Boiler deslagging system and method for coal-fired power plant, electronic equipment and storage medium

Abstract

The invention relates to a boiler deslagging system and method for a coal-fired power plant, electronic equipment and a storage medium, and the system comprises a data collection module which is used for collecting a current image and a current temperature of boiler bottom slag; the edge calculation module is used for identifying the actual slag falling position, the actual size and the actual temperature of the falling slag; the intelligent decision-making module is used for generating slag discharging system adjusting parameters and / or starting slag removing operation according to the actual slag falling position, the actual size and the actual temperature of the falling slag and historical data; and the execution control module is used for driving the corresponding equipment to execute the corresponding deslagging action according to the deslagging system adjusting parameters and / or starting the deslagging operation. Therefore, the problems that in the related technology, due to the fact that the slag discharging system utilizes a big data analysis method, the calculation capacity is limited, a sensor only monitors the temperature and the pressure, the actual position, the actual size and the actual temperature of falling slag cannot be accurately recognized, and the intelligent boiler slag discharging system is delayed in data processing, low in recognition precision and the like are solved.

Description

Technical Field

[0001] The present application relates to the field of intelligent technology for coal-fired power plants, and in particular to a boiler slag removal system, method, electronic equipment, and storage medium for a coal-fired power plant. Background Art

[0002] The boiler deslagging process in traditional coal-fired power plants relies primarily on manual operation and monitoring, resulting in low efficiency, significant safety hazards, and high resource consumption. With the rapid development of intelligent technology, applying advanced information technology to the deslagging process in coal-fired power plants to improve the system's automation and intelligence has become an inevitable trend in the industry.

[0003] In related technologies, the slag discharge system uses thermocouples and piezoresistive pressure sensors to monitor the temperature and pressure inside the boiler in real time, uses automatic control equipment such as frequency converters and control cabinets to receive sensor signals and control the operation of the slag discharge equipment, and uses big data analysis to process and analyze sensor data to optimize the slag discharge process.

[0004] However, in related technologies, the slag discharge system uses big data analysis methods, which results in limited computing power. The sensors can only monitor the temperature and pressure inside the boiler and cannot accurately identify the actual position, size and temperature of the slag. As a result, the intelligent boiler slag discharge system has problems such as data processing delay and low recognition accuracy, which urgently need to be improved. Summary of the Invention

[0005] The present application provides a boiler slag discharge system, method, electronic equipment and storage medium for a coal-fired power plant to solve the problems in related technologies, in which the slag discharge system uses big data analysis methods, resulting in limited computing power, sensors that can only monitor the temperature and pressure in the boiler, and cannot accurately identify the actual position, actual size and actual temperature of the slag, resulting in data processing delays, low recognition accuracy and other problems in the intelligent boiler slag discharge system.

[0006] The first aspect of the present application provides a boiler slag discharge system for a coal-fired power plant, including: a data acquisition module for collecting a current image and a current temperature of slag falling from the bottom of the boiler furnace; an edge computing module for processing the current image and the current temperature to obtain processed data, and identifying the actual slag position, actual size and actual temperature of the slag according to the processed data; an intelligent decision-making module for generating slag discharge system adjustment parameters and / or starting a slag cleaning operation according to the actual slag position, actual size and actual temperature of the slag and historical data; and an execution control module for driving corresponding equipment to perform corresponding slag discharge actions according to the slag discharge system adjustment parameters and / or the starting of the slag cleaning operation.

[0007] The embodiment of the present application can use the current image and current temperature to identify the actual slag position, actual size and actual temperature of the slag, so as to adjust the parameters of the slag discharge system and start the slag cleaning operation. That is, through the cooperation of multiple modules, the efficient operation of the boiler slag discharge system is ensured, the accuracy and safety of the control are improved, and the intelligence, automation and efficiency of the boiler slag discharge process are realized.

[0008] Optionally, in one embodiment of the present application, it also includes: a safety monitoring module, which is used to detect the current operating status of the boiler slag discharge system based on at least one key parameter of the boiler, so as to generate an alarm message for warning when the current operating status is unstable, and execute preset safety measures when the reminder duration is greater than the preset duration or the alarm message meets the preset serious conditions.

[0009] The embodiment of the present application can monitor the current operating status of the boiler slag discharge system in real time through the safety monitoring module, ensuring that the system can take safety measures in a timely manner when abnormal situations occur, thereby effectively preventing equipment damage or safety accidents and improving the safety and reliability of the system.

