140 results about "Safety status" patented technology

The invention relates to the technical field of storage visual management, in particular to a chemical storage digital visual management system and method. The method comprises the following steps: deploying environment monitoring equipment for a storage area, constructing a multi-parameter fusion intelligent sensing network, and collecting temperature and humidity, gas concentration, pressure and vibration parameters in real time to obtain real-time environment data; based on the real-time environment data, evaluating a storage safety state, identifying an abnormal behavior and evaluating an environment risk to obtain a safety risk evaluation result; and deploying a distributed emergency response network based on a security risk assessment result, dividing risk levels and formulating a multi-level response strategy to obtain an emergency response execution scheme. According to the invention, a chemical warehouse management closed-loop system integrating multi-dimensional perception, intelligent analysis, dynamic control and three-dimensional visualization is constructed, so that accurate and safe management and control of a whole process, a whole space and a whole state are realized.

The invention discloses a power equipment safety state assessment method and system, equipment and a readable storage medium, and relates to the technical field of power equipment assessment, and the method comprises the steps: collecting a power equipment communication interaction data flow, carrying out the time synchronization and outlier elimination, and constructing a multi-modal data matrix; evaluating the exception probability score and an exception probability threshold to obtain an exception state flag, and generating a security event data packet in combination with the preliminary exception type and the power equipment communication interaction data stream; adopting a LiNGAM causal discovery algorithm to perform non-Gaussian test and time sequence lag analysis on an abnormal event time sequence in the security event data packet, and constructing a directed acyclic causal graph; dynamically adjusting the causal intensity of the directed acyclic causal graph according to the real-time equipment load rate and the communication quality index, and outputting a dynamic causal graph; according to the method, the accuracy and adaptability of abnormal propagation analysis are improved, and finally the real-time performance and credibility of safety assessment of the power equipment are enhanced.

The invention provides an intelligent monitoring method and system for the full life cycle safety state of an oil and gas pipeline, and relates to the technical field of oil and gas pipelines, and the method comprises the steps: collecting the operation state data of the oil and gas pipeline, building a digital twin model, constructing a multi-dimensional feature vector, and carrying out the feature fusion; and constructing a fault evolution prediction model based on the fusion feature vector in combination with a graph neural network, calculating a residual life prediction value, continuously optimizing the safety state evaluation accuracy through online iterative training, and generating a safety state evaluation report and a maintenance decision suggestion. Intelligent monitoring and prediction of the safety state of the oil and gas pipeline are achieved, and the reliability of safe operation of the pipeline is improved.

The invention discloses a multi-parameter dynamic intelligent judgment method for the safety state of an operator, and belongs to the technical field of operation safety monitoring. According to the method, by integrating an intelligent wearable device, a sensor and an eye movement tracking device, physiological parameters (such as heart rate, blood pressure, oxyhemoglobin saturation, electroencephalogram signals and the like), behavior parameters (such as action frequency, posture change and the like), psychological parameters (such as pressure level, fatigue degree and the like) and environmental parameters (such as temperature, humidity, noise and the like) of an operator are collected in real time; and a multi-dimensional monitoring system is constructed. Collected data is subjected to cleaning, standardization and feature extraction and then is input into a safety state judgment model based on a bidirectional long short-term memory network (BiLSTM), the real-time safety state of an operator is dynamically analyzed, and low-risk, medium-risk and high-risk three-level early warning results are output.

The invention discloses a construction method of a bridge member safety knowledge graph based on multi-category monitoring information and hidden danger information, and relates to the technical field of bridge structure safety monitoring, and the method comprises the steps: determining a structure reliability index as a representation index of bridge structure safety, building a two-dimensional collaborative analysis system based on monitoring items and hidden danger items, and obtaining a bridge structure safety knowledge graph; building a multi-source data fusion structure reliability analysis framework by taking a structure reliability index as a final analysis purpose; based on a structure reliability analysis framework, a four-layer ontology model comprising a structure physical layer, a damage monitoring layer, a reliability assessment layer and an auxiliary decision-making layer is designed through Protege software, a knowledge graph is formed, a knowledge representation path of bridge structure safety assessment decision is established, and timely dynamic update and reliable maintenance decision of a bridge structure safety state are realized. According to the method, the knowledge graph is constructed through the four-layer ontology model with the causal conduction mechanism, and a knowledge representation path capable of systematically analyzing the safety of the bridge structure is formed.

