Multi-parameter intelligent control and safety evaluation system and method for thermal power generating unit

Abstract

The invention relates to the field of thermal power generating unit safety evaluation emerging software technology service, and discloses a thermal power generating unit multi-parameter intelligent control and safety evaluation system and method, and the system comprises a central processor, and a safety situation sensing module, a real-time alarm module and a visual display module which are connected with the central processor. A safety assessment grade table is preset in the central processing unit, and the central processing unit is used for receiving sensing information of the safety situation sensing module, comparing standard values of corresponding parameter items in the safety assessment grade table, judging whether the corresponding safety sensing items are abnormal or not, and if yes, giving an alarm through the real-time alarm module. And at the same time, the visual display module marks abnormal items for display. According to the invention, safe, stable and efficient operation of the thermal power generating unit can be realized, and visual, quantifiable and refined management of field operation can be realized.

Description

Technical Field

[0001] The present invention relates to the emerging software technology service field of thermal power unit safety assessment, and in particular to a multi-parameter intelligent management and control and safety assessment system for thermal power units. Background Art

[0002] Thermal power units are large-scale power generation facilities that utilize the heat released by the combustion of fossil fuels (such as coal, oil, and natural gas) to generate electricity through a series of energy conversion processes. They primarily consist of core equipment such as boilers, steam turbines, and generators. They play a crucial role in the modern power supply system and are a key force in ensuring the electricity needs of society, both production and daily life.

[0003] Safety assessments are crucial for ensuring reliable operation in the operational management of thermal power units. Existing safety assessments have played a role in ensuring this. For example, regular physical checks of individual equipment or local systems, along with monitoring of key operating parameters, are conducted to identify potential equipment failures or operational anomalies. For example, non-destructive testing of boiler heating surface tubes is performed to check for defects such as cracks and corrosion. Turbine vibration and oil temperature are monitored, with alerts issued when any parameters exceed normal ranges.

[0004] However, with the continuous development of thermal power unit technology and the increasing complexity of the operating environment, the limitations of existing safety assessments have become increasingly prominent, mainly manifested in the following aspects:

[0005] 1. The presentation of evaluation results is not intuitive

[0006] Existing assessment systems typically display monitoring results through simple data reports or static charts, lacking effective visualization. For example, abnormal furnace tube temperature is only indicated by a numerical value exceeding the standard, without visually displaying the specific location and severity of the abnormal area. This makes it difficult for maintenance personnel to accurately and promptly identify the problem.

[0007] 2. Inaccurate evaluation structure

[0008] Traditional assessment methods often rely on single-parameter thresholds, failing to fully consider the interplay between multiple parameters. For example, abnormal equipment temperature may involve multiple factors, such as the cooling system and load variations. However, existing systems are unable to comprehensively analyze these interrelated factors, resulting in deviations between assessment results and actual conditions.

[0009] 3. The evaluation process is seriously delayed

[0010] Existing assessment systems lack a connection between data collection and analysis. After an abnormal event occurs, historical data must be manually retrieved for retrospective analysis, resulting in significant response delays. For example, when a device anomaly is detected, relevant operating parameters cannot be correlated in real time for analysis, delaying the optimal time for fault diagnosis and resolution.

[0011] In terms of safety and protection, existing assessment systems also have significant shortcomings. They lack the ability to comprehensively analyze multi-dimensional data, such as equipment operating status, resulting in inaccurate assessments when faced with complex operating conditions. Furthermore, data from different monitoring systems is isolated, making it difficult to form a comprehensive assessment basis.

[0012] For the condition assessment of key equipment, traditional methods are often limited to regular inspections and simple parameter monitoring, and cannot achieve real-time and comprehensive condition assessment.

[0013] Furthermore, existing assessment systems face difficulties in data integration. Different monitoring devices and systems use independent data formats and communication protocols, making it difficult to effectively integrate the data needed for assessment, thus affecting the comprehensiveness and accuracy of the assessment.

[0014] Therefore, the existing thermal power unit safety assessment system has obvious deficiencies in terms of visualization effect, assessment accuracy and real-time performance. It is urgent to improve the existing assessment system and methods to better meet the needs of modern thermal power unit operation and management. Summary of the Invention

[0015] The present invention aims to provide a multi-parameter intelligent management and control and safety assessment system for thermal power units to solve the current problem of being unable to perform global assessment.

[0016] In order to solve the above problems, the present invention adopts the following technical solutions:

[0017] Solution 1: A multi-parameter intelligent management and safety assessment system for thermal power units, comprising a central processing unit (CPU), a safety situation awareness module, a real-time alarm module, and a visual display module, each connected to the CPU. The CPU is pre-installed with a safety assessment level table, which receives perception information from the safety situation awareness module, compares it with the standard value of the corresponding parameter item in the safety assessment level table, and determines whether the corresponding safety perception item is abnormal. If abnormal, the real-time alarm module issues a warning, and the visual display module simultaneously displays the abnormal item.

[0018] The visual display module is used to dynamically display the following content:

[0019] A 3D panoramic simulation model of the entire plant supports interactive operations and marks risk points, hidden danger distribution, and personnel trajectories;

[0020] The grid-based hierarchical management interface displays regional risk maps and core indicators at multiple levels.

[0021] Through monitoring by the security situation awareness module, assessment and judgment by the central processing unit, and alerts from the real-time alarm module, anomalies can be promptly detected and warned. The visualization display module uses a three-dimensional panoramic simulation model of the entire plant and a grid-based hierarchical management interface to dynamically display risk points, hidden dangers, personnel trajectories, and regional core indicators. This allows staff to intuitively grasp the situation, achieve efficient and intelligent management and control, and improve the operational safety and management efficiency of thermal power units.

[0022] Preferably, the visual display module is used to dynamically display the following content:

[0023] Personnel positioning and operation supervision interface, linked access control, vital signs monitoring and camera tracking functions;

[0024] Confined space operation monitoring data and electronic fence control status in key areas.

[0025] The visual display module uses the personnel positioning and operation supervision interface to link access control, vital signs monitoring and camera tracking, so as to grasp personnel location, movement trajectory and operation status in real time and ensure personnel safety. At the same time, it displays the monitoring data of confined space operations and the control status of electronic fences in key areas, realizing effective supervision of special operations and key areas, and improving the safety of the production process of thermal power units and the level of refined management.

[0026] Preferably, a grid-based hierarchical management interface displays regional risk maps and core indicators according to the "red, orange, yellow, and blue" levels of risk from high to low.

[0027] The grid-based hierarchical management interface displays regional risk maps and core indicators according to the "red, orange, yellow, and blue" levels, allowing managers to intuitively and clearly understand the risk level of each region, quickly locate high-risk areas, and implement precise policies based on core indicators, thereby improving the pertinence and efficiency of thermal power unit safety management and timely preventing and handling potential risks.

[0028] Preferably, the security situation awareness module includes:

[0029] Environmental monitoring sensors, electrical equipment monitoring sensors, and network traffic monitoring devices are used to collect data on dust concentration, chemical concentration, equipment temperature, current, voltage, and network anomalies;

[0030] The gun-ball linked camera monitors the dynamics of the production area in real time.

[0031] The safety situation awareness module uses environmental monitoring sensors, electrical equipment monitoring sensors, network traffic monitoring devices and gun-ball linkage cameras to comprehensively collect multiple types of data such as dust concentration and equipment temperature and monitor the production area in real time. It can promptly detect environmental, equipment and network anomalies, provide comprehensive risk warnings for the safe and stable operation of thermal power units, and ensure production safety.

[0032] Preferably, the grid-based hierarchical management interface is set with the distance between adjacent beacons arranged in the factory area as the minimum grid unit.

[0033] Preferably, the visual display module has a camera linkage function, which automatically calls the nearest camera to track the target in real time through the personnel positioning platform, and supports one-click retrieval of monitoring images.

