Anti-slagging control method for coal slime circulating fluidized bed

Abstract

The invention discloses an anti-slagging control method for a coal slime circulating fluidized bed, and relates to the field of combustion of the coal slime circulating fluidized bed, which comprises the following steps: S1, data acquisition: monitoring the interior of the CFB by using a high-precision temperature sensor, a pressure sensor, an oxygen analyzer, a microwave material concentration sensor and a laser particle size analyzer; the method comprises the steps of S1, building a prediction model, S2, utilizing training and prediction learning of a vector machine (SVM) algorithm model machine to recognize potential slagging risks in advance, S3, optimizing combustion conditions, S4, carrying out a slag removal program, S5, carrying out data analysis, S6, carrying out equipment maintenance and S7, carrying out multi-system linkage coordination. According to the method, through data acquisition, prediction model establishment, combustion condition optimization, real-time monitoring and dynamic combustion parameter adjustment, the problem of unstable combustion caused by slagging is effectively avoided, it is ensured that the CFB can stably operate under various working conditions, the energy utilization efficiency is improved, and the frequency of slagging events in the CFB operation period can be greatly reduced.

Description

Technical Field

[0001] This invention relates to the field of circulating fluidized bed combustion of coal slime, and in particular to a method for preventing slagging in circulating fluidized bed combustion of coal slime. Background Technology

[0002] Circulating fluidized bed (CFB) boilers utilize the most advanced clean coal combustion technology in industrial applications. These boilers employ fluidized bed combustion and primarily consist of two parts: a combustion chamber (including dense and dilute phase zones) and a recirculation system (including a high-temperature gas-solid separator and a return system). The biggest difference between CFB boilers and bubbling fluidized bed combustion technology is the higher operating velocity, which enhances heterogeneous reaction processes such as combustion and desulfurization. Boiler capacity can be expanded to large capacities acceptable to the power industry (600MW or higher). CFB boilers have effectively solved fundamental problems in thermodynamics, mechanics, and materials science, as well as engineering issues such as expansion, wear, and overheating, making them an advanced technology for the energy utilization of difficult-to-burn solid fuels (such as coal gangue, oil shale, municipal waste, sludge, and other waste materials).

[0003] Traditional circulating fluidized bed (CFB) boilers are widely used in coal-fired power generation due to their high combustion efficiency and low pollution emissions. However, CFB boilers are prone to slagging in the furnace during operation, which leads to problems such as decreased combustion efficiency and increased maintenance costs.

[0004] Currently, the industry generally adopts methods such as adjusting combustion temperature, adding desulfurizing agents, and regular slag removal to prevent and alleviate slagging in the furnace. Although these methods can suppress slagging to a certain extent, they are still difficult to effectively avoid severe slagging during continuous operation, especially when high-sulfur coal and low-quality fuel are used, which affects combustion stability and economic efficiency.

[0005] Existing anti-slagging methods cannot accurately control the combustion state in a circulating fluidized bed in real time under complex coal quality conditions, resulting in frequent slagging. Summary of the Invention

[0006] The purpose of this invention is to address the shortcomings of existing technologies by proposing a method for preventing slagging in a circulating fluidized bed of coal slime, thereby solving the problem of frequent slagging in the aforementioned technical solutions.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a method for preventing slagging in a circulating fluidized bed of coal slime, comprising the following control methods: S1. Data Acquisition: High-precision temperature sensors, pressure sensors, oxygen analyzers, microwave material concentration sensors, and laser particle size analyzers are used to monitor the temperature, pressure, oxygen content, material concentration, and material particle size inside the CFB and collect relevant data in real time. S2. Establish a predictive model: Based on the relevant data collected in step S1, use the vector machine (SVM) algorithm model to train and predict the learning process, analyze the correlation between historical combustion data and slagging, establish a predictive model, and identify potential slagging risks in advance. S3. Optimize combustion conditions: Based on the risk level predicted by the model in step S2, dynamically adjust the feed rate, air distribution ratio and auxiliary fuel quantity to optimize combustion conditions and prevent the formation of a continuous overheating state in the high-temperature zone. S4. Slag Removal Program: Monitors ash deposition in the furnace. When the accumulated deposits exceed the threshold, the slag removal program is automatically started to maintain the CFB in good working condition. S5. Data Analysis: As per step S4, after each slag removal procedure is completed, the system quickly initiates a comprehensive data collection process. S6. Equipment Maintenance: Based on steps S2 and S4, for the feeding device, comprehensively analyze the data of motor current, feeding rate stability, material blockage and sensor signals to assess the wear of the feeding components and potential failure risks. S7. Multi-system linkage and coordination: By establishing a high-speed data transmission network and a unified data interface standard, the CFB anti-slagging control system is closely connected with other relevant systems in the power plant to achieve real-time data interaction and sharing.

