280 results about "Safety status" patented technology

The invention provides a tunnel safety-oriented safety step pitch monitoring method and system, and the method comprises the steps: deploying an edge calculation module at a sensor node, carrying out the preprocessing and compression of collected monitoring data, reducing the data transmission amount through data dimension reduction and feature extraction, relieving the data transmission pressure, and improving the data transmission efficiency and real-time performance. An incremental learning algorithm is adopted to carry out online analysis on monitoring data, an anomaly detection model is dynamically updated according to a newly collected data sample, an early warning threshold value is adaptively adjusted, the accuracy and the real-time performance of anomaly recognition are improved, and misinformation and missing report are reduced; a multi-sensor data fusion technology is comprehensively applied, correlation analysis is carried out on sensor data of different types and different positions, the reliability and accuracy of monitoring data are improved through data redundancy and complementation, and comprehensive evaluation of the tunnel construction safety state is achieved.

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 discloses an urban rail transit information safety protection method, and relates to the technical field of information protection, and the method comprises the steps: building a ground wireless communication network, installing a reconfigurable surface structure on the surface of a leaky cable, determining the number of reflection units, and carrying out the real-time detection and early warning of data through artificial intelligence. The method has the advantages that the monitoring data of a plurality of safety management domains can be integrated by establishing cross-domain safety collaboration, comprehensive perception of the safety situation of the whole rail transit system is formed, network flow data, equipment operation state data, passenger behavior data and the like of different lines are integrated, and the safety of the whole rail transit system is improved. A safety situation awareness platform is constructed by using a data analysis technology, the safety condition of the system is monitored in real time, potential safety risks are found in advance, dynamic safety assessment can be performed on the rail transit system based on shared information and global safety situation awareness, and when it is found that a safety risk index exceeds a normal range, early warning can be given out in time.

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.

The invention provides a safety early warning method and system based on an intelligent mine and a related device, and the method comprises the following steps: collecting basic information of the mine, the basic information comprising geographic information, ecological information and operation and maintenance information; constructing a sample database based on the basic information; building a safety state early warning model based on the sample database; obtaining early warning information based on the operation and maintenance information and a safety state early warning model; according to the safety early warning method and system based on the smart mine and the related device, comprehensive perception and intelligent analysis of coal mine safety production data are achieved, combined research and judgment and collaborative early warning of safety risks of all service links are achieved by building a service collaborative early warning model, and the timeliness and accuracy of early warning are improved; by establishing a data collaborative intelligent early warning platform integrating data processing, model training and early warning publishing, the whole-process closed-loop management of data flow, service flow and alarm flow is realized, and an intelligent management and control means is provided for coal mine safety production.

The invention discloses a safety monitoring and early warning management system and method for a coal mine tunnel, and the method comprises the following steps: S1, deploying a plurality of monitoring nodes; s2, collecting real-time environment data of a plurality of monitoring nodes, and preprocessing the real-time environment data; s3, analyzing the similarity between the preprocessed environmental data and environmental data in historical accident hidden dangers, simulating and predicting the potential risk of an emergency situation, evaluating the safety state, and determining the risk level; s4, triggering of an early warning mechanism is determined, and an emergency plan is generated; and S5, visually displaying the environment data, the analysis data and the risk level, and dynamically adjusting the list of the change data to realize safety monitoring and early warning management. According to the invention, safety monitoring and early warning with real-time early warning and prediction capability can be provided, and the safety state of the coal mine tunnel can be comprehensively and accurately reflected, so that more accurate and efficient management and protection of the coal mine tunnel are realized, and the safety and production efficiency of coal mine production are greatly improved.

The invention provides a test fault early warning method, system and device and a medium, and belongs to the field of fault diagnos.The method comprises the following steps that a test safety monitoring system is divided into a plurality of subsystems, each subsystem comprises a plurality of monitoring indexes, and each monitoring index is collected through a plurality of channels; making an alarm value assignment rule of each monitoring index according to whether the channel of each monitoring index gives an alarm or not; counting the score of each subsystem according to an alarm value assignment rule, obtaining a weighting coefficient of each subsystem, weighting the score of each subsystem according to the weighting coefficient of each subsystem and then superposing to obtain a test safety score interval, judging a fault type according to the test safety score interval, and performing early warning according to the fault type. According to the invention, comprehensive analysis can be carried out on the safety state of the test environment, the influence relationship among the subsystems is considered, the accuracy of fault diagnosis is improved, real-time and accurate early warning is carried out on operators, and the safety of the operators is ensured.

