Management method, device, equipment and medium for safety production of thermal power plant

Abstract

The invention relates to the technical field of intelligent management and control of a thermal power plant, and discloses a management method, platform, equipment and medium for safe production of the thermal power plant. Real-time audio and video data are directly acquired through front-end equipment at a key position, so that centralized collection of field data is realized, and the complexity of scattered collection is avoided; secondly, analyzing the data according to a corresponding strategy to obtain real-time key content, and connecting data acquisition and carding without independent carding of a switching system; then, the data and the key content are dynamically displayed in an associated area, so that collection, carding and presentation are completed through a set of processes, and managers are helped to timely and comprehensively master the real-time state; and finally, based on the display area, directly receiving the management and control demand and linking the management and control equipment to operate, breaking the disjunction of information acquisition and management and control execution, reducing operation links, avoiding delay of problem processing, and meeting the temporary operation supervision demand.

Description

Technical Field

[0001] This invention relates to the field of intelligent control of thermal power plants, specifically to a management method, device, equipment, and medium for safe production in thermal power plants. Background Technology

[0002] In the safety management of thermal power plants, temporary operations often involve multiple dispersed areas, and the initiation and adjustment of these operations are relatively sudden, requiring real-time monitoring of the on-site situation to support supervision. However, current supervision of such operations lacks a coherent method for processing real-time on-site information. The key steps of collecting on-site data, organizing the collected data, and presenting the organized information to management personnel often need to be carried out separately and cannot be completed smoothly through a single process. This makes it difficult for management personnel to have a timely and comprehensive understanding of the real-time status of temporary operations.

[0003] Meanwhile, current supervision of temporary operations at thermal power plants faces a disconnect between information acquisition and execution. Even after obtaining on-site information, if adjustments to the work area are deemed necessary, the existing information cannot be directly integrated into the control and management process. This not only increases the workload for management personnel but may also delay addressing potential problems in temporary operations, failing to meet the demands for efficiency and centralized management in temporary work scenarios. Summary of the Invention

[0004] In view of this, embodiments of the present invention provide a management method, device, equipment and medium for safe production in thermal power plants, in order to solve the problem that in the current supervision of temporary operations in thermal power plants, on-site data collection, sorting and information presentation cannot be completed in a coherent process, and there is a disconnect between information acquisition and control execution, which makes it difficult for managers to grasp the real-time status in a timely and comprehensive manner, increases the number of operation steps and may delay the handling of problems.

[0005] In a first aspect, embodiments of the present invention provide a management method for safe production in thermal power plants, the method comprising: Real-time audio and video data collected by different front-end devices are acquired, wherein the front-end devices are deployed at various key locations in the production area of ​​the thermal power plant. The corresponding real-time audio and video data is parsed according to the parsing strategy of the front-end device to obtain the real-time key content of the corresponding thermal power plant generation area. Determine the display area associated with the front-end device, and dynamically display the real-time key content and real-time audio and video data corresponding to the front-end device in the corresponding display area; The system receives control requests applied to a target display area and, based on these requests, performs control operations on the corresponding thermal power plant generation area using the control devices associated with the target display area. The target display area can be any one of multiple display areas.

[0006] Furthermore, before parsing the corresponding real-time audio and video data according to the parsing strategy corresponding to the front-end device, the method further includes: The clarity of the real-time audio and video data is detected; if the clarity does not reach the preset threshold for identifying key content, the reasons for the clarity not reaching the preset threshold are analyzed. Adjust the operating parameters of the environmental control equipment in the corresponding thermal power plant production area according to the reasons stated above. The environmental conditioning equipment is controlled to perform environmental conditioning according to the equipment's operating parameters until the clarity of the real-time audio and video data collected by the front-end equipment in the corresponding thermal power plant production area reaches a preset threshold.

[0007] Furthermore, the step of using the control device associated with the target display area based on the control command to perform control operations on the corresponding thermal power plant production area includes: Acquire at least one target front-end device associated with the target display area; Obtain the target thermal power plant production area where each of the target front-end devices is deployed, and obtain the list of control devices associated with the target thermal power plant production area; Using equipment priority and operation logic, the target controlled equipment for which instructions need to be executed is selected from the list of controlled equipment; Based on the control requirements, determine the operation parameter configuration strategy, and generate control instructions based on the operation parameter configuration strategy; The control commands are sent to the target control device through the industrial control network, and the execution results fed back by the target control device are obtained. The execution results are then updated in the target display area simultaneously.

[0008] Furthermore, the step of determining the operation parameter configuration strategy based on the control requirements includes: Determine the types of key parameters that need to be regulated based on control requirements; Based on the key parameter types and the equipment configuration information of the target control equipment, determine the allowable adjustment range of each equipment parameter; Based on the difference between the real-time operating data of the target thermal power plant's production area and the expected value corresponding to the control requirements, the initial parameter adjustment value is determined within the allowable adjustment range. The initial parameter adjustment values ​​are verified and corrected based on the correlation constraints between device parameters, and the corrected parameter adjustment values ​​are integrated according to the device control protocol format to obtain the parameter configuration strategy.

[0009] Furthermore, the method also includes: By comparing the real-time key content with the hazard characteristics recorded in the historical safety incident database, the types of potential hazards currently existing and their corresponding probabilities of occurrence are obtained; Based on the probability of occurrence of potential hazard types and the estimated scope of impact, determine the corresponding level of pre-control measures and the corresponding control equipment; Based on the execution rules corresponding to the level of pre-control measures, the potential hazard type and its corresponding probability of occurrence are converted into preventive control instructions containing specific operating parameters, and the preventive control instructions are issued to the control equipment so that the control equipment can intervene in advance according to the preventive control instructions.

[0010] Furthermore, the method also includes: The regional safety status of the thermal power plant's production area is determined based on the aforementioned real-time key information. The thermal power plant production areas where the safety status of the area is not safe are designated as abnormal thermal power plant production areas. The real-time distribution of affected personnel in the abnormal thermal power plant production areas is then determined, and the optimal evacuation route is determined based on the real-time distribution and the area map of the abnormal thermal power plant production areas. Determine the guidance equipment and area control equipment along the optimal evacuation route; The control parameters of the guidance equipment and the area control equipment are calculated using the movement speed of the affected personnel and the response time of the equipment. The control parameters are sent to the corresponding guidance devices and area control devices, and the evacuation progress of the affected personnel is tracked and displayed in real time. Once the evacuation is confirmed, the area isolation operation is triggered.

[0011] Furthermore, the calculation of control parameters for the guidance device and the area control device using the movement speed of the affected personnel and the device response time includes: Based on the type of personnel affected within the production area of ​​the abnormal thermal power plant, determine the corresponding baseline movement speed for different personnel; Based on the length of each segment of the optimal evacuation route and the baseline movement speed of the personnel in the corresponding segment, calculate the time required for the affected personnel to reach the key nodes of each segment from their current location. Based on the equipment parameters of the guidance equipment and the area control equipment, determine the standard response time for each type of equipment; Based on the time required for personnel to reach key nodes and the equipment response time, calculate the advance start time of the guidance equipment and the area control equipment, and determine the action duration of the guidance equipment and the area control equipment in combination with evacuation requirements; The control parameters are determined based on the advance start time and the duration of the action.