[0008] Furthermore, step S1 includes the following specific monitoring methods: T1. Temperature monitoring: Multiple temperature sensors are reasonably arranged in key areas such as the dense phase zone and the dilute phase zone in the CFB combustion chamber. The accuracy range of the temperature sensors is ±1℃ and the response time is less than 0.5 seconds. T2. Pressure detection: Multiple pressure sensors are installed at different heights in the CFB combustion chamber, such as the bottom, middle and top of the furnace. The measurement accuracy of the pressure sensors is within ±0.1 kPa. T3. Oxygen content detection: Paramagnetic oxygen analyzers are installed at the junction of the dense phase zone and the dilute phase zone of the furnace and at the furnace outlet flue. Each oxygen analyzer has 3 sampling points at different positions on the cross-section of the flue. T4. Material concentration monitoring: Install a pair of microwave material concentration sensors every 6 meters in the dense phase zone and dilute phase zone of the furnace. T5. Material particle size monitoring: Laser particle size analyzers are installed at the feed inlet and return valve to monitor the particle size of coal slime and circulating materials in real time, and automatically sample and analyze once every 5 minutes.

[0009] Furthermore, in step T1, in the dense phase zone, three layers of measuring points are set at 1-meter intervals along the cross-section of the furnace, with five K-type thermocouple temperature sensors in each layer, for a total of 15 temperature measuring points with an accuracy of ±0.8℃; in the dilute phase zone, at 3 meters, 6 meters, and 9 meters from the top of the furnace, four S-type thermocouple temperature sensors are evenly arranged along the four walls of the furnace in each layer, for a total of 12 measuring points with an accuracy of ±0.5℃; at the bottom of the furnace, three pressure sensors are evenly installed on the air distribution plate with an accuracy of ±0.05kPa; in the middle of the furnace, one pressure sensor is installed on each of the four walls at half the height of the furnace, for a total of four, to monitor the pressure inside the furnace at this height with an accuracy of ±0.1kPa; at the top of the furnace, two pressure sensors are set at the furnace outlet flue to monitor the furnace outlet pressure with an accuracy of ±0.15kPa.

[0010] Furthermore, in step S2, historical records of coal slime ash content between 20% and 50%, volatile matter content between 15% and 35%, combustion parameters under operating loads between 50% and 100%, and whether slagging occurs are collected. After cleaning and preprocessing, these data are input into the SVM algorithm model machine for algorithm learning.

[0011] Furthermore, in step S3, when a high risk of slagging is detected, the automatic control system dynamically adjusts the feeding rate; the automatic control system dynamically adjusts the air volume and wind speed to optimize the airflow structure in the combustion chamber; and the automatic control system dynamically adjusts the amount of auxiliary fuel added to reasonably increase the amount of auxiliary fuel.

[0012] Furthermore, in step S4, a laser rangefinder and image monitoring equipment are installed in the CFB combustion chamber. The ash deposition monitoring device and the slag cleaning system adopt a combination of steam blowing, sonic blowing and mechanical cleaning.

[0013] Furthermore, in step S5, the temperature, pressure, oxygen content, combustion parameters, material concentration, and material particle size of key areas in the CFB combustion chamber before and after slag removal are collected, and the discharged ash is sampled and analyzed to obtain detailed information on its composition and particle size distribution.

[0014] Furthermore, in step S6, when the equipment operating parameters are close to the preset fault threshold or the remaining lifespan is less than the set period, the system immediately generates detailed equipment maintenance and upkeep reminders to inspect and maintain the fan.

