59 results about "Plant safety" patented technology

The invention relates to the technical field of industrial safety, in particular to a factory safety intelligent management and control method based on a heterogeneous multi-system cross service fusion technology, and the method comprises the steps: collecting factory multi-source heterogeneous data, and carrying out the time-space alignment and fusion; constructing a risk assessment model based on a deep learning algorithm, and performing quantitative risk analysis on personnel behaviors, environmental parameters and equipment states; a dynamic grading early warning mechanism is established, and warning and automatic handling are achieved according to the risk grade; introducing risk trend prediction, and analyzing a risk evolution trend; and a safe closed-loop optimization mechanism is constructed, and self-adaptive adjustment of the management and control strategy is realized. According to the method, a full-process and dynamically-optimized intelligent safety management and control scheme is constructed, and comprehensive perception, quick response and continuous optimization of factory safety management are realized.

The invention discloses a BIM-based power plant personnel position dynamic monitoring and early warning method and system, and relates to the related field of power plant safety alarm, and the method comprises the steps: constructing the approaching monitoring demands of unauthorized personnel and the entering safety monitoring demands of authorized personnel corresponding to a plurality of risk regions for a target power plant, and carrying out the BIM modeling marking, constructing a power plant BIM model; zero-trust personnel monitoring is carried out through personnel positioning equipment, and first temporary risk personnel corresponding to the first risk area are determined in combination with approaching monitoring requirements; verifying whether authorization exists or not; if the verification is passed, carrying out risk protection behavior detection; if the verification is not passed, reading the to-be-executed task, and connecting a historical personnel behavior monitoring log library to carry out abnormal detection on a personnel track; and performing abnormity early warning according to the first risk protection abnormal value or the second risk protection abnormal value. The technical problem that existing position monitoring is insufficient in monitoring and early warning capacity is solved, and the technical effect of improving the monitoring and early warning capacity is achieved.

The invention relates to the technical field of data early warning, in particular to an intelligent power plant safety early warning method based on multi-data coupling. The method comprises the following steps: acquiring multi-source coupling data including power plant production operation data, key equipment state monitoring data, environment monitoring data and historical accident records, and calculating acquisition time intervals and synchronous delays between data sources; defining the ratio of the acquisition time interval to the topological distance between the corresponding nodes of the key equipment as a coupling propagation rate; constructing a time sequence-topology association window based on the coupling propagation rate, and judging the state type of the key equipment according to the time sequence-topology association window; a key equipment risk parameter is obtained by quantifying the state type; according to the method, key equipment risk parameter quantification and potential risk marking are realized through multi-source coupling data and time sequence-topology correlation analysis, so that dynamic grading early warning is supported, and the operation safety and early warning real-time performance of a power plant are improved.

The invention discloses a thermal power plant safety operation early warning method and system, and relates to the technical field of power plant safety early warning. The method comprises the following steps: acquiring operation parameters from a DCS (Distributed Control System) configured by a target thermal power plant, and carrying out data preprocessing; training a multivariable Gaussian distribution model as a normal operation reference; the technical key points are as follows: the whole early warning scheme has the characteristics of self-adaption, learnability and high robustness, the safety monitoring level of the thermal power plant under complex working conditions is remarkably improved, the problem of high misjudgment rate of a fixed threshold value is solved by setting a dynamic threshold value, the early warning accuracy is improved, and the safety of the thermal power plant is improved. The first correction mechanism can solve the problem that a traditional scheme lacks self-adaptive ability, so that the current state is better matched, multi-level sensitive mode division can accurately respond to different risks, the second correction mechanism solves the problem that the traditional scheme lacks learning feedback, automatic threshold optimization is achieved, and the method better meets actual requirements.