[0012] Secondly, embodiments of the present invention provide a management platform for safe production in thermal power plants, the platform comprising: The acquisition module is used to acquire real-time audio and video data collected by different front-end devices, wherein the front-end devices are deployed at various key locations in the production area of ​​the thermal power plant. The parsing module is used to parse the corresponding real-time audio and video data according to the parsing strategy of the front-end device to obtain the real-time key content of the corresponding thermal power plant generation area. The determination module is used to determine the display area associated with the front-end device and dynamically display the real-time key content and real-time audio and video data corresponding to the front-end device in the corresponding display area; The control module is used to receive control instructions applied to the target display area, and to perform control operations on the corresponding thermal power plant generation area by the control equipment associated with the target display area based on the control instructions, wherein the target display area is any one of multiple display areas.

[0013] Thirdly, embodiments of the present invention provide a computer device, including: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to perform the method described in the first aspect or any corresponding embodiment thereof.

[0014] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing computer instructions that cause a computer to perform the method described in the first aspect or any of its corresponding embodiments.

[0015] This application firstly acquires real-time audio and video data directly from front-end devices at key locations, achieving centralized data collection on-site and avoiding the cumbersome process of scattered collection. Secondly, it parses the data according to corresponding strategies to obtain real-time key content without switching systems for separate processing, thus streamlining the connection between data collection and processing. Then, it dynamically displays the data and key content in associated areas, allowing collection, processing, and presentation to be completed through a single process, helping managers to grasp the real-time status in a timely and comprehensive manner. Finally, it directly receives control requests based on the display area and links the operation of control devices, breaking down the disconnect between information acquisition and control execution, reducing operational steps, avoiding delays in problem handling, and meeting the needs of temporary operation supervision. Attached Figure Description

[0016] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0017] Figure 1 This is a flowchart illustrating a management method for safe production in a thermal power plant according to some embodiments of the present invention. Figure 2 This is a flowchart illustrating another management method for safe production in a thermal power plant according to some embodiments of the present invention. Figure 3 This is a flowchart illustrating another management method for safe production in a thermal power plant according to some embodiments of the present invention. Figure 4 This is a structural block diagram of a management platform for safe production in thermal power plants according to an embodiment of the present invention; Figure 5 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] According to embodiments of the present invention, a management method, platform, equipment, and medium for safe production in thermal power plants are provided. It should be noted that the steps shown in the flowcharts in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowcharts, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0020] This embodiment provides a management method for safe production in thermal power plants. Figure 1 This is a flowchart of a management method for safe production in a thermal power plant according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps: Step S101: Obtain real-time audio and video data collected by different front-end devices, wherein the front-end devices are deployed in various key locations in the production area of ​​the thermal power plant.

[0021] In this embodiment, firstly, based on the process characteristics and safety risk level of the power plant's production area, the deployment location and equipment type of the front-end equipment are determined. For example, network cameras with high-temperature resistance and dustproof / explosion-proof functions are deployed in key areas such as around the boiler furnace, turbine building, cable trays, and fuel tank areas. Additionally, dome cameras with audio acquisition capabilities are deployed in areas with frequent personnel access, such as the main control room entrance and hazardous chemical storage rooms, ensuring coverage of the three core scenarios: equipment operation monitoring, personnel behavior monitoring, and environmental safety monitoring. After deployment, a unique equipment identifier is assigned to each front-end device, and a mapping relationship between the equipment identifier and the deployment location is established and stored in the equipment management database for convenient subsequent data traceability and correlation operations.

[0022] Secondly, before activating the real-time acquisition function of the front-end device, it is necessary to initialize and configure the device. Acquisition parameters should be set according to the monitoring needs of different areas. For example, in boiler areas where light changes significantly, the camera's dynamic exposure parameters should be adjusted to "high sensitivity mode," and the frame rate set to 25fps to ensure smooth video playback. In dimly lit areas such as cable trays, the camera's infrared night vision function should be enabled, and the infrared illumination distance adjusted to cover the entire monitoring range. For audio acquisition devices, the microphone sensitivity threshold should be set to "medium noise reduction mode" based on the ambient noise level to filter low-frequency noise generated by the device's operation, ensuring clear acquisition of personnel conversations and abnormal sounds. After configuration, a connection is established between the front-end device and the back-end data receiving server via industrial Ethernet. Audio and video data are transmitted using the RTSP real-time streaming protocol, while the TCP protocol is enabled to ensure data transmission reliability and prevent data loss or buffering due to network fluctuations.

[0023] Finally, during the data acquisition process, the backend system needs to monitor the operating status of each front-end device in real time, and determine whether the device is online through the device heartbeat mechanism. If a device fails to receive a heartbeat packet three times in a row, an offline alarm will be triggered immediately, and an alarm message will be pushed to the operation and maintenance terminal. At the same time, the system monitors the packet loss rate and latency rate of the transmitted real-time audio and video data. If the packet loss rate exceeds 5% or the latency exceeds 100 milliseconds, the system will automatically switch to the backup transmission link (such as a 4G / 5G wireless backup channel) and adjust the data compression algorithm (such as switching H.264 encoding to H.265 encoding) to reduce bandwidth consumption while ensuring image clarity.

[0024] Step S102: Analyze the corresponding real-time audio and video data according to the parsing strategy of the front-end device to obtain the real-time key content of the corresponding thermal power plant generation area.

[0025] In this embodiment of the application, before parsing the corresponding real-time audio and video data according to the parsing strategy of the front-end device, the method further includes: detecting the clarity of the real-time audio and video data; if the clarity does not reach the preset threshold for identifying key content, analyzing the reasons why the clarity does not reach the preset threshold; adjusting the equipment operating parameters of the environmental control equipment in the corresponding thermal power plant production area according to the reasons; controlling the environmental control equipment to perform environmental control according to the equipment operating parameters until the clarity of the real-time audio and video data collected by the front-end device in the corresponding thermal power plant production area reaches the preset threshold.

[0026] In this embodiment, before initiating the parsing of audio and video data from the front-end device, it is necessary to first ensure that the clarity of the data meets the requirements for key content recognition through multi-dimensional detection, and then accurately locate the reasons for the lack of clarity. First, the system detects the clarity of the received real-time video data by combining edge sharpness analysis and texture detail extraction: the Sobel operator is used to calculate the edge gradient values ​​of key areas such as device outlines and instrument scales in the video frame. If the average gradient value is lower than the preset 0.25 (range 0-1, the higher the value, the clearer the edge), it is initially determined that the video clarity is not up to standard. At the same time, the signal-to-noise ratio calculation and feature frequency extraction algorithm are used for the audio data. If the signal-to-noise ratio of target audio such as human voices and equipment operation sounds is lower than 25 dB, or the signal strength of key frequencies (such as the 1000-2000 Hz band of the safety valve opening sound) is lower than the background noise, it is determined that the audio clarity is not up to standard.