[0015] In summary, this invention provides a method for preventing slagging in a circulating fluidized bed of coal slime, which has the following beneficial effects: 1. By collecting data, establishing predictive models, and optimizing combustion conditions, combustion parameters are monitored and dynamically adjusted in real time, effectively avoiding combustion instability caused by slagging, ensuring stable operation of the CFB under various operating conditions, improving energy utilization efficiency, and significantly reducing the frequency of slagging events during CFB operation.

[0016] 2. By optimizing combustion conditions, slag removal procedures, and equipment maintenance, damage to heating surfaces and equipment components caused by slag buildup has been reduced, equipment maintenance costs and downtime have been lowered, equipment service life has been extended, and the continuity and reliability of production have been improved.

[0017] 3. Through data acquisition, data analysis, and multi-system linkage and coordination, an automated control strategy was implemented, which reduced manual intervention, lowered the labor intensity of operators, and improved the accuracy and efficiency of control. This met the needs of modern industrial production, reduced the possibility of human error affecting the response time of the entire system, and significantly improved operational stability. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the process architecture of a coal slime circulating fluidized bed anti-slagging control method according to the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Example 1: Please see Figure 1 As shown, the present invention provides a technical solution: a method for preventing slagging in a circulating fluidized bed of coal slime, comprising the following control methods: S1. Data Acquisition: High-precision temperature sensors, pressure sensors, oxygen analyzers, microwave material concentration sensors, and laser particle size analyzers are used to monitor the temperature, pressure, oxygen content, material concentration, and material particle size inside the CFB and collect relevant data in real time. S2. Establish a predictive model: Based on the relevant data collected in step S1, use the vector machine (SVM) algorithm model to train and predict the learning process, analyze the correlation between historical combustion data and slagging, establish a predictive model, and identify potential slagging risks in advance. S3. Optimize combustion conditions: Based on the risk level predicted by the model in step S2, dynamically adjust the feed rate, air distribution ratio and auxiliary fuel quantity to optimize combustion conditions and prevent the formation of a continuous overheating state in the high-temperature zone. S4. Slag Removal Program: Monitors ash deposition in the furnace. When the accumulated deposits exceed the threshold, the slag removal program is automatically started to maintain the CFB in good working condition. S5. Data Analysis: As per step S4, after each slag removal procedure is completed, the system quickly initiates a comprehensive data collection process. S6. Equipment Maintenance: Based on steps S2 and S4, for the feeding device, comprehensively analyze the data of motor current, feeding rate stability, material blockage and sensor signals to assess the wear of the feeding components and potential failure risks. S7. Multi-system linkage and coordination: By establishing a high-speed data transmission network and a unified data interface standard, the CFB anti-slagging control system is closely connected with other relevant systems in the power plant to achieve real-time data interaction and sharing.

[0021] Step S1 includes the following specific monitoring methods: T1. Temperature monitoring: Multiple temperature sensors are reasonably arranged in key areas such as the dense phase zone and the dilute phase zone in the CFB combustion chamber. The temperature sensors have an accuracy range of ±1℃ and a response time of less than 0.5 seconds, which can monitor the temperature distribution in each area in real time and ensure that any abnormal temperature changes can be captured. T2. Pressure detection: Multiple pressure sensors are installed at different heights in the combustion chamber, such as the bottom, middle and top of the furnace, to measure the pressure changes at different heights in the combustion chamber, thereby understanding the flow state and pressure distribution of the airflow. The measurement accuracy of the pressure sensors is within ±0.1 kPa, which can accurately reflect the pressure fluctuations in the combustion chamber. This is of great significance for judging the fluidization quality in the combustion chamber and whether there is local blockage. T3. Oxygen content detection: Paramagnetic oxygen analyzers are installed at the junction of the dense phase zone and the dilute phase zone of the furnace and at the furnace outlet flue. Each oxygen analyzer has three sampling points at different positions on the cross-section of the flue. The paramagnetic oxygen analyzer has a fast response speed and a measurement accuracy of ±0.08%. The average value is taken as the measurement result to ensure the representativeness of the oxygen content data, thereby accurately judging the degree of fuel-air mixing and combustion. T4. Material concentration monitoring: A pair of microwave material concentration sensors are installed every 6 meters in the dense phase zone and dilute phase zone of the furnace. The material concentration is measured by the degree of microwave signal attenuation, which is used to understand the material distribution and optimize the combustion and fluidization state. T5. Material Particle Size Monitoring: Laser particle size analyzers are installed at the feed inlet and return valve to monitor the particle size of coal slime and circulating materials in real time. The analyzer is automatically sampled and analyzed every 5 minutes to ensure that the particle size of the material entering the furnace meets the combustion requirements and to avoid the impact of abnormal particle size on combustion and slagging.