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.

The invention relates to the technical field of coal mine early warning, in particular to a coal mine safety behavior visual monitoring and early warning system which comprises an information acquisition unit, a monitoring display unit, an image recognition unit, a data analysis unit, a central processing unit and a safety early warning unit. The information acquisition unit is used for monitoring equipment parameters in real time and acquiring images in a mine; the monitoring display unit is used for displaying equipment parameters and fault properties and places; the image recognition unit is used for carrying out recognition processing on the image; the data analysis unit is used for calculating the deviation degree of the working face, judging the running state of the scraper conveyor, calculating the uniformity of coal briquettes and performing risk assessment on the coal piling condition; the central processing unit is used for automatically controlling the equipment; and the safety early warning unit is used for carrying out voice broadcast on the transfer point and the equipment and sending out an early warning signal. According to the invention, by detecting various operation parameters of the equipment in the mining transportation process, visual monitoring and early warning are carried out on the safety state of the equipment.

The invention belongs to the field of safety production management, relates to a data analysis technology, is used for solving the problem that synchronous monitoring and correlation analysis cannot be carried out on a production environment and risk behaviors of a production area in the prior art, and particularly relates to a safety production management monitoring method and system based on big data analysis. The management monitoring platform is in communication connection with an environment monitoring module, a behavior monitoring module, a safety evaluation module and a storage module; the environment monitoring module is used for carrying out production environment monitoring on a safety production area; the behavior monitoring module is used for monitoring and analyzing risk behaviors of the safety production area; the safety evaluation module is used for evaluating and analyzing the safety production state of the safety production area; according to the method, the safety production state of the safety production area can be evaluated and analyzed, the evaluation coefficient is obtained, the evaluation coefficient can be used for feeding back and evaluating the overall safety production state of the monitoring area, and safety supervision of the corresponding monitoring area is enhanced if necessary.

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 constructional engineering safety supervision, and discloses a constructional engineering safety supervision early warning monitoring system and method.The constructional engineering safety supervision early warning monitoring system comprises a sensor layer, a supervision center layer, a data transmission layer, a data processing layer and a user layer; the data transmission layer transmits data to the supervision center in real time, the data processing layer processes and analyzes the collected data, and the supervision center layer can realize remote monitoring and management, so that supervision personnel can monitor and manage the safety condition of the construction site at a place far away from the construction site; identity verification is carried out on construction site personnel through the face recognition technology, illegal personnel are prevented from entering a construction site, the safety of the construction site is guaranteed, the data storage layer can store collected data and processing results, and data query and statistical analysis functions are provided for supervisors. And supervisors can conveniently track and manage the safety condition of the construction site for a long time.

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 invention provides a linear driving thrust optimization design method and system, and relates to the technical field of thrust optimizing.The linear driving thrust optimization design method comprises the steps that firstly, a permanent magnet and an electromagnet are arranged, a motor system and related magnetic field data are collected, and a mixed magnetic field is calculated; and based on the mixed magnetic field, current output is optimized by using a PID controller so as to realize matching of the target thrust and the actual thrust. Besides, the system calculates a safety index by analyzing the temperature, the vibration intensity and the thrust fluctuation of the motor, and compares the safety index with a preset safety threshold, thereby judging the safety state of the motor. When the safety index is lower than the threshold value, the system can give out early warning in time, and the reliability and safety of the system are ensured.

The invention discloses a motor controller safety state control method and circuit and a storage medium. Comprising the following steps: acquiring a phase current frequency of a three-phase full-bridge circuit of a motor controller, a bus voltage value of a target vehicle and a line voltage between target acquisition points; determining a first voltage according to the phase current frequency, determining a second voltage according to the bus voltage value, and determining a third voltage according to the line voltage; a first level is output according to the first voltage and the second voltage, and a second level is output according to the second voltage and the third voltage; and a logic signal is generated according to the first level and the second level, a logic control signal is generated according to the logic signal, and when the motor rotating speed detection function of the target vehicle is abnormal, motor safety state switching can be completed.

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.