The invention discloses a terminal active emergency method and device, terminal equipment and a medium, and relates to the technical field of communication, and the method comprises the steps: obtaining safety condition information, carrying out the processing of the safety condition information based on a preset emergency triggering rule, and judging whether the terminal equipment needs to be switched to an emergency mode or not; the safety condition information is used for evaluating whether an emergency event exists or not; after the terminal equipment enters the emergency mode, automatically executing one or more emergency operations according to a preset emergency response rule; wherein the emergency trigger rule and the emergency response rule are dynamically updated according to local learning or remote pushing. By adopting the method, the terminal equipment can have an automatic response capability under an emergency situation, so that the response efficiency and the user safety guarantee capability under emergency scenes such as disasters and the like are improved.

The invention discloses a house safety monitoring and early warning system based on a wireless sensor, which relates to the technical field of house safety monitoring and is characterized in that a plurality of wireless sensor data, door and window state data Sw, smoke concentration Sm, environment temperature St, heat source change amplitude Sr and environment noise intensity Sn are integrated, and a data fusion and analysis technology is utilized to monitor the safety of a house. Various risk factors can be effectively and comprehensively considered, and false alarm and missing alarm caused by a single sensor are reduced. Through comprehensive analysis of multi-dimensional data, the accuracy of house safety monitoring can be improved, it is ensured that the system can still make correct judgment in a complex environment, and the reliability of the early warning system is improved. When the system detects an abnormal event, the risk index fiRfu can be automatically corrected, and it is ensured that the alarm level is matched with the real-time safety condition. Security threats in different situations can be effectively handled, the situation of excessive alarm or alarm missing is avoided, and the high efficiency and usability of the alarm system are ensured.

The invention provides a safety state monitoring and early warning method and system for elderly people living alone, and relates to the technical field of smart pension, the system comprises a sensing layer, a transmission layer, a processing layer and an application layer, during implementation, a sensing unit is firstly installed, then relay equipment is installed, then adaptability training of the system is carried out, and finally alarm information is processed. Through dual-mode cooperation of environment perception and attitude monitoring, accurate analysis of home behaviors of the elderly living alone is realized, the probability of false alarm is greatly reduced, deep learning is combined to drive closed-loop optimization, through three-stage threshold iteration, the tumble recognition rate is greatly improved, the false alarm rate is greatly reduced, linkage response is triggered in an emergency scene, and the accuracy of tumble recognition is improved. The community disposal efficiency is greatly improved, the beacons are integrated with intelligent insoles / magnetic chest cards and other non-inductive wearing designs, and the house type self-adaptive base station deployment is combined, so that the disturbance of grid members to the old is reduced, and meanwhile, the monitoring efficiency and accuracy are improved.

The invention relates to the technical field, and particularly discloses a telegraph pole construction limiting alarm system based on data analysis, and the system comprises a hardware module, an edge calculation module, a safety alarm module, a cloud information module, and a visualization module. Through integration of the remote short message alarm unit, real-time feedback of the safety state of a construction site is achieved, it is ensured that managers can rapidly obtain key information and take measures in time, the risk of safety accidents is effectively reduced, through construction of the cloud information module, efficient storage and management of a large amount of construction data are achieved, and the safety of the construction site is improved. And a safe distance algorithm is continuously optimized through deep analysis of historical data by a model optimization unit, so that the system can adapt to various complex construction environments and weather conditions, and the practicability and accuracy of the system are improved.

The invention relates to the technical field of charging pile management, in particular to a charging pile safety monitoring method and system based on diversified analysis, and the system comprises a charging pile safety monitoring center, a potential state division unit, a safety monitoring analysis unit, a multi-dimensional evaluation unit, a persistence evaluation unit and a state early warning unit. According to the method, analysis is preliminarily carried out from the state angle of the charging gun head of the charging pile so as to carry out early warning management on the charging gun head which is not completely installed, so that the safety of the charging pile is improved, analysis is carried out from the fire early warning angle of the charging pile, and through the whole process design of image recognition-dynamic verification-multi-source cross verification, the safety of the charging pile is improved. Real-time and reliable technical guarantee is provided for safe operation of the charging pile, multi-dimensional health comprehensive evaluation analysis is carried out in an information progressive mode, comprehensive, objective and quantitative evaluation of the safe state of the charging pile is achieved, and powerful support is provided for safe operation and intelligent management of the charging pile.