[0027] If the clarity of the test results does not reach the preset threshold, the system will combine the front-end device deployment information, environmental monitoring data and device operation logs to conduct a cause analysis. The first step is to retrieve data from the temperature and humidity sensors and dust concentration monitors associated with the front-end device. If the ambient temperature corresponding to the camera in the boiler area exceeds 60 degrees Celsius and the humidity is higher than 85%, or the dust concentration around the camera in the coal conveying corridor exceeds 10 milligrams per cubic meter, it is primarily determined that "environmental factors have led to a decrease in clarity" (high temperature and humidity can easily cause the lens to fog up, and dust can easily adhere to the lens). The second step is to check the operating parameters of the front-end device itself. By checking the camera's focal length, aperture, infrared fill light intensity, and other configurations through the device management module, if the focal length deviates from the preset value by more than 5%, the aperture opening is less than 30%, or the infrared fill light is not activated, it is determined that "the device parameters are improperly configured". The third step is to combine the device maintenance records. If the camera's lens has not been cleaned for more than 30 days, or the microphone dustproof net has not been replaced on time, it is determined that "physical pollution caused by untimely device maintenance" is the cause. The fourth step is to check the data transmission link. By checking the packet loss rate and latency of the audio and video streams through the network monitoring module, if the packet loss rate exceeds 8% and the latency exceeds 150 milliseconds, it is determined that "the data distortion is caused by an unstable transmission link". Through the above-mentioned tiered investigation, the core reasons for the lack of clarity can be accurately identified, providing a basis for subsequent environmental adjustments and parameter optimization.

[0028] Implementation process of adjusting environmental control equipment parameters and verifying control effect After identifying the cause of the insufficient clarity, the system will match the corresponding environmental control equipment based on the cause type and generate a targeted parameter adjustment plan. If the cause is "high temperature and high humidity," the system will associate the industrial air conditioner and dehumidifier in that area, lowering the air conditioner's cooling temperature from the default 26 degrees Celsius to 22 degrees Celsius, increasing the dehumidifier's operating power from 50% to 80%, and simultaneously activating the lens temperature control device (maintaining the lens temperature between 25-30 degrees Celsius to prevent fogging due to temperature differences). If the cause is "excessive dust concentration," the system will activate the corresponding bag filter or high-pressure spray dust suppression equipment, increasing the dust collector's filtration velocity from 1.2 meters per minute to 1.5 meters per minute, shortening the spray frequency of the spray dust suppression equipment from 30 seconds / time to 15 seconds / time, and simultaneously activating the camera's built-in lens cleaning device to "high-frequency wiping mode." If the cause is "improper device parameter configuration", then adjust the front-end device parameters directly through the remote control module to restore the offset focal length to the preset reference value, adjust the aperture opening to 50%, and turn on infrared supplementary light (the supplementary light intensity is dynamically adjusted according to the ambient light intensity, such as setting the supplementary light intensity to 70% when the night light intensity is less than 50 lux); if the cause is "unstable transmission link", then coordinate with the network switch and router to upgrade the transmission bandwidth priority of this device from "normal" to "highest", and at the same time enable the backup 4G transmission channel to ensure that the packet loss rate of audio and video data transmission is controlled within 3%.

[0029] After parameter adjustments are completed, the system will initiate a closed-loop control process of "adjustment-detection-feedback" to ensure that the clarity meets the standards. First, the control environment adjustment equipment will run continuously for 5 minutes according to the adjusted working parameters (to ensure that the environment or equipment status is stable). Then, real-time audio and video data of the front-end device will be collected again, and the previous clarity detection process (edge ​​gradient value, audio signal-to-noise ratio, etc.) will be repeated. If the first retest shows that the clarity meets the standards (video edge gradient value ≥ 0.25, audio signal-to-noise ratio ≥ 25 dB), the current equipment parameters will be maintained, and the adjustment plan will be recorded in the "Clarity Optimization Case Library". If the retest still fails to meet the standards, the reasons will be analyzed again (such as whether there are multiple factors superimposed or insufficient parameter adjustment).

[0030] For example, if the lens still fogs up after the initial adjustment of the air conditioning temperature, the power of the lens temperature control device can be increased by 20%, and the dehumidifier's running time can be extended. If the dust concentration still exceeds the standard, the coverage area of ​​the spray dust suppression equipment can be increased, or maintenance personnel can be arranged to clean the lens on-site. The system will recheck every 5 minutes until the clarity of the image is shown to be up to standard after 3 consecutive tests, at which point the environmental adjustment operation will stop. If the image is still not up to standard after 10 consecutive adjustments, a level 1 alarm will be triggered, and a notification of "manual on-site intervention required" will be pushed to the maintenance terminal, along with a cause analysis report and preliminary handling suggestions, to ensure that the audio and video data always meet the subsequent analysis requirements.

[0031] Step S103: Determine the display area associated with the front-end device, and dynamically display the real-time key content and real-time audio and video data corresponding to the front-end device in the corresponding display area.

[0032] In this embodiment, the system first divides the display area according to the production management architecture of the thermal power plant: a main display wall is set up in the central control room, divided into four main display areas: "boiler system", "steam turbine system", "electrical system" and "auxiliary system"; independent display terminals are configured for each workshop operation and maintenance room to display real-time data of the production area of ​​their respective workshop; a lightweight display interface is set up for the mobile operation and maintenance APP, which supports quick retrieval of corresponding data by device ID or area name. At the same time, a mapping relationship of "front-end device ID-display area-display priority" is established in the system background. For example, "CAM-001 (#1 boiler) corresponds to the 'boiler system' area of ​​the main display wall, with a display priority of 'high' (25% screen area); CAM-101 (coal conveying corridor) corresponds to the 'auxiliary system' area, with a display priority of 'medium' (12.5% ​​screen area)".

[0033] During the data display phase, the system dynamically pushes real-time data according to preset rules: the main display wall adopts a "multi-screen split + key highlight" mode, displaying real-time audio and video data of high-priority equipment (such as boiler furnace images) in a large window, and simultaneously overlaying real-time key content (such as temperature and pressure values ​​floating in red numbers in the corner of the screen, and personnel violations marked with yellow boxes); the workshop operation and maintenance room display terminal adopts a "single-area full-screen + data list" mode, displaying real-time video of the corresponding area on the left, and listing key operating parameters of all equipment in that area in a table format on the right (such as equipment name, current status, and number of abnormal alarms); the mobile APP adopts an "on-demand loading" mode, after the user clicks the "#2 steam turbine" icon, the real-time video of the corresponding camera and the key content record of the past 10 minutes are immediately loaded (such as "10:05 steam turbine vibration value 6.5 mm / s, 10:10 vibration value dropped to 5.2 mm / s"). In addition, the system supports dynamic adjustment of the displayed content: when an abnormality occurs in a certain area (such as parsing "smoke in the fuel tank area"), the display priority of that area is automatically increased, its image is switched to the large window in the center of the main display wall, and a flashing reminder is triggered.

[0034] Step S104: Receive a control request applied to the target display area, and perform control operations on the corresponding thermal power plant generation area using the control equipment associated with the target display area based on the control request. The target display area is any one of multiple display areas.

[0035] First, maintenance personnel submit a control request to "increase the feedwater flow of boiler #1" by clicking the target display area (e.g., clicking the "#1 Boiler Water Level Adjustment" button in the "Boiler" area) on the touch panel of the main display wall. Workshop maintenance personnel input control commands via the keyboard of the display terminal (e.g., entering "reduce the speed of turbine #2 to 2980 rpm" on the "Turbine" terminal). Mobile users submit requests via the "Emergency Control" module of the app (e.g., clicking the "Emergency Shutdown" button to trigger the shutdown of feedwater pump #3). Upon receiving the request, the system first parses the request content: extracting the target display area (e.g., "boiler #1"), the control type (e.g., "parameter adjustment," "equipment start / stop," "emergency linkage"), and the specific control objective (e.g., "increase the feedwater flow from 200 tons per hour to 220 tons per hour").

