of unexcavated earthwork; determining a plurality of initial safety excavation points based on the three-dimensional point cloud model of the unexcavated earthwork; determining a plurality of preliminary excavation lines based on the plurality of initial safe excavation points and the three-dimensional point cloud model of the unexcavated earthwork, wherein each preliminary excavation line passes through each initial safe excavation point; generating a simulation excavation video of each preliminary excavation line based on the preliminary excavation lines, the three-dimensional point cloud model of the unexcavated earthwork and the excavation video of the excavated earthwork; and determining a target excavation line based on the simulated excavation video of each preliminary excavation line. The method can accurately determine the target excavation line of the earthwork excavation operation.

To allow a plurality of management companies for managing a space object flying in space to efficiently perform sharing execution of danger analysis.SOLUTION: Each of space transportation management devices 100 includes all of space transportation management rule information, a space information recorder 101, a danger alarm device 102, and a danger analysis device 103. Further, each of the plurality of space transportation management devices 100 includes all of a danger avoidance behavior support device 104 for displaying role sharing of an avoidance behavior of a space object, a danger avoidance behavior execution plan, a measurement error scrutiny device, and a security device 105 for preventing information falsification. The danger alarm device 102 notifies an approach or a collision of the space object, and even an anybody of a plurality of management companies quickly shares information among related companies with minimal effort in the case of foreseeing danger.SELECTED DRAWING: Figure 11

The invention relates to a monitoring system and method for monitoring a personnel transportation device. The monitoring system comprises at least one hazard analysis module, an interaction module, a control module and at least one motion detection module, which components are connected to one another via a data network. As soon as the hazard analysis module recognizes a critical situation in the motion sequence recording of the motion detection module, the hazard analysis module sends an alarm signal to the interaction module and the control module, wherein the motion sequence recording associated with the alarm signal is reproduced on the display of the interaction module immediately after receipt of the alarm signal and the control module exerts an influence on the operation in the personnel transportation device associated with the alarm signal. By manually operating an input device, the monitoring personnel can revoke the initiated influence on the operation.

The invention relates to the technical field of electric vehicle fire simulation, and discloses an underground parking lot electric vehicle whole vehicle fire simulation and hazard analysis method comprising the following steps: carrying out a thermal runaway test on an electric vehicle power battery monomer to obtain related data; building a three-dimensional geometric model of the underground parking lot and the electric vehicle according to the actual structure size, simplifying a vehicle body of the electric vehicle and reserving combustible parts, restoring the structure of the parking lot and considering the influence of beam columns, and carrying out hierarchical modeling on surrounding vehicles; pyrosim software is used for simulation, multiple parameters are set, and test data are used as boundary conditions to obtain a result; after simulation, based on multi-dimensional analysis of monitoring data, an evaluation model is constructed by using a specific method to quantitatively evaluate fire hazard; the objective of the invention is to solve the technical problem of lack of simulation of multi-vehicle coupling and large-space fire spreading behaviors in the existing simulation multi-focus single-vehicle scene.

The present application relates to the technical field of inspection planning, and particularly relates to a UAV low-altitude inspection planning system and method based on danger analysis, which performs detailed evaluation on the route of the UAV, combines environmental abnormal influence and dangerous area influence, and considers building collision danger, performs multi-dimensional calculation on flight complexity evaluation, flight height danger and building density danger, comprehensively calculates dynamic and static risks, finally, comprehensively obtains global route danger evaluation result by combining building collision danger of each area and risk evaluation result, and selects the route with the minimum danger according to the global route danger evaluation result, so that the whole scheme realizes multi-dimensional and comprehensive risk evaluation, considers various factors such as environment and building, meets relevant standard requirements, and can effectively reduce UAV flight risk.

The invention provides a marine methanol hydrogen energy risk assessment method and device based on a fusion strategy, and relates to the technical field of system safety engineering and risk management.The risk assessment method comprises the steps that unsafe control behaviors of a power system are identified through system-level hazard analysis, and the risk of the power system is evaluated through assembly-level failure analysis; constructing a hazard causal chain from a bottom-layer physical failure mode to a top-layer system-level hazard; based on a hazard causal chain, constructing a hierarchical causal hazard and operability knowledge graph; the method comprises the following steps of: converting an unstructured multi-modal data stream into a structured semantic event sequence in real time by carrying out multi-modal sensing on an operation state of a power system; and carrying out matching and cognitive reasoning on the structured semantic event, the causal hazard and the operability knowledge graph to output a diagnosis report of the current risk state of the power system so as to complete risk assessment.