The invention relates to the technical field of power plant safety management, in particular to a personnel safety management and control system and method used in a power plant area. Comprising a monitoring unit which comprises a plurality of monitoring modules and a plurality of sensing modules; the monitoring module is arranged at a monitoring point and is used for acquiring image data of each monitoring point; the sensing module is used for collecting monitoring index data of each worker; wherein each sensing module comprises a positioning sub-module, a pressure sub-module and a smoke sub-module; a sensing module worn by a person is constructed based on UWB and Beidou positioning technologies, so that position data, pressure data and all-around smoke concentration data of the person in a factory are monitored in real time, a plurality of monitoring modules are arranged in the factory, posture and motion amplitude data of the worker are collected, illegal behaviors are recognized and early warned in time, and the safety of the worker is improved. The safety of operators in the power plant is ensured.

The invention provides a multi-mode electronic fence forbidden zone intrusion identification method and system based on AI. The method comprises the following steps: firstly, acquiring synchronous multi-modal data acquired by a heterogeneous sensor network; secondly, according to the real-time production activity state, the type attribute and the real-time vehicle scheduling information, a differential perception focusing strategy is generated; performing weighted focusing fusion on the synchronous multi-modal data according to a differential sensing focusing strategy to generate dynamic intrusion sensing features; and then performing pattern analysis through an artificial intelligence model based on the dynamic intrusion sensing features, and finally identifying an intrusion behavior which accords with a preset factory safety regulation definition. According to the technical scheme provided by the invention, the identification precision of real threats in a complex industrial environment and the overall adaptability of the system are improved, and high-precision and self-adaptive intelligent identification of forbidden zone intrusion behaviors in the complex industrial environment is also realized.

The invention belongs to the technical field of power production safety, and discloses a power plant safety production management method and device. The method comprises the steps of obtaining safety information data of a power plant from a database; identifying safety production risk factors existing in the power plant based on the safety information data; analyzing the safety production risk factors to determine the relevance between the safety production risk factors and each safety accident type; extracting a key safety production risk factor corresponding to each safety accident type from the safety production risk factors based on the relevance; and performing risk assessment based on the key safety production risk factors, and performing safety production management based on a risk assessment result. Through the above mode, the risk can be effectively and comprehensively detected, the problem that risk identification is not timely and accurate due to a manual management mode is avoided, and effective management of safety production of a power plant is ensured.

The utility model relates to the technical field of thermal power plant safety protection, in particular to a safety protection device for a thermal power plant. The protective fence comprises a mounting base and a protective fence body. The number of the mounting seats is two, and the two mounting seats are arranged in parallel; the protective fence is installed between the two installation bases in a sliding mode. And a driving assembly for driving the protective fence to move along the mounting seat is arranged on the mounting seat. By arranging the movable protective fence and the guide rail structure, the protective fence can be conveniently driven to linearly move along the guide rail under the action of the driving assembly, the distance between internal equipment and the protective fence can be further conveniently adjusted, a worker can conveniently overhaul and maintain the equipment through the space, and the working efficiency is improved.

The invention discloses a power plant safety intelligent early warning method based on a dynamic electronic fence, and the method comprises the steps: firstly analyzing the historical work ticket data of a power plant through a BERT-BiLSTM-CRF hybrid model, and recognizing an equipment entity, an operation type and a risk level; in combination with space coordinates of a power plant equipment three-dimensional model, an initial virtual safety boundary is automatically divided according to work ticket operation content, operation personnel operation actions, multi-person position relations and equipment states are fused in real time, and a buffer distance is dynamically adjusted to form a dynamic electronic fence; based on a dynamic electronic fence and high-precision positioning data, a group operation anti-collision model and a safe path planning strategy are established, a graded early warning mechanism is constructed, and corresponding grade early warning is triggered according to the real-time distance between an operator and the electronic fence through linkage of an intelligent wearable device and a power plant monitoring system. According to the invention, the intelligence and refinement level of power plant safety management can be significantly improved, and the occurrence rate of operation safety accidents is effectively reduced.

The invention discloses an intelligent factory personnel positioning and safety early warning method, which comprises the following steps of: accurately identifying a risk source, dividing direct and indirect risk induction areas, and marking a position and an influence range by a three-dimensional map to plan a personnel route, so that a high-risk area is effectively avoided, path planning is optimized to enable personnel to be far away from potential danger, and an exposure risk is reduced; a risk chain model is constructed to quantify a risk transmission path and an influence weight, a path deviation value is calculated in combination with real-time positioning, and a risk value can be dynamically and accurately calculated based on the constructed risk assessment model, so that the risk assessment accuracy is improved; when the risk value exceeds the threshold value, early warning is performed in time, the accident response time is shortened, the accident occurrence probability is greatly reduced, personnel and equipment safety is comprehensively guaranteed, and a firm defense line is built for factory safety production.