[0010] Optionally, in one embodiment of the present application, it further includes: a human-computer interaction module, used to display at least one of the current operating status, the slag discharge system adjustment parameters, and the alarm information.

[0011] The embodiment of the present application can provide an intuitive and easy-to-use user interface through the human-computer interaction module. Operators can view system status, adjust parameters and alarm information in real time through the touch screen, support remote access and control functions, and improve the flexibility and operational convenience of the system.

[0012] Optionally, in one embodiment of the present application, the edge computing module includes: an image recognition unit for identifying the initial slag position, initial size and initial temperature of the slag based on the current image; a data analysis unit for extracting key information based on the initial slag position, initial size and initial temperature of the slag, so as to obtain the actual slag position, actual size and actual temperature of the slag based on the key information; and a decision support unit for using the actual slag position, actual size and actual temperature of the slag to support the intelligent decision module.

[0013] The embodiments of the present application can ensure that the system can quickly and accurately identify slag information, generate decision recommendations, and transmit them to the intelligent decision-making module through a high-speed network interface through efficient processing capabilities, thereby ensuring the real-time and accuracy of decisions.

[0014] Optionally, in one embodiment of the present application, the intelligent decision-making module includes: a data preprocessing unit, used to perform at least one preprocessing operation on the actual slag position, actual size and actual temperature of the slag to obtain processed data; a model training unit, used to output prediction results based on the processed data and a pre-built prediction model; a decision execution unit, used to generate the slag discharge system adjustment parameters and / or the start of the slag cleaning operation according to the prediction results.

[0015] The embodiments of the present application can generate precise adjustment parameters or slag removal operation instructions to ensure that the system can respond quickly and execute corresponding operations, avoiding equipment damage or safety hazards caused by untimely slag removal, thereby improving the operating efficiency and stability of the system.

[0016] Optionally, in one embodiment of the present application, it also includes: a backup module, used to back up at least one of the data acquisition module, the edge computing module, the intelligent decision-making module and the execution control module to perform the corresponding module functions.

[0017] The embodiments of the present application can ensure the normal operation of the system through the redundant design of the backup module, ensure that the system can be quickly restored when a failure occurs, and significantly improve the reliability and stability of the system.

[0018] The second aspect of the present application provides a method for boiler slag removal in a coal-fired power plant, comprising the following steps: collecting a current image and a current temperature of slag falling from the bottom of the boiler furnace; processing the current image and the current temperature to obtain processed data, and identifying the actual slag position, actual size and actual temperature of the slag based on the processed data; generating slag removal system adjustment parameters and / or starting a slag cleaning operation based on the actual slag position, actual size and actual temperature of the slag and historical data; and driving corresponding equipment to perform corresponding slag removal actions based on the slag removal system adjustment parameters and / or the starting of the slag cleaning operation.

[0019] Optionally, in one embodiment of the present application, it also includes: detecting the current operating state of the boiler slag discharge system based on at least one key parameter of the boiler, so as to generate an alarm message for warning when the current operating state is unstable, and executing preset safety measures when the reminder duration is greater than the preset duration or the alarm message meets the preset serious conditions.

[0020] Optionally, in one embodiment of the present application, it further includes: displaying at least one of the current operating status, the slag discharge system adjustment parameters, and the alarm information.

[0021] Optionally, in one embodiment of the present application, the current image and the current temperature are processed to obtain processed data, and the actual slag position, actual size and actual temperature of the slag are identified based on the processed data, including: based on the current image, identifying the initial slag position, initial size and initial temperature of the slag; extracting key information based on the initial slag position, initial size and initial temperature of the slag to obtain the actual slag position, actual size and actual temperature of the slag based on the key information; and using the actual slag position, actual size and actual temperature of the slag to support the intelligent decision-making module.

[0022] Optionally, in one embodiment of the present application, the generating of slag discharge system adjustment parameters and / or the initiation of slag cleaning operation based on the actual slag falling position, actual size and actual temperature of the slag falling and historical data includes: performing at least one preprocessing operation on the actual slag falling position, actual size and actual temperature of the slag falling to obtain processed data; outputting prediction results based on the processed data and a pre-built prediction model; generating the slag system adjustment parameters and / or the initiation of slag cleaning operation based on the prediction results.

[0023] Optionally, in one embodiment of the present application, it also includes: backing up at least one of the data acquisition module, the edge computing module, the intelligent decision-making module and the execution control module to execute the corresponding module function.

[0024] The third aspect of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the boiler slag discharge method for a coal-fired power plant as described in the above embodiment.