[0034] The visual display module's camera linkage function is very practical. Leveraging the personnel positioning platform, it automatically calls the nearest camera to track the target in real time, allowing managers to monitor the target's movements at all times. It also supports one-click access to monitoring images, greatly improving the convenience of obtaining monitoring information. This helps to promptly detect and address abnormal conditions within the thermal power unit production area, ensuring safe and efficient production.

[0035] Preferably, the visual display module has a limited space management function, and integrates oxygen content and toxic gas sensors, which automatically trigger an alarm and lock the working area when the limit is exceeded.

[0036] The confined space management function of the visual display module monitors the environmental conditions in the confined space in real time by integrating oxygen content and toxic gas sensors. Once the indicators exceed the limit, it will automatically alarm and lock the working area, which can effectively prevent people from inhaling harmful gases and ensure the safety of people working in confined spaces.

[0037] Solution 2: A multi-parameter intelligent control and safety assessment method for thermal power units, using the system described above, includes the following steps:

[0038] Data collection and safety monitoring: The safety situation awareness module collects real-time operating parameters of thermal power units, including temperature, pressure, dust concentration, chemical concentration, electrical equipment status, and network traffic data, and conducts abnormal behavior identification and security threat analysis.

[0039] Safety and equipment status assessment: The central processing unit analyzes the collected data according to the pre-stored safety assessment level table, determines whether it exceeds the standard and triggers an alarm;

[0040] Visual integrated management and control: Use the visual display module to achieve the following functions:

[0041] A 3D panoramic simulation display of the entire plant dynamically presents risk points, hidden danger distribution, and personnel trajectories;

[0042] Grid-based hierarchical management, marking core indicators and responsibility information according to risk levels;

[0043] Personnel positioning and operation supervision, linked to access control, cameras and vital signs monitoring;

[0044] Real-time monitoring of confined spaces and key areas, including gas monitoring and electronic fence control.

[0045] Preferably, the grid-based hierarchical management interface is set up with the distance between adjacent beacons deployed in the factory area as the minimum grid unit, with the distance between two adjacent beacons being 4.3-5 meters. This distance setting can simultaneously meet the data accuracy requirements of grid-based hierarchical management while minimizing the amount of data transmitted.

[0046] Preferably, the visual display module further realizes the linkage between positioning and monitoring, and automatically calls the nearest camera for real-time tracking through the personnel coordinates; the data of the security situation awareness module are transmitted to the central processor via wired or wireless means, and are updated synchronously with the visual display module to form an intelligent management and control system with closed-loop feedback.

[0047] The central processing unit is equipped with a dynamic priority processing mechanism to prioritize abnormal data that could cause casualties, major equipment damage, or environmental pollution. This dynamic priority processing mechanism prioritizes abnormal data that could cause serious consequences. This allows for timely response before dangerous situations occur, allowing for rapid initiation of countermeasures, minimizing the risk of casualties, equipment damage, and environmental pollution, and ensuring the safe and stable operation of thermal power units.

[0048] The principles and advantages of this solution are:

[0049] The multi-parameter intelligent control and safety assessment system for thermal power units of the present invention achieves comprehensive safety assurance, significant cost control, intelligent operation management, and strong system adaptability and stability through the collaborative operation of hardware and software. The safety situation awareness module uses a variety of sensors and equipment for real-time monitoring, promptly identifying and addressing various safety hazards. The furnace tube loss assessment unit can also predict furnace tube problems to avoid accidents. The central processing unit determines anomalies based on a preset level table and handles them in a graded manner, achieving intelligent operation. The system's data acquisition, transmission, and analysis functions support optimized management, and the hardware and software configuration ensures efficient and stable operation, adapting to the complex environment of thermal power units.

[0050] The present invention relies on a visual display module to integrate multiple applications to form an interconnected overall management and control system. In terms of production safety management, regional gridding and risk quantification management are realized, risks are accurately located, and management targeting is improved; through on-site monitoring, environmental monitoring and intelligent inspections, equipment and environmental conditions are timely grasped, and anomalies are quickly discovered and handled. In terms of personnel management, personnel positioning, identity recognition and high-risk operation area management are combined to ensure personnel safety and operation specifications. The positioning video linkage function further enhances the monitoring capability. Overall, the present invention improves the timeliness, dynamism and intelligence level of production safety management without making too many changes to the existing equipment installation in the factory area, effectively reduces safety risks, and ensures the safe and efficient conduct of production activities.

[0051] This solution addresses the problems of existing thermal power unit safety assessment systems. Addressing deficiencies such as insufficient multi-abnormal event processing capabilities, bottlenecks in processing massive amounts of data, limited visualization, and poor system compatibility, this system integrates a multi-module system architecture, advanced data processing technologies, 3D visualization, and a unified data management interface. It achieves intelligent correlation analysis of multiple abnormal events, efficient data processing and retrieval, intuitive visualization, and excellent system compatibility. Its advantages include rapid identification of key issues, accurate prediction of faults, improved management efficiency, and the elimination of information silos, effectively ensuring the safe and stable operation of thermal power units. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 2 is a structural block diagram of the system in an embodiment of the present invention.

[0053] Figure 2 This is a diagram showing the display screen of a gun-ball linkage camera in an embodiment of the present invention.

[0054] Figure 3 This is a diagram showing the display screen of a gun-ball linkage camera in an embodiment of the present invention.

[0055] Figure 4 This is a diagram showing the display screen of a gun-ball linkage camera in an embodiment of the present invention.

[0056] Figure 5 This is a five-color diagram display interface of a risk operation presented by the visual display module of an embodiment of the present invention. Figure 6 2 is a system architecture diagram of an embodiment of the present invention. DETAILED DESCRIPTION

[0057] The following is further described in detail through specific implementation methods:

[0058] The present invention aims to provide a multi-parameter intelligent management and safety assessment system and method for thermal power units, so as to solve the problems existing in the operation and management of existing thermal power units, such as fuel management difficulties, safety protection loopholes, insufficient equipment detection, and lack of global safety assessment, so as to achieve safe, stable and efficient operation of thermal power units, reduce operating costs and improve enterprise competitiveness.

[0059] like Figure 1 As shown, the multi-parameter intelligent management and safety assessment system for thermal power units of the present invention includes a central processing unit, and a safety situation perception module, a real-time alarm module, and a visual display module respectively connected to the central processing unit; the central processing unit is preset with a safety assessment level table for receiving perception information from the safety situation perception module, comparing the standard values of the corresponding parameter items in the safety assessment level table, and judging whether the corresponding safety perception items are abnormal. If abnormal, a warning is issued through the real-time alarm module, and the relevant information can be transmitted to the visual display module for display, especially the abnormal items are marked with color and font.

[0060] The safety situation awareness module also includes gun-ball linkage cameras, environmental monitoring sensors and electrical equipment monitoring sensors arranged in each production area; the gun-ball linkage camera consists of a gun-type camera and a ball-type camera, which is used to collaboratively monitor the production area; the environmental monitoring sensor is used to monitor the dust and gas environmental indicators in different areas of the thermal power plant; the electrical equipment monitoring sensor is used to monitor the temperature, current and voltage of key electrical equipment. These monitoring data can be transmitted to the visual display module for display.

[0061] The central processor sets processing priorities based on the perception information detected and fed back by the components of the security situation awareness module, giving priority to abnormal situations that may cause casualties, major equipment damage or serious environmental pollution. The processing results and abnormal information can be presented in the visual display module.

[0062] The visualization display module has the function of three-dimensional panoramic simulation display of the entire plant, and establishes a twin three-dimensional model of the indoor and outdoor power plant. In the three-dimensional visualization platform, the overall situation of the power plant can be viewed in a simulation scene that is completely consistent with the actual scene. The platform supports interactive operations such as rotating and zooming the plant area to view the details of every corner of the plant area, and can display high and medium risk points, hidden danger distribution, personnel trajectories, and on-site monitoring points in real time on the model.