The invention relates to the technical field of safety evaluation of isolated power supply systems, and discloses a safety evaluation and control method, system and device for an isolated power supply system and a medium. The method comprises the following steps: constructing an N-0 security domain model and an N-1 security domain model of an isolated power supply system based on feeder capacity constraint, main transformer capacity constraint and frequency constraint; solving based on the N-0 security domain model and the N-1 security domain model to obtain a security boundary; acquiring a safety distance between the operation point and the safety boundary; judging whether the operating point is located in a safety domain of the isolated power supply system according to the safety distance; and if not, adopting prevention and control measures to adjust the operation point until the operation point returns to the safety domain of the isolated power supply system. By calculating the safety distance in real time, a dispatcher can monitor the safety state and the safety degree of the operation point, timely take prevention and control measures and adjust the unsafe operation point to the safety state, so that the safety operation level of the isolated power supply system is improved.

The invention provides a ship lock metal structure safety detection and evaluation standardization system and method, and relates to the technical field of ship lock engineering safety detection. A distributed intelligent sensing module is obtained, and multi-dimensional dynamic parameters of a ship lock metal structure are collected through the distributed intelligent sensing module; the computer sends a starting instruction to the distributed intelligent sensing module through a preset sensor control program, receives and stores dynamic parameters returned by each sensor in real time, and establishes a timestamp index. Compared with the prior art, the method has the following beneficial effects: by integrating multi-dimensional dynamic parameters such as vibration acceleration, temperature gradient, corrosion current density and the like, the state change of the ship lock metal structure under dynamic load and severe environment can be comprehensively captured, and the sampling frequency is automatically adjusted in combination with a trigger type sampling mechanism; therefore, the transient response under the sudden load is effectively captured, early damage missed judgment caused by only monitoring static parameters is avoided, and the actual safety condition of the structure is reflected more truly.

The invention relates to the technical field of elevators, in particular to an elevator construction management system and method.The elevator construction management system comprises a data acquisition module used for acquiring operation parameters and environment parameters in the elevator construction process in real time; the data twinning module is used for updating an elevator construction twinning model according to the operation parameters and the environment parameters; the data processing module is used for processing the current elevator construction data reflected by the elevator construction twinning model and generating an optimized construction scheme according to a processing result; and the safety monitoring module is used for generating a construction safety state according to the operation parameters, the environment parameters and the current elevator construction data and generating construction early warning information based on the construction safety state, so that early discovery and active intervention of safety risks are realized. And finally, the core problems of potential safety hazard identification lagging and low transportation efficiency in a traditional mode are solved.

The invention discloses an intelligent three-dimensional warehouse monitoring system, and relates to the technical field of intelligent storage automation, and the system comprises an early warning response module which is used for generating early warning signals of different levels according to a three-dimensional warehouse safety index, and triggering a corresponding control instruction; the control execution module is used for receiving the control instruction sent by the early warning response module and adjusting operation parameters of the environment adjusting equipment and the logistics equipment in the stereoscopic warehouse. According to the method, the specific calculation formulas of the environment risk coefficient, the equipment health coefficient and the inventory abnormity coefficient are designed, the stereoscopic warehouse safety evaluation model is constructed based on the three coefficients, the abstract stereoscopic warehouse safety state is converted into a quantifiable and comparable numerical value, a traditional subjective judgment mode is replaced, objective and accurate evaluation of the stereoscopic warehouse safety level is achieved, and the stereoscopic warehouse safety evaluation efficiency is improved. And potential safety hazards can be quickly and accurately identified.

