42 results about "Active security" patented technology

The application provides a kind of active safety control method and device of vehicle.When dangerous target appears in front of the vehicle, the active safety control method includes: according to whether brake system and AEB module have fault, AEB fault condition is set to allow triggering or prohibit triggering;According to whether steering system and AES module have fault, AES fault condition is set to allow triggering or prohibit triggering;According to the vehicle speed of the vehicle, AEB speed condition is set to allow triggering or prohibit triggering, and AES speed condition is set to allow triggering or prohibit triggering;According to TTB_limit, TTB_trigger, TTT_limit, TTT_trigger and collision time, AEB collision time condition is set to allow triggering or prohibit triggering, and AES collision time condition is set to allow triggering or prohibit triggering;When multiple AEB conditions are all allowed to trigger, the AEB module can be triggered to execute AEB function;When multiple AES conditions are all allowed to trigger, the AES module can be triggered to execute AES function.In this way, the triggering of active safety function is accurate and safe, and the connection between functions is smooth.

A device establishes a first encrypted tunnel with a first active security gateway at a first data center to enable the device to communicate, via the first encrypted tunnel, with a first access and mobility management function (AMF) at the first data center. The device forwards, via the first encrypted tunnel and the first active security gateway, a first User Equipment device (UE) message to the first AMF. The device determines an occurrence of a failure or overload condition at the first active security gateway, and establishes, based on the determined occurrence of the failure or overload condition, a second encrypted tunnel with a standby security gateway at a second data center to enable the device to communicate, via the second encrypted tunnel, with the first AMF. The device forwards, via the second encrypted tunnel and the standby security gateway, at least one second UE message to the first AMF.

A method, device, vehicle, and storage medium for tire blowout control of a vehicle are disclosed, relating to the field of active safety technology for automobiles. The method includes: acquiring the vehicle's current state information and tire blowout information; adjusting the current state information based on the tire blowout information to obtain tire blowout state information after the blowout, wherein the tire blowout state information includes the actual yaw rate and actual sideslip angle of the vehicle after the blowout; if the vehicle is in an unstable state, acquiring the vehicle's desired yaw rate and desired sideslip angle, and determining a sliding surface control function based on the desired yaw rate, desired sideslip angle, actual yaw rate, and actual sideslip angle; determining a balancing yaw moment based on the sliding surface control function, and controlling the non-blowout wheels based on the balancing yaw moment and the tire blowout information. This application controls the vehicle based on the corrected state information, improving the accuracy of tire blowout control.

The present application relates to the field of hoisting construction, and relates to a compressed air energy storage power station large tank type gas storage hoisting method and system, the method comprising obtaining a gas storage construction basic data set and a multi-dimensional constraint condition; performing global non-conflict scheduling optimization processing according to the gas storage construction basic data set and the multi-dimensional constraint condition, to obtain a non-conflict dynamic scheduling summary table; performing hoisting path planning processing according to the non-conflict dynamic scheduling summary table, to obtain a path set of all hoisting tasks; performing dynamic safety risk assessment processing according to the path set of the hoisting tasks and obtained real-time positioning information, to obtain a three-dimensional dynamic risk area; and performing hoisting operations according to the three-dimensional dynamic risk area and the non-conflict dynamic scheduling summary table, the present application realizes individualized and real-time active safety early warning of personnel and equipment, changes a traditional fixed warning area and a passive security and protection mode of manual lookout, and eliminates a safety management blind area in a three-dimensional intersection operation.

This application provides a third-party monitoring method for road transport safety management, including: a monitoring platform determining the status of a vehicle entering or exiting an assigned electronic fence based on vehicle satellite positioning data, and generating a regional alarm when a vehicle crosses the boundary or violates speed limits; executing a verification and processing procedure for various alarms generated by the monitoring platform, including platform alarms and proactive safety alarms, supporting enterprise users to appeal the verification results and subsequent review; marking the status of vehicles in special states such as being out of service, under maintenance, scrapped, or suspended from monitoring, and providing abnormal movement records and offline duration statistics queries; pushing announcement documents to subordinate enterprises or initiating safety inspection tasks, and requiring enterprises to submit reading receipts or inspection responses; generating statistical reports on daily, weekly, monthly, and yearly cycles, and supporting scheduled automatic or instant push to designated email addresses.