[0036] In this embodiment of the application, the control equipment associated with the target display area performs control operations on the corresponding thermal power plant generation area based on control requirements, including the following steps A1-A4: Step A1: Obtain at least one target front-end device associated with the target display area; obtain the target thermal power plant production area where each target front-end device is deployed, and obtain a list of control devices associated with the target thermal power plant production area.

[0037] First, based on the target display area selected by the user (such as the "Boiler" area on the main display wall of the central control room), the list of associated target front-end devices is retrieved from the "Display Area - Front-end Devices" mapping table. This mapping table needs to be configured in advance according to the production architecture of the thermal power plant. For example, the "Boiler" display area is associated with the #1 boiler furnace camera (ID: CAM-001), the water-cooled wall tube temperature monitoring camera (ID: CAM-002), and the feedwater pump area audio collector (ID: MIC-001). Each front-end device is labeled with detailed information about its deployment location (such as "CAM-001 is deployed at the furnace observation hole on the east side of the 3rd floor of the #1 boiler, and the monitoring range covers the furnace flame and the upper part of the water-cooled wall tubes").

[0038] After acquiring the target front-end equipment, the target thermal power plant production area corresponding to each device is located through the "Front-end Equipment - Production Area" association module. For example, based on the deployment location information of CAM-001, its corresponding "#1 Boiler Furnace Area" is determined; based on the deployment record of MIC-001, its corresponding "#1 Boiler Feedwater Pump Room Area" is determined. Subsequently, the "Production Area - Controlled Equipment" database is retrieved to obtain a complete list of controlled equipment associated with the target production area. This database needs to store equipment information by region. For example, the controlled equipment associated with the "#1 Boiler Furnace Area" includes furnace pressure regulating valve (ID: VAL-001), flame detector (ID: DET-001), and emergency flameout device (ID: STOP-001); the controlled equipment associated with the "#1 Boiler Feedwater Pump Room Area" includes feedwater pump frequency converter (ID: INV-001), feedwater pump inlet and outlet valves (ID: VAL-002 / VAL-003), and pump room ventilator (ID: FAN-001). At the same time, the online status of the control equipment needs to be checked in real time. If a device is in an "offline" or "fault" state (such as "fault code E02" reported by VAL-001), the abnormal status needs to be marked in the list, and the associated backup device (such as the backup valve VAL-004 of VAL-001) needs to be added to ensure that there are devices with executable instructions available for selection during subsequent screening.

[0039] Step A2: Using device priority and operation logic, select the target controlled device from the list of controlled devices to execute the command.

[0040] First, load the preset equipment priority rules, which classify priority levels according to "safety impact degree - process relevance - operation response speed" (e.g., emergency flameout devices are prioritized as "Special Grade", pressure regulating valves as "Level 1", and ventilation fans as "Level 2"). For example, when the control requirement is "#1 boiler furnace pressure exceeds the standard", prioritize Special Grade equipment (emergency flameout devices) and Level 1 equipment (pressure regulating valves) from the list, and temporarily exclude Level 2 equipment (ventilators). Second, verify the rationality of equipment selection based on the operational logic of the thermal power plant's production process: for example, if "open the feedwater pump inlet and outlet valves (VAL-002 / VAL-003)" is selected, it is necessary to first confirm whether "feedwater pump frequency converter (INV-001)" has been included in the selection - because according to the process logic, it is necessary to ensure that the frequency converter is in an operational state before operating the valve to avoid the water pump failing to start after the valve is opened, resulting in pipeline pressure buildup. If a logical conflict is found (such as only screening valves and not frequency converters), the missing associated devices will be automatically added (INV-001 will be included in the target control device), and the logical correction process will be recorded in the background to facilitate subsequent rule optimization.

[0041] Furthermore, for devices with interdependent relationships (such as pressure regulating valves and flame detectors, which require simultaneous monitoring of flame status and adjustment of valve opening), all must be included in the target control devices. For devices with mutually exclusive relationships (such as inlet and outlet valves on the same pipeline, which cannot be closed simultaneously), a single executing device must be determined based on the control requirements (e.g., if the requirement is "stop the water supply pump," only the outlet valve VAL-003 should be closed, while the inlet valve VAL-002 should be slightly open to balance the pressure). After screening, a "Target Control Device List" is generated, marking the priority, operating logic, and current status of each device, providing a clear device foundation for subsequent parameter configuration and command generation.

[0042] Step A3: Determine the operation parameter configuration strategy based on the control requirements, and generate control instructions based on the operation parameter configuration strategy.

[0043] First, analyze the core objectives and constraints of the control requirements: For example, the control requirement is to "increase the water supply flow rate of the #1 boiler feedwater pump from 200 tons per hour to 220 tons per hour," the core objective is "increase the flow rate by 20 tons per hour," and the constraints include "the feedwater pump motor current does not exceed 20 amps" and "the outlet pressure does not exceed 1.2 MPa." Then, retrieve the technical parameter database of the target control equipment (feedwater pump frequency converter INV-001) to obtain the key operating thresholds (such as "the frequency converter's rated frequency is 50 Hz, corresponding to a maximum flow rate of 250 tons per hour; for every 1 Hz increase in frequency, the flow rate increases by 5 tons per hour; the rated current is 20 amps, corresponding to a frequency of 50 Hz"). Preliminary calculations of the operating parameters are then performed: to increase the flow rate by 20 tons per hour, the frequency converter frequency needs to be increased from the current 40 Hz (200 tons per hour ÷ 5 tons per hour = 40 Hz) to 44 Hz (220 tons per hour ÷ 5 tons per hour = 44 Hz).

[0044] Next, based on the real-time operating data of the target production area, the operating parameters are verified and optimized: by collecting real-time key information from the front-end equipment (CAM-002 and MIC-001), the "current feedwater pump motor current 16A" and "outlet pressure 1.0 MPa" are obtained, both of which are lower than the constraint thresholds (20 amps and 1.2 MPa), and the preliminary parameter (44 Hz) is deemed feasible; if the real-time data shows "current has reached 19 amps", then the parameters need to be adjusted, and the frequency increase should be reduced to 3 Hz (flow rate increase of 15 tons per hour) to avoid the current exceeding the standard. Meanwhile, referring to the historical operation case library, if in the past "increasing the frequency from 40 Hz to 44 Hz" caused the motor vibration value to rise to 8 mm / s (normal ≤ 6 mm / s), then the parameter is supplemented as follows: "For every 1 Hz increase, maintain operation for 10 seconds, monitor the vibration value, and if it exceeds 6 mm / s, pause the adjustment", forming a complete operation parameter configuration strategy: "The frequency of the inverter INV-001 is gradually increased from 40 Hz to 44 Hz, with a step size of 1 Hz / time. After each step, maintain for 10 seconds, monitor the motor current (≤20A), outlet pressure (≤1.2 MPa), and vibration value (≤6 mm / s). If the target is met, continue to the next step; if the target is not met, adjust back by 0.5 Hz."