[0063] The visual display module has a grid-based hierarchical management function, which grids the entire plant area and manages it according to different levels of "red, orange, yellow, and blue". It designs and displays the risk map of the entire project according to regional distribution, and displays the core indicators of each area, including the area name, safety person in charge, production person in charge, high-risk operations occurring in the area, and the number of unrectified hidden dangers.

[0064] The visual display module has the function of personnel visualization management. It manages the location and movement trajectory of all personnel in the factory through positioning chips (safety helmets, badges, wristbands), and is linked with the access control to visualize the personnel situation, including quantity, unit, real-time entry and exit, and time control. It is also associated with special operations to monitor the safety and vital signs of operators in real time.

[0065] The visual display module has the application function of positioning and camera linkage, establishes a personnel positioning platform, and automatically mobilizes nearby monitoring equipment to track and monitor the target of interest in real time based on its coordinates, realizing one-click retrieval of monitoring images, that is, one-click viewing.

[0066] The visual display module has the function of confined space operation management, monitors the oxygen content and toxic gases in the confined space in real time, effectively supervises the number of people working in the space at the same time, and visually displays the monitoring and supervision information.

[0067] The visual display module has a key area supervision function, and effectively controls intrusion and crossing of key areas through the application of electronic fences, and the control information is presented on the visual display module.

[0068] The multi-parameter intelligent control and safety assessment method for thermal power units of the present invention adopts the system as described above and includes the following steps:

[0069] Step 1: Data Collection and Transmission. The various sensors in the safety situation awareness module collect real-time data on the thermal power unit's operating temperature, pressure, humidity, current, voltage, dust concentration, and chemical concentration. These sensors convert the analog signals into digital signals and transmit them to the central processing unit and visual display module via wired or wireless means.

[0070] Realize comprehensive real-time collection and efficient transmission of unit operation data, provide basic data support for subsequent analysis, and initially display it through the visualization module.

[0071] Step 2: The security situation awareness module performs security monitoring. It collects and analyzes network traffic and device status data in real time, identifies abnormal behavior and security threats, and transmits relevant information to the visualization display module.

[0072] Timely discover potential network security risks and equipment anomalies, and provide dynamic data input for security assessments.

[0073] Step 3: Security situation assessment.

[0074] The central processing unit determines whether data such as dust concentration and transformer temperature exceed the standard based on the safety assessment level table. If so, an alarm instruction is triggered and the assessment results and alarm information are displayed visually.

[0075] Achieve quantitative assessment and automatic early warning of security risks to assist in quick decision-making.

[0076] Step 4: The visualization module provides a 3D panoramic simulation of the entire plant. This module creates a twin 3D model of the plant's interior and exterior, supporting interactive operations (rotation and zooming) and displaying risk points, hidden danger distribution, personnel trajectories, and monitoring points in real time.

[0077] Provides an immersive global perspective to intuitively grasp the power plant's safety status and spatial correlation information.

[0078] Step 5: The visual display module implements grid-based hierarchical management. The entire plant is gridded according to the "red, orange, yellow, and blue" levels, displaying risk maps and regional core indicators (such as responsible persons and the number of high-risk operations).

[0079] Implement hierarchical management and control of risk areas, and clarify the division of responsibilities and key supervision areas.

[0080] Step 6: The visual display module performs visual personnel management. The location and trajectory of personnel are monitored through positioning chips (safety helmets, badges, etc.), and access control and special operations monitoring are linked to monitor vital signs.

[0081] Improve the efficiency of personnel safety supervision and ensure operational compliance and emergency response capabilities.

[0082] Step 7: The visualization display module realizes the linkage application of positioning and camera. Based on the coordinates of the person, the nearest camera is automatically mobilized to track the target in real time, supporting "one-click viewing".

[0083] Enhance the dynamic monitoring capabilities of key targets.

[0084] Step 8: Use the visualization module to manage confined space operations. Monitor oxygen levels, toxic gases, and the number of workers in the confined space in real time, and visualize the data.

[0085] Ensure the safety of operations in confined spaces and prevent accidents such as gas poisoning.

[0086] Step 9: Visual display module monitors key areas. Use electronic fences to control intrusions into key areas and visualize boundary crossing information.

[0087] Strengthen access control to key areas to reduce the risk of unauthorized entry.

[0088] This method forms a closed-loop management chain from data collection to multi-dimensional visual management and control, realizing the full-process intelligent safety management and control of thermal power units from "monitoring-assessment-early warning-display".

[0089] The present invention solves the problem that existing assessment systems and methods are insufficient in their ability to handle multiple abnormal events:

[0090] Optimized Architecture and Intelligent Analysis: This solution utilizes a multi-module system architecture, with the central processing unit collaborating with the safety situation awareness module, enabling simultaneous processing of data from multiple sources. For example, the safety situation awareness module incorporates multiple sensors, enabling comprehensive monitoring. Furthermore, using a pre-set safety assessment rating table and intelligent algorithms, it can rapidly analyze abnormal data and identify causal relationships between abnormal events. For example, it can identify potential correlations between abnormal furnace tube wear and electrical equipment failures, thus avoiding confusion in alarm information.

[0091] Efficient decision support: The real-time alarm module works in conjunction with the visualization module to highlight key anomaly information. The visualization module uses 3D panoramic simulation and grid-based hierarchical management to enable operators to quickly identify key issues. For example, by visually identifying high-risk areas and potential hazards on a 3D model, they can take timely action to avoid delays.

[0092] The present invention solves the bottleneck problem of massive data processing in existing evaluation systems and methods:

[0093] Advanced Data Processing Architecture: This solution utilizes high-performance servers and an optimized data transmission network, combined with technologies such as Redis cache servers to accelerate data processing. Furthermore, leveraging big data processing technology and a distributed database architecture, it efficiently stores and processes massive amounts of monitoring data, meeting real-time processing requirements and reducing data analysis delays.

[0094] The present invention solves the problem of limited visualization effects of existing evaluation systems and methods:

[0095] 3D Visualization and Dynamic Display: This solution's visualization module creates a twin 3D model of the power plant's interior and exterior, supporting interactive operations like rotation and zooming. It intuitively displays the 3D spatial relationships of equipment and facilitates anomaly location. It also offers dynamic display capabilities, presenting parameter trends in real time. For example, it uses animations to show changes in equipment operating status and personnel movement trajectories, making key information more visible.

[0096] Enhanced human-machine interaction experience: A user-friendly human-machine interface allows operators to easily access information and perform operations. For example, by simply viewing detailed equipment parameters in a 3D model, efficient human-machine interaction is achieved, improving management efficiency.

[0097] The present invention solves the problem of poor compatibility of existing evaluation systems and methods:

[0098] Unified data management and interface design: This solution uses unified data standards and interface specifications to standardize data processing for both new and existing equipment, and is compatible with multiple protocols such as Modbus and PROFIBUS. The development of universal interfaces reduces system expansion costs, facilitates the integration of new equipment and the migration of historical data, and breaks down information silos.

[0099] Flexible system scalability: Built on a microservices architecture based on Spring and the SpringBoot+SpringCloud framework, it offers excellent scalability. Functional modules can be flexibly added or modified as needed to accommodate expansion of monitoring scale and business changes, such as easily integrating new monitoring devices or features.

[0100] This invention solves the problems of outdated technical architecture and single algorithm model in existing evaluation systems and methods:

[0101] Advanced technical architecture: This system abandons the limitations of traditional relational databases and adopts a technology architecture more suitable for real-time analysis. It rationally allocates computing resources to prioritize critical tasks. For example, during security assessments, it prioritizes abnormal data that could cause serious consequences, ensuring efficient system operation.

[0102] Intelligent algorithm application: Introducing intelligent algorithms such as machine learning to enhance multi-parameter coupling analysis capabilities. For example, in furnace tube loss assessment, combining multiple parameters and deep learning models can improve the accuracy of the prediction model, reduce errors, and more accurately assess the equipment operating status.