Techniques described herein can efficiently detect network endpoints that are vulnerable to individual security threats. New security threats are constantly emerging. Identifying endpoints that are vulnerable to a security threat enables proactive protection of the vulnerable endpoints. Furthermore, detecting endpoints that are vulnerable to a security threat enables tailored protection operations that are limited to protecting vulnerable endpoints without necessarily also expending resources to protect invulnerable endpoints. Historic vulnerability data is used to group endpoints into cohorts that share similar histories of security infections and compromises. When an active security compromise is discovered at an affected endpoint, cohort protection operations can be applied to protect endpoints in the same cohort as the affected endpoint.

This invention discloses an escalator system based on new energy electric car power drive and control technology, comprising a sensing layer, a decision-making layer, a drive layer, an energy layer, and an execution layer. The sensing layer collects real-time data on the escalator's operating status, passenger flow information, and environmental parameters through a fault acquisition board, providing accurate and comprehensive data support for the decision-making layer. The decision-making layer receives various data collected by the sensing layer, executes control strategy calculations, and outputs precise control commands to the drive layer. The drive layer achieves efficient power output and high-precision control of the execution layer through control circuits. The energy layer constructs an efficient energy supply and recovery system for the escalator through an energy storage unit. The execution layer is an electric motor power unit responsible for receiving power output from the drive layer and achieving smooth operation of the steps. This invention achieves high efficiency, energy saving, stable operation, intelligent self-adaptation, and active safety protection for the escalator, while reducing equipment wear and maintenance costs and improving equipment reliability and scenario adaptability.

The utility model discloses a kind of gas active safety defense devices, it is related to gas safety equipment technical field, including shell, one side in the shell is equipped with air inlet pipe, another side in the shell is equipped with air outlet pipe, one end of the air inlet pipe and the air outlet pipe respectively with gas pipeline air inlet pipe and gas pipeline air outlet pipe intercommunication after penetrating out the shell, another end of the air inlet pipe and the air outlet pipe is communicated with gas meter after penetrating out the shell;Valve is installed on the air inlet pipe, valve front pressure sensor and valve rear pressure sensor are respectively installed on the air inlet pipe located the two sides of valve before and after;Flow sensor is installed on the air outlet pipe.The utility model gas active safety defense device can detect the data of gas pipeline in real time, can determine that gas pipeline under pressure, overpressure, gas over flow, leakage, earthquake and other abnormalities in time, and actively cut off gas pipeline, greatly improve the security of gas use.

A mode switching circuit, control method, device, and vehicle are disclosed, relating to the field of energy-saving technology, to improve the safety of the mode switching process. The mode switching circuit includes a control device, a first chip, and a second chip. The first chip implements a first safety function and a second safety function, and the second chip implements a third function, which includes the second safety function and / or a non-safety function. The control device supports the first and third safety functions in a first mode, and supports both the first and second safety functions when switching from the first mode to the second mode. By pre-deploying the second safety function in the first chip, and directly activating the second safety function in the first chip after the second mode is triggered, all active safety functions can be implemented in conjunction with the first safety function in the first chip. Thus, even during mode switching, the device can maintain active safety functions, improving the safety of the mode switching process.

The application relates to the technical field of battery regulation, and discloses a battery SOC real-time regulation method and device based on active safety protection of abnormalities, which comprises the following steps: acquiring real-time parameters of a target battery operation system, analyzing SOC state characteristics and constructing a battery protection boundary, monitoring a voltage drift amount, determining key boundary nodes and risk coefficients, analyzing charge and discharge response characteristics in sequence, fitting a charging curve, identifying an abnormal section, calculating a charge deviation rate, generating an energy scheduling sequence through attenuation compensation, analyzing an energy attenuation gradient, generating an equalization regulation instruction input into a BMS, and actively optimizing and regulating the target battery. The application can improve the service life of the battery.