The invention relates to a ship production workshop safety monitoring device and method and computer equipment. According to the application, the video stream, the sound data and the environmental parameters are acquired through the multi-mode monitoring terminal, and the procedure exclusive behavior recognition module performs special illegal behavior recognition, so that precise monitoring of procedures such as welding, coating, hoisting and the like is realized, and the recognition accuracy of the special illegal behaviors is improved. When a suspected illegal behavior is detected, the system automatically triggers the authority face recognition camera to carry out secondary verification of the identity and the operation authority of the person, so that closed-loop control of behavior recognition-identity verification-authority verification is realized, and the safety risk caused by operation of an unauthorized person is effectively avoided. The industrial-grade super computer carries out centralized processing on identification results and sends violation information to the grading early warning module, and the grading early warning module carries out three-stage grading early warning and corresponding processing measures according to violation risk grades, so that automation and timeliness of a response mechanism are realized, and safety management is promoted.

The utility model provides a water spraying system for fire extinguishing in a power plant, which belongs to the technical field of power plant safety and comprises a water conveying pipeline, a fire-fighting water pipeline and a fire-fighting pool. The water inlet end of the fire-fighting water pipeline is communicated with a fire-fighting pool arranged underground through an underground pipeline; the water inlet end of the water conveying pipeline is communicated with a fire-fighting water pipeline, the fire-fighting water pipeline is used for providing fire extinguishing water for the water conveying pipeline, and the water outlet end of the water conveying pipeline is communicated with a spray head. According to the utility model, the fire extinguishing water delivery pipeline is communicated with the fire-fighting water pipeline, and the fire-fighting water pipeline is used for taking water from the underground fire-fighting water pool, so that the problem that the water delivery header pipe is frozen due to lower outdoor temperature is effectively avoided, and the fire extinguishing system can quickly respond and effectively deliver water even in a low-temperature environment; therefore, a fire source is extinguished in time, and economic loss and casualties possibly caused by the fire are greatly reduced.

The invention discloses a three-dimensional visual intelligent power plant personnel positioning system, and relates to the technical field of power plant personnel positioning systems. The system comprises a real-time position display module, an inspection planning module, a historical track query module, an alarm function configuration module, an attendance management module, a visitor management module, an equipment function management module, a label management module, a camera module and an access control module. Personnel distribution and on-duty conditions in a power plant are mastered in real time through a personnel positioning system, pre-warning processing of personnel entering can be achieved by delimiting an electronic fence in a dangerous area, historical tracks can be inquired to trace accident causes after dangerous accidents occur, and the system plays a crucial role in power plant safety management and control. Workers in the real-time inspection process are positioned in the personnel positioning system, information such as inspection routes, inspection point positions and inspection periods is planned in advance, and a management layer can check the completion condition and completion progress of each inspection task in real time.

Strengthen safety management for workers. [Solution] A mobile body equipped with an imaging device, a control device, and a notification device, wherein the control device includes a movement control unit that controls the body to move within the factory based on a patrol route for patrolling the work area within the factory, a detection unit that processes motion image data captured by the imaging device after the start of the patrol to detect events that increase the risk of occupational accidents for workers, and a notification instruction unit that, when an event that increases the risk of occupational accidents for workers is detected, provides notification via the notification device to encourage the reduction of the risk of occupational accidents.

The utility model relates to the technical field of power plant safety protection, disclose a kind of power plant production safety management protection device, including base, the bottom four corners of base are uniformly provided with universal wheel, the top of base is provided with foldable fence, the front side of foldable fence is installed with warning sign, the left and right sides of foldable fence are provided with main vertical rod, and the inside of main vertical rod is provided with extension assembly, and the extension assembly includes control rod, the outside of control rod is equipped with pressurized spring, and the middle part of control rod is fixedly connected with limit plate. In the utility model, through foldable fence, and install warning sign at front end, cooperate with the infrared sensor of base front side and the loudspeaker in control box, can effectively prompt the pedestrian close to construction area. Meanwhile, extension assembly is arranged in the main vertical rod of fence two sides, can flexibly adjust protection range according to need, ensure the safety and isolation effect of work area.