[0025] A fourth aspect of the present application provides a computer-readable storage medium, which stores a computer program. When the program is executed by a processor, it implements the above-mentioned boiler slag discharge method for a coal-fired power plant.

[0026] The fifth aspect of the present application provides a computer program product, which stores a computer program that, when executed by a processor, implements the above-mentioned boiler slag discharge method for a coal-fired power plant.

[0027] The embodiments of the present application can use the current image and current temperature of the boiler bottom slag to determine the actual slag location, size, and temperature of the slag, thereby adjusting the slag removal system adjustment parameters or executing the corresponding slag removal action, thereby realizing intelligent and automated control of the boiler slag removal. This solves the problem that the slag removal system in the related art uses big data analysis methods, resulting in limited computing power. The sensor can only monitor the temperature and pressure in the boiler and cannot accurately identify the actual location, size, and temperature of the slag, resulting in data processing delays and low recognition accuracy in the intelligent boiler slag removal system.

[0028] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0030] Figure 1 This is a schematic structural diagram of a boiler slag discharge system for a coal-fired power plant provided according to an embodiment of the present application;

[0031] Figure 2 This is a flow chart of a boiler slagging method for a coal-fired power plant provided according to an embodiment of the present application;

[0032] Figure 3 A schematic diagram of the structure of an electronic device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0033] The following describes in detail embodiments of the present application, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0034] The following describes the boiler slag discharge system, method, electronic device and storage medium of the coal-fired power plant of the embodiment of the present application with reference to the accompanying drawings. In view of the related art mentioned in the above background technology center, the slag discharge system uses a big data analysis method, resulting in limited computing power, and the sensor can only monitor the temperature and pressure in the boiler, and cannot accurately identify the actual position, actual size and actual temperature of the slag, so that the intelligent boiler slag discharge system has problems such as data processing delay and low recognition accuracy. The present application provides a boiler slag discharge system for a coal-fired power plant, in which the current image and current temperature of the slag at the bottom of the boiler can be used to determine the actual slag discharge position, actual size and actual temperature of the slag, so as to adjust the slag discharge system adjustment parameters or perform corresponding slag discharge actions, thereby realizing intelligent and automated control of the boiler slag discharge. Thus, the related art solves the problem that the slag discharge system uses a big data analysis method, resulting in limited computing power, and the sensor can only monitor the temperature and pressure in the boiler, and cannot accurately identify the actual position, actual size and actual temperature of the slag, so that the intelligent boiler slag discharge system has problems such as data processing delay and low recognition accuracy.

[0035] Specifically, Figure 1 This is a structural schematic diagram of a boiler slag discharge system for a coal-fired power plant provided in an embodiment of the present application.

[0036] like Figure 1 As shown, the boiler slag discharge device 10 of the coal-fired power plant includes: a data acquisition module 100, an edge computing module 200, an intelligent decision-making module 300 and an execution control module 400.

[0037] Specifically, the data acquisition module 100 is used to collect the current image and current temperature of the boiler bottom slag.

[0038] It is understandable that in the embodiment of the present application, the collection of the current image and the current temperature can be completed by, but is not limited to, a high-definition camera and an infrared temperature sensor.

[0039] For example, in the embodiment of the present application, the data acquisition module 100 may include, but is not limited to, at least one 5G high-definition camera and an infrared temperature sensor. The 5G high-definition camera has a resolution of 4096x2160 pixels, a frame rate of not less than 30 frames per second, supports 4K high-definition video recording, and has night vision and dust-proof and waterproof design to ensure stable operation in various environments, thereby collecting the current image of the boiler bottom slag; the infrared temperature sensor has an accuracy of ±0.5°C, a measurement range of 0-1200°C, a response time of no more than 0.1 second, and uses non-contact temperature measurement technology to perform real-time measurement, thereby collecting the current temperature of the boiler bottom slag. The embodiment of the present application can capture the current image and current temperature of the boiler bottom slag in real time by collecting data in real time, ensuring that the system can respond to changes in the boiler slag discharge process in a timely manner, and improving the automation and intelligence level of the system.

[0040] The edge computing module 200 is used to process the current image and the current temperature to obtain processed data, and identify the actual slag position, actual size and actual temperature of the slag based on the processed data.

[0041] It can be understood that in the embodiment of the present application, the edge computing module 200 processes the current image and the current temperature to obtain the initial position, initial size and initial temperature of the slag, and identifies the actual slag position, actual size and actual temperature of the slag based on the initial position, initial size and initial temperature of the slag.

