Variable load regulation pulverizing system and method, electronic equipment and storage medium

Abstract

The invention provides a variable load adjusting coal pulverizing system and method, electronic equipment and a storage medium. The system comprises a monitoring module, a coal mill and a control module. The monitoring module is connected with the coal mill and the control module and used for monitoring running state data of the coal mill and sending the running state data to the control module. The control module is respectively connected with the coal mill and the monitoring module, and the control module is used for performing data analysis on the load related data and the operation state data of the generator set, determining the operation condition of the generator set and generating a control instruction of the coal mill according to the operation condition; the coal mill is connected with the monitoring module and the control module and used for adjusting the internal circulation rate of the coal mill according to the control instruction. Compared with the prior art, the internal circulation rate of the coal mill can be accurately adjusted according to different load change conditions; and the condition of large parameter fluctuation in the running process of the coal mill can be avoided.

Description

Technical Field

[0001] The present disclosure relates to the field of data processing technology, and in particular to a variable load regulation pulverizing system and method, an electronic device, and a storage medium. Background Art

[0002] In coal-fired power generation, improving the boiler's response rate and combustion efficiency is key to enhancing the performance of the entire generator set. The boiler's dynamic response characteristics are directly related to the unit's peak-shaving capability and grid stability. Traditional coal-fired boiler control systems often use fixed control logic and parameter settings, making it difficult to adapt to the dynamic processes of rapidly changing loads. Under deep peak-shaving conditions, boiler combustion stability and response speed face even greater challenges. Because the mill's internal circulation rate and transient pulverized coal discharge rate directly affect the boiler's combustion efficiency and heat output, optimizing the control strategy for these two parameters is a key approach to improving the boiler's response rate.

[0003] While there are currently several optimization solutions for coal mill control systems, these solutions mostly focus on adjusting static parameters and are insufficient for dynamic process control during load fluctuations. Especially during rapid load changes, the coal mill's internal circulation rate and pulverized coal discharge rate are difficult to quickly adjust to optimal conditions, limiting the boiler's response speed and potentially leading to unstable combustion. Summary of the Invention

[0004] The present disclosure provides a load-variable pulverizing system and method, electronic equipment, and storage medium, primarily to address the problem of low pulverizing efficiency and inability of coal mills to cope with rapid load changes.

[0005] According to a first aspect of the present disclosure, a load-variable pulverizing system is provided, the system comprising: a monitoring module, a coal mill, and a control module;

[0006] The monitoring module is connected to the coal mill and the control module respectively, and is used to monitor the operating status data of the coal mill and send the operating status data to the control module;

[0007] The control module is connected to the coal mill and the monitoring module respectively, and is used to perform data analysis on the load-related data of the generator set and the operating status data, determine the operating condition of the generator set, and generate control instructions for the coal mill according to the operating condition;

[0008] The coal mill is connected to the monitoring module and the control module respectively, and is used to adjust the internal circulation rate of the coal mill according to the control instructions.

[0009] In some embodiments, the system further comprises: a raw coal feeding module;

[0010] The raw coal feeding module is connected to the coal mill and is used to feed the raw coal to the coal mill.

[0011] Accordingly, the monitoring module is further configured to:

[0012] The raw coal characteristic data delivered to the coal mill by the raw coal feeding module is monitored, and the raw coal characteristic data is sent to the control module.

[0013] In some embodiments, the control module is further configured to:

[0014] The control strategy is adjusted according to the raw coal characteristic data.

[0015] In some embodiments, the control module includes: a dynamic separator feedforward submodule;

[0016] The dynamic separator feedforward submodule is used to generate a control instruction for the dynamic separator in the coal mill according to the operating conditions, so as to control and adjust the internal circulation rate of the coal mill according to the control instruction.

[0017] In some embodiments, the control module further includes: a hot air regulating door feedforward submodule;

[0018] The hot air regulating door feedforward submodule is used to determine the hot air flow regulation data and temperature regulation data of the coal mill according to the operating conditions, and generate a control instruction for the hot air regulating door of the coal mill, so as to control and adjust the internal circulation rate of the coal mill according to the control instruction.

[0019] According to a second aspect of the present disclosure, a pulverizing method with variable load regulation is provided, the method comprising:

[0020] Obtaining coal mill operating status data and generator set load-related data;

[0021] Performing data analysis on the load-related data and the operating status data to determine the operating condition of the generator set;

[0022] According to the operating conditions, a control instruction of the coal mill is generated, so as to adjust the internal circulation rate of the coal mill based on the control instruction.