The application discloses a power plant safety intelligent monitoring device based on the Internet of Things, which comprises annular guide vane shaft connecting plates and wheel shaft connecting plates, the guide vane shaft connecting plates can be connected to each guide vane shaft of an impeller machine, the wheel shaft connecting plates can be sleeved in the wheel shaft of the impeller machine, and three inclined deformation sensors are uniformly distributed between the guide vane shaft connecting plates and the wheel shaft connecting plates in a circumferential direction. Compared with the prior art, the application can meet the monitoring requirement, reduce the manufacturing and maintenance costs of the device, and provides an efficient and economical safety monitoring solution for a power plant.

The invention discloses an isolation warning device for power plant safety management, and belongs to the technical field of power plant safety management devices. The plurality of pyroelectric sensors are connected to the multi-degree-of-freedom trolley in an annular array; the plurality of groups of alarms are connected to the multi-degree-of-freedom trolley in an annular array, and the plurality of groups of alarms are in one-to-one correspondence with the plurality of pyroelectric sensors; the vacuum pump is mounted on the multi-degree-of-freedom trolley; a plurality of elongated airbags; the multi-degree-of-freedom trolley is arranged in a protection area, a pyroelectric sensor senses that a worker walks in the corresponding direction and triggers an alarm to give an alarm so as to warn the worker to leave the area, a controller controls a corresponding electromagnetic valve to be opened, a vacuum pump sucks air into a corresponding long-strip-shaped air bag, and therefore the worker can be protected. After the long-strip-shaped air bag is opened, a worker is visually warned, and the isolation warning effect is good.

The invention discloses a power plant safety monitoring system based on STC space-time coding. The power plant safety monitoring system comprises a sensor data acquisition module, an STC space-time coding module, a data analysis module, an alarm generation module, a user interface module, a communication module, a storage module and a control module. By introducing the STC space-time coding technology, the performance of the power plant safety monitoring system is remarkably improved, the system can efficiently code and process space-time data, reduce misinformation and missed information and achieve more accurate threat detection and real-time response, meanwhile, data storage and transmission are optimized, the system load is reduced, the overall reliability and efficiency are improved, and the power plant safety monitoring system is suitable for popularization and application. And the system can be easily integrated into the existing infrastructure, so that the safety management level of the power plant is enhanced, and self-adaptive adjustment is supported to adapt to different operation conditions.

This invention discloses a safe hoisting system for factory buildings, belonging to the field of construction technology. The system includes baffles at both ends of a crossbeam. The crane comprises a body with a recessed groove on its top surface. Drive wheels are rotatably mounted on both sides of the groove. Drive protrusions are located on the support surfaces on both sides of the crossbeam, positioned along the movement lines of the drive wheels. When the crane moves to the end of the crossbeam, the drive wheels contact the drive protrusions. Slots are opened at both ends of the body, each containing an airbag. Air cylinders are fixedly connected to the ends of the airbags. A rotating wheel is coaxially mounted at the ends of the two air cylinders at both ends of the body. Threaded posts are coaxially mounted on both sides of the rotating wheel, with threaded sealing plates connected to the posts. The sealing plates are movable within the air cylinders. The drive wheels drive the rotating wheels to rotate. The airbag-type buffer ensures a soft impact and minimal rebound distance at the edge of the crossbeam. Furthermore, with the presence of an anti-collision structure, the crane's overall structure can be retracted, improving its tightness.