[0042] For example, the embodiment of the present application can adopt a high-performance AI computing platform with a built-in GPU and deep learning accelerator, with a processing speed of not less than 200 frames per second, accurately identifying the actual slag location, actual size and actual temperature of the slag, with an identification accuracy rate of not less than 98% and a false alarm rate of not more than 2%. It also supports real-time data analysis and processing, and can complete a complete image recognition and analysis process within 0.1 seconds.

[0043] The embodiment of the present application can ensure that the system can quickly complete the image recognition and analysis process through the fast processing capabilities of the edge computing module, identify the actual slag location, actual size and actual temperature of the slag, and significantly improve the system's response speed and decision-making efficiency.

[0044] Optionally, in one embodiment of the present application, the edge computing module 200 includes: an image recognition unit, a data analysis unit, and a decision support unit. The image recognition unit is configured to identify the initial slag position, initial size, and initial temperature of the slag based on the current image; the data analysis unit is configured to extract key information based on the initial slag position, initial size, and initial temperature of the slag, so as to obtain the actual slag position, actual size, and actual temperature of the slag based on the key information; and the decision support unit is configured to use the actual slag position, actual size, and actual temperature of the slag to support the intelligent decision module.

[0045] It can be understood that in the embodiment of the present application, the image recognition unit obtains the initial slag position, initial size and initial temperature of the slag; the data analysis unit obtains the actual slag position, actual size and actual temperature of the slag based on the initial slag position, initial size and initial temperature of the slag; and the decision support unit generates decision recommendations based on the actual slag position, actual size and actual temperature.

[0046] During the actual implementation process, the embodiment of the present application can adopt an image recognition model based on a deep learning algorithm in a deep learning accelerator through the image recognition unit, and can adopt a deep learning framework such as TensorFlow or PyTorch to extract features in the image captured by the high-definition camera, and learn the slag position, size and temperature of the slag through a large amount of training data, so as to accurately identify the initial position, initial size and initial temperature of the slag in actual applications; the initial slag position, initial size and initial temperature of the slag output by the image recognition unit are further analyzed by the built-in GPU of the data analysis unit, for example, using the NVIDIA Jetson Xavier NX high-performance AI computing platform for analysis, and using data mining and machine learning algorithms to extract the actual slag position, actual size and actual temperature of the slag; the decision support unit generates a decision recommendation based on the results of the data analysis unit, for example, by analyzing the actual temperature of the slag to determine whether it is within the normal range, and transmits it to the intelligent decision module through the high-speed network interface to provide decision support for the intelligent decision module.

[0047] The embodiments of the present application can ensure that the system can quickly and accurately identify slag information through efficient processing capabilities, providing reliable data support for subsequent intelligent decision-making.

[0048] The intelligent decision module 300 is used to generate adjustment parameters of the slag discharge system and / or start the slag removal operation according to the actual slag falling position, actual size and actual temperature and historical data.

[0049] It can be understood that in the embodiment of the present application, the intelligent decision-making module 300 generates adjustment parameters or starts a slag cleaning action based on the actual slag falling position, actual size, actual temperature and historical data of the slag falling; the intelligent decision-making module 300 is connected to the edge computing module 200 and the execution control module 400 through a high-speed network interface to ensure the real-time and accuracy of instruction transmission; the adjustment parameter can be to adjust the slag discharger speed.

[0050] For example, the embodiment of the present application can generate slag discharge system adjustment parameters and start slag cleaning operations based on the actual slag falling position, actual size, actual temperature and historical data of the slag falling, and the operating status of the boiler slag discharge system can be intelligently predicted based on the reinforcement learning algorithm. The adjustment parameters of the slag discharge system can also be generated and the slag cleaning operations can be started. The adjustment parameters may include the speed of the slag discharger, the opening of the hydraulic shut-off door, etc. For example, if the model predicts that the temperature of the slag falling is too high, the intelligent decision-making module 300 will generate an instruction to adjust the speed of the slag discharger. The intelligent decision-making module has a built-in high-performance CPU and memory, supports multi-threaded parallel processing, can process a large amount of data in a short time and generate slag discharge system adjustment parameters and make decisions. The decision-making speed does not exceed 0.2 seconds, thereby improving the response speed of the system and ensuring the accuracy and timeliness of the slag discharge operation.

[0051] The embodiment of the present application can be based on a reinforcement learning algorithm, and can intelligently predict the operating status of the boiler slag discharge system based on historical data and real-time data, and make adjustment decisions in advance to ensure the real-time and accuracy of instruction transmission.