[0023] In some embodiments, generating a control instruction for the coal mill according to the operating condition includes:

[0024] generating a control instruction for a dynamic separator in the coal mill according to the operating conditions;

[0025] And / or, according to the operating conditions, hot air flow adjustment data and temperature adjustment data of the coal mill are determined, and control instructions for the hot air adjustment door of the coal mill are generated.

[0026] According to a third aspect of the present disclosure, there is provided an electronic device, including:

[0027] at least one processor; and

[0028] a memory communicatively connected to the at least one processor; wherein,

[0029] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method described in the second aspect.

[0030] According to a fourth aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable the computer to execute the method described in the second aspect.

[0031] According to a fifth aspect of the present disclosure, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the method as described in the second aspect above.

[0032] The present disclosure provides a variable load regulation pulverizing system and method, electronic equipment and storage medium, the system comprising: a monitoring module, a coal mill, and a control module; the monitoring module is connected to the coal mill and the control module, respectively, for monitoring the operating status data of the coal mill and sending the operating status data to the control module; the control module is connected to the coal mill and the monitoring module, respectively, and the control module is used to perform data analysis on the load-related data and the operating status data of the generator set, determine the operating conditions of the generator set, and generate control instructions for the coal mill according to the operating conditions; the coal mill is connected to the monitoring module and the control module, respectively, for adjusting the internal circulation rate of the coal mill according to the control instructions. Compared with the related art, the embodiment of the present disclosure monitors the coal mill operating status data in real time through the monitoring module, and analyzes it in combination with the load-related data of the generator set. The control module can accurately judge the operating conditions and generate appropriate control instructions; this allows the coal mill to quickly adjust the internal circulation rate according to the instructions, thereby timely changing the transient powder discharge speed; whether within the normal load regulation range or under special operating conditions such as deep peak regulation, the system can accurately adjust the coal mill internal circulation rate according to different load changes; the monitoring module continuously monitors the operating status data, and the control module adjusts the control instructions in real time according to these data, which can avoid large fluctuations in parameters of the coal mill during operation.

[0033] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The accompanying drawings are provided to facilitate a better understanding of the present invention and do not constitute a limitation of the present disclosure.

[0035] Figure 1 A schematic structural diagram of a load-variable powder-making system provided in an embodiment of the present disclosure;

[0036] Figure 2 A schematic structural diagram of a load-variable powder-making system provided in an embodiment of the present disclosure;

[0037] Figure 3 A schematic flow chart of a pulverizing method with variable load regulation provided in an embodiment of the present disclosure;

[0038] Figure 4 A schematic block diagram of an exemplary electronic device provided for an embodiment of the present disclosure. DETAILED DESCRIPTION

[0039] The following description of exemplary embodiments of the present disclosure is made in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding. These details should be considered as merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0040] The following describes the variable load regulation pulverizing system and method, electronic device and storage medium of the embodiments of the present disclosure with reference to the accompanying drawings.

[0041] Figure 1 A schematic structural diagram of a load-variable powder-making system provided in an embodiment of the present disclosure.

[0042] like Figure 1 As shown, the system includes: a monitoring module 11, a coal mill 12, and a control module 13;

[0043] The monitoring module 11 is connected to the coal mill 12 and the control module 13 respectively, and is used to monitor the operating status data of the coal mill 12 and send the operating status data to the control module 13 .

[0044] Specifically, in the embodiment of the present disclosure, the monitoring module 11 serves as a sensing unit in the entire variable load regulation pulverizing system, and establishes connections with the coal mill 12 and the control module 13 through communication links and interfaces. This connection not only ensures the efficient transmission of data, but also lays a solid foundation for achieving precise control. In terms of connection with the coal mill 12, the monitoring module 11 adopts various types of sensors and data acquisition equipment, which are reasonably distributed in various key parts of the coal mill 12 so as to be able to fully and accurately obtain the operating status data of the coal mill 12. At the same time, the connection with the control module 13 utilizes a high-speed and reliable communication bus (such as industrial Ethernet, etc.) to ensure that the collected data is transmitted to the control module 13 in real time and accurately for in-depth analysis and decision-making.