[0103] Example 1

[0104] The multi-parameter intelligent management and safety assessment system for thermal power units in this embodiment includes: a central processing unit, and a security situation perception module, a real-time alarm module, and a visual display module respectively connected to the central processing unit; a security assessment level table is preset in the central processing unit, and the central processing unit receives perception information transmitted by each safety protection component in the security situation perception module according to the security assessment level table shown in Table 1, and judges whether the corresponding security perception item is abnormal by comparing and judging the standard value of the corresponding parameter item in the security assessment level table. If so, an alarm is issued through the real-time alarm module and presented through the visual display module.

[0105] Table 1

[0106]

[0107] The security situation awareness module, composed of multiple security protection components, is used to monitor the safety status of the production control area of the thermal power unit in real time, perceive the security situation and provide security warnings;

[0108] The security situation awareness module in this embodiment includes a furnace tube loss assessment unit. The furnace tube loss assessment unit is used to divide the furnace tubes of the thermal power unit into multiple sections, construct a spatiotemporal temperature field of the furnace tubes, and predict the loss of the furnace tubes based on the spatiotemporal temperature field.

[0109] The security situation awareness module also includes gun-ball linked cameras, environmental monitoring sensors and electrical equipment monitoring sensors arranged in various production areas.

[0110] like Figure 2 、 Figure 3 and Figure 4 As shown, the gun-ball linkage camera system consists of multiple sets of coordinated, linked gun and dome cameras. Gun cameras are fixed and monitor the production area, providing a relatively stable panoramic view of the area. Dome cameras can rotate, zoom, and flexibly adjust their viewing angles, providing localized views of areas requiring focused observation or where anomalies may or have occurred. The gun-ball linkage system leverages the advantages of both. When the gun camera detects an anomaly, the dome camera can quickly and automatically turn to the anomaly area for more detailed and comprehensive tracking and filming, achieving more efficient and accurate monitoring of the target area. This system plays a significant role in improving the safety and reliability of thermal power unit operations. In the risk management process, if a gun-ball linkage system is installed in a risky operation area, if the gun camera detects someone illegally entering the risky operation area (for example, when an electronic fence is triggered), the dome camera will immediately turn to the area to track and film the intruder, obtaining a clearer picture of their characteristics and behavior. This image information will be transmitted to the system in real time. Relevant personnel can use the monitoring images to promptly determine the intentions of the intruders and the possible risks, and thus quickly take corresponding measures, such as notifying on-site staff or security personnel to handle the situation and ensure the safety of the work area.

[0111] In real-time monitoring and alarm processes, the gun-ball linkage can also optimize alarm response mechanisms. When the system triggers an alarm (such as an alarm indicating excessive gas concentration), the gun-ball linkage device not only provides a real-time image of the alarm area, but also uses the dome camera's zoom function to more clearly display key information such as the operating status of equipment within the alarm area and the presence of leaks. This helps personnel quickly and accurately assess the severity of the alarm, make more reasonable decisions, improve the efficiency of handling alarm events, and ensure the safe and stable operation of thermal power units.

[0112] Environmental monitoring sensors include dust sensors and gas sensors installed in the coal storage area, combustion area, and chemical storage area of thermal power plants, as well as chemical leakage sensors installed in key locations of chemical storage tanks and transportation pipelines.

[0113] The dust sensor monitors the dust concentration in the air and transmits the dust concentration value to the central processing unit. The central processing unit determines whether the current dust concentration is abnormal based on the preset dust concentration standard value X in the safety assessment level table. The dust concentration standard value X is the lower explosion limit. According to the safety assessment level table, if the current dust concentration reaches X (X is 60% in this embodiment), the dust concentration is determined to be abnormal. The central processing unit controls the real-time alarm module to immediately issue a warning signal, reminding personnel to check the ventilation and dust removal system and take dust reduction measures.

[0114] Gas sensors are used to detect fire-hazard-related gases (such as carbon monoxide and smoke) and chemical leaks (such as ammonia and sulfur dioxide). In the chemical storage area, if the ammonia sensor detects that the ammonia concentration exceeds the ammonia standard value Y ppm (in this embodiment, Y is 20 ppm) specified in the safety assessment level table, the central processing unit controls the alarm module to send a warning signal, notifying personnel to wear protective equipment and conduct leak investigation and treatment.

[0115] Chemical leak sensors include a liquid leak detection sensor and a gas leak detection probe, both connected together by a pressure sensing unit and a liquid level sensing unit. For liquid chemicals, the liquid level sensing unit monitors the liquid level in the storage tank. If the liquid level drops abnormally within a short period of time, exceeding a preset liquid level change standard value M (M is 5%), combined with the pipeline pressure change detected by the pressure sensing unit, a possible liquid leak is detected. For gaseous chemicals, the gas leak detection probe detects a gas leak when the gas leakage concentration reaches the standard value. The central processing unit controls the real-time alarm module to sound an alarm, activate the ventilation system to expel the leaked gas, and notify professionals to repair the leak.

[0116] Electrical equipment monitoring devices include temperature sensors, current sensors, and voltage sensors installed on various key electrical equipment.

[0117] Temperature sensors, current sensors, and voltage sensors are installed on key electrical equipment such as transformers and generators. Temperature sensors monitor the temperature of key parts of electrical equipment in real time and set a corresponding temperature standard value, Z°C, based on the equipment's operating characteristics (the temperature standard value, Z, corresponding to the transformer winding temperature is set to 105°C). When the temperature exceeds the standard value, the central processing unit issues an overheating warning through the real-time alarm module, allowing staff to adjust the equipment load or shut down for maintenance as appropriate. Current sensors and voltage sensors monitor current and voltage changes in real time. When the current exceeds the standard current change value, W%, of the rated current (W is 120%), or the voltage fluctuation exceeds the standard voltage fluctuation range (e.g., ±10%), the central processing unit determines that an overload or short circuit may exist and issues a timely alarm through the real-time alarm module, prompting staff to troubleshoot and repair the problem.

[0118] In this embodiment, the security assessment level table preset in the central processing unit sets processing priorities based on the detection and feedback information from each component of the security situation module, taking into account the potential impact of abnormal situations on personnel safety, equipment damage, production interruption, and environmental pollution. Generally, abnormal situations that may cause casualties, major equipment damage, or serious environmental pollution are handled with a higher priority. The following are the processing priorities set according to different abnormal situations:

[0119] Priority Level 1: Abnormalities that seriously threaten the safety of personnel and equipment, including:

[0120] Furnace tube rupture or severe leakage: Furnace tubes are critical components of the boiler. If a rupture or severe leak occurs, high-temperature, high-pressure steam or water will instantly erupt, potentially causing an explosion, scalding operators, and forcing an emergency shutdown of the boiler, seriously impacting production. If the gun-ball camera captures abnormal steam or flames in the furnace tube area, and the environmental monitoring sensors detect abnormal high temperature and high pressure signals, the system immediately issues the highest-level alarm. At this point, the system prioritizes the emergency shutdown procedure, automatically cutting off the fuel supply and power to related equipment, while simultaneously activating the emergency cooling system to prevent further escalation of the accident. A professional maintenance team is notified to rush to the scene, wearing protective equipment, to carry out emergency repairs.

[0121] Severe short circuits in electrical equipment can cause fires: A severe short circuit in critical electrical equipment, such as transformers and generators, can cause fires and damage the equipment. It can also cause widespread power outages and threaten the lives of operators. When the fire alarm system detects smoke and flames in the electrical equipment area, and the electrical equipment monitoring device detects a short circuit fault current, it quickly shuts off power to the equipment and related wiring, activating on-site fire extinguishing devices (such as a carbon dioxide fire extinguishing system). Evacuation is organized to ensure the safe departure of personnel, and the fire department and professional electrical maintenance personnel are notified to extinguish the fire and repair the equipment.

