592 results about "Safety zone" patented technology

The invention belongs to the field of unmanned aerial vehicle emergency control systems, and relates to a risk identification and emergency method when an unmanned aerial vehicle flies in an airspace adjacent to an expressway, and the method comprises the steps: obtaining the balance state of the unmanned aerial vehicle through constructing a six-degree-of-freedom dynamic model and incorporating environmental factors and control intentions; dynamically comparing the balance state with real-time data to obtain a state deviation, deducing the fault probability of the unmanned aerial vehicle according to the state deviation, and realizing sensitive early warning of possible faults of the unmanned aerial vehicle; besides, the method constructs a double-layer linkage framework of an electromagnetic safety boundary and a physical safety boundary, realizes safety risk identification in combination with a fault probability, and ensures that a safety area between the unmanned aerial vehicle and a motorcade on a highway can be represented by a risk value along with speed, motorcade density and interference intensity; the fault probability of the unmanned aerial vehicle flying in the air is considered, when the fault probability is larger than a preset threshold value, the out-of-control state of the unmanned aerial vehicle is judged, a corresponding control strategy is adopted, and the flight safety of the unmanned aerial vehicle during partial or comprehensive out-of-control is guaranteed.

The invention discloses a safety-enhanced trajectory planning method based on an Astar algorithm, and belongs to the technical field of intelligent robot navigation and path planning, and the method comprises the following steps: 1, constructing a grid map, and marking an obstacle region; 2, establishing a security evaluation mechanism, evaluating the surrounding environment of the path node, and quantifying a security index; 3, in a node expansion process, combining a heuristic item and a security index in a cost function to realize priority search for a security region during path selection; 4, key nodes of the obtained initial safety path are extracted based on a Douglas-Peucker algorithm to generate a rectangular safety corridor, and smoothing processing of the initial path is achieved based on a segmented Bezier curve. On the basis of guaranteeing path optimality, safety is used as an auxiliary guiding basis in the path searching process, and the path searching efficiency is improved. Therefore, consideration of the path length and the environmental risk is realized, and the navigation path with higher execution safety is generated.

The invention relates to a safe starting control method, device, equipment and medium for a bootstrap drive inverter, and the method comprises the steps: obtaining a detection voltage representing an output filter inductance voltage after responding to any starting event and before formally transmitting a drive signal; comparing the negative voltage with a preset negative voltage safety threshold value; only when the detected voltage is higher than the safety threshold, a driving enable signal is generated to allow the inverter to be normally started; otherwise, generating a driving blocking signal, carrying out detection and judgment again after waiting for preset time delay, and circulating the process until the system state enters the safe area; the method is realized by modifying a control algorithm, no power hardware needs to be added, the starting impact risk is eliminated with low cost, and the contradiction between the hardware limitation of a bootstrap drive circuit and the negative residual voltage possibly existing on the output inductance of the inverter is solved; therefore, the safety problem of direct connection between the impact current and the bridge arm during starting in an unfavorable initial state is solved.

The invention provides a construction site safety supervision method and system based on multi-mode intelligent perception, and relates to the technical field of highway construction supervision. A construction area is scanned through a 5G camera, multi-mode intelligent sensing data such as videos, positioning and environment sensors are fused, a three-dimensional model of a construction site is constructed, and the positions of equipment and personnel are accurately determined. Beidou positioning and safe area setting are combined, real-time safety detection is carried out, illegal intrusion of external vehicles and personnel is effectively prevented, and construction of equipment and personnel outside a safe area is avoided. According to the method, illegal behaviors of not wearing safety helmets and the like are intelligently identified by using AI, post-accident tracing is realized through the Internet of Things, accurate traffic guidance information is published in combination with Atdes and Baidu maps, the collision risk and potential safety hazards are reduced, and the safety of a highway construction site is comprehensively improved.