This invention relates to a model-based method and apparatus for aircraft functional hazard analysis (FHA), comprising: 1) determining the basic data for FHA; 2) automatically acquiring the functional model; 3) defining functional failure states according to the function; 4) determining the initiating events and acquiring event attributes; 5) determining the resulting event data; 6) constructing an event sequence model; 7) automatically generating FHA based on the event sequence; and 8) automatically generating safety mission reliability requirements. The apparatus includes: a database, a basic data setting module, a functional model import module, a functional failure state determination module, an initiating event determination module, a resulting event determination module, an event sequence model construction module, an FHA automatic generation module, and a safety mission reliability requirement generation module. This invention applies the event sequence model to the aircraft FHA process, automatically generating safety mission reliability requirement documents, reducing the complexity of manual entry and analysis.

The present invention proposes a method for analyzing unknown hazards of the expected functional safety of in-vehicle digital twins based on a Bayesian model, which includes four steps. Step 1: First, a digital twin of the autonomous driving vehicle to be evaluated is constructed using CARLA, and an autonomous driving scenario is constructed using CARLA, including a map, other traffic participants, etc. The twin scenario is repeatedly run, and the driving data of the vehicle to be evaluated and the probability of being exposed to risks are recorded; Step 2: A risk map is constructed based on the driving data of the vehicle to be evaluated, and the risk map is converted into a Bayesian risk map; Step 3: Based on the Bayesian risk map and combined with the Noisy-OR and Noisy-AND structures, a conditional probability table of triggering events of each node is calculated; Step 4: According to the conditional probability table obtained in step 3 and combined with the CVSS universal vulnerability scoring system, the expected functional safety with unknown triggering events is comprehensively evaluated, and a safety evaluation score is given.

The present invention relates to the field of collaborative control technology, and is a collaborative management control method and system for the linkage of multifunctional modules in a smart park, comprising: estimating the initial effective loading margin of the current collaborative equipment; constructing a forward loading capacity prediction model, outputting the forward effective loading capacity prediction value of the current collaborative equipment, fusing the forward effective loading capacity prediction value with the real-time remaining effective loading capacity to obtain a real-time fused loading margin; performing a garbage seepage hazard analysis and a garbage escape hazard analysis on the garbage distribution based on real-time garbage status data; evaluating the processing urgency of the garbage collection points in each sub-collaborative area to obtain a processing urgency sequence; and determining whether to trigger a reverse loading instruction based on the processing urgency sequence. The present invention solves the problems of high operating costs and poor collaboration of collaborative equipment in the prior art.

The present invention discloses a short-circuit fault warning system for a line, and relates to the technical field of fault warning. The present invention comprises: a transmission line analysis unit, a short-circuit hazard prejudgment unit, a short-circuit warning module and a local database. The present invention uses a drone to intelligently adjust the distance value to the corresponding transmission line according to the voltage value of each transmission line belonging to the target area, and compensates the appearance variation coefficient of each wire of each section of the transmission line belonging to the target area to a certain value according to the distance value, thereby reducing the incidence rate of short-circuit problems caused by appearance damage of the transmission line. By performing short-circuit hazard analysis on each section of the transmission line belonging to the target area according to the rainfall status, and taking into account the hazards of wind tripping during the analysis, the incidence rate of short-circuit problems caused by wind tripping of the transmission line is reduced, thereby improving the power safety of the transmission line and improving the transmission efficiency of urban power use.

The present invention relates to the field of battery operation management, and discloses an energy storage battery operation risk prediction system. The system collects real-time operation data of multiple groups of energy storage batteries; an environmental data collection module and environmental data; then comprehensively calculates an operation risk coefficient based on the operation data and the environmental data, and after comparing it with a preset comparison range of the system, determines whether the energy storage battery is in a potential risk state; then gives an early warning to the energy storage battery in a potential risk state, conducts early warning monitoring and key marking on the energy storage battery in a critical state; then conducts a predictive hazard analysis on the key-marked energy storage battery to obtain a status value, and compares the status value with a preset status range; finally, executes corresponding emergency measures according to the comparison result. The present invention comprehensively predicts the operation risk of the energy storage battery through environmental data and operation data, issues an early warning in a timely and accurate manner, and conducts in-depth analysis on the energy storage battery in a critical state to establish a maintenance order.