[0122] Priority Level 2: Abnormalities that may cause equipment damage, production interruption, or environmental pollution, including:

[0123] Large-scale leakage of chemical substances: Large-scale leakage of chemical substances (such as acid, alkali, ammonia, etc.) in thermal power plants will cause serious harm to human health, equipment and the environment. When the chemical substance leakage detection device detects that the concentration of chemical substances in the storage tank or pipeline exceeds the dangerous threshold and the leakage volume reaches a certain level (such as more than 10% of the storage volume), the system activates the leakage emergency response procedure. First, start the ventilation system to dilute and discharge the leaked chemicals to prevent them from accumulating indoors. Notify on-site personnel to wear protective equipment and perform emergency plugging operations on the source of the leak. If the leakage may cause pollution to the surrounding environment, notify the environmental protection department in a timely manner and take corresponding pollution control measures, such as setting up cofferdams, neutralizing leaked substances, etc.

[0124] Abnormal boiler combustion may cause explosions: During the mixed coal combustion process, if the combustion is abnormal (such as uneven fuel supply, imbalanced air ratio, etc.), it may cause the boiler to explode. When the environmental monitoring sensor detects an abnormal increase in pressure and temperature in the boiler, and the flame monitoring device detects that the flame is unstable, flickering, or extinguished, the system will sound an alarm. At this time, the system automatically adjusts the fuel supply and air intake to try to restore normal combustion. If the abnormal situation is not alleviated, the emergency shutdown procedure will be immediately initiated to prevent an explosion. Organize technical personnel to inspect and repair the combustion system to find out the cause of the abnormal combustion and repair it.

[0125] Priority Level 3: Exceptions that affect production efficiency or pose potential safety risks, including:

[0126] Dust concentration approaches the lower explosion limit: Excessive dust concentrations in coal transportation, storage, and combustion areas can cause explosions. When the dust sensor detects dust concentrations reaching 60% of the lower explosion limit (this value can be adjusted based on actual conditions), the system issues an alert. The ventilation and dust removal system is prioritized, increasing ventilation to reduce dust concentration. Staff are notified to inspect and maintain dust-generating equipment, such as checking the tightness of conveyor belts and the operating status of dust collectors, to prevent further dust accumulation.

[0127] Abnormal electrical equipment temperatures but not reaching dangerous levels: When the electrical equipment monitoring device detects that the temperature of electrical equipment such as transformers and motors exceeds the normal range but does not reach the dangerous threshold that could cause equipment damage (such as exceeding 20% of the normal operating temperature), the system issues a temperature anomaly warning. The system records the temperature trend and notifies maintenance personnel to inspect the equipment. Maintenance personnel can adjust the equipment load and enhance heat dissipation (such as starting cooling fans and cleaning heat sinks) to prevent further temperature increases.

[0128] When the central processor receives the perception information of all security protection components of the security situation awareness module, if an abnormal situation is found, it controls the gun-ball linkage camera in the corresponding production area to focus on the area where the abnormal situation occurs. Not only does it switch the main observation page to the corresponding production area and display the panoramic picture of the production area taken by the ball camera in real time, but it also focuses on displaying the local picture of the abnormal situation taken by the gun camera in real time by adding a small window interface.

[0129] The visual display module divides the responsibility area of the entire power plant, associates the responsible departments of the plant structures with the three-dimensional model of the plant, and displays clear responsible departments and persons in charge in each area. Events in this area can automatically remind the corresponding responsible persons through SMS, APP, etc. Figure 5 As shown, regional risks are quantified and divided into red, orange, yellow, and blue levels to form a five-color risk map. Those who illegally enter the risk area will be alerted through the alarm prompts preset by the central processor. Click the risk area of the corresponding color block on the visual display module to view the specific risk event details. The specific operations are as follows:

[0130] Click on the layer to display the grid. If the layer is not displayed, please contact the Safety Monitoring Center of the Safety Supervision Department.

[0131] Displays a five-color risk map, which is determined based on the risk operation level of the day. The area with the largest level is taken as the area level.

[0132] The specific implementation process is as follows:

[0133] (1) Hardware environment construction

[0134] like Figure 6 As shown, the architecture of the system in this embodiment is

[0135] 1) The system adopts B / S architecture;

[0136] 2) Support 3D visualization engine;

[0137] 3) Support satellite-ground integrated positioning;

[0138] 4) Support computer vision AI recognition;

[0139] 5) Support IoT protocols;

[0140] 6) Support LAN and Internet access, support PC access;

[0141] 7) The system has a good technical and business architecture and is well adaptable to future expansion or changes in business needs;

[0142] 8) Support the rapid expansion of business application needs and realize modification and expansion based on the original system modules;

[0143] 9) Support the expansion of hardware environment as data grows, and achieve rapid capacity expansion based on the original hardware server.

[0144] When deploying this system, high-performance servers were selected as the core hardware for system operation. The server configuration features a 20-core, 40-thread multi-threaded processor with a base frequency of 2.5GHz and a turbo frequency of up to 3.9GHz, 128GB of DDR4 3200MHz memory, and a 2TB NVMe solid-state drive to ensure efficient processing of large amounts of data and complex business logic. Regarding network equipment, high-performance switches and routers were used to build a stable and reliable network environment, ensuring high-speed and stable data transmission. Numerous sensors were deployed at key locations within the factory, such as production workshops and equipment rooms, for data collection.

[0145] Environmental monitoring sensors: For confined space working areas, various gas monitoring sensors, such as oxygen sensors, hydrogen sulfide sensors, carbon monoxide sensors, etc., are installed to monitor the gas composition and concentration in the working environment in real time to ensure the safety of workers.

[0146] Video surveillance equipment: Gun and dome cameras are installed in different areas to provide comprehensive visual monitoring of the work site and equipment operating status. These cameras feature high-definition recording, night vision, and pan / tilt control, enabling clear image capture and adjustable shooting angles as needed.

[0147] At the same time, staff are equipped with handheld mobile terminals, such as customized industrial tablets or smartphones with specific functions. These terminals are waterproof, dustproof, and drop-proof, and have fast running speeds and long battery life, ensuring that staff can use the system stably in complex industrial environments.

[0148] (2) Software system deployment

[0149] The system software is developed in Java, using a microservices architecture based on the Spring and SpringBoot+SpringCloud frameworks. The Java Runtime Environment (JDK), MySQL database management system, Redis cache server, and Tomcat web server are installed on the server. The JDK provides the system's operational foundation; MySQL is used to store various system data, such as user information, risky operation data, and device information; Redis, as a cache server, caches frequently used data to improve system responsiveness; and Tomcat, as a web server, works with the Nginx reverse proxy to achieve load balancing and ensure stable operation under high concurrency conditions.

[0150] (3) Overall system operation process

[0151] Real-time monitoring and alarm process

[0152] Real-time data collection and transmission: Environmental monitoring sensors, video surveillance equipment, electronic fences, and other hardware devices collect real-time data, such as gas concentrations, video footage, and intrusion information. This data is transmitted to the server via wired or wireless networks, which organizes and stores the data.

[0153] Monitoring and Alarm Processing: The system analyzes collected data in real time and immediately triggers an alarm when it detects an abnormality, such as excessive gas concentrations or illegal intrusion into an electronic fence. Alarm information is notified to relevant personnel via the system interface, SMS, and app push notifications. Relevant personnel can then view the alarm details and handle it promptly.

[0154] The system and method of this embodiment have demonstrated significant effects in many aspects in actual applications, effectively improving the operation and management level of thermal power units.