[0022] In step T1, three layers of measuring points are set at 1-meter height intervals along the furnace cross-section in the dense phase zone. Each layer has five K-type thermocouple temperature sensors, for a total of 15 temperature measuring points with an accuracy of ±0.8℃. The K-type thermocouple temperature sensors have a response time of less than 0.3 seconds, enabling them to capture temperature changes at different locations and heights in the dense phase zone in real time and monitor temperature peaks and fluctuations in the concentrated combustion area of ​​the fuel. In the dilute phase zone, at distances of 3 meters, 6 meters, and 9 meters from the top of the furnace, four S-type thermocouple temperature sensors are evenly arranged along the four walls of the furnace in each layer, for a total of 12 measuring points with an accuracy of ±0.5℃. The S-type thermocouple temperature sensors have good stability and are used to monitor the flue gas temperature in the dilute phase zone, determining heat transfer and the temperature distribution of the gas after combustion. This is of great significance for preventing slagging caused by local overheating. Three pressure sensors with an accuracy of ±0.05 kPa are evenly installed on the air distribution plate at the bottom of the furnace to measure the air chamber pressure and the air distribution plate resistance, monitor the uniformity of air distribution, and judge the fluidization quality. Four pressure sensors are installed on the four walls at half the height of the furnace in the middle of the furnace to monitor the pressure inside the furnace at this height with an accuracy of ±0.1 kPa, reflecting the pressure change during the upward flow of air and providing data for analyzing the flow field in the combustion chamber. Two pressure sensors are installed at the furnace outlet flue at the top of the furnace to monitor the furnace outlet pressure with an accuracy of ±0.15 kPa, to judge the smoothness of flue gas discharge and prevent abnormal pressure from affecting the combustion conditions.

[0023] In step S2, historical records of coal slime ash content between 20% and 50%, volatile matter content between 15% and 35%, combustion parameters under operating loads between 50% and 100%, and whether slagging occurred are collected. After cleaning and preprocessing, this data is input into the SVM algorithm model machine for algorithm learning. Training with the vector machine algorithm can improve the accuracy and recall of the model in predicting slagging risk, quickly predict the slagging risk level, and provide a decision-making basis for the implementation of subsequent anti-slagging measures.

[0024] In step S3, the automatic control system dynamically adjusts the feeding rate. When a high risk of slagging is detected, the feeding rate is reduced by 10% to 20% to prevent excessive fuel accumulation in the high-temperature zone and reduce the possibility of slagging caused by incomplete combustion. The automatic control system also dynamically adjusts the air volume and velocity to optimize the airflow structure in the combustion chamber. When the risk of slagging increases, the air volume is increased by 10% to 15%, and the velocity is increased by 5 to 10 m / s to ensure thorough mixing of air and fuel, improve combustion efficiency, and prevent the formation of localized high-temperature zones. The automatic control system also dynamically adjusts the amount of auxiliary fuel added. When the risk of slagging is high, the amount of auxiliary fuel is increased appropriately, by 5% to 10% of the normal amount, to improve combustion conditions, stabilize combustion temperature, and prevent continuous overheating in the high-temperature zone.

[0025] In step S4, a laser rangefinder and image monitoring equipment are installed in the CFB combustion chamber. The laser rangefinder, with a measurement accuracy of ±1mm, can accurately measure the thickness and coverage area of ​​the deposits. When the deposit thickness exceeds 5mm or the coverage area exceeds 20% of the heating surface, it is determined that the deposit accumulation exceeds the threshold. When the deposit accumulation exceeds the preset threshold, the slag removal program is automatically activated. The slag removal system uses a combination of steam blowing, sonic blowing, and mechanical cleaning to ensure thorough removal of slag in the furnace, maintain the good working condition of the circulating fluidized bed, and ensure stable boiler operation.

