204 results about "Safety status" patented technology

The invention discloses an intelligent monitoring and early warning system for the safety state of an electrical cabinet, and belongs to the technical field of electrical variable measurement, and the system comprises a data collection module which is used for obtaining multi-source sensing data of the electrical cabinet, and the multi-source sensing data comprises a current waveform parameter, an infrared temperature distribution parameter and a mechanical vibration spectrum parameter; the health feature evaluation module is used for generating a health state feature vector of the electrical cabinet by using the multi-source sensing data; the instruction generation module is used for outputting an early warning decision instruction according to a matching result of the health state feature vector and a preset fault propagation rule base; and the safety protection module is used for executing a safety protection action when the early warning decision instruction meets a preset execution condition. A multi-source sensing data fusion analysis technology is adopted to construct an electrothermal mechanical composite feature vector, a fault propagation rule base is coupled to realize cross-domain conduction path modeling, composite hidden dangers such as contact deterioration and the like can be accurately identified in a fault incubation period, and graded active safety protection measures are triggered.

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 road transportation government affair safety supervision and management method, and relates to the technical field of road transportation safety supervision data processing. The vehicle and road safety supervision and management method comprises the following steps: collecting passing driving dynamic information from any traffic observation device; the vehicle behavior monitoring device and the road surface state monitoring device are integrated, the vehicle driving behavior data and the road safety condition data are collected in real time, and the monitoring frequency is dynamically adjusted according to the space interval, the abnormal information and the historical data, so that the utilization efficiency of monitoring resources is improved, and the monitoring cost is reduced. The system collects historical data and real-time abnormal data of vehicle driving behaviors and road safety conditions, then a primary space and a secondary space are calculated through a calculation and analysis engine, corresponding correction coefficients are determined according to intervals and historical safety condition information, then the observation frequency of the monitoring device is adjusted, and the monitoring accuracy is improved. And resource allocation is optimized while the detection coverage rate of the system is ensured.

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 relates to the technical field of collaborative management, in particular to a thermal power plant construction collaborative management method and system based on a BIM technology, and the method comprises the following steps: setting a data input interface in a BIM model, collecting personnel information and equipment types required by thermal power plant construction, and counting position data and safety state information; initial resource configuration is calculated according to input personnel and equipment data, and an initial resource distribution diagram is generated; according to the method, thermal power plant construction management is coordinated through the BIM technology, dynamic data integration and instant messaging in the construction process are achieved, decision and resource allocation processes are optimized, the state of a construction site is allowed to be continuously monitored, personnel and equipment layout is adjusted in real time, and the capacity of coping with emergencies is greatly improved; the automatic safety monitoring and real-time alarm system enhances risk management, significantly reduces the possibility of safety accidents, not only improves the working efficiency, but also ensures the construction safety and quality control, and has a significant effect in improving the project management efficiency.

The invention provides a laboratory safety monitoring method and system based on multi-data fusion. The method comprises the steps that S1, a data acquisition module monitors and acquires environmental data in a laboratory in real time; environment data in a laboratory are preprocessed; performing weight distribution on the laboratory internal environment data and the manual alarm function triggering state, and introducing a comprehensive threat index; s2, calculating a comprehensive threat index according to the collected laboratory internal environment data, the manual alarm function trigger state and the weight; s3, judging a security threat level based on the comprehensive threat index; judging a security threat type based on the security threat level, the laboratory internal environment data and the manual alarm function triggering state; and S4, taking security countermeasures according to the security threat type. The comprehensive threat index can comprehensively reflect the safety condition in the laboratory; and safety countermeasures are taken for the safety threat type, so that the accuracy of safety condition identification and the pertinence and effectiveness of the countermeasures are improved, and personnel and property loss is avoided.

A sensor bar or other array of sensors are mounted to the bus beneath or adjacent to a doorway of the bus. Ultrasonic sensors are located within the sensor bar and detect the presence of foreign objects such as an entrapped passenger close to the doorway. A safety output is generated by the system when an unsafe condition is detected. Examples of safety outputs can include warning sounds, warning lights, automatic door opening, using the brake transmission shift interlock (BTSI) to prevent transmission shifting for vehicle movement, and other safety outputs.

The invention relates to the technical field of scenic spot guidance, and discloses an intelligent scenic spot intelligent safety guidance system comprising a data acquisition module which is provided with a sensor and a camera and is used for monitoring people flow, vehicle and weather information in real time and collecting personal information, position data, health data and the like of users; the data processing and analyzing module is used for cleaning and sorting the collected data and analyzing the data by using a statistical method and a machine learning algorithm; the personalized route recommendation module is used for recommending personalized sightseeing routes to the tourists based on the tourist information; and the safety management module monitors the safety condition of the scenic spot in real time through a camera and a sensor. According to the invention, a dynamic adjustment mechanism, a real-time feedback system and a group route recommendation model are introduced, it is ensured that the recommended route always meets the actual demand of the tourist, and the comprehensive and flexible personalized recommendation mechanism can respond to the change demand of the tourist in the touring process in time and provide more comfortable, safer and personalized touring service for the tourist.

A safety status monitoring system and method includes a master control chip to issue a master control chip hardware failure signal; a power management chip; a bus voltage comparator; a three-phase bridge switching circuit; a safety control logic generator to generate a hardware failure mode enable signal and a hardware failure status control signal based on the master control chip hardware failure signal, safety status entry and safety status switching signals; a gate driver to generate gate drive signals based on the hardware failure mode enable signal and the hardware failure status control signal to perform on / off operations on power transistors in the three-phase bridge switching circuit; and a drive safety status monitor to generate a drive safety status feedback control signal based on the hardware failure mode enable signal, the hardware failure status control signal, a gate driver failure status signal, and a power transistor working status signal.