The invention relates to the technical field of geo-fence triggering, in particular to a multi-mode positioning data fused GEO fence triggering method and triggering system. The method comprises the following steps that according to the distance between equipment and the fence boundary, a layered positioning strategy is adopted to demarcate a safe area, a transition area and a critical area; when the device is located in the safe area, outputting a coarse position coordinate of the device and a corresponding coarse positioning confidence coefficient by adopting a low-power-consumption coarse positioning algorithm; when the equipment is located in the transition area, fusing the GPS data and the IMU data by adopting an adaptive fusion algorithm to obtain an intermediate fusion position, an intermediate fusion speed and an intermediate positioning confidence coefficient; fusing the multi-modal data when the equipment is located in the critical zone, and predicting the probability that the equipment invades the fence by combining a trajectory risk assessment algorithm based on the equipment acceleration and the distance between the equipment and the fence boundary. Through hierarchical positioning strategy and multi-modal data fusion, the problems of insufficient precision and high power consumption of a single positioning mode in a complex scene are solved.

An apparatus for controlling autonomous driving of a vehicle is introduced. The apparatus may comprise a controller configured to determine, in a merging section on a road, at least one area of a safety area, a yield area, or a stop area, wherein the safety area may comprise a first part of the merging section designated for vehicles that have a right of way, the yield area may comprise a second part of the merging section designated for vehicles that should yield to traffic on the road, and the stop area may comprise a third part of the merging section designated for vehicles that should stop before merging onto the road, and determine a driving strategy of the vehicle for the at least one area, and a brake configured to, based on the driving strategy, adjust a speed of the vehicle.

The invention discloses a simulator supporting multiple debugging permissions. According to the embodiment of the invention, the simulator supporting multiple debugging permissions comprises a simulator management module which comprises a configuration unit, and the configuration unit is used for configuring the debugging permissions; a storage unit of the simulator hardware module is divided into a safe area and a non-safe area; the security area is used for storing security data, the non-security area is used for storing non-security data, and the debugging permission comprises a security mode and a limited mode; in the security mode, allowing access to the security area and the non-security area; and in the limited mode, the access to the safe area is prohibited, and the access to the non-safe area is allowed. According to the emulator supporting the multiple debugging permissions, debugging requirements of different security levels can be effectively distinguished, and flexible access control is provided for development and maintenance while data security is guaranteed.

The invention discloses an aircraft deployment method based on a dynamic airspace network and reinforcement learning, and relates to the field of air traffic management, and the method comprises the steps: obtaining flight information and task priority weight information of each flight in a historical time period and a current time period; dynamically dividing the airspace into an independent sub-airspace and a shared airspace by using flight information in a historical time period; calculating the safe area of each flight through a space-time buffer zone model, and determining a flight path according to the safe area; and according to the flight information, the airspace division result and the flight path, a release action instruction set including height adjustment, course correction and speed change is generated, and real-time deployment is performed on the flight. The technical effects of the invention lie in that airspace changes can be responded in real time, flight paths of flights are optimized, potential conflicts are reduced, and the airspace utilization rate is improved, so that the air traffic control efficiency and the flight safety are improved.

According to the motion planning method and device for the multi-mechanical-arm cooperative task, a large number of potential conflicts are actively avoided in the early stage of task allocation through division of a virtual wall and a safety area and a danger area, the difficulty and the calculated amount of follow-up track collaboration are remarkably reduced, and the success rate and the efficiency of planning are improved. Cost and load balance are considered in the task allocation stage; in the path point sorting stage, minimizing the total movement distance and the total completion time is taken as a target; and track generation adopts a time optimal algorithm. The layered decoupling design avoids the huge calculation overhead of centralized planning, and meanwhile, the quality of a final solution is ensured through the optimization strategy of each stage. The innovative cost function takes collision distance into consideration, and guides the planner to select a safer path. Through layered and ordered collision solution strategies, such as deceleration, local re-planning and optimal waiting, it is ensured that a collision-free solution can be always found in a complex dynamic environment, and robustness is high.

An autonomous mobile device (AMD) may move around a physical space while performing tasks. The AMD may have sensors with a field of view (FOV) facing forward. As the AMD moves forward, a safe region is determined based on data from those forward-facing sensors. The safe region describes a geographical area that is clear of obstacles during recent travel. If the AMD moves outside of the FOV, such as moving backwards, a check is made as to whether the AMD remains within the safe region. If a portion of the AMD moves beyond the safe region, the AMD stops. This prevents the AMD from colliding with obstacles that are outside of the safe region and also outside of the FOV while moving.