[0045] Based on the operational parameter configuration strategy, standardized control instructions are generated. The instruction format must include "Device ID, Operation Type, Specific Parameters, Execution Sequence, Monitoring Indicators, and Anomaly Handling Rules." For example, the instruction for INV-001 is: "Device ID: INV-001; Operation Type: Frequency Adjustment; Parameters: Initial 40 Hz, Target 44 Hz, Step Size 1 Hz; Execution Sequence: 10-second interval between each step; Monitoring Indicators: Current ≤ 20A, Pressure ≤ 1.2 MPa, Vibration ≤ 6 mm / s; Anomaly Handling: If any indicator exceeds the limit, immediately revert to 0.5 Hz and issue an alarm." For multi-device linkage instructions (such as "Open pressure regulating valve VAL-001 + monitor flame detector DET-001"), the order of device operation must be clearly specified in the instruction (e.g., "First increase the opening of VAL-001 from 30% to 40%, then start DET-001 flame intensity monitoring after 5 seconds, and provide data feedback every 2 seconds") to avoid safety risks caused by chaotic operation sequences.

[0046] Step A4: Send the control command to the target control device through the industrial control network, obtain the execution result fed back by the target control device, and update the target display area simultaneously with the execution result.

[0047] In this embodiment, determining the operational parameter configuration strategy based on control requirements includes: determining the types of key parameters to be regulated based on control requirements; determining the allowable adjustment range of each equipment parameter based on the key parameter types and the equipment configuration information of the target controlled equipment; determining the initial parameter adjustment value within the allowable adjustment range based on the difference between the real-time operating data of the target thermal power plant production area and the expected value corresponding to the control requirements; verifying and correcting the initial parameter adjustment value based on the correlation constraints between equipment parameters; and integrating the corrected parameter adjustment value according to the equipment control protocol format to obtain the parameter configuration strategy.

[0048] Based on the core objectives of the control requirements (such as "reducing the furnace temperature of boiler #1 to 500 degrees Celsius" and "increasing the turbine speed to 3000 rpm"), the key parameter types that need to be controlled are identified: if the requirement is temperature regulation, key parameters include furnace burner power, feedwater flow, and induced draft; if the requirement is speed control, key parameters include turbine inlet valve opening and steam pressure. After determining the parameter types, the system retrieves the configuration information of the target control equipment (such as burner model parameters and valve technical manuals), and, in conjunction with the thermal power plant's production process standards, defines the allowable adjustment range for each parameter: for example, the safe operating range for boiler #1 burner power is 30%-90% (corresponding to a temperature of 300-600 degrees Celsius), and the allowable opening of the inlet valve is 0-80% (to avoid overpressure). Furthermore, the step size limits for parameter adjustments are clearly defined (such as burner power adjustments not exceeding 5% each time, and valve opening adjustments not exceeding 10% each time), ensuring that parameter adjustments are within the dual constraints of equipment tolerance and process safety.

[0049] Based on real-time operating data of the target production area (e.g., current furnace temperature 550 degrees Celsius, turbine speed 2900 rpm) and expected control requirements (500 degrees Celsius, 3000 rpm), the difference between the two is calculated (temperature difference -50 degrees Celsius, speed difference +100 rpm), and the initial parameter adjustment values ​​are determined within the allowable adjustment range. For example, to reduce the temperature by 50 degrees Celsius, based on the historical curve that "a 10% decrease in burner power corresponds to a temperature decrease of 80 degrees Celsius," the burner power is initially set to decrease from the current 70% to 63% (a 7% decrease, with an expected temperature drop of 56 degrees Celsius); to increase the speed by 100 rpm, based on the relationship that "a 5% increase in valve opening corresponds to a 200 rpm increase in speed," the valve opening is initially set to increase from the current 50% to 52.5% (an increase of 2.5%). Subsequently, based on parameter-related constraints (such as the need to simultaneously increase induced draft by 10% to avoid incomplete combustion when burner power decreases), the initial values ​​were verified and corrected: the induced draft was adjusted from the current 40% to 44%, and it was confirmed that the combination of burner power of 63% and induced draft of 44% showed no abnormal fluctuations in historical operating data. Finally, according to the equipment control protocol, the corrected parameters (power 63%, induced draft 44%, valve opening 52.5%) were converted into a standardized format (including register address, data type, and checksum), and integrated to form a parameter configuration strategy that can be directly used for instruction generation.

[0050] In the embodiments of this application, such as Figure 2 As shown, the method also includes: Step S201: Compare the real-time key content with the hidden danger characteristics recorded in the historical safety accident database to obtain the current potential hidden danger types and their corresponding occurrence probabilities.

[0051] First, a pre-established database of historical safety incidents is acquired and stored, categorized by "hazard type - multi-dimensional features - quantification threshold - historical cases." For example, for the hazard of "boiler superheater tube rupture," video features (reddish tube wall color, localized deformation), equipment parameter features (outlet temperature exceeding 450 degrees Celsius, pressure fluctuation ≥ 0.3 MPa), and audio features (high-frequency abnormal noise before the abnormal rupture sound) need to be recorded. This is then correlated with the frequency of accidents under different combinations of features in historical cases (e.g., when the temperature is 450-460 degrees Celsius and the pressure fluctuation is 0.3-0.5 MPa, tube rupture occurred in 15 out of 100 records). The database is updated monthly to include newly occurring hazard handling data, ensuring comprehensive feature coverage.

[0052] During the comparison phase, quantitative parameters such as temperature, pressure, and vibration were extracted from equipment operation data (e.g., "Current outlet temperature of superheater #3 is 455 degrees Celsius, pressure fluctuation is 0.4 MPa"), equipment appearance features were extracted from video data (e.g., "Local dark red pipe wall with no obvious deformation"), and abnormal sound features were extracted from audio data (e.g., "A continuous high-frequency abnormal sound of 2500 Hz was detected"). Subsequently, a "weighted feature matching algorithm" was used to compare real-time features with potential hazard features in the database: weights were assigned to each feature dimension (temperature matching 0.3, pressure fluctuation 0.3, video features 0.2, audio features 0.2), and a comprehensive matching score was calculated—if the temperature of 455 degrees Celsius falls within the "superheater tube rupture" temperature threshold range (450-470 degrees Celsius), 0.9 points are awarded; if the pressure fluctuation of 0.4 MPa matches the threshold, 0.8 points are awarded; if the video features partially match, 0.6 points are awarded; and if the audio features completely match, 1.0 points are awarded.

[0053] The overall score is calculated as follows: 0.9 × 0.3 + 0.8 × 0.3 + 0.6 × 0.2 + 1.0 × 0.2 = 0.27 + 0.24 + 0.12 + 0.2 = 0.83. When the overall score is ≥ 0.6, a corresponding hazard type is identified. Combining this with the probability of accidents occurring within the same score range in historical cases (e.g., 18 out of 100 records of pipe bursts within the 0.8-0.9 score range), the probability of the current hazard is calculated to be 18%. If real-time features match multiple hazards (e.g., simultaneously matching "superheater pipe burst" and "pipe blockage"), the overall score and probability of each hazard are calculated separately. A "potential hazard list" containing feature matching details and calculation basis is generated, ordered from highest to lowest probability, to provide data support for subsequent prevention and control measures.

[0054] Step S202: Based on the probability of occurrence of potential hazard types and the estimated scope of impact, determine the corresponding level of pre-control measures and the corresponding control equipment.