[0155] Comprehensively upgraded safety assurance: The security situation awareness module integrates multiple monitoring devices to achieve comprehensive real-time monitoring. The furnace tube loss assessment unit predicts furnace tube loss in advance, successfully avoiding furnace tube leakage accidents, reducing the risk of equipment damage and production interruptions, and ensuring stable unit operation. Gun-ball-linked cameras, environmental monitoring sensors, and electrical equipment monitoring sensors work together to promptly detect and address various safety hazards. In risky operating areas, the gun-ball-linked cameras track and capture illegal intruders, enabling personnel to take swift action to ensure operational safety. During real-time monitoring, the zoom function assists personnel in assessing alarm situations, improving response efficiency and ensuring safe and stable operation of the thermal power unit. Environmental monitoring sensors accurately monitor dust and gas concentrations. For example, dust sensors provide timely warnings when dust concentrations approach 60% of the lower explosion limit, preventing explosions. Gas sensors notify personnel when leaks of chemicals such as ammonia are detected, ensuring both personnel and the environment. Electrical equipment monitoring devices monitor the temperature, current, and voltage of critical electrical equipment in real time, providing prompt alarms when equipment anomalies occur, providing a basis for maintenance and reducing the risk of damage.

[0156] Significant cost control: The mixed coal blending module precisely optimizes the blending plan based on power generation requirements, desulfurization system capacity, and coal quality parameters. In actual operation, by adjusting the blend ratio of low-sulfur and high-sulfur coal, power generation requirements are met while ensuring the average sulfur content of the blend meets desulfurization system requirements, thereby reducing desulfurization costs. Air intake and the blend ratio are adjusted based on changes in oxygen content to ensure complete combustion, improve combustion efficiency, reduce coal waste, and achieve cost control.

[0157] Improved Intelligent Operation and Management: The central processing unit (CPU) uses a safety assessment table to quickly and accurately identify safety anomalies and handle them in a graded manner. When an anomaly occurs, the system rapidly initiates appropriate measures. For example, if a furnace tube burst or electrical equipment short circuit causes a fire, the system automatically performs an emergency shutdown, cuts power, activates fire extinguishing devices, and notifies relevant personnel to handle the situation, ensuring the safety of personnel and equipment. If no anomalies are detected, the system automatically controls the operation of the mixed coal blending module, achieving intelligent operation and management. The system implements centralized data collection, transmission, and analysis, transmitting various sensor data to a server via wired or wireless networks for organization and storage. Based on this data, the system can conduct in-depth analysis of the operating status of thermal power units, providing strong support for optimizing operation and management and enabling intelligent decision-making.

[0158] Enhanced system adaptability and stability: The hardware utilizes high-performance servers and stable network equipment, combined with a variety of environmental monitoring and video surveillance sensors, ensuring efficient and stable data collection and processing. The software, built on Java and frameworks such as Spring, offers excellent scalability and compatibility. JDK provides the operational foundation, MySQL stores data, Redis improves response speed, and Tomcat and Nginx implement load balancing, ensuring stable system operation under high concurrency conditions and adapting to the complex operating environments and business requirements of thermal power units.

[0159] Example 2

[0160] Different from the first embodiment, the safety situation awareness module includes a furnace tube loss assessment unit, which includes a segment division unit, a temperature field construction unit and a loss prediction unit; the segment division unit is used to divide the furnace tube into multiple segments, the temperature field construction unit is used to construct the spatiotemporal temperature field of the furnace tube, and the loss prediction unit is used to predict the furnace tube loss based on the spatiotemporal temperature field combined with the furnace tube material characteristics and operating parameters. The prediction results can be displayed through a visual display module.

[0161] In this embodiment, during the safety situation assessment process, the furnace tube loss assessment module also assesses furnace tube loss. This module divides the furnace tubes into sections, collects temperature data to construct a spatiotemporal temperature field, predicts loss, and issues warnings. The results are then presented through a visualization module.

[0162] Accurately predict furnace tube life to avoid unplanned downtime due to wear and tear.

[0163] The furnace tube loss assessment unit comprises a segmentation unit, a temperature field construction unit, and a loss prediction unit. The segmentation unit divides the furnace tube into multiple segments, the temperature field construction unit constructs the temporal and spatial temperature field of the furnace tube, and the loss prediction unit predicts furnace tube loss based on the temporal and spatial temperature field. In thermal power plant applications, the segmentation unit divides the furnace tube into multiple segments based on its structural and functional characteristics. The temperature field construction unit uses high-precision temperature sensors installed on the furnace tube to collect temperature data at different locations and times, and then uses data processing algorithms to construct the temporal and spatial temperature field of the furnace tube. The loss prediction unit uses a deep learning model based on the temporal and spatial temperature field, combined with the material properties and operating parameters of the furnace tube, to predict furnace tube loss. In actual monitoring, this module predicts the potential loss risk of a specific furnace tube segment in advance, allowing for timely maintenance and avoiding furnace tube leakage accidents.

[0164] In this embodiment, the central processing unit performs multiple parameter evaluations according to the preset security assessment level table shown in Table 2:

[0165] Table 2

[0166]

[0167] This embodiment establishes a data index and optimizes query algorithms to improve the efficiency of historical data retrieval. Combined with machine learning algorithms, it conducts in-depth analysis of historical and real-time data, enabling more accurate trend analysis and fault prediction. For example, by studying historical data on multiple parameters such as furnace tube temperature and pressure, furnace tube wear trends can be predicted in advance. This minimizes safety risks and reduces losses without increasing computing costs.

[0168] Example 3

[0169] Unlike the first embodiment, the central processing unit in this embodiment is further connected to a mixed coal combustion module. The mixed coal combustion module includes a data acquisition unit, a data analysis unit, and a solution generation unit. The data acquisition unit is used to collect various parameters of low-sulfur coal and high-sulfur coal. The data analysis unit is used to analyze the data and establish a database. The solution generation unit is used to generate an optimal mixed coal combustion solution based on the database, combined with power generation demand and desulfurization system capabilities.

[0170] The multi-parameter intelligent control and safety assessment system for thermal power units in this embodiment includes: a central processing unit, and a safety situation perception module, a real-time alarm module, and a mixed coal blending module respectively connected to the central processing unit; a safety assessment level table is preset in the central processing unit, and the central processing unit receives the perception information transmitted by each safety protection component in the safety situation perception module according to the safety assessment level table shown in Table 3, and judges whether the corresponding safety perception item is abnormal by comparing and judging the standard value of the corresponding parameter item in the safety assessment level table. If so, an alarm is issued through the real-time alarm module. Otherwise, a mixed coal to be burned is prepared in real time from low-sulfur coal and high-sulfur coal through the mixed coal blending module, so that the combustion heat of the mixed coal meets the standard while the sulfur content of the generated gas meets the standard.

[0171] Table 3

[0172]

[0173] When the central processor receives sensor information from all security protection components of the security situation awareness module and detects an anomaly, it controls the gun-and-ball cameras in the corresponding production area to focus on the area where the anomaly occurred. Not only does the main observation page switch to the corresponding production area, displaying a panoramic view of the production area captured in real time by the ball camera, but it also opens a small window interface to highlight the local view of the anomaly captured in real time by the gun-and-ball camera. If the central processor detects no anomaly after receiving all the sensor information, it controls the mixed coal combustion module to burn a mixture of low-sulfur coal and high-sulfur coal according to the current environment.

[0174] The mixed coal blending module in this embodiment is used to establish a parameter database of low-sulfur coal and high-sulfur coal, and optimize the mixed coal blending scheme of the thermal power unit based on the database to achieve efficient operation and cost reduction of the desulfurization system;

[0175] The mixed coal blending module includes a data acquisition unit, a data analysis unit and a scheme generation unit. The data acquisition unit is used to collect various parameters of low-sulfur coal and high-sulfur coal, the data analysis unit is used to analyze data and establish a database, and the scheme generation unit generates the optimal mixed coal blending scheme based on the database.

[0176] When the mixed coal combustion module is working, assuming that the power generation demand of the thermal power unit is P e (MW), the thermal efficiency of the unit is η ep (%), the lower calorific value of standard coal is Q net，ar (KJ / Kg).

[0177] According to the formula The required total coal consumption B (t / h) can be calculated.