The invention relates to the technical field of intelligent security and protection, and discloses an intelligent security and protection alarm method and system based on an intelligent park. The method comprises the following steps: acquiring original security and protection data by using sensing equipment arranged in a smart park; performing standardization and redundancy elimination processing on the original security and protection data, dividing safety areas of the park through a pattern recognition algorithm, calculating a load intensity index of each area, and generating a security and protection situation summary; according to the security situation summary, a heuristic search algorithm is adopted to determine alarm trigger parameter initial values including detection sensitivity and alarm intervals, and a basic alarm parameter group is generated; performing nonlinear correction on the basic alarm parameter group, and outputting an environment perception alarm parameter group; training the historical security data set by adopting a neural network model, and analyzing the interaction between the load and the threat to obtain a threat diffusion model; and comparing the threat diffusion model with the real-time security data points, performing difference measurement, reconstructing alarm trigger logic according to a measurement result, and completing autonomous regulation and control of security and protection of the smart park.

The invention discloses an under-mine environment accurate positioning system based on a UWB technology, and relates to the technical field of data processing and positioning, an underground area is divided into a safe area and a dangerous area by obtaining the structure risk value of each sub-area and combining the structure risk value and the position information of the corresponding sub-area, and the safe area and the dangerous area are accurately positioned. A plurality of rescue robots are arranged in the underground area; acquiring position information of the mobile tag, displaying the position information on an electronic map, generating an air quality coefficient, and dividing the plurality of sub-regions into risk regions and safety regions according to the air quality coefficient; and sending inquiry information to the miner, acquiring a corresponding safety coefficient, and if the acquired safety coefficient is lower than a safety threshold value, planning a support path to the miner for the rescue robot, so that the rescue robot rescues the miner along the support path. After the miner is found according to the position information of the miner, the miner is rescued through guidance of the rescue robot, and the miner is prevented from getting lost and being lost.

The invention relates to the technical field of environment monitoring, in particular to an environment parameter real-time early warning method and system for a digital chicken house, and the method comprises the following steps: collecting ammonia gas concentration, temperature and humidity and illumination intensity data in a chicken house, uniformly integrating and generating a monitoring record, extracting a safety interval, counting the exposure time of ammonia gas, and judging a multi-factor deviation state; and carrying out conjoint analysis on environment distribution change, and outputting a risk state and early warning information. According to the method, multi-source environment data are integrated through a unified time reference, the time sequence consistency among parameters is improved, the identification capability of low-concentration long-term exposure is enhanced by screening an ammonia gas safety interval and counting the exposure duration, and a multi-factor time sequence offset feature is constructed by collecting the deviation state of temperature and humidity and illumination intensity; the conjoint analysis of exposure and deviation distribution is combined, the continuity and accuracy of environmental risk judgment are improved, high-risk time periods and monitoring data thereof are extracted, and the positioning and response efficiency of abnormal states is enhanced.

The invention discloses an intelligent monitoring and early warning method and system for a dangerous large project on a building construction site, and the method comprises the steps: carrying out the fusion processing of multi-source data, such as displacement, inclination and axial force, collected by edge Internet of Things equipment, extracting the characteristics of structural deformation and load change, and constructing a comprehensive situation representation; a high-risk area and a safety area of a construction site are identified by adopting clustering analysis, a spatial proximity relationship between the areas is established, a risk coupling degree is calculated, and a differentiated monitoring strategy is delimited according to the spatial proximity relationship; performing time sequence density analysis on the abnormal event data, fitting a risk evolution curve, positioning a situation mutation node, and establishing association mapping of construction conditions and risk steps; according to the method, a transmission path is tracked based on a risk attenuation rule, a preliminary early warning sequence is generated, an early warning trigger threshold value is determined through adaptive grading and boundary matching, a graded early warning instruction is output after gradient verification, and timely and accurate early warning information can be provided for safety management and control of dangerous engineering.

The invention relates to a robot dog dynamic balance and fall self-recovery method and device for a complex terrain, and the method comprises the steps: building a robust local elevation map through fusing multi-sensor data and quantifying the motion uncertainty of a robot; and a safe foot region set defined by the convex polygon is extracted through geometric feature analysis and plane segmentation. Then, collaborative planning of the trunk and the landing point is carried out in combination with a user instruction and the region set. In a control layer, a nonlinear model predictive control algorithm is adopted, a safety area is used as a hard constraint, and incomplete speed constraint is applied to a wheel type foot end, so that an optimized trunk track and a foot end force reference are output. The whole-body controller converts an upper-layer instruction into an accurate joint torque through a multi-task optimization framework with a weight. When instability is detected, the system can autonomously plan and execute a recovery action sequence including curling, controllable rolling and cooperative supporting.