[0026] In step S5, the temperature, pressure, oxygen content, combustion parameters, material concentration, and particle size of key areas in the CFB combustion chamber are collected before and after slag removal. The discharged ash is sampled and analyzed to obtain detailed information on its composition and particle size distribution. At the same time, using image recognition technology to accurately measure the slag area, thickness, and slag location distribution based on slag images recorded by a high-definition camera, the subsequent combustion conditions are optimized based on the parameter changes before and after combustion to reduce the risk of subsequent slag formation due to slag residue.

[0027] In step S6, when the equipment operating parameters approach the preset fault threshold or the remaining lifespan is less than the set period, the system immediately generates detailed equipment maintenance and upkeep reminders to inspect and maintain the fan. Maintenance measures include cleaning accumulated dust from the impeller after shutdown; measuring the impeller's dynamic balance using specialized tools; checking bearing lubrication and replacing grease if necessary; and detecting bearing wear. If the wear exceeds the allowable range, the bearing should be replaced promptly. The expected maintenance time is one working day. After maintenance, at least two hours of no-load test run are required to ensure the fan returns to normal operation. This precise reminder and guidance effectively prevents sudden equipment failures, ensures the continuous and stable operation of the CFB system, and reduces downtime and economic losses caused by equipment failures.

[0028] Example 2: This embodiment presents a method for preventing slagging in a circulating fluidized bed coal slime system. It establishes a prediction model using a vector machine (SVM) algorithm for machine learning, and performs model training and parameter optimization. The collected historical data, after cleaning and preprocessing, was divided into three sets: 70% training set, 15% validation set, and 15% test set. During the training phase, the penalty parameter C and kernel function parameter γ of the SVM model were fine-tuned using a grid search method. The search range for C was set to [0.1, 1, 10], and the search range for γ was set to [0.01, 0.1, 1]. These parameters were combined one by one for model training. The model performance was evaluated on the validation set, and the parameter combination that achieved the highest accuracy on the validation set was selected. Simultaneously, to prevent overfitting, a five-fold cross-validation technique was used to further optimize the training set. The model is further divided into 5 subsets. Each time, 4 subsets are used to train the model, and the remaining subset is used for validation. After 5 iterations, the average performance index is used as the evaluation result. The trained SVM model is evaluated using a test set, and the accuracy, recall, F1 score and other indicators are calculated to improve the accuracy and recall of the model in predicting slagging risk. It can accurately classify slagging risk into three levels: low, medium and high. The trained model is applied to actual CFB operation monitoring. Based on the real-time collected combustion parameters, it can quickly predict the slagging risk level and provide a decision-making basis for the implementation of subsequent anti-slagging measures.

[0029] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments for application in other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A method for preventing slagging in a circulating fluidized bed of coal slime, characterized in that: Including the following control methods: S1. Data Acquisition: High-precision temperature sensors, pressure sensors, oxygen analyzers, microwave material concentration sensors, and laser particle size analyzers are used to monitor the temperature, pressure, oxygen content, material concentration, and material particle size inside the CFB and collect relevant data in real time. S2. Establish a predictive model: Based on the relevant data collected in step S1, use the vector machine (SVM) algorithm model to train and predict the learning process, analyze the correlation between historical combustion data and slagging, establish a predictive model, and identify potential slagging risks in advance. S3. Optimize combustion conditions: Based on the risk level predicted by the model in step S2, dynamically adjust the feed rate, air distribution ratio and auxiliary fuel quantity to optimize combustion conditions and prevent the formation of a continuous overheating state in the high-temperature zone. S4. Slag Removal Program: Monitors ash deposition in the furnace. When the accumulated deposits exceed the threshold, the slag removal program is automatically started to maintain the CFB in good working condition. S5. Data Analysis: As per step S4, after each slag removal procedure is completed, the system quickly initiates a comprehensive data collection process. S6. Equipment Maintenance: Based on steps S2 and S4, for the feeding device, comprehensively analyze the data of motor current, feeding rate stability, material blockage and sensor signals to assess the wear of the feeding components and potential failure risks. S7. Multi-system linkage and coordination: By establishing a high-speed data transmission network and a unified data interface standard, the CFB anti-slagging control system is closely connected with other relevant systems in the power plant to achieve real-time data interaction and sharing.