The application discloses an open-pit mine unmanned vehicle end system architecture, a control method and equipment. The system architecture comprises an application system layer, a first module layer and a second module layer; the first module layer is located below the application system layer and comprises a plurality of independent function nodes, the independent function nodes comprising a positioning module, a perception module, a planning module, a control module, a state detection module, a remote driving active safety module and a chassis arbitration module; the second module layer is located inside the first module layer, and the second module layer comprises a plurality of second function modules, and each second function module corresponds to an independent function node; the independent function nodes are connected through a topic mechanism and a service mechanism of ROS2 for data interaction, the topic mechanism is used for publishing and subscribing real-time data flow, and the service mechanism is used for synchronous request and response of data. The system architecture can promote efficient cooperation between the function modules, strengthen the safety guarantee of the whole vehicle operation, and significantly improve the adaptability of the system to complex mine environments.

The application discloses an AI native intelligent interaction terminal with active sensing and emergency response capability, and belongs to the technical field of artificial intelligence terminals and man-machine interaction. The terminal integrates a multi-modal interaction module, a local AI inference engine capable of offline voice recognition, negotiation strategy generation and multi-language real-time translation, and an end-cloud collaborative scheduling unit. The terminal adopts an independent transfer box form with integrated charging function or an integrated terminal form with integrated charging bin, and can provide charging and power supply functions for matched earphones, glasses and other peripherals. The core feature of the terminal is the built-in motion state sensor and environmental sound recognition model, which can actively sense user falls, impacts or dangerous acoustic events, and automatically trigger an emergency response program. The terminal also supports a covert real-time word prompting function based on voiceprint recognition and cognitive state detection, provides long-term personalized services through a localized user cognitive model, and supports seamless task relay with a local AI host. The application deeply integrates intelligent interaction, active safety guardianship and privacy protection, and can be widely applied to various independent AI interaction scenes.

This invention discloses an intelligent alarm method, device, and computer-readable storage medium. The method includes: acquiring the current interaction data of a target user and acquiring historical context data associated with the current interaction data; fusing the current interaction data and historical context data to generate a semantic sequence to be analyzed; performing feature mining on the semantic sequence to extract implicit emotional features and risk intent information corresponding to the target user; acquiring preset alarm triggering conditions; matching and judging the implicit emotional features and risk intent information with the alarm triggering conditions; and generating an alarm triggering command if the alarm triggering conditions are met; and responding to the alarm triggering command by calling an associated execution component to perform the corresponding alarm operation. This invention eliminates the dependence on explicit distress commands, significantly reduces the false negative rate in implicit risk scenarios, and achieves highly accurate, loosely coupled, and highly scalable proactive safety monitoring.

The application relates to the field of smart home control, and provides a non-sensing interaction control method and system based on multi-sensor fusion, which comprises the following steps: acquiring inertial sensing data and electroencephalogram signal data; determining an effective direction intention and generating a direction control instruction based on the inertial sensing data through direction keeping judgment; determining a concentration state and generating a permission control signal for limiting movement based on the electroencephalogram signal data; recognizing at least two kinds of trigger mechanism emergency stop intentions and generating an emergency stop signal based on the electroencephalogram signal data; arbitrating the direction control instruction, the permission control signal and the emergency stop signal according to a priority rule, and outputting a final control instruction, wherein the priority of the emergency stop signal is the highest, and the priority of the permission control signal is higher than that of the direction control instruction. The application aims to solve the problems of high false trigger rate of existing auxiliary equipment, lack of active safety guarantee and unreliable emergency stop. Through multi-sensor fusion and multi-level priority arbitration, the application realizes high safety, anti-interference and non-sensing interaction control.

The application belongs to the technical field of unmanned vehicle attitude fault tolerance, mechanical arm dynamic obstacle avoidance and automatic driving limit regression, and particularly relates to a robust active safety control method, device and medium for a nonlinear system, which can solve the problems of infeasible initial state and non-smooth mutation of constraint boundary faced by a high-order nonlinear system, and proposes a robust active safety control method. The method aims to solve the control singularity and the shaking problem caused by constraint mutation when the initial value exceeds the limit in the prior art. By constructing an autonomous recovery mechanism based on a time-varying virtual parameter, the singularity is eliminated by using dynamic buffering, the system is guided to smoothly converge to a safe envelope from a violation area, a differentiable constraint smoothing transition mechanism is introduced to convert a step constraint into a continuous signal, and the actuator shaking is effectively inhibited, and a recursive feasibility framework of cascaded dynamics is established to prevent the divergence of internal states.