The invention discloses a nuclear magnetism safety interval confirmation device, and the device comprises a quantum noise suppression module which is used for eliminating radar signal noise caused by the quantum tunneling effect on the surface of a metal object in an ultrahigh field intensity environment; the multi-sensor fusion center is used for integrating the radar cleaning signal, the real-time magnetic field intensity data and the terahertz penetrability detection result to generate fused object position information; the dynamic magnetic field reconstruction engine is used for calculating a magnetic field distortion gradient by analyzing Hall sensor array data and a magnetohydrodynamic model in real time; the nonlinear danger scoring module is used for receiving object distance, magnetic field gradient, existence time and object classification data; the hierarchical response system is used for triggering a corresponding response according to the danger score; and the cesium atomic clock synchronization module is used for eliminating a timing error caused by a time crystal effect through a block chain timestamp verification mechanism. According to the invention, risk closed-loop control in a high-field-intensity MRI environment is truly realized.

The invention relates to the technical field of ship offset early warning, and provides a ship offset early warning method for a deep-sea mining in-situ pilot production system, which can solve the problem that the existing mother ship offset monitoring mode is too simple, improve the accuracy of judging the position of a ship body and perform effective early warning. Comprising the following steps: S100, establishing an information transmission network and carrying out data acquisition; s200, carrying out coordinate conversion on the collected real-time longitude and latitude information of the ship and the vehicle, and calculating a relative distance between the ship and the vehicle; s300, calculating a ship offset area of the mining system, calculating an allowable offset of a mining ship relative to a mining vehicle, dividing operation states according to the offset, and determining a reasonable ship offset area map; and S400, the ship deviation safety early warning area is built in a system early warning program, monitoring data are read at regular time, monitoring information such as environment monitoring information, ship-vehicle distance and the like and umbilical cable length monitoring information are read in real time, and the ship deviation state is judged in real time according to the ship deviation safety area.

The invention discloses a safe area management method and system for a zoo, and relates to the field of animal positioning. The safe area management method for the zoo comprises the following steps: monitoring an image and multiple environmental parameters of an animal activity area in real time; identifying the position and the moving track of the animal in the image; when it is detected that the position and the moving track of the animal are abnormal, early warning is given out; performing three-dimensional modeling on the animal activity area; identifying a dynamic obstacle in the animal activity area; and analyzing a movable area and a movable path of the animal according to the dynamic obstacle. According to the invention, recognition and prediction of complex animal behaviors are realized, and an early warning mechanism of animal abnormal behaviors is perfected.

The invention provides a head-eye posture fused driver state grading intervention method and system, and the method comprises the steps: dividing a fixation region which comprises a safety region, an alarm region and a dangerous region based on an in-vehicle three-dimensional coordinate system; calculating an initial line-of-sight vector according to the driver face key points, obtaining a final line-of-sight vector by combining line-of-sight deviation angle correction, and obtaining a fixation point coordinate based on the eye point coordinate and the final line-of-sight vector; based on fixation point coordinates and fixation area matching, the driver fixation area category is judged; and acquiring the current vehicle speed and the fixation duration in the fixation area, inputting the current vehicle speed and the fixation duration into a pre-trained decision model to obtain a graded intervention strategy, and executing an intervention action according to the strategy. The accuracy of the fixation point position is ensured through fusion of the head posture and the sight line deviation; a grading intervention strategy is obtained by combining the fixation point position, the fixation duration and the vehicle speed, interference to normal driving is reduced, effective early warning can be achieved in the risk accumulation stage, and the method has adaptability to complex vehicle use scenes.

The present application relates to the technical field of intelligent city infrastructure safety monitoring, and discloses a real-time response system for safety events of intelligent pedestrian tiles. The system comprises a real-time state monitoring module, a dynamic event detection module, a multi-dimensional event difference analysis module, a safety area correlation positioning module and a self-adaptive response generation module. The sensor array collects tile pressure distribution, surface humidity and temperature fluctuation data, and combines historical event data to construct a dynamic prediction model to output potential safety event probability values. A multi-dimensional difference analysis generates an event-level difference feature matrix, and a spatial topology network and environmental parameters are used to generate a safety event heat distribution map and locate high-risk areas. Finally, response parameters are adaptively configured. The system realizes real-time sensing, accurate positioning and dynamic response of safety events in urban pedestrian areas.