The present invention provides a safety monitoring and alarm system for power metering field operations, designed in the field of monitoring and early warning technology. The system includes: an acquisition module for collecting an initial video stream of the power operation site based on the safety helmets worn by workers, and multiple sensors configured to sense the power and environmental parameters of the power operation site in real time; a compression module for compressing the collected data at each moment and transmitting it to a backend; a backend for setting a sliding window to lock the received compressed data at a specific moment, analyzing the hazard type and hazard trigger probability of the first processed data at the locked moment; and further for chronologically arranging all hazard types and hazard trigger probabilities, generating a reminder instruction, and issuing it to the alarm module of the corresponding safety helmet for reminder. Data compression and hazard analysis ensure the reliability of safety warnings, facilitating effective management and effectively ensuring personnel safety.

The present invention discloses a method for assessing flood disaster risk at ancient sites by coupling quantitative simulation with qualitative analysis. The method comprises collecting relevant data on flood disasters at ancient sites, preprocessing the data, and performing hazard analysis and vulnerability analysis on the data. The hazard analysis involves: integrating environmental data and rainfall data, setting rainfall scenarios using a hydrodynamic model, and performing numerical simulation to obtain rainfall data, thereby assessing the disaster to obtain a quantitative hazard level. The vulnerability analysis involves classifying the vulnerability levels according to the stability, value loss, and repairability of the artifacts under the disaster scenario to obtain a qualitative vulnerability level. The quantitative hazard level and the qualitative vulnerability level are then organically coupled to obtain a flood disaster risk level map for the ancient sites. This method not only improves the accuracy of flood disaster risk assessment for ancient sites, but also has good interpretability and can be directly used in ancient site flood disaster risk assessment systems.

The invention provides an electronic rearview mirror system function safety concept stage analysis method, and belongs to the technical field of electronic rearview mirror design, and the method comprises the steps: defining the function, use scene, initial architecture, operation mode and external interface of a CMS in a whole vehicle as related items; performing hazard analysis and risk assessment from the aspects of controllability, severity and exposure on the basis of the defined related items in combination with a main operation scene of the CMS determined from the adaptive scene, and determining a safety target of the CMS and a corresponding automobile safety integrity level; and according to the determined safety target and the automobile safety integrity level, in combination with the defined initial architecture, decomposing the safety target to each electronic component of the electronic rearview mirror system, and generating a functional safety demand allocated to each electronic component. According to the method, from the whole vehicle level, related items are comprehensively defined, hazard analysis and risk assessment are accurately carried out, safety requirements are reasonably decomposed, reliable operation of the CMS is ensured, and the driving safety is improved.

The invention discloses a smart home security system based on the Internet of Things, and relates to the technical field of smart home, the smart home security system comprises a data monitoring module, a potential safety hazard analysis module, a security protection module, a remote early warning module and a database, a house is divided into regions, and the information of each region is monitored in real time; whether gas danger exists in the house or not is judged according to the change of the gas concentration in each area, meanwhile, whether dangerous activities exist in the house or not is judged according to the activity information and the body data of the monitoring target and the dangerous article list of the monitoring target, and security and protection regulation and control are conducted on the smart home according to the gas concentration and the dangerous activities. Meanwhile, casualty risks of people in the house are analyzed, remote early warning is carried out on the local rescue terminal, prevention can be carried out in advance, rescue can be carried out in time, the effectiveness of smart home safety protection and the accuracy of potential safety hazard judgment are guaranteed, and the safety of people in the house is also guaranteed.

The invention relates to a method for increasing the driving safety of an at least partially automated driving vehicle (10), in which environmental data of a real environment (12) of the vehicle (10) is generated by means of a camera (11) and transmitted to a control device (13), by means of which the vehicle (10) is driven by means of the camera (11). A hazard analysis is performed on a current driving situation of the vehicle (10) in the environment presented by the environment data (12), a characteristic value suitable for evaluating a potential hazard situation is determined on the basis of the hazard analysis, and an enhanced image content (15) is determined from the determined characteristic value. And displaying, by means of a display device (16), the enhanced image content from the perspective of the observer in a fused manner into the real environment (12) in order to mark the potentially hazardous situation; the invention further relates to a vehicle (10) having an at least partially automated driving function and a control device (13) which is designed to carry out a method of this type.