[0055] The probability of occurrence is divided into three levels: high (≥60%), medium (30%-60%), and low (<30%). The estimated impact range is quantified according to production factors (0.2 for a single piece of equipment, 0.5 for a single system, 0.8 for cross-system production, and 1.0 for personnel safety). The risk value = probability × impact range, corresponding to three levels: high risk (≥0.6), medium risk (0.3-0.6), and low risk (<0.3). For example, the risk value of "#3 boiler superheater tube rupture (probability 18%, impact range 0.8)" is 0.18 × 0.8 = 0.14, which is judged as low risk; the risk value of "combustible gas leakage in the fuel tank area (probability 70%, impact range 1.0)" is 0.7 × 1.0 = 0.7, which is judged as high risk.

[0056] Subsequently, the system matches the level of pre-control measures and the controlled equipment according to the risk level: High risk corresponds to "emergency pre-control", which requires triggering equipment linkage within 10 seconds, linking emergency shut-off valves, audible and visual alarms and other equipment (such as linking VAL-501 emergency shut-off valve and ALM-501 audible and visual alarm when there is a leak in the fuel tank area). Medium risk corresponds to "routine pre-control", which requires parameter adjustment to be initiated within 1 minute, and related equipment such as frequency converters and regulating valves (e.g., when the turbine vibration exceeds the standard, the INV-301 speed frequency converter is linked). Low risk corresponds to "observation and prevention," which requires continuous data monitoring and the use of related sensors, recorders, and other equipment (e.g., when the risk of a superheater tube rupture is low, the SEN-301 temperature sensor should be used).

[0057] Simultaneously, the system verifies the status of controlled equipment: if VAL-501 associated with a high-risk hazard is faulty, the pre-control level is immediately upgraded to "Special Level," a backup valve VAL-502 is added, and an equipment maintenance alarm is pushed; if sensor data associated with a low-risk hazard fluctuates greatly, the sampling frequency is automatically increased to once every 30 seconds. Finally, a "Pre-control Measures - Controlled Equipment" list is generated, marking equipment priorities (e.g., emergency shut-off valves are "mandatory," alarms are "auxiliary"), ensuring that operations focus on core equipment.

[0058] Step S203: Based on the execution rules corresponding to the level of pre-control measures, the potential hazard type and its corresponding probability of occurrence are converted into preventive control instructions containing specific operating parameters, and the preventive control instructions are issued to the control equipment so that the control equipment can intervene in advance according to the preventive control instructions.

[0059] First, the system breaks down operational requirements according to the execution rules of the pre-control measures level: high-risk "emergency pre-control" requires operation according to the "early warning-isolation-hazard elimination" sequence (e.g., when there is a leak in the fuel tank area, first activate the ALM-501 audible and visual alarm, then close the VAL-501 shut-off valve after 3 seconds, and then start the FAN-501 explosion-proof fan after 5 seconds); medium-risk "routine pre-control" requires operation according to the "adjustment-monitoring-stabilization" logic (e.g., when the turbine vibration exceeds the standard, first reduce the speed of INV-301, and then monitor the vibration value through SEN-302); low-risk "observation pre-control" requires operation according to the "sampling-analysis-early warning" process (e.g., when the superheater is at low risk, SEN-301 samples once every 1 minute, and triggers an early warning if the standard is exceeded).

[0060] During the parameter calculation phase, the system determines specific operating values ​​by combining equipment technical parameters and process standards. For example, the shut-off valve VAL-501 needs to close within 3 seconds. Based on its parameter of "pneumatic drive, closing time 2 seconds," the instruction is set to "start 1 second in advance to ensure it is in place within 3 seconds." INV-301 needs to reduce its rotation speed from 3000 rpm to 2950 rpm. Referring to the characteristic of "10 seconds for every 10 rpm reduction," the instruction is set to "10 rpm step, 10-second interval, 5 steps in total." Standardized instructions are then generated, including the equipment ID, operation type, parameters, timing, and exception rules (e.g., "VAL-501: Close, time limit 3 seconds, if timeout, start VAL-502"). Instructions are issued using industrial Ethernet + 4G dual links to ensure reliable transmission. After the equipment executes the instruction, its status is fed back in real time (e.g., "VAL-501 is closed, current pressure 0 MPa"). The system compares the results with expectations; if the target is met, it records "intervention effective"; otherwise, it triggers a retry or manual intervention. At the same time, the instruction content, execution process, and feedback results are stored in the log and the historical database is updated.

[0061] In the embodiments of this application, such as Figure 3 As shown, the method also includes: Step S301: Determine the regional safety status of the thermal power plant's production area based on real-time key information.

[0062] First, key data is collected in real time using various sensors deployed within the power plant's production area. This includes, but is not limited to, data on temperature and pressure in the boiler room, vibration frequency in the turbine building, current and voltage in the power distribution room, and the concentration of combustible gases in the fuel storage area. Simultaneously, real-time alarm information from the production monitoring system, such as equipment fault alarms and pipeline leak warnings, is also collected. Then, the collected real-time data is compared one by one with preset safety thresholds for each area. If any key data in a certain area exceeds the threshold, or if there is an unresolved valid alarm, the area is determined to be in an unsafe state. If all key data are within the safety threshold range and there are no valid alarms, the area is determined to be in a safe state.

[0063] Step S302: The thermal power plant production area with an unsafe status is designated as the abnormal thermal power plant production area. The real-time distribution of affected personnel in the abnormal thermal power plant production area is then determined, and the optimal evacuation route is determined based on the real-time distribution and the area map of the abnormal thermal power plant production area.

[0064] First, thermal power plant production areas with an unsafe status are identified and defined as abnormal thermal power plant production areas. Then, using personnel-worn positioning terminals, AI positioning functions from video surveillance within the area, and real-time entry and exit records from the access control system, the specific locations of affected personnel within the abnormal area are determined, creating a real-time personnel distribution chart. Next, a high-precision electronic map of the abnormal area is retrieved, marking key information such as safety exits, evacuation route widths, temporary refuge areas, and hazard locations. Combined with the real-time personnel distribution, a path planning algorithm (such as the A* algorithm) is used to plan optimal evacuation routes for affected personnel in different locations, either individually or in groups, with the goals of "shortest evacuation time, avoiding hazard sources, and avoiding route congestion." The length of each route, the estimated evacuation time, and key nodes along the route are clearly defined.

[0065] Step S303: Determine the guidance equipment and area control equipment along the optimal evacuation route.

[0066] The equipment ledger in the thermal power plant's equipment management system is retrieved. Based on the specific direction and coverage of the optimal evacuation route, all equipment within a 5-10 meter range along the route is selected. Then, based on the equipment's functional attributes, the selected equipment is divided into two categories: guidance equipment (such as emergency indicator lights, voice broadcasters, and LED evacuation signs) and area control equipment (such as fire doors, roller shutters, and smart turnstiles). Subsequently, the real-time operating status of these devices is queried through the equipment IoT platform to eliminate faulty, offline, or uncontrollable equipment. Finally, a list of effective equipment that can be used for evacuation guidance and area control is determined, and the specific location and function of each device in the route are marked.

[0067] Step S304: Calculate the control parameters of the guidance equipment and the area control equipment using the movement speed of the affected personnel and the equipment response time.