[0045] The monitoring module 11 is equipped with a series of advanced sensors for accurately monitoring various operating status data of the coal mill 12. For example, high-precision current transformers and voltage transformers are installed on the drive motor of the coal mill 12 to monitor the motor's current and voltage signals in real time, thereby indirectly obtaining the load condition of the coal mill 12. Vibration sensors are installed near the tank or grinding components of the coal mill 12 to keenly capture vibration characteristic data such as the vibration frequency and amplitude of the coal mill 12 during operation. This data can reflect the degree of wear of the internal components of the coal mill 12, the smoothness of operation, and whether there are abnormal impacts or imbalances. In addition, pressure sensors and temperature sensors are installed on the inlet and outlet pipes of the coal mill 12 to monitor parameters such as wind pressure, air pressure, wind temperature, and air temperature at the inlet and outlet. These parameters are important for evaluating the ventilation conditions inside the coal mill 12, the material flow, and the energy conversion efficiency during the grinding process. At the same time, a coal powder concentration sensor and a coal powder fineness analyzer are installed inside or at the outlet of the coal mill 12 to monitor the concentration and fineness of the coal powder in real time, so as to timely understand the grinding effect and powder quality of the coal mill 12 and ensure that the coal powder that meets the combustion requirements is provided to the boiler.

[0046] Once these operating status data are monitored, the monitoring module 11 will immediately perform a series of preprocessing operations on the data to improve the quality and availability of the data. First, the collected data is filtered to remove noise and interference components in the signal to ensure the accuracy and stability of the data. Then, the data is calibrated and normalized to convert the data collected by different sensors into a unified standard format and range for subsequent analysis and comparison. After completing the preprocessing, the monitoring module 11 uses its built-in communication protocol to package the processed data in a predetermined format and frequency and send it to the control module 13. During the data transmission process, the monitoring module 11 also has a data retransmission and error checking mechanism to ensure the reliability of data transmission. Even if there is a certain interference or failure in the communication environment, it can ensure that the control module 13 receives complete and accurate operating status data, thereby providing strong support for the control module 13 to make correct decisions.

[0047] The control module 13 is connected to the coal mill 12 and the monitoring module 11 respectively. The control module 13 is used to perform data analysis on the load-related data of the generator set and the operating status data, determine the operating conditions of the generator set, and generate control instructions for the coal mill 12 based on the operating conditions.

[0048] Specifically, in the embodiment of the present disclosure, the control module 13 serves as the decision-making unit of the entire variable load regulation pulverizing system, and establishes a close data interaction link with the coal mill 12 and the monitoring module 11 through a stable communication interface. On the one hand, it receives detailed operating status data of the coal mill 12 transmitted from the monitoring module 11 in real time. These data cover various key aspects of the coal mill 12, such as motor current, voltage, equipment vibration, inlet and outlet pressure and temperature, coal powder concentration and fineness, and other information. On the other hand, the control module 13 is also connected to the load monitoring system of the generator set to obtain real-time load-related data of the generator set, including current load value, load change rate, load change trend, and power grid dispatch instructions. The control module 13 summarizes and organizes these data from different data sources and different types in a unified manner to prepare for subsequent in-depth analysis.

[0049] Once complete data is received, the operating status data of the coal mill 12 is analyzed in real time. A complex mathematical model is established to assess the current operating status of the coal mill 12. For example, the actual power consumption of the coal mill 12 is calculated based on the motor current and voltage data and compared with a preset power curve to determine whether the coal mill 12 is within the normal load operating range. Spectral analysis is performed using vibration sensor data to identify the degree of wear and potential failure risks of the coal mill 12's internal components. Combined with inlet and outlet pressure and temperature data, the ventilation and material flow characteristics within the coal mill 12 are analyzed to assess its operating efficiency. Simultaneously, the load-related data of the generator set is combined to comprehensively assess the overall operating condition of the generator set. When the load increases rapidly and the rate of change exceeds a certain threshold, the current operating status of the coal mill 12 (such as whether it is at the high load limit or whether the pulverized coal supply is sufficient) is used to determine that the generator set is in a rapidly increasing load condition. If the load remains relatively stable for a period of time, but there are slight fluctuations in the operating parameters of the coal mill 12, the cause is analyzed to determine whether it is a change in coal quality or a minor equipment failure, and the generator set is then determined to be in a stable operating condition but requires fine-tuning. Through this all-round, multi-dimensional data analysis, the control module 13 can accurately determine the specific operating conditions of the generator set at different times.