This invention discloses an elevator bearing safety early warning method, device, and medium based on the Internet of Things (IoT), relating to the field of control testing and monitoring technology. The method includes: acquiring raw analog signals and preprocessing them to generate synchronous data frames; decomposing fault impact sequences from the synchronous data frames and obtaining a bearing safety status index through weighted D-S evidence, while simultaneously matching a pre-diagnostic control logic library to generate a pre-diagnostic confidence identifier; based on the pre-diagnostic confidence identifier and the bearing safety status index, obtaining a dynamic health baseline through sliding retrieval and elastic tracking compensation, and dynamically extrapolating the control envelope through a stochastic control boundary evolution algorithm to generate a dynamic safety threshold; comparing the bearing safety status index with the dynamic safety threshold, evaluating link quality, and selecting a candidate route set; and obtaining the optimal route through a shortest delay tree to form an encrypted alarm stream. This invention achieves accurate generation of the dynamic safety threshold.

The utility model relates to the technical field of limited space safety protection, and discloses a limited space internet-of-things monitoring device for safety protection, which comprises an industrial control converged communication terminal, a monitoring equipment terminal and gas detection equipment, the industrial control converged communication terminal comprises an external machine and an internal machine, and the external machine is wirelessly connected with the internal machine; the internal machine is connected with the monitoring equipment terminal gas detection equipment; and the monitoring equipment terminal is worn on an operator. According to the invention, external personnel can detect the safety condition of operating personnel in real time.

This invention belongs to the field of nuclear power plant technology and discloses a method and system for assessing the safety status of the pressure boundary of a reactor primary circuit. The method includes: collecting data based on characteristic variables of a key component of the pressure boundary; preprocessing the characteristic variable data collected from the key component; inputting the processed data into the safety status assessment model corresponding to the component; performing calculations through the model to obtain the safety status assessment result for the component; associating the assessment result with the component and its identifier; quantifying the assessment result; displaying the quantified result in the form of a planar coordinate axis; associating the key component with its basic information, which can be viewed through the basic information menu on the visualization display page, such as production date, manufacturer, and rated parameters; and managing the data of all components through a data management module and a database.

The invention discloses a multi-level information safety protection system, method and device for an electric vehicle and a medium, and the method comprises the steps: determining the operation state, environment parameters and bus messages of the vehicle, and analyzing the operation state, the environment parameters and the bus messages through a preset neural network, so as to obtain a trust score; and determining a safety state of the vehicle according to the trust score, and determining a corresponding response mechanism according to the safety state so as to perform safety protection on the vehicle according to the response mechanism. According to the method, the vehicle running state, the environment parameters and the bus message are collected in real time, and deep analysis is performed by using the preset neural network, so that the trust score can be accurately generated. The scoring mechanism effectively quantifies the safety state of the vehicle, and is convenient to quickly judge and take corresponding response measures. According to the safety state and the response mechanism determined according to the scoring result, safety protection can be performed in a targeted manner, the protection accuracy and efficiency are improved, and the vehicle information safety is ensured.

This invention discloses an intelligent safety belt system. The terminal device includes an online detection module; a server is electrically connected to the online detection module; the server includes a high-altitude work environment detection module, a high-altitude work status detection module, a safety status detection module, a positioning module, and a two-way voice communication module; the two ends of the safety belt body are opened and closed via buckle assemblies, and a second electrical box is used to detect the opening and closing status of the buckle assemblies; the second electrical box is electrically connected to the server; several hook devices include hook assemblies and a first electrical box, the hook assemblies are connected to the safety belt body, and the first electrical box is used to detect the opening and closing status of the hook bodies; the first electrical box is electrically connected to the server. This system enables monitoring of personnel working at heights.

The present application discloses a system and method for implementing battery protection processing, which is applied to the transportation of new energy vehicles in a maritime environment. The new energy vehicles include vehicle power batteries, including: a collection unit for collecting battery safety-related information of the vehicle power battery and transmitting the collected battery safety-related information to a vehicle supervision platform; a vehicle supervision platform for determining the temperature rise rate based on temperature information; determining safety level information based on whether the determined temperature rise rate and battery safety-related information are within a pre-set safety level threshold; determining corresponding processing instructions based on the determined safety level information, and sending the safety level information and processing instructions to a processing device; and a processing device for executing battery safety processing based on the received safety level information and processing instructions. The disclosed embodiment determines the safety status of the vehicle power battery through battery safety-related information, can promptly execute disaster relief processing, and improves the transportation safety and safety processing efficiency of the vehicle power battery.