If an overlap of two or more extended reality (XR) safe play areas, associated with active XR devices (e.g., VR devices) operating in a physical space is detected, then a combined safe area is determined based on the first and second safe areas. A configured first XR safe area is generated. A virtual partition may demarcate the separation between the safe areas. The virtual partition may include a buffer zone that separates the reconfigured first safe area from the reconfigured second safe area. An errant XR device may be guided back to its safe area.

A method or system for adaptive vehicle spacing, including determining a current state of a vehicle based on sensor data captured by sensors of the vehicle; for each possible action in a set of possible actions: predicting, based on the current vehicle state a first zone future safety value corresponding to a first safety zone of the vehicle; and selecting, based on the first zone future safety values for each of the possible actions in the set, a vehicle action.

The invention provides a bracelet anti-lost fence construction method and system for old people for cognitive impairment, and the method comprises the steps: collecting the geographic information data of a daily activity region of the old people, covering the coordinates of a frequently-going place and an activity path coordinate sequence, carrying out the feature extraction of the activity region, generating a boundary coordinate set of a basic safety region, and carrying out the construction of a bracelet anti-lost fence for the old people; adjusting the boundary in combination with the health condition and travel habit feature data of the elderly to obtain an initial anti-lost fence boundary coordinate set, dynamically updating the boundary according to the external environment feature change data, and finally establishing a real-time data interaction link with the bracelet; and the bracelet generates a prompt signal and sends the prompt signal to the guardian terminal equipment, so that the pertinence, practicability and reliability of the anti-lost fence are improved, and the risk that the old with cognitive impairment gets lost is effectively reduced.

A video analytic worker safety monitoring system includes at least one video camera having a field of view including a defined safety zone in a workplace, the defined safety zone including or being proximate to a workplace hazard such as an electrical hazard, a machine hazard, or a medical procedure hazard. An image processor receives a video feed from the at least one camera, wherein the image processor is configured to, based on image analysis of the received video feed, detect worker safety deficiency events.

The invention discloses a large-diameter drilling tool clamping and shackling device and an automatic drilling rod assembling and disassembling control method. The large-diameter drilling tool clamping and shackling device comprises a drilling tool clamping and shackling device body, a rod adding mechanical arm and a transfer table. During drilling, the mechanical arm grabs the drill rod from the transfer table, and after the drill rod is positioned through the rear clamping device, the power head completes automatic buckling of the driving drill rod, the drill rod and the drill rod in a hole in two stages according to a preset self-adaptive buckling algorithm; during shackling, the swing oil cylinder drives the front clamp holder to rotate anticlockwise to pre-loosen threads, the power head rotates reversely while the front clamp holder clamps, and automatic shackling between the power head and the drill rod in the hole is achieved according to a preset self-adaptive shackling algorithm. According to the invention, through cooperative movement control of the double holders, matching with the rotating speed of the power head and the feeding / pulling speed, accurate butt joint of drill rod threads is ensured, and manual intervention is not needed in the whole process; the time consumed for connecting and dismounting the drill rod is effectively reduced, the operation distance of workers is prolonged to a safe area outside 2 meters, labor intensity and accident risks are remarkably reduced, and technical guarantee is provided for safe operation of the drilling machine under complex geological conditions.

The invention relates to the technical field of wafers, in particular to a multi-track wafer carrying manipulator and a control method.The multi-track wafer carrying manipulator adopts a mechanical arm assembly and an end effector to execute actions, and the mechanical arm assembly comprises three execution arms which are rotationally connected in sequence; the end effector is installed at the tail end of the execution arm farthest from the base. The method comprises the following steps that S1, a safety area is set, so that the multiple execution arms are located in the safety area all the time in the movement process; s2, gradually iterating the coordinates of each point from the boundary to the center in the safe area, and generating a safe link; s3, in one safety link, the end effector always faces the site position, the center of the end effector is made to move along the safety link, and the angles a, b and c between the adjacent execution arms of each point and the angle d between the execution arms and the end effector are calculated; s4, performing traversal optimization on the distance C in the step S3, and finding an optimal C value; and S5, obtaining the optimal time according to the optimal C value.