[0050] Based on the precisely determined operating conditions, control module 13 applies its pre-programmed control strategy and optimization algorithm to generate control instructions for coal mill 12. The logic for generating control instructions varies under different operating conditions. For example, under conditions where the generator set's load is rapidly increasing, control module 13 calculates the required increase in pulverized coal supply to coal mill 12. Based on parameters such as the current internal circulation rate and pulverized coal fineness, it generates corresponding control instructions. These instructions increase the speed of the dynamic separator and the opening of the hot air damper, thereby accelerating the internal circulation rate of coal mill 12 and increasing the transient pulverized coal discharge rate to meet the boiler's rapidly increasing demand for pulverized coal. Furthermore, when generating control instructions, control module 13 also considers factors such as the equipment lifespan and energy consumption of coal mill 12, making optimization adjustments. For example, while meeting load requirements, it minimizes energy waste and equipment wear caused by excessive grinding in coal mill 12. By optimizing control instructions, coal mill 12 operates efficiently and economically. In addition, the control module 13 also has adaptive learning capabilities, and can continuously adjust and optimize the control strategy according to the actual operating results, so that the generated control instructions are more accurate and reasonable, further improving the operating performance of the entire pulverizing system and the generator set.

[0051] The coal mill 12 is connected to the monitoring module 11 and the control module 13 respectively, and is used to adjust the internal circulation rate of the coal mill 12 according to the control instructions.

[0052] Specifically, in the embodiment of the present disclosure, the coal mill 12 serves as the execution terminal of the entire variable load regulation pulverizing system, and maintains connection with the monitoring module 11 and the control module 13 through the communication interface. After the control module 13 generates control instructions based on a comprehensive analysis of the load-related data of the generator set and the operating status data of the coal mill 12, the coal mill 12 can quickly and accurately receive these instructions. The coal mill 12 is equipped with an advanced instruction parsing system that can quickly identify and interpret the various parameters and requirements in the control instructions. For example, the instructions may contain information such as the specific value for adjusting the speed of the dynamic separator, the amplitude of the change in the opening of the hot air regulating door, the increase or decrease in the feed amount of the coal feeder, etc. The instruction parsing system will decompose this information into operating instructions that can be understood by each execution component, and prepare for the subsequent action execution.

[0053] Based on the parsed control instructions, multiple key components within the coal mill 12 begin working in coordination to precisely adjust the internal circulation rate. In a medium-speed coal mill, upon receiving a command to increase the internal circulation rate, the loading device increases pressure on the grinding rollers, enhancing the grinding force between the rollers and the grinding discs. This allows the raw coal to be more thoroughly ground on the grinding discs, thereby increasing the material circulation rate within the mill. Simultaneously, the actuator associated with the dynamic separator adjusts the speed of the dynamic separator according to the command, increasing its centrifugal force. This allows unqualified coal dust to be separated more quickly and returned to the mill for further grinding, further improving the internal circulation rate. Furthermore, the actuator of the hot air control door increases its opening according to the command, allowing more hot air to enter the mill and increase ventilation within the mill. This not only helps remove moisture and fines generated during the grinding process, but also provides better power conditions for the transportation and circulation of the coal dust, promoting an increase in the internal circulation rate. Throughout the adjustment process, each component cooperates through precise timing control and feedback regulation mechanisms to ensure rapid and stable adjustment of the internal circulation rate.

[0054] In the process of adjusting the internal circulation rate, the coal mill 12 will also collect its own operating parameters in real time and feed these parameters back to the monitoring module 11 and the control module 13. For example, through the sensors installed inside the coal mill 12, the changes in parameters such as the current, vibration, inlet and outlet pressure difference, coal powder concentration and fineness of the coal mill 12 are monitored in real time. The control module 13 evaluates the effect of the internal circulation rate adjustment in real time based on these feedback data. If it is found that the actual adjustment result deviates from the expected target, the control module 13 will immediately correct and optimize the control instructions and resend them to the coal mill 12 so that the coal mill 12 can perform adaptive adjustments. This real-time feedback and adaptive adjustment mechanism ensures that the internal circulation rate of the coal mill 12 can always be accurately and stably adjusted according to the operating conditions and load requirements of the generator set, thereby achieving efficient and stable operation of the entire pulverizing system, ensuring a stable and appropriate supply of coal powder to the boiler, and meeting the power generation needs of the generator set under various operating conditions.