This invention provides a vehicle door safety control method, comprising: receiving model parameters from a vehicle body domain controller to update a local model, and generating feature data characterizing the safety status of the corresponding vehicle door based on local multimodal sensor data; broadcasting the feature data and receiving feature data broadcast by other subordinate safety sub-controllers via a dedicated internal bus connecting all subordinate safety sub-controllers; performing collaborative reasoning based on its own feature data and all received feature data to determine the judgment result of the safety status of the vehicle door, and executing corresponding vehicle door safety control actions according to the judgment result. This invention solves the problems of insufficient accuracy and comprehensiveness in determining the safety status of vehicles door in the prior art, lack of coordination among vehicle door control units, lack of effective redundancy guarantee capability, and difficulty in meeting continuous reliability requirements.

The present application belongs to the technical field of steel structure platform monitoring, and specifically relates to a steel structure platform and an early warning system and method for safety monitoring of a floor. The present application can timely discover potential safety hazards by monitoring the safety status of the steel structure platform and the floor in real time, thereby effectively preventing and reducing accidents. By collecting and analyzing real-time data, combining evaluation functions and early warning mechanisms, the present application can accurately evaluate the safety status of the steel structure platform and the floor, and take corresponding early warning measures according to the evaluation results. In addition, by matching the early warning level and the monitoring frequency, the present application can also optimize the allocation of monitoring resources and improve the monitoring efficiency. That is, when the risk is low, the system can reduce the monitoring frequency to save resources; when the risk is high, the system can increase the monitoring frequency to ensure the safety of the steel structure platform and the floor.

This invention relates to the field of security control technology, and in particular to a method and system for optimizing security control strategies based on data timeliness. The method includes the following steps: S1, calculating the data timeliness of each experience in the experience pool, A i =t current -t i The process involves: S1) calculating the sampling probability of experience based on data timeliness, extracting a batch of experience from the experience pool based on the sampling probability, and using the extracted experience to train the Actor network and Critic network; S2) collecting the vehicle state at the current time and inputting the vehicle state into the trained Actor network to output the control action; S3) collecting the vehicle state after the vehicle control system executes the control action, and inputting the collected vehicle state and the control action into the trained Critic network to output the safety status assessment result; and S4) adjusting the trained Actor network based on the safety status assessment result. This invention utilizes a time-based sampling strategy to improve safety and stability in uncertain environments.

The control device of the present invention includes a plurality of control units (400, 420, 440, 460) interconnected via a communication path (200), each control unit (400, 420, 440, 460) including a switching processing unit (406, 426) that selects a control unit that causes the software of the control unit that has detected an abnormality to continue to operate based on the action requirements of the software that has detected an abnormality and the safety status and control status of control units other than the control unit that has detected an abnormality.

The invention discloses a distribution network grounding operation safety state intelligent early warning and measurement and control system and method. The system comprises an intelligent jointing clamp, an intelligent grounding pin and a visual monitoring platform. The intelligent jointing clamp is integrated with a pressure sensing module used for sensing the hooking state of the intelligent jointing clamp and a wire, a positioning module used for conducting grounding point space positioning, and a safety authentication module used for equipment identity authentication. The intelligent grounding pin is integrated with a posture sensing module used for monitoring the embedding posture of the grounding pin, a depth measuring module used for measuring the embedding depth of the intelligent grounding pin, and a vibration sensing module used for identifying the impact characteristic in the embedding process of the intelligent grounding pin. And the visual monitoring platform is used for receiving the multi-modal sensing data uploaded by the intelligent jointing clamp and the intelligent grounding pin, and performing diagnosis and early warning of the grounding operation state according to the multi-modal sensing data. According to the invention, by constructing an end-edge-cloud collaborative system architecture, the operation and maintenance security of the power system is improved.

The invention provides a bulk commodity storage supervision method, which comprises the following steps: S1, multi-dimensional data acquisition: configuring acquisition equipment according to bulk commodity types, and acquiring commodity quantity data, environment data, safety protection data and circulation information; s2, data preprocessing: denoising, calibrating and splicing the collected original data; s3, data calculation and analysis: calculating the actual weight or volume of the commodity based on the preprocessed data; s4, real-time monitoring and early warning are carried out, and commodity inventory, environment and safety states are displayed on a monitoring terminal; and S5, control and information management are executed, and the automatic control equipment is docked to execute the regulation and control instruction. Through laser radar three-dimensional modeling and density dynamic correction, the method is superior to traditional manual estimation, solves the problem of inconsistency between accounts and reality, prevents and controls quality risks in real time, collects environmental data in real time, can effectively avoid losses such as grain mildew and dangerous chemical leakage, realizes multi-sensor linkage monitoring and automatic control, and realizes early warning and rapid disposal of risks such as fire and theft.