[0178] Assume that the sulfur content of low-sulfur coal is S1 (%), the calorific value is Q1 (KJ / Kg), the sulfur content of high-sulfur coal is S2 (%), the calorific value is Q2 (KJ / Kg), the mass fraction of low-sulfur coal is x, and the mass fraction of high-sulfur coal is 1-x. The average sulfur content of mixed coal is S 混合煤 =xS1+(1-x)S2, average calorific value of mixed coal Q 混合煤 =xQ1+(1-x)Q2.

[0179] In actual operation, when the oxygen sensor detects a decrease in the oxygen content in the air, it means that the amount of oxygen in the same volume of air has decreased. To ensure sufficient combustion, the air intake needs to be increased. Assuming the original air intake is V1, and the air intake after the oxygen content changes is V2, according to the ideal gas state equation PV = nRT (when the temperature T and pressure P remain unchanged, the gas volume V is proportional to the amount of substance n).

[0180] Since the amount of oxygen substance is related to the oxygen content, when the oxygen content changes from Q1 to Q2, the adjusted air intake can be calculated based on the proportional relationship.

[0181] At the same time, in order to ensure that the calorific value generated by the mixed combustion meets the standard, the total coal consumption B calculated according to the power generation demand remains unchanged, and the average calorific value Q of the mixed coal is 混合煤 The thermal efficiency requirements of power generation must be met. If the combustion conditions change due to changes in oxygen content, affecting the actual calorific value of the mixed coal, the mixing ratio of low-sulfur coal and high-sulfur coal can be adjusted to ensure that the calorific value meets the standard. For example, when the oxygen content decreases, resulting in incomplete combustion and the actual calorific value of the mixed coal is lower than the requirement, the proportion of high-calorific value coal (assuming that high-sulfur coal has a higher calorific value) can be appropriately increased, that is, the value of 1-x is increased, and the value of x is reduced accordingly, and the mixing ratio is recalculated and adjusted to make Q 混合煤 =xQ1+(1-x)Q2 to meet the calorific value requirements corresponding to the thermal efficiency of power generation. In this process, the designed SO2 processing capacity of the desulfurization system must also be considered to ensure the average sulfur content S of the mixed coal. 混合煤 Within the processing capacity of the desulfurization system, to ensure that sulfur dioxide emissions meet standards.

[0182] Based on the above system, the multi-parameter intelligent control and safety assessment method for thermal power units includes the following steps:

[0183] Parameters such as sulfur content and calorific value of low-sulfur and high-sulfur coal are collected to establish a database. The blending ratio of the mixed coal is determined based on power generation demand and desulfurization system capabilities. The security situation awareness module then conducts security monitoring, collecting and analyzing data such as network traffic and device status in real time to identify abnormal behavior and security threats. Finally, the furnace tube loss assessment module assesses furnace tube loss, divides the furnace tubes into sections, collects temperature data, and constructs a spatiotemporal temperature field to predict furnace tube loss and provide timely warnings.

[0184] Data Collection and Transmission: Various sensors in the security situation awareness module (such as environmental monitoring sensors, electrical equipment monitoring devices, and chemical leak detection devices) collect real-time data on the operation of the thermal power unit, including but not limited to temperature, pressure, humidity, current, voltage, dust concentration, and chemical concentration. These sensors convert the collected analog signals into digital signals and transmit the data to the central processing unit via wired (such as industrial Ethernet) or wireless (such as Wi-Fi, ZigBee, etc.) transmission methods.

[0185] Safety situation assessment: After the central processing unit receives the perception information from the safety situation awareness module, it processes it according to the pre-stored safety assessment level table. The safety assessment level table specifies in detail the standard value range of different safety perception items and the corresponding safety assessment levels. For the dust concentration data collected by the environmental monitoring sensor, if it exceeds the normal threshold specified in the safety assessment level table (such as reaching 60% of the lower explosion limit), the central processing unit determines that the safety perception item is abnormal; if the transformer temperature data transmitted by the electrical equipment monitoring device exceeds the specified normal operating temperature range (such as exceeding 20% of the normal operating temperature), it is also judged to be abnormal. Once it is determined that there is an abnormality in the safety perception item, the central processing unit immediately sends an alarm instruction to the real-time alarm module.

[0186] Real-time alarm processing: Upon receiving the alarm command from the central processor, the real-time alarm module rapidly activates multiple alarm methods. Sound and light alarms emit strong audible and visual signals at the thermal power plant site, attracting the attention of on-site personnel. Simultaneously, alarm information is sent to relevant personnel's mobile phones via SMS and app push notifications, ensuring they are promptly notified of any abnormalities. Alarm information includes key information such as the location of the abnormality, the type of abnormality, and the potential impact, facilitating a quick response.

[0187] Mixed coal combustion control: If the central processor determines that the information sent by the security situation awareness module is normal, the mixed coal combustion module will be started. The mixed coal combustion module first obtains the current power generation demand P of the thermal power unit. e (MW), unit power generation thermal efficiency η ep (%) and the lower calorific value of standard coal Q net，ar(KJ / Kg).

[0188] According to the formula Calculate the total coal consumption B (t / h) required to meet power generation needs.

[0189] Assume that the sulfur content of low-sulfur coal is S1 (%), the calorific value is Q1 (KJ / Kg), the sulfur content of high-sulfur coal is S2 (%), the calorific value is Q2 (KJ / Kg), the mass fraction of low-sulfur coal is x, and the mass fraction of high-sulfur coal is 1-x. The average sulfur content of mixed coal is S 混合煤 =xS1+(1-x)S2, average calorific value of mixed coal Q 混合煤 =xQ1+(1-x)Q2. In order to make the combustion heat of the mixed coal meet the standard and the sulfur content of the generated gas meet the standard, the mixed coal blending module adjusts the value of x to ensure the average sulfur content S of the mixed coal under the premise of meeting the power generation demand. 混合煤 Meet the design requirements of the desulfurization system (such as not exceeding the maximum sulfur content of the desulfurization system) and ensure the average calorific value Q of the mixed coal 混合煤 During the adjustment process, the calculated mixture ratio may need to be appropriately corrected taking into account some factors in the actual combustion process (such as combustion efficiency, etc.).

[0190] Continuous Monitoring and Dynamic Adjustment: During the operation of the thermal power unit, the Safety Situation Awareness Module continuously collects data, and the central processing unit continuously performs safety assessments and adjusts the mixed coal combustion. When power demand changes, the mixed coal combustion module recalculates and adjusts the mixed coal combustion ratio. If the Safety Situation Awareness Module detects a new anomaly, the central processing unit promptly activates the real-time alarm module and suspends or adjusts the mixed coal combustion module's operation, ensuring that the thermal power unit maintains safe, stable, and efficient operation.

[0191] Example 4

[0192] In this embodiment, the entire plant area of the thermal power unit is divided into grids based on regional functions, equipment distribution, and risk factors; the grids are hierarchically managed according to different levels of "red, orange, yellow, and blue." The grid division rules are dynamically updated based on real-time data such as the number of equipment failures, the number of hidden dangers, and the frequency of abnormal environmental indicators collected by the safety situation awareness module. The risk map of the entire project is displayed by regional distribution in the visualization display module, and the core indicators of each grid area are also displayed. The core indicators include the area name, safety person in charge, production person in charge, the number of high-risk operations occurring in the area, and the number of unrectified hidden dangers. The division of the smallest grid unit is determined and adjusted based on the equipment scale, risk distribution, historical accident data, equipment failure frequency, the location of hidden dangers, and the coverage and data collection capabilities of the monitoring equipment.

[0193] Grid-based hierarchical management is implemented as follows: First, the entire plant area is divided into appropriately sized grid units based on regional functions, equipment distribution, and risk factors. For example, areas with dense equipment or hazardous chemical storage are used as the basis for division. Each grid area is controlled between 50 and 500 square meters to ensure relatively consistent risks within each grid. For large buildings, large grids can be composed of multiple grids. Next, dynamic updates are performed based on real-time data collected by the security situation awareness module, such as the number of equipment failures, the number of hidden dangers, and the frequency of abnormal environmental indicators. If a grid experiences more than three electrical equipment failures within a week or has five or more unrectified hidden dangers, the grid's risk level is increased. Simultaneously, the security situation awareness module and various sensors collect real-time information such as the number of high-risk operations within the area and the status of hidden danger rectification. This information is promptly fed back to the visualization module, which updates the grid monitoring display to ensure a high degree of consistency with actual conditions.