[0055] The present disclosure provides a variable load regulation pulverizing system, which includes: a monitoring module, a coal mill, and a control module; the monitoring module is connected to the coal mill and the control module, respectively, and is used to monitor the operating status data of the coal mill and send the operating status data to the control module; the control module is connected to the coal mill and the monitoring module, respectively, and the control module is used to perform data analysis on the load-related data and the operating status data of the generator set, determine the operating conditions of the generator set, and generate control instructions for the coal mill according to the operating conditions; the coal mill is connected to the monitoring module and the control module, respectively, and is used to adjust the internal circulation rate of the coal mill according to the control instructions. Compared with the related art, the embodiment of the present disclosure monitors the coal mill operating status data in real time through the monitoring module, and analyzes it in combination with the load-related data of the generator set. The control module can accurately judge the operating conditions and generate appropriate control instructions; this allows the coal mill to quickly adjust the internal circulation rate according to the instructions, thereby timely changing the transient powder discharge speed; whether within the normal load regulation range or under special operating conditions such as deep peak regulation, the system can accurately adjust the coal mill internal circulation rate according to different load changes; the monitoring module continuously monitors the operating status data, and the control module adjusts the control instructions in real time according to these data, which can avoid large fluctuations in parameters of the coal mill during operation.

[0056] Furthermore, in a possible implementation of this embodiment, as Figure 2 As shown, the system further includes: a raw coal feeding module 14;

[0057] The raw coal feeding module 14 is connected to the coal mill 12 and is used to feed the raw coal to the coal mill 12.

[0058] Accordingly, the monitoring module 11 is further configured to:

[0059] The raw coal characteristic data delivered to the coal mill 12 by the raw coal feeding module 14 is monitored, and the raw coal characteristic data is sent to the control module 13 .

[0060] Specifically, the raw coal feeding module 14 serves as the source of raw coal supply for the pulverizing system. It is connected to the pulverizer 12 through a special conveying pipeline. The pipeline has good wear resistance and fluidity, and can adapt to the stable transportation of raw coal under different coal types and working conditions. The raw coal feeding module 14 is equipped with a high-precision feeding device, such as a speed-regulating feeder or a weighing feeder, which can accurately control the feeding amount of raw coal according to the instructions of the control module 13. At the same time, in order to ensure the smooth transportation of raw coal, necessary auxiliary equipment is also set up, such as raw coal bins, vibrating feeders, etc. The raw coal bins are used to store a certain amount of raw coal, and the vibrating feeders can restore the normal flow state of the raw coal through vibration when the raw coal may be blocked or not smooth. In order to achieve comprehensive monitoring of the raw coal characteristic data, the monitoring module 11 installs sensors for monitoring raw coal at key positions of the raw coal feeding module 14. First, coal type identification sensors are installed at the outlet of the raw coal bin or at the inlet of the feeder. These sensors analyze the physical properties of the raw coal (such as density, hardness, and gloss) or utilize spectral analysis techniques to identify the type of raw coal. This is because different coal types have significant variations in combustion characteristics and grindability. Moisture sensors are also installed, using capacitive, microwave, or resistive measurement principles to accurately measure the moisture content of the raw coal. Excessive moisture in the raw coal can affect the grinding efficiency of the pulverizer and the drying effect of the pulverized coal, thereby affecting the operation of the entire pulverizing system. Furthermore, ash analyzers are installed to determine the ash content of the raw coal through real-time analysis of raw coal samples. Ash content affects the ash handling and combustion efficiency of the boiler after combustion. The particle size distribution of the raw coal is monitored using a laser particle size analyzer or screening device to understand the proportion of different particle sizes within the raw coal. This is important for adjusting pulverizer grinding parameters and predicting pulverizer output.

[0061] Once the monitoring module 11 obtains the raw coal characteristic data, it will immediately pre-process the data, such as data cleaning, calibration and normalization, to improve the accuracy and availability of the data. The processed raw coal characteristic data is then sent to the control module 13 via a high-speed communication link. The control module 13 optimizes and adjusts the entire pulverizing system based on these raw coal characteristic data, combined with the load demand of the generator set and the current operating status of the pulverizer 12. For example, when it is detected that the moisture content of the raw coal is high, the control module 13 will adjust the opening and temperature of the hot air regulating door, increase the amount and temperature of the hot air entering the pulverizer 12, to ensure that the raw coal can be fully dried, and appropriately reduce the feed rate of the pulverizer 12 to prevent the pulverizer 12 from being blocked or the output from being reduced due to excessive moisture in the raw coal. If the raw coal is found to be large in particle size, the control module 13 will adjust the grinding pressure of the pulverizer 12 and the rotation speed of the dynamic separator according to the grindability index of the coal type, extend the grinding time of the raw coal in the pulverizer 12, and ensure that the pulverizer 12 can produce coal powder of qualified fineness, thereby ensuring that the entire pulverizing system can operate efficiently and stably under different raw coal characteristics, provide a stable and high-quality coal powder supply to the boiler, and improve the overall operating performance of the generator set.