This invention discloses a multi-source sensing fusion method for safety status assessment of geotechnical structures, belonging to the field of geotechnical engineering monitoring technology. This invention collects comprehensive data through a multi-source sensing network, preprocesses and aligns it spatiotemporally, then extracts four types of heterogeneous features using an improved PCA algorithm and performs fusion and dimensionality reduction to obtain a multimodal feature map. A hybrid assessment model combining a spatiotemporally adaptive graphical neural network (ST-AGNN) and multi-field coupled numerical simulation is constructed. Through parallel inference combined with a risk evolution trend prediction algorithm, a safety status index and risk evolution curve are output. The safety level is determined based on the safety status index, and a tiered early warning and response are triggered by combining an emergency response priority algorithm. The model is periodically trained and parameters are calibrated using actual anomaly or disaster data as labels, resulting in adaptive optimization of the assessment model. This invention balances monitoring accuracy, prediction reliability, and response timeliness, solving the problems of insufficient comprehensiveness and accuracy in geotechnical structure safety assessment, and has broad application value.

The invention relates to the technical field of operation safety, and discloses an early warning information pushing device based on a safety portrait, and the device comprises a first portrait module, an early warning module, a second portrait module, and an alarm module. According to the method, the safety portrait is generated by collecting the safety data, risk early warning and alarming are achieved, and the digital management level is improved; the initial portrait is generated by quantifying the security data, and fine management is realized; by planning an early warning project, pre-risk early warning is emphasized; a basis is provided for dynamic correction of the portrait by calculating difference parameters; by generating a dynamic correction portrait, the safety state is accurately mastered; the early warning value is dynamically adjusted according to the risk level, and the early warning pertinence and accuracy are improved; various kinds of information are integrated into the dynamically-corrected portrait, and early warning value adjustment is achieved through the risk evolution index; precise personal risk management and control are realized, management and control problems are solved, risk prevention and control perspectiveness, effectiveness and refinement are enhanced, enterprise safety production management capability is improved, and enterprise production safety is guaranteed.

The invention relates to a sampling station personnel safety state detection method and system. The method comprises the following steps: acquiring a sampling station area image; target detection is carried out on a sampling station area image to obtain the position of a person, the position of a safety helmet, the position of a human body key point, the position of a safety rope and the positions of hooks at the two ends of a safety belt in the sampling station area image, and the position of the safety helmet and the position of the human body key point are determined based on the position of the person. The human body key points comprise a first detection point at the top of the head and a plurality of second detection points at other parts of the body, and the plurality of second detection points form a directed closed graph; according to the position relation between the safety helmet and the first detection point, the position relation between the hook and the directed closed graph, and the position relation between the hook and the safety rope, the sampling station personnel safety state detection is completed; according to the method, the safety state detection of the personnel performing the sampling operation can be accurately realized.

A method for monitoring the safety status of coal mine shafts based on blockchain technology obtains analysis results of weak areas in the shaft wall; identifies weak areas on the shaft wall that may cause cracking; sets monitoring nodes at different monitoring layers and monitoring directions; sets up blockchain nodes, connects multiple monitoring nodes and blockchain nodes at different monitoring directions in the same monitoring layer, and forms a private chain for the monitoring layer; connects multiple blockchain nodes underground and the first block on the surface to establish a blockchain shaft wall monitoring system; activates smart contracts; analyzes the status of each blockchain node through blockchain accounting nodes and a blockchain monitoring cloud platform to obtain key status information; determines whether the key status information is within a safe range; and forms a shared cloud monitoring platform for multiple coal mine shafts on the blockchain monitoring cloud platform. This method can achieve real-time monitoring of shaft safety status based on blockchain technology, with relatively comprehensive monitoring content, shared by multiple people, and authentic and valid data.