The invention relates to the technical field of intelligent power plants, in particular to a power plant safety production personnel management method and device, equipment, a storage medium and a product. Determining an assessment data extreme value corresponding to each assessment index in the assessment data set; performing forward processing and standardization processing on the assessment data set according to the category of the assessment data and the assessment data extreme value to obtain a target assessment data matrix; scoring assessment is carried out based on the target assessment data matrix, a comprehensive assessment result of each user is obtained, the influence of data isolation of the users in different power plant production environments on assessment scoring is reduced, the data processing efficiency in the assessment scoring process is improved, the personnel assessment effect in the power plant safety production process is improved, and the user experience is improved. The technical problems that in the prior art, in the safety production process of a power plant, the workload of personnel management assessment is large, data isolation exists, and the assessment effect is poor are solved.

The invention relates to the field of power systems, in particular to a thermal power plant safety monitoring system and method based on a 5G network. The system comprises a self-driven detection vehicle, an equipment nameplate, monitoring equipment and a control module. The detection vehicle moves along a preset track to approach equipment in the thermal power plant; a data memory and a signal transmitter are arranged in the equipment nameplate, and information is provided for the detection vehicle; the monitoring device integrates a camera, a temperature sensor and a 5G communication module and uploads data to the control module. The control module compares the data with preset security data, and gives an alarm when the data does not meet the standard. The method comprises the steps of controlling the detection vehicle to move along the track, receiving equipment information, detecting temperature and shooting environment, uploading data, comparing a result, and deciding whether to give an alarm or not according to the comparison result, so that efficient and safe monitoring of thermal power plant equipment is realized. According to the invention, the inspection efficiency is improved, and the safety risk caused by insufficient obstacle avoidance capability of the robot in a complex environment is reduced.

This invention discloses an artificial intelligence-based safety monitoring method and system for thermal power plants, comprising: firstly, responding to a thermal power plant safety monitoring start command, acquiring current boiler parameters at preset time intervals; then, calling a pre-trained boiler status assessment model to determine whether the current boiler parameters are in a boiler warning state; and finally, when the current boiler parameters are in a boiler warning state, acquiring and executing a target warning resolution strategy for the current boiler parameters. This design, compared to the prior art's process of reporting first and then processing, can improve the efficiency of safety monitoring and processing for thermal power plants.

The invention provides a multi-source target inspection method for inter-plant safety. According to the method, an unmanned aerial vehicle carries high-definition camera shooting to carry out target identification, and the target is transmitted to a ground station cloud platform to carry out component defect diagnosis, so that the problems of high labor intensity, low efficiency and easiness in being influenced by the environment in a traditional inspection mode are solved, and the problems of error detection and missing detection caused by inspection personnel through pictures on a remote controller are solved; and unmanned aerial vehicle inspection can enter a high-risk area, so that personnel are prevented from directly contacting a dangerous environment, and the working safety is remarkably improved.

The invention relates to a deep learning-based factory safety device identification method. The method comprises the following steps of S1, acquiring a to-be-identified image in a factory environment through image acquisition equipment; s2, inputting the to-be-recognized image into a pre-trained target detection model; wherein the target detection model is a neural network model which is based on a YOLOv8 architecture and introduces an attention optimization mechanism, and is used for identifying the category and the position of a safety device in the image; and S3, receiving and outputting a safety device identification result returned by the target detection model. The method has the advantages that the safety equipment can be detected and recognized in real time in a factory through a deep learning algorithm and in combination with a factory management department, it is ensured that a worker wears necessary safety equipment and whether the equipment is correctly placed or not, potential safety hazards are reduced, and the overall safety level of the factory is improved.

The present invention provides a primary air volume coupling and adjustment system for mixed coal volatile matter and ignition distance, relating to the field of energy conservation and environmental protection technology for power plants. The system uses a relational database interface to read the blended coal types and ratios established by the coal blending system, as well as the corresponding coal volatile matter, moisture, and ash parameters for the coal types in the coal yard, to calculate the pulverizer mixed coal fuel ratio. It also uses a real-time system database interface to read primary air volume and coal feed rate data from the SIS system and calculate the pulverizer mixed coal air-coal ratio. Based on experimental data, a fuzzy system is constructed to establish the coupling relationship between ignition distance, mixed coal volatile matter, and primary air volume. Using sliding window module technology, the system calculates the offset of the primary air volume set value in real time using a real-time weighted average, real-time primary air volume set value, and real-time ignition distance data. The system uses an external plug-in mode to interact with the original pulverizer control system, ensuring power plant safety.