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.

System, methods, and other embodiments described herein relate to improving the safety of pedestrians at a road crossing. In one embodiment, a method includes acquiring sensor data about a pedestrian and a vehicle in surroundings of a road crossing. The method further includes identifying an intention to cross the road crossing of the pedestrian and a driving behavior of the vehicle. The method additionally includes determining a safety condition for the pedestrian to cross the road crossing based, at least in part, on the driving behavior. Moreover, the method includes controlling at least one lighting mechanism of the road crossing according to the safety condition.

The invention relates to the technical field of building electrical safety, and discloses a building electrical safety risk intelligent diagnosis method and system based on big data, and the method comprises the steps: collecting the operation condition data of a building electrical system in real time; cleaning the collected operation condition data to remove noise, and performing normalization processing on the denoised operation condition data to obtain preprocessed data; feature extraction is carried out on the preprocessed data, time domain features and frequency domain features are extracted, energy distribution under different scales is obtained through wavelet transform, electrical signal abnormity is captured, and multi-dimensional electrical feature data are obtained; inputting the multi-dimensional electrical characteristic data into an intelligent diagnosis model, diagnosing the electrical safety state of the building through the intelligent diagnosis model, and outputting a safety diagnosis result; determining a building electrical safety risk level according to the safety diagnosis result, and sending corresponding early warning information based on the safety risk level; according to the invention, the electrical potential safety hazard of the building is accurately identified in real time, and the electricity safety of the building is guaranteed.

The utility model relates to the technical field of rail train operation safety monitoring, and discloses a rail working condition digital sampling device for an urban rail passenger car, which comprises a rail detection mounting beam, a sampling assembly, a detection assembly and a control box. The sampling assembly comprises a left rail surface detection installation support and a right rail surface detection installation support. And the left rail surface detection mounting bracket and the right rail surface detection mounting bracket are respectively arranged at two ends of the bottom of the rail detection mounting beam. The detection assembly comprises a left strand steel rail detection module, a right strand steel rail detection module, a left strand outside rail detection module, a rail middle detection module and a right strand outside rail detection module. The left strand steel rail detection module and the right strand steel rail detection module are installed on the left rail surface detection installation support and the right rail surface detection installation support respectively. The left strand rail outer detection module, the rail middle detection module and the right strand rail outer detection module are all located on the same side of the rail detection installation beam and arranged at intervals. Safety state comprehensive monitoring and fault hidden danger excavation early warning for online operation trains can be provided.

The invention discloses a personnel safety monitoring system based on coal mine tunneling operation, relates to the technical field of safety monitoring, and solves the technical problems that the safety condition of an operation site is difficult to comprehensively and accurately master in real time, and various safety accidents cannot be effectively prevented and handled. According to the invention, comprehensive environmental parameters such as harmful gas concentration, temperature and humidity in a coal mine area can be acquired in real time through the sensor data acquisition module, and the acquired environmental parameters are compared with a normal range value set by an operator, so that the safety of a working area corresponding to the operator can be accurately judged; a powerful basis is provided for safety assessment of the working environment, the accuracy and timeliness of environment safety monitoring are improved, action track information of workers is continuously and accurately obtained, analysis and judgment are carried out according to dangerous areas marked by an electronic map, physiological state parameters and behavior state parameters are collected in real time and analyzed, and the safety of the working environment is improved. And the abnormal state of the staff can be found in time.

The present disclosure provides a method and an apparatus for assisting in vehicle lane change. The method comprises: determining a lane change safety status corresponding to a current lane change behavior of a vehicle; and dynamically displaying the lane change safety status to enable a driver to dynamically receive information about changes in danger level throughout an entire lane change process.

The invention belongs to the field of intelligent safety management, and discloses a filling mining safety management method and system based on intelligent monitoring, and the method comprises the steps: collecting and preprocessing safety management data of a filling mining area; the safety management data comprises environment data, operation condition data and filling material conveying data; performing time sequence analysis and anomaly detection on the preprocessed security management data to obtain a data feature vector; establishing a safety risk assessment model by adopting an artificial bee colony algorithm, and assessing the safety state of the filling mining area according to the data feature vector and the historical accident data to obtain a safety level assessment result; and based on the safety level evaluation result, an emergency plan and an operation adjustment scheme are established, and filling mining safety management based on intelligent monitoring is completed.

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.

Various aspects of techniques, systems, and use cases may be used for using a safety depth camera for controlling an autonomous mobile robot. An example technique may include receiving infrared data from at least two infrared receivers of a safety depth camera affixed to a robotic system, determining a safety status of the robotic system related to a detected object in an environment based on the infrared data, and sending an indication to at least one of emergency braking circuitry of the robotic system or adjustable braking circuitry of the robotic system based on the safety status.

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.

The invention relates to the technical field of compressed air energy storage power station safety, and discloses a compressed air energy storage power station safety state assessment method comprising the following steps: collecting equipment operation state data of a compressed air energy storage power station for standardization processing, and constructing an equipment operation state twin model of the compressed air energy storage power station; the running state of the equipment is monitored in real time to obtain prediction data; comparing the prediction data with the real-time monitoring data to judge whether the equipment operation state of the compressed air energy storage power station is abnormal or not; when the equipment operation state of the compressed air energy storage power station is abnormal, predicting the equipment abnormality rate based on a preset BP neural network model; recording the number of devices when the abnormal rate of the devices exceeds a set value, and calculating the safety coefficient of the compressed air energy storage power station according to the number of the devices. The equipment operation condition of the compressed air energy storage power station is monitored in real time, so that hidden dangers can be found and eliminated in time, and the stable and safe operation of the compressed air energy storage power station is ensured.

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.