[0052] Optionally, in one embodiment of the present application, the intelligent decision module 300 includes: a data preprocessing unit, a model training unit, and a decision execution unit. The data preprocessing unit is configured to perform at least one preprocessing operation on the actual slag location, actual size, and actual temperature of the slag to obtain processed data; the model training unit is configured to output a prediction result based on the processed data and a pre-built prediction model; and the decision execution unit is configured to generate adjustment parameters for the slag discharge system and / or initiate a slag removal operation based on the prediction result.

[0053] It is understandable that the preprocessing operation in the embodiment of the present application can be to clean and normalize the input data; the pre-built prediction model can adopt a deep learning framework such as TensorFlow or PyTorch.

[0054] In the actual implementation process, the embodiment of the present application can use the data preprocessing unit to perform preprocessing operations such as cleaning and normalization on the input data, but is not limited to using the Python programming language, calibrate the temperature data of the slag to ensure the accuracy of the data, and denoise the image data to improve the accuracy of subsequent analysis. It uses libraries such as Pandas and NumPy to align the time series and interpolate missing values of historical data (such as slag discharge frequency and temperature), and perform at least one preprocessing operation on the actual slag position, actual size and actual temperature of the slag; the model training unit uses deep learning frameworks such as TensorFlow or PyTorch to strengthen learning algorithms , train the pre-processed data, generate a prediction model based on historical data and real-time data, and predict the operating status of the boiler slag discharge system based on the processed data and the pre-built prediction model, and output the prediction results; the decision execution unit can generate slag discharge system adjustment parameters according to the prediction results, and can also start the slag cleaning operation according to the prediction results. It can also generate slag discharge system adjustment parameters and start the slag cleaning operation according to the prediction results. The adjustment parameters may include the speed of the slag discharger, the opening of the hydraulic shut-off door, etc. For example, if the model predicts that the temperature of the slag falling is too high, it will generate an instruction to adjust the speed of the slag discharger to reduce the temperature, and transmit the adjustment parameters to the execution control module 400 through the high-speed network interface.

[0055] The embodiment of the present application can ensure that the system can make adjustment decisions in advance through the intelligent prediction capability of the intelligent decision-making module 300, thereby avoiding equipment damage or safety hazards caused by untimely slag discharge, thereby improving the operating efficiency and stability of the system.

[0056] The execution control module 400 is used to adjust parameters of the slag discharge system and / or start the slag cleaning operation to drive the corresponding equipment to perform the corresponding slag discharge action.

[0057] It can be understood that in the embodiment of the present application, the corresponding equipment can be driven to perform the corresponding slag discharge action by controlling the operation of the slag discharge machine, hydraulic shut-off door and other equipment through a PLC (Programmable Logic Controller).

[0058] For example, the embodiments of the present application can, but are not limited to, use the Siemens S7-1200 series PLC to receive instructions from the intelligent decision-making module. The instructions may include adjusting parameters of the slag discharge system, starting slag cleaning operations, and generating control signals based on adjusting parameters of the slag discharge system and starting slag cleaning operations. The instructions require adjusting the speed of the slag discharger, and the execution control module 400 will generate corresponding control signals to adjust the operating speed of the slag discharger; the slag discharger and the hydraulic shut-off door receive signals, and convert the control signals into actual actions of the equipment through motors, hydraulic cylinders, etc., drive these devices to perform corresponding slag discharge actions, and accurately control parameters such as the slag discharger speed and the opening of the hydraulic shut-off door. For example, the execution control module 400 can control the opening of the hydraulic shut-off door to adjust the slag discharge flow rate; the use of high-precision sensors can monitor the operating status of the equipment in real time and provide data feedback for closed-loop control.

[0059] The embodiment of the present application can ensure that the system can accurately control parameters such as the slag discharger speed and the hydraulic shut-off door opening according to the instructions of the intelligent decision-making module through the precise control capability of the execution control module 400, thereby improving the operating efficiency and stability of the system.

[0060] Optionally, in one embodiment of the present application, the boiler slag discharge device 10 of a coal-fired power plant further includes a safety monitoring module. The safety monitoring module is configured to detect the current operating state of the boiler slag discharge system based on at least one key parameter of the boiler, generate an alarm message to provide a warning when the current operating state is unstable, and execute preset safety measures if the reminder duration exceeds a preset duration or the alarm message meets a preset severity condition.

[0061] It can be understood that the security monitoring module in the embodiment of the present application can be but is not limited to built-in high-precision sensors and alarm devices; the security monitoring module is connected to the intelligent decision-making module and the execution control module through an internal bus to ensure real-time and reliability; the preset serious condition in the embodiment of the present application can be that the alarm duration is greater than the preset duration.