This invention discloses an active safety protection and control system for a test chamber, relating to the field of protection and control technology. It includes a multi-source data acquisition module, a correlation feature analysis module, a trend prediction module, a safety risk assessment module, and an active protection module. The correlation feature analysis module extracts primary and secondary correlation data from battery test data, quantifies the degree of correlation between them, and obtains the correlation degree between the primary and secondary correlation data. This allows for the quantification of the correlation strength between the core temperature and internal resistance of the battery cell, enabling in-depth analysis of temperature correlation data, effectively improving the accuracy of risk identification and reducing the probability of false alarms and missed alarms. Simultaneously, by combining the correlation degree with the current temperature deviation to correct the temperature prediction results, it achieves an adaptive effect of automatically increasing the correction magnitude at high temperatures and automatically reducing the false alarm rate at low temperatures, improving the accuracy of thermal runaway prediction, increasing response time for active protection, and ensuring the effectiveness of the test chamber's safety protection capabilities.

This invention belongs to the field of vehicle braking control and autonomous driving control technology, and relates to a control method and device for a full-time active safety automatic emergency braking system. The method includes: collecting environmental perception, vehicle operating status, takeover status, boundary constraints, and FAS-AEB system health data, performing time alignment and validity checks; calculating risk fusion values ​​using a unified risk fusion model and mapping them to risk levels; generating graded safety control commands based on risk levels, and generating control switching commands based on risk fusion values; periodically sending safety status identifiers through an independent safety link; continuously monitoring anomalies, triggering graded failure protection based on anomaly duration, and restoring and re-looping in reverse order after anomaly resolution. This invention achieves continuous online active safety throughout the entire process of autonomous driving, local takeover, and remote takeover, reducing the risk of collisions during takeover, operational interruptions caused by single emergency stops, and the insufficient availability of single-level failure protection.

Embodiments of the present application disclose a terminal security monitoring and early warning method and device based on 5G Internet of Things, equipment and medium. The method belongs to the technical field of Internet of Things, which comprises: if it is detected that a to-be-tested terminal has not accessed a 5G network and meets a security monitoring condition, then based on a configured scanning strategy, active security monitoring is performed on the to-be-tested terminal to obtain a non-access monitoring result; if it is detected that the to-be-tested terminal has accessed the 5G network and received service data collected and sent by a 5G Internet of Things data collection device, then through a harmful program propagation monitoring method and a network attack monitoring method, passive monitoring is performed on the service data to obtain an access monitoring result; and according to the non-access monitoring result and the access monitoring result, the security of the to-be-tested terminal is warned. Through the combination of active monitoring and passive monitoring, the embodiments of the present application can comprehensively identify and warn the security of Internet of Things terminals, discover the self-vulnerability of the Internet of Things terminals in time, and improve the security and stability of the Internet of Things terminals.

This application discloses a remote security isolation method based on digital fingerprinting and vehicle behavior anomaly detection. This method involves periodically generating and uploading "vehicle behavior digital fingerprints" containing features such as acceleration and steering angle at the vehicle end; using a dynamic benchmark model built in the cloud based on real-time learning of a large number of normal vehicle fingerprints, and employing Mahalanobis distance to accurately detect abnormal vehicles; for suspected vehicles, multi-source collaborative verification is initiated, combining surrounding vehicle perception and controller security self-checks to cross-confirm the authenticity of the anomaly; finally, a graded remote isolation strategy is executed according to the anomaly level. This application transforms passive response into active defense, achieving high-precision characterization of driving behavior through "digital fingerprinting," solving the problem of high false alarm rates with fixed thresholds using a "dynamic benchmark model," ensuring the reliability of anomaly judgment through "multi-source collaborative verification," and achieving progressive security intervention through "graded isolation," significantly improving the active safety protection capabilities of intelligent connected vehicles.

This invention belongs to the field of energy and power engineering control technology, specifically relating to a peak-shaving control system for low-pressure cylinder low-output operation. This system uses a distributed control system as a platform and, without adding new hardware, achieves stable control of a 350 MW supercritical coal-fired unit under 20% rated load and below operating conditions through software logic reconfiguration. It includes: a refined steam flow control module, a low-output safety monitoring and closed-loop regulation module, a seamless operation mode switching control module, and a cold-end system collaborative optimization control module. Through software logic reconfiguration, this invention not only solves the problems of steam flow control instability, safety logic conflicts, and lack of cold-end coordination in 350 MW supercritical coal-fired units under deep peak-shaving conditions at 20% rated load and below, but also achieves high-precision micro-flow regulation, active safety protection, and stable operation under all operating conditions, significantly improving the unit's deep peak-shaving capability and operating economy.