[0194] In this multi-parameter intelligent management and safety assessment system for thermal power units, the grid edge design requires comprehensive consideration of multiple factors. For areas where equipment is concentrated, such as those housing core equipment like boilers and turbines, the grid edges are defined based on the equipment's physical boundaries, maintenance access, or functional zoning. This ensures strong connectivity among equipment within the same grid, facilitating centralized management and monitoring. In areas with densely distributed pipelines, the grid edges are defined along the pipeline's route and along key nodes such as valves and instruments to facilitate monitoring of the pipeline system's integrity and safety.

[0195] To ensure the appropriate minimum grid unit, the initial grid size must first be determined based on the equipment scale and risk distribution. For example, in areas with dense equipment layouts and higher risks, such as fuel storage areas, the minimum grid unit can be set to 50 square meters. This ensures that risk factors within each grid are relatively concentrated and facilitates accurate monitoring. In relatively open areas with lower risks, such as some auxiliary equipment areas, the minimum grid unit can be set to 500 square meters. Secondly, through analysis of historical accident data, equipment failure frequency, and the locations of hidden dangers, the grid division is continuously optimized. If a smaller grid frequently experiences safety issues or has large fluctuations in monitoring data, the grid can be appropriately reduced in size. If a larger grid has no anomalies for an extended period and the equipment correlation is weak, the grid can be appropriately expanded. In addition, adjustments should be made based on the coverage and data collection capabilities of the monitoring equipment to ensure that the grid division can fully utilize existing monitoring resources and achieve comprehensive and accurate safety management and control.

[0196] In this embodiment, the smallest unit of the grid is a cube. When the smallest unit of the grid is expanded or reduced, its length, width, and height increase or decrease proportionally. The magnitude of each increase or decrease is determined based on a combination of multiple factors. If adjustments are made based on equipment failure frequency, when the failure frequency of equipment in a particular grid suddenly increases and exceeds the warning threshold, the grid can be reduced by 20%-50% to more accurately locate the problem, focusing on the faulty area and conducting in-depth analysis of the cause. If equipment in a certain area has been operating stably for a period of time and the risk is low, the grid can be appropriately expanded, with the expansion controlled at 30%-60%, to reduce unnecessary monitoring nodes and improve management efficiency. For areas where risks fluctuate frequently, such as fuel processing areas, the adjustment range can be relatively small, controlled at around 20%, to ensure accurate risk monitoring. For relatively stable areas, such as some auxiliary equipment areas, the adjustment range can be increased to around 50%.

[0197] This quantitative grid-level management can clearly present the risk status of each area, and intuitively distinguish them with "red, orange, yellow, and blue", allowing managers to quickly locate high-risk areas, such as focusing on red areas for inspection, to improve safety management efficiency; clarify the safety and production responsibilities of each area, implement responsibilities, and improve management accuracy; timely grasp risk changes, and prevent risk expansion in advance, such as dealing with hidden dangers in yellow areas in advance to avoid escalation to red areas, and ensure the safe and stable operation of thermal power units.

[0198] The above is only an embodiment of the present invention, and the common knowledge such as the specific technical solutions and / or characteristics in the solution are not described in detail here. It should be pointed out that for those skilled in the art, without departing from the technical solution of the present invention, several variations and improvements can be made, which should also be regarded as the scope of protection of the present invention, and these will not affect the effect of the implementation of the present invention and the practicality of the patent. The scope of protection required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the description can be used to interpret the content of the claims.

Claims

1. A multi-parameter intelligent control and safety assessment system for thermal power units, characterized in that: The system comprises a central processing unit, and a security situation awareness module, a real-time alarm module, and a visual display module respectively connected to the central processing unit; the central processing unit is pre-set with a security assessment level table, which is used to receive perception information from the security situation awareness module, compare the standard values of corresponding parameter items in the security assessment level table, and determine whether the corresponding security perception items are abnormal. If abnormal, an alarm is issued through the real-time alarm module, and the abnormal items are marked and displayed on the visual display module; The visual display module is used to dynamically display the following content: A 3D panoramic simulation model of the entire plant supports interactive operations and marks risk points, hidden danger distribution, and personnel trajectories; The grid-based hierarchical management interface displays regional risk maps and core indicators at multiple levels.

2. The multi-parameter intelligent management and safety assessment system for thermal power units according to claim 1 is characterized in that: The visual display module is used to dynamically display the following content: Personnel positioning and operation supervision interface, linked access control, vital signs monitoring and camera tracking functions; Confined space operation monitoring data and electronic fence control status in key areas.

3. The multi-parameter intelligent management and safety assessment system for thermal power units according to claim 1 is characterized in that: The grid-based hierarchical management interface displays regional risk maps and core indicators according to the "red, orange, yellow, and blue" levels of risk from high to low.

4. The multi-parameter intelligent management and safety assessment system for thermal power units according to claim 1 is characterized in that: The security situation awareness module includes: Environmental monitoring sensors, electrical equipment monitoring sensors, and network traffic monitoring devices are used to collect data on dust concentration, chemical concentration, equipment temperature, current, voltage, and network anomalies; The gun-ball linked camera monitors the dynamics of the production area in real time.

5. The multi-parameter intelligent management and safety assessment system for thermal power units according to claim 1 is characterized in that: The grid-based hierarchical management interface is set with the distance between adjacent beacons arranged in the factory area as the minimum grid unit.

6. The multi-parameter intelligent management and safety assessment system for thermal power units according to claim 1 is characterized in that: The visual display module has a camera linkage function, which automatically calls the nearest camera to track the target in real time through the personnel positioning platform, and supports one-click retrieval of monitoring images.

7. The multi-parameter intelligent management and safety assessment system for thermal power units according to claim 1 is characterized in that: The visual display module has a limited space management function and integrates oxygen content and toxic gas sensors. When the limit is exceeded, it automatically triggers an alarm and locks the working area.

8. A multi-parameter intelligent control and safety assessment method for thermal power units, characterized in that: The system according to claim 1 comprises the following steps: Data collection and safety monitoring: The safety situation awareness module collects real-time operating parameters of thermal power units, including temperature, pressure, dust concentration, chemical concentration, electrical equipment status, and network traffic data, and conducts abnormal behavior identification and security threat analysis. Safety and equipment status assessment: The central processing unit analyzes the collected data according to the pre-stored safety assessment level table, determines whether it exceeds the standard and triggers an alarm; Visual integrated management and control: Use the visual display module to achieve the following functions: A 3D panoramic simulation display of the entire plant dynamically presents risk points, hidden danger distribution, and personnel trajectories; Grid-based hierarchical management, marking core indicators and responsibility information according to risk levels; Personnel positioning and operation supervision, linked with access control, cameras, and multi-gas detectors; Real-time monitoring of confined spaces and key areas, including gas monitoring and electronic fence control.

9. The multi-parameter intelligent control and safety assessment method for thermal power units according to claim 8, characterized in that: The grid-based hierarchical management interface is set with the distance between adjacent beacons arranged in the factory area as the minimum grid unit, and the distance between two adjacent beacons is 4.3-5 meters.

10. The multi-parameter intelligent control and safety assessment method for thermal power units according to claim 8, characterized in that: The visual display module further realizes the linkage between positioning and monitoring, and automatically calls the nearest camera for real-time tracking through the personnel coordinates; the data of the security situation awareness module are transmitted to the central processor via wired or wireless means, and are updated synchronously with the visual display module to form an intelligent management and control system with closed-loop feedback.

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