[0062] For example, the embodiment of the present application can monitor the temperature, pressure, vibration and other key parameters of the boiler slag discharge system in real time, and monitor at least one key parameter of the boiler slag discharge system in real time through high-precision sensors. For example, the temperature sensor can monitor the temperature of the boiler furnace bottom in real time, and the pressure sensor can monitor the pressure changes of the slag discharge system; when the parameters exceed the set range, that is, when the current operating state is unstable, the alarm is automatically triggered, and the sound and light alarm method is used to attract the attention of the operator, and the preset safety measures are executed when the reminder duration is greater than the preset duration or the alarm information meets the preset serious conditions, and control elements such as relays are used to take corresponding safety measures according to the alarm information, such as shutting down, cutting off the power supply, etc.

[0063] The embodiment of the present application can monitor the current operating status of the boiler slag discharge system in real time through the safety monitoring module to ensure that the system can take safety measures in time when abnormal situations occur to avoid equipment damage or safety accidents.

[0064] It should be noted that the preset severe condition can be set by those skilled in the art according to actual conditions and is not specifically limited here.

[0065] Optionally, in one embodiment of the present application, the boiler slag discharge device 10 of a coal-fired power plant further includes a human-computer interaction module, wherein the human-computer interaction module is configured to display at least one of the current operating status, adjustment parameters of the slag discharge system, and alarm information.

[0066] It can be understood that in the embodiment of the present application, at least one of the current operating status, the slag discharge system adjustment parameters, and the alarm information can be displayed through the display screen.

[0067] For example, in the embodiment of the present application, the human-computer interaction module is composed of a touch screen display and an embedded system. The touch screen display can be, but is not limited to, a 10.1-inch high-definition touch screen with a display resolution of 1920x1200 pixels and supports multi-touch operation. The touch screen display is used to display the operating status, alarm information and operation guide of the boiler slag discharge system. For example, the operator can view the current slag discharge machine speed, hydraulic shut-off door opening and other parameters through the touch screen; the embedded system can be, but is not limited to, an ARM Cortex-A series processor with high performance and low power consumption. The embedded system is responsible for processing the user's input instructions and transmitting the instructions to the corresponding module. The human-computer interaction module has a built-in embedded system, which processes the user's input instructions through a high-performance processor and a graphics accelerator and transmits the instructions to the corresponding module. It supports smooth user interface operation and graphics rendering; the human-computer interaction module can display the operating status, alarm information and operation guide of the boiler slag discharge system in real time through the display screen, and provide parameter setting and alarm confirmation functions. At the same time, it supports remote access and control functions through network technologies such as VPN (Virtual Private Network), which facilitates operators to monitor and operate the system from a remote location and ensures the security of remote operation.

[0068] The embodiments of the present application can improve the flexibility and convenience of the system through the intuitive and easy-to-use interface of the human-computer interaction module, making it easier for operators to perform system monitoring and parameter setting.

[0069] Optionally, in one embodiment of the present application, the boiler slag discharge device 10 of a coal-fired power plant further includes a backup module, wherein the backup module is configured to back up at least one of the data acquisition module, the edge computing module, the intelligent decision-making module, and the execution control module to perform the corresponding module functions.

[0070] It is understandable that in the embodiment of the present application, when a module fails, the backup module can immediately take over the work to ensure the normal operation of the system.

[0071] During the actual implementation process, the embodiment of the present application can use the backup module to immediately take over when a key module fails, execute the corresponding module functions, ensure the normal operation of the system, and support automatic switching and fault recovery functions, which can restore the normal operation of the system in a short time. When the faulty module returns to normal, the backup module will automatically switch back to the standby state.

[0072] The embodiments of the present application can ensure that the system can recover quickly when a failure occurs through the redundant design of the backup module, thereby improving the reliability and stability of the system.

[0073] According to the coal-fired power plant boiler slag removal system proposed in the embodiment of the present application, the actual slag position, size, and temperature of the slag can be determined using the current image and temperature of the slag falling from the boiler furnace bottom, thereby adjusting the slag removal system adjustment parameters or performing corresponding slag removal actions, thereby realizing intelligent and automated control of the boiler slag removal. This solves the problem that the slag removal system in the related art uses big data analysis methods, resulting in limited computing power. The sensor can only monitor the temperature and pressure in the boiler and cannot accurately identify the actual position, size, and temperature of the slag, resulting in data processing delays and low recognition accuracy in the intelligent boiler slag removal system.