This invention discloses a smart wearable device for sanitation emergency operations, comprising a shell, a fixing mechanism, a sensing and positioning module, and a controller. The shell integrates a biosensing window, a check-in button, and an active safety warning module. The controller is used to recognize check-in signals and switch operation modes; when responding to emergency tasks, it calculates the thermal pressure load index based on personnel age, physiological characteristics, and environmental microclimate, and determines the matching degree between personnel and tasks based on spatial distance; after successful matching, it automatically broadcasts the tool carrying list and drives the warning module to emit corresponding flashing signals; during operation, it compares the action posture with the standard operation model in real time, identifies valid operation actions, and automatically marks progress. This invention realizes scientific scheduling, material linkage reminders, active safety protection, and automatic attendance acceptance for sanitation emergency operations.

This invention relates to the field of building construction technology and discloses a hoisting construction process with fall arrest locking for prefabricated buildings, comprising the following steps: S1, pre-hoisting preparation and intelligent verification; S2, component hooking and status self-check; S3, lifting and full-process active fall arrest monitoring; S4, judgment and execution of multi-level fall arrest locking mechanism; S5, precise positioning and intelligent assisted docking; S6, safe unlocking and installation confirmation; S7, data recording and process iteration. This invention, by introducing an intelligent decision and control unit, a multi-sensor fusion perception system, and a multi-level fall arrest locking mechanism, achieves intelligent monitoring and active safety protection throughout the entire hoisting process. It significantly improves hoisting safety by implementing a layered response from risk warning to emergency locking through three-level fall arrest locking, especially in the event of electrical control failure, where it can still quickly lock through purely mechanical means, effectively preventing fall accidents.

This invention discloses a replaceable reaction fixture for thermal runaway (CTRR), belonging to the field of fixture technology. The CTRR replaceable reaction fixture includes an H-shaped base with buffer components mounted on both sides to absorb vibrations caused by thermal expansion and volume changes during thermal runaway. A top plate is fixedly connected to the top of the buffer components, and a fixing frame is fixedly connected to one side of the top surface of the top plate. An active safety linkage self-locking component is slidably connected through the fixing frame to convert destructive pressure into enhanced safety force. This invention, by employing buffer components and an active safety linkage self-locking component, converts the pressure generated inside the battery into enhanced locking force, forming negative feedback and eliminating the greatest safety hazard of battery detachment under high pressure. Furthermore, it does not rely on external power or signals and can automatically operate even in the event of system failure, providing the highest level of safety redundancy.

The present application belongs to the field of medical rehabilitation equipment and intelligent safety protection technology, and discloses a rehabilitation treadmill active safety protection system based on multi-modal brain-computer visual perception, which comprises: collecting original multi-modal data, performing hierarchical quality marking, and generating an original multi-modal data set; real-time detection of twin physiological event anchors, dynamic time alignment to generate a multi-modal synchronous data set; extraction of multi-dimensional safety features, generation of a weighted five-dimensional safety state vector through environmental factor weight modulation, generation of a non-constrained intention suggestion package through synchronous intention suggestion generation; intention legality and safety verification, generation of legal execution instructions, and then multi-state hierarchical protection decision, formation of standardized execution control instructions; execution of hierarchical protection actions, phased closed-loop effect verification and abnormal execution safety upgrade, acquisition of full-process operation data and intervention events, reverse optimization update combined with therapist feedback, and closed-loop iteration.

The application discloses a kind of based on multi-source data fusion model's public transport intelligent scheduling optimization method and system, it is related to intelligent traffic and public transport operation management technical field, it is applicable to intelligent public transport use scene, including: terminal acquisition continuous sampling operation data and active safety alarm, form local data stream;According to the division of public transport event semantics, generate versioned evidence, report fragment abstract.The terminal receives and analyzes the scheduling instruction generated by the cloud platform based on the abstract, the instruction carries the consistency of evidence, observation freeze control, candidate action and intensity range and effective window, two-stage instruction, instruction sequence number and evidence version binding field;Prepared state is low disturbance and can be revoked, submission state is strong action and executes after meeting the condition.The terminal is processed according to sequence number and version number idempotent and executes in stages.The present application effectively reduces repeated issue, revocation back jump and gate flip, improves execution consistency and replayability.