[0062] Furthermore, in a possible implementation of this embodiment, as Figure 2 As shown, the control module 13 is further used for:

[0063] The control strategy is adjusted according to the raw coal characteristic data.

[0064] Specifically, after receiving the raw coal characteristic data from the monitoring module 11, the control module 13 conducts a comprehensive and in-depth analysis of this data. The control module 13 accurately assesses the moisture content of the raw coal and its potential impact on the operation of the pulverizer 12. High-moisture raw coal requires more heat to dry during the grinding process, which not only affects the temperature distribution within the pulverizer 12 but may also cause the pulverized coal to adhere to pulverizer 12 components, reducing grinding efficiency. The control module 13 also analyzes the ash content of the raw coal. A higher ash content means more ash is produced during combustion, affecting the boiler's heat transfer efficiency and potentially leading to slagging and other problems. Furthermore, the control module 13 carefully examines the volatile matter content of the raw coal. Volatile matter is a key factor affecting the ignition and combustion stability of pulverized coal. Coal with different volatile matter contents has significantly different combustion characteristics, requiring targeted adjustments to the control parameters of the pulverizing system and combustion process. Through this detailed analysis of these raw coal characteristic data, the control module 13 fully understands the properties of the raw coal, laying the foundation for subsequent precise adjustment of the control strategy.

[0065] Based on the analysis results of the raw coal characteristic data, the control module 13 dynamically adjusts the key parameters in the control strategy. When the moisture content of the raw coal is high, the control module 13 will increase the opening of the hot air regulating door to increase the temperature and flow of the hot air entering the pulverizer 12 to ensure that the raw coal can be fully dried in the pulverizer 12. At the same time, the feeding speed of the pulverizer 12 is appropriately reduced to prevent the pulverizer 12 from being blocked or the output being reduced due to excessive moisture in the raw coal. For raw coal with a high ash content, the control module 13 will adjust the speed and separation efficiency curve of the dynamic separator to minimize the ash content of the separated coal powder. At the same time, it will optimize the boiler's combustion air distribution strategy, increase the disturbance of the secondary air, promote the discharge of ash slag, and reduce the risk of slagging. Regarding volatile matter content, if the raw coal has a low volatile content, control module 13 will reduce the speed of the dynamic separator to finer the coal powder, increasing its specific surface area and facilitating the release of volatile matter and ignition and combustion. Simultaneously, the grinding pressure of pulverizer 12 is adjusted to appropriately reduce the grinding intensity to avoid excessive fines from over-grinding, which can lead to unstable combustion. Conversely, for raw coal with a high volatile content, the dynamic separator speed and grinding pressure of pulverizer 12 are appropriately increased, increasing the output of pulverizer 12 to accommodate its rapid combustion characteristics.

[0066] By precisely adjusting the control strategy based on raw coal property data, control module 13 optimizes the operating performance of the entire pulverizing system and generator set. While ensuring stable operation of the pulverizer 12, the quality and efficiency of pulverized coal preparation are improved. Pulverized coal that is fully dried, appropriately fine, and has a reasonable ash content is delivered to the boiler, ensuring stable and efficient boiler combustion. The boiler is able to maintain a good combustion state under various raw coal property conditions, reducing incomplete combustion losses, improving thermal efficiency, and lowering pollutant emissions. Furthermore, the optimized control strategy also considers equipment maintenance and lifespan management, avoiding excessive equipment wear or failure due to changes in raw coal properties. For example, when processing high-hardness raw coal, appropriate adjustment of the grinding parameters of the pulverizer 12 reduces wear on components such as the grinding rollers and grinding discs, extending the equipment's service life and reducing equipment maintenance costs. Ultimately, the entire pulverizing system and generator set can achieve safe, stable, and efficient operation under different raw coal property conditions, improving the economic benefits and competitiveness of the power generation enterprise.