[0074] Next, a boiler slag removal method for a coal-fired power plant proposed in accordance with an embodiment of the present application will be described with reference to the accompanying drawings.

[0075] Figure 2 A schematic flow chart of a boiler slagging method for a coal-fired power plant provided in an embodiment of the present application.

[0076] like Figure 2 As shown, the boiler slagging method of the coal-fired power plant includes the following steps:

[0077] In step S201 , the current image and current temperature of the boiler bottom slag are collected.

[0078] In step S202, the current image and the current temperature are processed to obtain processed data, and the actual slag position, actual size and actual temperature of the slag are identified based on the processed data.

[0079] In step S203, slag discharge system adjustment parameters are generated and / or slag removal operation is started according to the actual slag position, actual size and actual temperature of the slag and historical data.

[0080] In step S204, the parameters of the slag discharge system are adjusted and / or the slag cleaning operation is started to drive the corresponding equipment to perform the corresponding slag discharge action.

[0081] Optionally, in one embodiment of the present application, the boiler slag discharge method of a coal-fired power plant further includes: detecting the current operating state of the boiler slag discharge system based on at least one key parameter of the boiler, so as to generate an alarm message for warning when the current operating state is unstable, and executing preset safety measures when the reminder duration is greater than the preset duration or the alarm message meets the preset serious conditions.

[0082] Optionally, in one embodiment of the present application, the boiler slagging method of a coal-fired power plant further includes: displaying at least one of the current operating status, slagging system adjustment parameters, and alarm information.

[0083] Optionally, in one embodiment of the present application, the current image and the current temperature are processed to obtain processed data, and the actual slag position, actual size and actual temperature of the slag are identified based on the processed data, including: based on the current image, identifying the initial slag position, initial size and initial temperature of the slag; extracting key information based on the initial slag position, initial size and initial temperature of the slag to obtain the actual slag position, actual size and actual temperature of the slag based on the key information; and using the actual slag position, actual size and actual temperature of the slag to support the intelligent decision-making module.

[0084] Optionally, in one embodiment of the present application, the slag discharge system adjustment parameters and / or the slag cleaning operation are generated based on the actual slag falling position, actual size, actual temperature and historical data of the slag falling, including: performing at least one pre-processing operation on the actual slag falling position, actual size and actual temperature of the slag falling to obtain processed data; outputting a prediction result based on the processed data and a pre-built prediction model; and generating the slag discharge system adjustment parameters and / or the slag cleaning operation based on the prediction result. It should be noted that the aforementioned explanation of the embodiment of the boiler slag discharge system of a coal-fired power plant is also applicable to the boiler slag discharge method of a coal-fired power plant in this embodiment, and will not be repeated here.

[0085] Optionally, in one embodiment of the present application, the boiler slag discharge method of a coal-fired power plant further includes: backing up at least one of the data acquisition module, the edge computing module, the intelligent decision-making module and the execution control module to execute the corresponding module functions.

[0086] According to the boiler slag removal method for a coal-fired power plant proposed in an embodiment of the present application, the current image and current temperature of the slag falling from the bottom of the boiler furnace are used to determine the actual slag position, actual size, and actual temperature of the slag, thereby adjusting the slag removal system adjustment parameters or performing corresponding slag removal actions, thereby realizing intelligent and automated control of the boiler slag removal. This solves the problem that in related technologies, the slag removal system uses big data analysis methods, resulting in limited computing power. The sensor can only monitor the temperature and pressure inside the boiler and cannot accurately identify the actual position, actual size, and actual temperature of the slag, resulting in data processing delays and low recognition accuracy in the intelligent boiler slag removal system.

[0087] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device may include:

[0088] Memory 301 , processor 302 , and computer programs stored in the memory 301 and executable on the processor 302 .

[0089] When the processor 302 executes the program, the boiler slag discharge method for a coal-fired power plant provided in the above embodiment is implemented.

[0090] Furthermore, the electronic device further includes:

[0091] The communication interface 303 is used for communication between the memory 301 and the processor 302 .

[0092] The memory 301 is used to store computer programs that can be run on the processor 302 .

[0093] The memory 301 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0094] If the memory 301, processor 302, and communication interface 303 are implemented independently, the communication interface 303, memory 301, and processor 302 can be interconnected via a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0095] Optionally, in a specific implementation, if the memory 301 , the processor 302 and the communication interface 303 are integrated on a chip, the memory 301 , the processor 302 and the communication interface 303 can communicate with each other through an internal interface.