This invention provides a vehicle active safety warning system and method based on multimodal perception. It belongs to the field of vehicle safety warning technology. The system is built based on a vehicle-cloud collaborative architecture and includes: an on-board edge computing box (1) including: a multimodal perception data module (11), a fusion and risk identification module (12), a hierarchical warning module (13), and a data storage and synchronization module (14); a cloud operation platform (2) including: a rule configuration module (21), a trajectory anomaly marking and analysis module (22), an energy consumption prediction and range management module (23), a user interaction and display module (24), and a cloud storage module (25); the on-board edge computing box (1) communicates with the cloud operation platform (2) through a wireless communication network. This invention constructs a comprehensive, adaptive, and integrated active safety protection system through multi-source data fusion perception, hierarchical intelligent warning, and cross-domain data analysis.

This application discloses a rule-guided deep reinforcement learning-based autonomous driving decision-making method, device, equipment, and storage medium, relating to the field of autonomous driving technology. The method includes: based on determining the target mode according to rules, activating the deep reinforcement learning strategy only when entering an interactive game mode; simultaneously constructing state space information and the current state confidence distribution based on vehicle perception information; and then using the state space information and the state confidence distribution together as input to the policy function model to generate the target policy action. This ensures that the policy output is not only affected by the environmental state but also constrained by the system's uncertainty in state estimation. Thus, when the state confidence distribution is dispersed, the aggressiveness of the policy is actively adjusted. This achieves the goal of ensuring traffic efficiency while automatically enhancing safety under uncertain perception conditions through a state confidence-guided active safety mechanism, thereby improving the overall reliability and scenario adaptability of the system.

The application provides a building comprehensive management and control system and method based on artificial intelligence and multi-source data fusion, all subsystem data are fused and processed, cross-field and cross-system joint analysis and decision are realized, and the information island problem is solved.The application combines structure safety and environmental safety data, uses AI to perform risk assessment and prediction, changes passive alarm to active safety prevention and control, and significantly improves the building essential safety level.The application realizes on-demand supply and dynamic optimization based on the AI energy consumption model of multi-dimensional data, and achieves deep energy saving and consumption reduction.The application automatically creates a safe, healthy and comfortable building internal environment by sensing personnel activities and learning preferences, and meets the personalized human settlement environment demand.The application links with the smart city through a standard interface, makes the building an intelligent node responding to the city operation and contributing to the city data, and improves the fine level and overall efficiency of city management.

This invention relates to an intelligent exoskeleton system integrating environmental perception and physiological indicator monitoring, belonging to the field of intelligent exoskeleton protection. The solution first synchronizes multi-source sensor data in the time domain, and then inverts the theoretically expected physiological values ​​corresponding to the current work intensity based on joint movement speed and interaction torque. By calculating the physiological condition residual between the measured physiological data and the theoretical expected values, the system can dynamically isolate physiological indicator fluctuations caused by the movement itself, thereby extracting the true risk characteristics caused only by environmental risks or physical abnormalities. Based on this, it combines environmental parameters to perform correlation risk discrimination, accurately identifying specific risk types such as environmental risks or abnormal physiological indicators. Finally, the system automatically matches differentiated target impedance parameters and tactile cue signals according to the identification results, achieving active safety control and precise risk warning of the exoskeleton without interfering with high-intensity normal work.

The present application relates to the technical field of computing power equipment thermal management, and provides a computing power cabinet coupling device with active thermal management and safety interlocking function and a control method, which comprises a current sampling unit, a processing unit, a flow regulating unit, a controllable switch unit and a position detection unit; the current sampling unit, the flow regulating unit, the controllable switch unit and the position detection unit are connected with the processing unit respectively; the processing unit is configured to: output a feedforward control signal to the flow regulating unit based on the current transient characteristics obtained by the current sampling unit; and control the controllable switch unit to perform a disconnection action in response to an abnormal insertion state detected by the position detection unit. The present application realizes feedforward regulation of thermal management through current transient characteristics, solves the problem of thermal inertia lag, and realizes millisecond-level active safety protection through local logic interlocking.