[0068] First, basic information such as age, position, and physical condition of affected personnel is obtained from the thermal power plant personnel information system. Combined with historical evacuation drill data, the average movement speed of different personnel groups is determined (e.g., young employees approximately 1.2 m / s, elderly employees approximately 0.8 m / s). Then, the standard response time of guidance equipment and area control equipment is retrieved from the equipment management system (e.g., emergency indicator light activation response time ≤ 0.5 seconds, fire door closing response time ≤ 2 seconds). Finally, based on personnel movement speed, equipment response time, and distance between nodes along the evacuation route, the trigger time of guidance equipment (e.g., triggering a voice broadcast at a node 5 seconds in advance if personnel are expected to arrive at a node in 20 seconds), the displayed content (e.g., "Evacuate to the right →"), and the action time (e.g., closing fire doors 10 seconds after all personnel have evacuated) and action range (e.g., roller shutter doors fully lowered) of area control equipment are calculated.

[0069] Step S305: Send control parameters to the corresponding guidance equipment and area control equipment, and track and display the evacuation progress of the affected personnel in real time. Once the evacuation is confirmed, trigger the area isolation operation.

[0070] In this embodiment, the control parameters of the guidance equipment and the area control equipment are calculated using the movement speed of the affected personnel and the response time of the equipment. This includes: determining the baseline movement speed of different personnel based on their type within the abnormal thermal power plant production area; calculating the time required for the affected personnel to reach the key nodes of each section of the optimal evacuation route from their current location based on the length of each section and the baseline movement speed of the personnel in that section; determining the standard response time of various types of equipment based on the equipment parameters of the guidance equipment and the area control equipment; calculating the advance start time of the guidance equipment and the area control equipment based on the time required for personnel to reach the key nodes and the equipment response time; and determining the action duration of the guidance equipment and the area control equipment in conjunction with the evacuation requirements; and determining the control parameters based on the advance start time and the action duration.

[0071] Specifically, firstly, the personnel information system of the thermal power plant is used to retrieve the type information of affected personnel in the abnormal area. This information is categorized by age (e.g., young, middle-aged, elderly), job position (e.g., front-line operators, administrative staff, technical maintenance personnel), and physical condition (e.g., whether they have mobility impairments). Based on historical evacuation drill data and industry standards, a corresponding baseline movement speed is set for each type of personnel. For example, the baseline movement speed for young front-line employees is 1.3 m / s, and for elderly administrative staff it is 0.7 m / s. Next, the optimal evacuation route is broken down into multiple continuous segments. The specific length of each segment is extracted from the electronic map, and then the type of affected personnel and their corresponding baseline movement speed are matched within each segment. Using the formula "segment length ÷ baseline movement speed," the time required for different personnel to reach key nodes in each segment (e.g., intersections, 5 meters before safety exits) from their current location is calculated, and a time statistics table is generated.

[0072] Subsequently, equipment parameters for guidance equipment (such as emergency indicator lights and voice broadcasters) and area control equipment (such as fire doors and roller shutters) are retrieved from the power plant's equipment management system to determine the standard response time for each type of equipment. For example, the standard response time for emergency indicator lights is 0.3 seconds, and the standard response time for fire doors is 1.8 seconds. Using the arrival time of personnel at critical points as a benchmark, the advance start-up time of the equipment is calculated using "personnel arrival time at critical points - equipment standard response time" to ensure that the equipment is started and operational before personnel arrive. Simultaneously, considering evacuation needs and the estimated total time for personnel to pass through the section, the action duration of the guidance equipment (e.g., voice broadcasters continuously broadcast until all personnel have passed through the section) and the action duration of the area control equipment (e.g., fire doors remain open until all personnel have passed through before closing) are determined. Finally, the advance start-up time and action duration are integrated to form complete control parameters for the guidance equipment and area control equipment.

[0073] This embodiment also provides a management platform for safe production in thermal power plants. This device is used to implement the above embodiments and preferred embodiments, and details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0074] This embodiment provides a management platform for safe production in thermal power plants, such as... Figure 4 As shown, it includes: The acquisition module 401 is used to acquire real-time audio and video data collected by different front-end devices, which are deployed in various key locations in the production area of ​​the thermal power plant. The parsing module 402 is used to parse the corresponding real-time audio and video data according to the parsing strategy of the front-end device to obtain the real-time key content of the corresponding thermal power plant generation area. The determination module 403 is used to determine the display area associated with the front-end device and dynamically display the real-time key content and real-time audio and video data corresponding to the front-end device in the corresponding display area; The control module 404 is used to receive control commands applied to the target display area, and to perform control operations on the corresponding thermal power plant generation area by the control equipment associated with the target display area based on the control commands. The target display area can be any one of multiple display areas.

[0075] In this embodiment, the device further includes: a verification module for detecting the clarity of real-time audio and video data; if the clarity does not reach a preset threshold for identifying key content, analyzing the reasons why the clarity does not reach the preset threshold; adjusting the equipment operating parameters of the environmental control equipment in the corresponding thermal power plant production area according to the reasons; and controlling the environmental control equipment to perform environmental control according to the equipment operating parameters until the clarity of the real-time audio and video data collected by the front-end equipment in the corresponding thermal power plant production area reaches the preset threshold.

[0076] In this embodiment, the control module 404 is used to acquire at least one target front-end device associated with the target display area; acquire the target thermal power plant production area deployed by each target front-end device, and acquire a list of control devices associated with the target thermal power plant production area; select target control devices that need to execute instructions from the list of control devices using device priority and operation logic; determine the operation parameter configuration strategy according to control requirements, and generate control instructions based on the operation parameter configuration strategy; send the control instructions to the target control devices through the industrial control network, acquire the execution results fed back by the target control devices, and synchronously update the target display area with the execution results.

[0077] In this embodiment, the control module 404 is used to determine the types of key parameters to be regulated according to the control requirements; determine the allowable adjustment range of each equipment parameter according to the key parameter types and the equipment configuration information of the target control equipment; determine the initial parameter adjustment value within the allowable adjustment range according to the difference between the real-time operation data of the target thermal power plant production area and the expected value corresponding to the control requirements; verify and correct the initial parameter adjustment value according to the correlation constraints between the equipment parameters, and integrate the corrected parameter adjustment value according to the equipment control protocol format to obtain the parameter configuration strategy.

[0078] In this embodiment of the application, the device further includes: a comparison module, used to compare real-time key content with the hidden danger characteristics recorded in the historical safety accident database to obtain the currently existing potential hidden danger types and their corresponding occurrence probabilities; based on the occurrence probability and estimated impact range of the potential hidden danger types, to determine the corresponding pre-control measure level and the corresponding control equipment; and based on the execution rules corresponding to the pre-control measure level, to convert the potential hidden danger types and their corresponding occurrence probabilities into preventive control instructions containing specific operating parameters, and to issue the preventive control instructions to the control equipment so that the control equipment can intervene in advance according to the preventive control instructions.