[0067] Furthermore, in a possible implementation of this embodiment, as Figure 2 As shown, the control module 13 includes: a dynamic separator feedforward submodule 131;

[0068] The dynamic separator feedforward submodule 131 is used to generate a control instruction for the dynamic separator in the coal mill 12 according to the operating conditions, so as to control and adjust the internal circulation rate of the coal mill 12 according to the control instruction.

[0069] Specifically, the dynamic separator feedforward submodule 131, as a component of the control module 13, obtains the load-related data of the generator set (such as the load change rate, current load value, grid dispatch instructions, etc.) and the detailed operating status data of the pulverizer 12 (such as the pulverizer 12 current, vibration, inlet and outlet pressure and temperature, coal powder concentration and fineness, etc.) through close data interaction with other functional units in the control module 13 and the external monitoring module 11. At the same time, it also receives the raw coal characteristic data (such as coal type, moisture, ash content, volatile matter, particle size distribution, etc.) from the raw coal feeding module 14. The dynamic separator feedforward submodule 131 has built-in high-performance data processing chips and algorithms to perform real-time analysis and processing on these massive data. For example, data fusion technology is used to integrate data from different sources, filtering algorithms are used to remove noise interference in the data, and feature extraction algorithms are used to mine key features in the data, providing a solid data foundation for accurately judging the operating conditions.

[0070] Based on the processed data, the dynamic separator feedforward submodule 131 uses complex operating condition judgment logic to accurately determine the current operating condition of the generator set. Under different operating conditions, such as deep peak-shaving conditions (large load fluctuations and low levels), normal load regulation conditions (stable or small load fluctuations within the normal range), coal type switching, or conditions with significant changes in coal quality, the dynamic separator feedforward submodule 131 generates corresponding dynamic separator control instructions based on a pre-set strategy library. Under deep peak-shaving conditions, when the load drops rapidly, the feedforward submodule 131 quickly calculates the dynamic separator speed that needs to be reduced and generates corresponding control instructions to reduce the circulation rate within the pulverizer 12, avoiding over-grinding and excessively fine coal powder, while also reducing energy consumption. If a coal type switch occurs and the new coal type has a low volatile matter content, the feedforward submodule 131 adjusts the separation characteristics of the dynamic separator, reducing the speed to make the coal powder finer, thereby facilitating ignition and stable combustion of the new coal type and improving combustion efficiency. The generation of these control instructions fully considers the diversity and complexity of operating conditions, aiming to achieve optimal adjustment of the internal circulation rate of the coal mill 12 through precise control of the dynamic separator, ensuring efficient coordinated operation of the pulverizing system and the generator set. The generated dynamic separator control instructions are not static. The dynamic separator feedforward submodule 131 also has an instruction optimization function. It will dynamically adjust and optimize the control instructions based on the real-time feedback data from the system. For example, during the execution of the instruction, if it is found that the actual internal circulation rate change in the coal mill 12 does not meet the expectations, or the boiler combustion state fluctuates abnormally, the feedforward submodule 131 will immediately re-analyze the data and correct the parameters in the control instruction, such as adjusting the rate of change or target value of the dynamic separator speed. At the same time, the dynamic separator feedforward submodule 131 maintains close coordination and cooperation with other control units within the coal mill 12 (such as the coal feeder control unit, hot air adjustment door control unit, etc.). When adjusting the dynamic separator, a coordinated control signal will be sent synchronously to other related units to ensure that the overall operating parameters of the coal mill 12 (such as feed rate, ventilation volume, grinding pressure, etc.) match each other, and jointly achieve precise adjustment of the internal circulation rate, thereby improving the adaptability and stability of the entire pulverizing system to different operating conditions and ensuring the safe and economical operation of the generator set.

[0071] Furthermore, in a possible implementation of this embodiment, as Figure 2 As shown, the control module 13 further includes: a hot air regulating door feedforward submodule 132;

[0072] The hot air regulating door feedforward submodule 132 is used to determine the hot air flow regulation data and temperature regulation data of the coal mill 12 according to the operating conditions, and generate a control instruction for the hot air regulating door of the coal mill, so as to control and adjust the internal circulation rate of the coal mill 12 according to the control instruction.