The invention provides a composite robot safety protection system based on a dynamically configurable safety domain, which is applied to the technical field of composite robot safety control, and is characterized in that a safety area template configuration module makes a safety area template corresponding to a working point location of a composite robot, and the safety area template comprises at least one safety area; the map and real-time sensing module detects that the composite robot moves to a working point location, loads a safe area template corresponding to the working point location, and detects an intruding object intruding into a safe area through matching of point cloud data and the safe area template; the mechanical arm speed regulation and control module carries out speed regulation and control on the mechanical arm according to the detected intruding object, is suitable for a dynamic scene of the movable base and scene changes of different stations, can also be reused for collaborative operation of a plurality of composite robots, and can improve the space utilization rate, the production efficiency and the safety.

The invention discloses a multi-dimensional dynamic security domain construction method for a wind generating set, and the method comprises the steps: building a multi-dimensional dynamic security domain containing a plurality of key variables, such as wind speed, load and rotating speed, through a deep neural network technology of sharing weight in combination with a confidence level theory; the method comprises the following steps: firstly, carrying out abnormal value detection, filtering smoothing and normalization preprocessing on collected fan operation data; then, a deep neural network based on shared weight is adopted, multiple groups of two-dimensional safety surfaces such as wind speed-load, wind speed-rotating speed, load-rotating speed and the like are constructed according to the number of related variables, and the two-dimensional safety surfaces are combined into a complete multi-dimensional safety domain through a weighted fusion algorithm; further introducing a confidence level concept, calculating a confidence level from a state point to a security domain boundary by adopting an exponential decay function, and dividing the security domain into a security region, a critical security region and a dangerous region; and finally, designing a sliding time window and a time attenuation weight mechanism to realize adaptive dynamic updating of the security domain. According to the method, accurate physical modeling is not needed, the safe operation boundary of the fan under different working conditions can be accurately described, real-time adjustment can be carried out in a self-adaptive mode along with the system state and the environment change, reliable constraint conditions are provided for fan safety control, and the method is particularly suitable for safe operation monitoring and control of a large wind generating set under complex wind conditions. The invention provides an effective method for solving the problems that the safety boundary of the fan is difficult to describe and the multi-parameter coupling is difficult to operate, and the method has wide engineering application value.

The utility model belongs to the technical field of road operation vehicles, and particularly provides an automatic telescopic safety area operation guardrail which comprises a guardrail body, a telescopic support and an electric push rod, the guardrail body is a rectangular frame, the guardrail body, the telescopic support and the electric push rod form one-side guardrail assemblies, and the two one-side guardrail assemblies are arranged in a bilateral symmetry mode. The warning device further comprises a connecting plate, a warning lamp, a warning board and a flexible connecting piece. The operation guardrail does not occupy extra space in a folded state, and can be unfolded to forcibly delineate an operation area when an operation vehicle works, so that external personnel or vehicles are prevented from entering the operation area, and the safety of the road operation vehicle in the operation process is improved; the electric push rod and the electric hinge are adopted, the market development trend is met, different automatic operation vehicles can be adapted, and a worker can complete unfolding operation of the guardrail in a cab through an electric control system.

The invention discloses a real-time electric power scene personnel positioning safety alarm method and system, and the method comprises the steps: obtaining the image information of personnel in a working region of an electric power scene in real time, and obtaining the movement track data of a worker based on an intelligent device worn by a human body; fusing the acquired personnel image information of the working area of the electric power scene and the motion trail data of the working personnel to obtain real-time position information of the working personnel, and according to the real-time position information of the working personnel and the safety area of the electric power scene, if the real-time position information of the working personnel is far away from a set threshold value of the safety area of the electric power scene, judging whether the working personnel are in the safety area of the electric power scene; through fusion of visual and motion sensor data, under the condition that a special positioning base station does not need to be added, the equipment cost is reduced, positioning delay is controlled in a safety response time window through multi-source data complementation, the problem that early warning is not timely due to visual positioning delay is effectively solved, and the positioning accuracy is improved. And through multi-source data fusion, the positioning error is reduced to a level capable of meeting the safety control requirement.