[0096] The processor 302 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0097] An embodiment of the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned boiler slag discharge method for a coal-fired power plant.

[0098] An embodiment of the present application further provides a computer program, on which a computer program is stored, and when the program is executed by a processor, the above-mentioned boiler slag discharge method of a coal-fired power plant is implemented.

[0099] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.

[0100] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of technical features indicated. Thus, a feature specified as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of this application, "N" means at least two, for example, two, three, etc., unless otherwise specifically defined.

[0101] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing a custom logical function or process step, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may be performed in a different order than shown or discussed, including performing functions in a substantially simultaneous manner or in a reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application pertain.

[0102] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or N wires (electronic devices), a portable computer disk cartridge (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and programmable read-only memory (EPROM or flash memory), fiber optic devices, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program can be obtained electronically by optically scanning the paper or other medium and then editing, interpreting or processing it in other suitable ways as necessary, and then storing it in a computer memory.

[0103] It should be understood that various parts of the present application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiment, the N steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented using hardware, as in another embodiment, it can be implemented using any one or a combination of the following technologies known in the art: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0104] Those skilled in the art will understand that all or part of the steps in the method of the above embodiment can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

[0105] In addition, the functional units in the various embodiments of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into a module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0106] The storage medium mentioned above may be a read-only memory, a magnetic disk, or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application. Persons skilled in the art may make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A boiler slag removal system for a coal-fired power plant, characterized in that: include: Data acquisition module, used to collect the current image and current temperature of the boiler bottom slag; an edge computing module, configured to process the current image and the current temperature to obtain processed data, and identify the actual slag position, actual size, and actual temperature of the slag according to the processed data; An intelligent decision-making module, configured to generate adjustment parameters for a slag discharge system and / or initiate a slag removal operation based on the actual slag falling position, actual size, actual temperature, and historical data of the slag falling; The execution control module is used to drive the corresponding equipment to perform the corresponding slag discharge action according to the adjustment parameters of the slag discharge system and / or the start of the slag cleaning operation.

2. The system according to claim 1, wherein: Also includes: A safety monitoring module is used to detect the current operating state of the boiler slag discharge system based on at least one key parameter of the boiler, so as to generate an alarm message for warning when the current operating state is unstable, and to execute preset safety measures when the reminder duration is greater than a preset duration or the alarm message meets a preset serious condition.

3. The system according to claim 2, characterized in that Also includes: The human-computer interaction module is used to display at least one of the current operating status, the slag discharge system adjustment parameters, and the alarm information.

4. The system according to claim 1, wherein: The edge computing module includes: An image recognition unit, configured to identify an initial slag falling position, an initial size, and an initial temperature of the slag falling based on the current image; a data analysis unit, configured to extract key information based on the initial slag position, initial size, and initial temperature of the slag, so as to obtain the actual slag position, actual size, and actual temperature of the slag based on the key information; A decision support unit is used to support the intelligent decision module by using the actual slag position, actual size and actual temperature of the slag.

5. The system according to claim 1 or 4, characterized in that The intelligent decision-making module includes: a data preprocessing unit, configured to perform at least one preprocessing operation on the actual slag falling position, actual size and actual temperature of the slag falling to obtain processed data; A model training unit, configured to output a prediction result based on the processed data and a pre-built prediction model; A decision execution unit is used to generate the slag discharge system adjustment parameters and / or start the slag removal operation according to the prediction result.

6. The system according to claim 1, wherein: Also includes: A backup module is used to backup at least one of the data acquisition module, the edge computing module, the intelligent decision-making module and the execution control module to perform the corresponding module functions.

7. A method for removing slag from a boiler in a coal-fired power plant, characterized in that: The following steps are involved: Collect the current image and current temperature of the boiler bottom slag; Processing the current image and the current temperature to obtain processed data, and identifying the actual slag position, actual size, and actual temperature of the slag according to the processed data; generating slag discharge system adjustment parameters and / or starting slag removal operation according to the actual slag falling position, actual size and actual temperature of the slag falling and historical data; According to the slag discharge system adjustment parameters and / or the start of the slag cleaning operation, the corresponding equipment is driven to perform the corresponding slag discharge action.

8. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the boiler slagging method for a coal-fired power plant according to claim 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the boiler slagging method for a coal-fired power plant according to claim 7 .

10. A computer program product comprising a computer program, characterized in that The computer program is executed to implement the boiler slagging method for a coal-fired power plant according to claim 7 .

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