2. The method for preventing slagging in a circulating fluidized bed of coal slime according to claim 1, characterized in that: The S1 step includes the following specific monitoring methods: T1. Temperature monitoring: Multiple temperature sensors are reasonably arranged in key areas such as the dense phase zone and the dilute phase zone in the CFB combustion chamber. The accuracy range of the temperature sensors is ±1℃ and the response time is less than 0.5 seconds. T2. Pressure detection: Multiple pressure sensors are installed at different heights in the CFB combustion chamber, such as the bottom, middle and top of the furnace. The measurement accuracy of the pressure sensors is within ±0.1 kPa. T3. Oxygen content detection: Paramagnetic oxygen analyzers are installed at the junction of the dense phase zone and the dilute phase zone of the furnace and at the furnace outlet flue. Each oxygen analyzer has 3 sampling points at different positions on the cross-section of the flue. T4. Material concentration monitoring: Install a pair of microwave material concentration sensors every 6 meters in the dense phase zone and dilute phase zone of the furnace. T5. Material particle size monitoring: Laser particle size analyzers are installed at the feed inlet and return valve to monitor the particle size of coal slime and circulating materials in real time, and automatically sample and analyze once every 5 minutes.

3. The method for preventing slagging in a circulating fluidized bed of coal slime according to claim 2, characterized in that: In step T1, three layers of measuring points are set at 1-meter intervals along the cross-section of the furnace in the dense phase zone, with five K-type thermocouple temperature sensors in each layer, for a total of 15 temperature measuring points with an accuracy of ±0.8℃. In the dilute phase zone, at 3 meters, 6 meters, and 9 meters from the top of the furnace, four S-type thermocouple temperature sensors are evenly arranged along the four walls of the furnace in each layer, for a total of 12 measuring points with an accuracy of ±0.5℃. Three pressure sensors are evenly installed on the air distribution plate at the bottom of the furnace with an accuracy of ±0.05kPa. One pressure sensor is installed on each of the four walls at half the height of the furnace in the middle of the furnace, for a total of four sensors, to monitor the pressure inside the furnace at this height with an accuracy of ±0.1kPa. Two pressure sensors are set at the top of the furnace at the furnace outlet flue to monitor the furnace outlet pressure with an accuracy of ±0.15kPa.

4. The method for preventing slagging in a circulating fluidized bed of coal slime according to claim 1, characterized in that: In step S2, historical records of coal slime ash content between 20% and 50%, volatile matter content between 15% and 35%, combustion parameters under operating loads between 50% and 100%, and whether slagging has occurred are collected. After cleaning and preprocessing, these data are input into the SVM algorithm model machine for algorithm learning.

5. The method for preventing slagging in a circulating fluidized bed of coal slime according to claim 1, characterized in that: In step S3, when a high risk of slagging is detected, the automatic control system dynamically adjusts the feeding rate; the automatic control system dynamically adjusts the air volume and air speed to optimize the airflow structure in the combustion chamber; and the automatic control system dynamically adjusts the amount of auxiliary fuel added to reasonably increase the amount of auxiliary fuel.

6. The method for preventing slagging in a circulating fluidized bed of coal slime according to claim 1, characterized in that: In step S4, a laser rangefinder and image monitoring equipment are installed in the CFB combustion chamber. The ash deposition monitoring device and the slag cleaning system adopt a combination of steam blowing, sonic blowing and mechanical cleaning.

7. The method for preventing slagging in a circulating fluidized bed of coal slime according to claim 1, characterized in that: In step S5, the temperature, pressure, oxygen content, combustion parameters, material concentration, and material particle size of key areas in the CFB combustion chamber before and after slag removal are collected, and the discharged ash is sampled and analyzed to obtain detailed information on its composition and particle size distribution.

8. The method for preventing slagging in a circulating fluidized bed of coal slime according to claim 1, characterized in that: In step S6, when the equipment operating parameters are close to the preset fault threshold or the remaining lifespan is less than the set period, the system immediately generates detailed equipment maintenance and upkeep reminders to inspect and maintain the fan.

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