The invention relates to the technical field of plant safety, and discloses a plant micro-vibration prevention intelligent monitoring and control method and system, and the method comprises the steps: S1, collecting the dynamic information of a plant in real time; s2, according to the collected dynamic information of the factory building, obtaining an amplitude characteristic value of the factory building; s3, establishing an amplitude prediction model according to the amplitude characteristic value; s4, predicting the vibration of the factory building through the amplitude prediction model to obtain an amplitude prediction value; s5, according to the amplitude predicted value and a standard vibration threshold value, determining the acceleration level of the factory building amplitude; s6, according to the dynamic information peak value of the factory building, determining the displacement grade of the factory building amplitude; s7, determining the state of the factory building according to the acceleration level and the displacement level; s8, determining to adopt an active control strategy or a passive control strategy according to the plant state; and S9, controlling the amplitude of the plant by adopting an active control strategy or a passive control strategy. The vibration level of the factory building can be effectively controlled.

The invention belongs to the technical field of power plant safety monitoring, and discloses a power plant safety monitoring system based on artificial intelligence. Comprising the following modules: a data acquisition module used for acquiring environment data and equipment data of all monitoring areas in a power plant in real time; according to the invention, through setting the fire occurrence remaining time prediction model and the support score, the fire prediction is promoted from simple probability evaluation to accurate time prediction, and the time interval from the current moment to the fire in the unit area is accurately predicted. The prediction of the time dimension enables the implementation of prevention and control measures to be more targeted, on this basis, a support score is established, state parameters such as the battery electric quantity, the fire extinguishing agent remaining amount, the historical reliability and the arrival time of the robot are comprehensively considered, the optimal scheduling of the fire extinguishing robot is realized, and the intelligent scheduling method improves the utilization rate of the robot and reduces the labor intensity of the robot. And meanwhile, prevention and control deployment is completed before a fire disaster occurs.

The invention relates to the technical field of wastewater treatment, and particularly discloses a wastewater treatment plant safety protection system which comprises a smoke exhaust mechanism, and a fire extinguishing mechanism is arranged on the surface of the smoke exhaust mechanism; a detection mechanism is further arranged on the front face of the smoke exhaust mechanism. Through the smoke exhaust mechanism, when the concentration of harmful gas in a plant exceeds the standard or smoke is generated in a fire disaster, a shaft rod can drive a main exhaust blade to rotate through driving of a motor, an upward air supply effect can be generated, and smoke in the plant can be sucked and exhausted into an outdoor smoke pipe through air inlet nozzles inside and outside an indoor smoke pipe; and finally, smoke is discharged outdoors through smoke exhaust holes in the smoke exhaust head, dust screen structures are installed on the air inlet part at the lower end in the indoor smoke pipe and the interior of the air inlet nozzle, and batting and dust can be prevented from entering the indoor smoke pipe to be gathered.

The utility model provides a power plant safety monitoring device, which comprises a front panel cover, a rear shell and an insulation pad, the insulation pad is positioned between the contact surfaces of the front panel cover and the rear shell after the opening parts of the front panel cover and the rear shell are connected, the top in the rear shell is connected with a guide shaft in a front-and-back sliding manner, and the guide shaft is positioned between the front panel cover and the rear shell. The front end of the guide shaft is rotationally connected with the back face of the front panel cover, the rear end of the guide shaft is fixedly connected with a right-angle hanging rod, and the top of a cross rod on the right-angle hanging rod is fixedly connected with a positioning plate. According to the utility model, the transmission shaft is slidably connected to the top in the housing, the transmission shaft is connected with the positioning plate used for installing instrument components through the right-angle suspension rod, one end of the transmission shaft is connected with the back surface of the front panel cover, and the front end cover can be opened when the transmission shaft is controlled to slide outwards. And meanwhile, the positioning plate carrying the components can be moved to the opening part of the shell, so that the components are in an exposed state, the maintenance space is increased, and the maintenance convenience is improved.