[0079] In this embodiment, the device further includes: a planning module, used to determine the regional safety status of the thermal power plant production area based on real-time key information; to identify thermal power plant production areas with an unsafe regional safety status as abnormal thermal power plant production areas, and to determine the real-time distribution of affected personnel in the abnormal thermal power plant production areas, and to determine the optimal evacuation route based on the real-time distribution and the regional map of the abnormal thermal power plant production area; to determine the guiding equipment and regional control equipment along the optimal evacuation route; to calculate the control parameters of the guiding equipment and regional control equipment using the movement speed of the affected personnel and the response time of the equipment; to send the control parameters to the corresponding guiding equipment and regional control equipment, and to track and display the evacuation progress of the affected personnel in real time, and to trigger the regional isolation operation after confirming that all evacuations have been completed.

[0080] In this embodiment, the planning module is used to determine the baseline movement speed corresponding to different personnel based on the type of affected personnel within the abnormal thermal power plant production area; calculate the time required for affected personnel to reach key nodes of each section of the optimal evacuation route from their current location based on the length of each section and the baseline movement speed of personnel in the corresponding section; determine the standard response time of various types of equipment based on the equipment parameters of the guidance equipment and the area control equipment; calculate the advance start time of the guidance equipment and the area control equipment based on the time required for personnel to reach key nodes and the equipment response time, and determine the action duration of the guidance equipment and the area control equipment in combination with evacuation requirements; and determine control parameters based on the advance start time and the action duration.

[0081] Please see Figure 5 , Figure 5 This is a schematic diagram of the structure of a computer device provided in an optional embodiment of the present invention, such as... Figure 5 As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system).

[0082] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0083] The memory 20 stores instructions executable by at least one processor 10 to cause the at least one processor 10 to perform the method shown in the above embodiments.

[0084] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device as shown by a landing page for an app. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, which can be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0085] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0086] The computer device also includes a communication interface 30 for communicating with other devices or communication networks.

[0087] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods shown in the above embodiments.

[0088] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A management method for safe production of a thermal power plant, characterized in that, The method comprises: acquiring real-time audio and video data collected by different front-end devices, wherein the front-end devices are deployed at key positions in a power plant production area; analyzing the corresponding real-time audio and video data according to the analysis strategy corresponding to the front-end device to obtain real-time key content of the corresponding power plant production area; determining a display area associated with the front-end device and dynamically displaying the real-time key content and real-time audio and video data corresponding to the front-end device in the corresponding display area; receiving a control requirement acting on a target display area, and based on the control requirement, controlling a control device associated with the target display area to perform a control operation on the corresponding power plant production area, wherein the target display area is any one of a plurality of display areas.

2. The method of claim 1, wherein, Before analyzing the corresponding real-time audio and video data according to the analysis strategy corresponding to the front-end device, the method further comprises: detecting the clarity of the real-time audio and video data; if the clarity does not reach a preset threshold for identifying key content, analyzing the reason why the clarity does not reach the preset threshold; adjusting the device working parameters of the environmental regulation device of the corresponding power plant production area according to the reason; controlling the environmental regulation device to perform environmental regulation according to the device working parameters until the clarity of the real-time audio and video data collected by the front-end device in the corresponding power plant production area reaches the preset threshold.

3. The method of claim 1, wherein, The control operation performed by the control device associated with the target display area on the corresponding power plant production area based on the control requirement comprises: acquiring at least one target front-end device associated with the target display area; acquiring a target power plant production area to which each target front-end device is deployed, and acquiring a list of control devices associated with the target power plant production area; using device priority and operation logic to filter out target control devices that need to execute instructions from the list of control devices; determining an operation parameter configuration strategy according to the control requirement, and generating a control instruction based on the operation parameter configuration strategy; sending the control instruction to the target control device through an industrial control network, and acquiring an execution result fed back by the target control device, and synchronously updating the execution result to the target display area.

4. The method of claim 3, wherein, The determination of the operation parameter configuration strategy according to the control requirement comprises: determining a key parameter type to be regulated according to the control requirement; determining an allowed adjustment range of each device parameter according to the key parameter type and device configuration information of the target control device; determining an initial parameter adjustment value within the allowed adjustment range according to the difference between the real-time running data of the target power plant production area and the corresponding expected value of the control requirement; verifying and correcting the initial parameter adjustment value according to the associated constraints between device parameters, and integrating the corrected parameter adjustment value according to a device control protocol format to obtain a parameter configuration strategy.

5. The method of claim 1, wherein, The method further comprises: comparing the real-time key content with hidden danger characteristics recorded in a historical safety accident database to obtain a type of potential hidden danger currently existing and a corresponding occurrence probability; determining a corresponding pre-control measure level and corresponding control device according to the occurrence probability and estimated influence range of the type of potential hidden danger; According to the execution rule corresponding to the pre-control measure level, the potential hazard type and the corresponding occurrence probability are converted into preventive control instructions containing specific operation parameters, and the preventive control instructions are issued to the management and control equipment, so that the management and control equipment performs early intervention according to the preventive control instructions.

6. The method of claim 1, wherein, The method further comprises: determining the area security state of the thermal power plant production area according to the real-time key content; regarding the thermal power plant production area with the non-safe state as an abnormal thermal power plant production area, determining the real-time distribution of the affected personnel in the abnormal thermal power plant production area, and determining the optimal evacuation path according to the real-time distribution and the area map of the abnormal thermal power plant production area; determining the guiding equipment and the area management and control equipment along the optimal evacuation path; calculating the control parameters of the guiding equipment and the area management and control equipment by using the personnel moving speed of the affected personnel and the equipment response time; sending the control parameters to the corresponding guiding equipment and area management and control equipment, and tracking and displaying the evacuation progress of the affected personnel in real time, and triggering the area isolation operation when all the evacuations are confirmed.

7. The method of claim 6, wherein, The calculation of the control parameters of the guiding equipment and the area management and control equipment by using the personnel moving speed of the affected personnel and the equipment response time comprises: determining the reference moving speed corresponding to different personnel according to the type of the affected personnel in the abnormal thermal power plant production area; calculating the time required for the affected personnel to reach the key nodes of each section from the current position according to the length of each section of the optimal evacuation path and the reference moving speed of the personnel on the corresponding section; determining the standard response time of each type of equipment according to the equipment parameters of the guiding equipment and the area management and control equipment; calculating the early start time of the guiding equipment and the area management and control equipment according to the time required for the personnel to reach the key nodes and the equipment response time, and determining the action duration of the guiding equipment and the area management and control equipment in combination with the evacuation demand; determining the control parameters based on the early start time and the action duration.

8. A management platform for safe production of a thermal power plant, characterized in that, The platform comprises: an acquisition module configured to acquire real-time audio and video data collected by different front-end devices, wherein the front-end devices are deployed at key positions in the thermal power plant production area; an analysis module configured to analyze the corresponding real-time audio and video data according to the analysis strategy corresponding to the front-end device to obtain the real-time key content of the corresponding thermal power plant production area; a determination module configured to determine the display area associated with the front-end device and dynamically display the real-time key content and real-time audio and video data corresponding to the front-end device in the corresponding display area; a control module configured to receive a management and control instruction acting on a target display area, and perform a management and control operation on the corresponding thermal power plant production area based on the management and control instruction of the management and control equipment associated with the target display area, wherein the target display area is any one of the plurality of display areas.

9. A computer device, comprising: comprises: A memory and a processor, which are connected in communication with each other, the memory storing computer instructions, and the processor executing the computer instructions to perform the method of any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions for causing a computer to perform the method of any one of claims 1 to 7.

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