[0073] Specifically, the air regulating gate feedforward submodule 132 receives key data from various sources in real time to achieve a precise understanding of the operating conditions. On the one hand, it obtains the operating status data of the coal mill 12 from the monitoring module 11, including parameters such as the current, vibration, inlet and outlet air pressure and temperature, coal powder concentration and fineness of the coal mill 12. These data can intuitively reflect the current working status of the coal mill 12 and the processing of internal materials. On the other hand, load-related data from the generator set, such as load change trends, current load levels, and load scheduling instructions from the power grid to the unit, are also the focus of this submodule. At the same time, the raw coal characteristic data provided by the raw coal feeding module 14, such as the moisture content, ash content, volatile matter content, and particle size distribution of the raw coal, are crucial for determining the hot air regulation strategy. Through the comprehensive collection and integration of these multi-source data, the hot air regulating gate feedforward submodule 132 lays a solid foundation for accurately judging the operating conditions and formulating a reasonable hot air regulation strategy. Based on the comprehensive data obtained, the hot air regulating door feedforward submodule 132 uses advanced algorithms and built-in logical rules to deeply analyze the current operating conditions, and then determine the hot air flow regulation data and temperature regulation data required by the coal mill 12, and generate corresponding hot air regulating door control instructions. Under different operating conditions, the regulation strategies vary significantly. For example, when the generator set is in deep peak regulation and the load rises rapidly, in order to quickly increase the internal circulation rate of the coal mill 12 to increase the coal powder production, the hot air regulating door feedforward submodule 132 will calculate a large increase in hot air flow and an appropriately increased hot air temperature set value, and generate corresponding control instructions to quickly open the hot air regulating door to allow more high-temperature hot air to enter the coal mill 12. This not only helps to accelerate the drying process of the raw coal, but also enhances the ventilation power within the coal mill 12, promotes the transportation and circulation of coal powder, and thus quickly improves the output of the coal mill 12. If the moisture content of the raw coal suddenly increases, even if the load is relatively stable, this submodule will promptly adjust the hot air flow and temperature, increasing the hot air volume and appropriately raising the hot air temperature to ensure sufficient drying of the raw coal, maintain good grinding and conveying conditions within the coal mill 12, and ensure that the internal circulation rate remains stable at an appropriate level. The generated hot air control gate control instructions are not set once and then permanently changed. The hot air control gate feedforward submodule 132 continuously monitors the system's real-time feedback data and dynamically optimizes the instructions. During the execution of the instructions, if the actual internal circulation rate change within the coal mill 12 is found to be inconsistent with the expected change, or if the boiler combustion effect is unsatisfactory, the submodule will immediately reassess the current operating conditions and analyze possible issues, such as uneven hot air distribution and reduced heat exchange efficiency. Based on the analysis results, the hot air flow and temperature control data are quickly adjusted, and the parameters in the control instructions are optimized, such as the hot air control gate opening change rate, the final target opening, and the hot air temperature adjustment range, to ensure that the hot air control can accurately adapt to the changing operating conditions.At the same time, the hot air adjustment gate feedforward submodule 132 maintains a close collaborative relationship with other control submodules within the coal mill 12 (such as the dynamic separator feedforward submodule 131 and the coal feeder control module). When adjusting hot air parameters, it communicates and coordinates with other submodules to ensure that the overall operating parameters of the coal mill 12 (such as the dynamic separator speed and feed rate) match the hot air adjustment. Together, they achieve precise control of the circulation rate within the coal mill 12, improve the stability and adaptability of the pulverizing system under various complex operating conditions, and ensure the efficient and stable operation of the generator set.

[0074] Figure 3 A schematic flow chart of a pulverizing method with variable load regulation provided in an embodiment of the present disclosure.

[0075] like Figure 3 As shown, the method comprises the following steps:

[0076] Step 201: Acquire the operating status data of the coal mill and the load-related data of the generator set.

[0077] Specifically, to fully understand the operating status of the coal mill, a series of advanced sensors have been meticulously deployed at key locations throughout the mill. High-precision current transformers and voltage transformers are installed around the mill's drive motor. These accurately measure the current and voltage levels during operation in real time. Continuous monitoring of these current and voltage data provides insight into the motor's load, as changes in motor current directly reflect the workload on the mill and, indirectly, the intensity of the mill's internal grinding components. Highly sensitive vibration sensors are installed within the mill's tank or grinding chamber. These sensors can keenly capture vibration signals generated during operation, including frequency, amplitude, and vibration trends. Vibration data is crucial for assessing the wear of the mill's internal components, operational stability, and the presence of abnormal shock or imbalance. For example, a sudden increase in vibration frequency or amplitude may indicate wear, looseness, or other faults within the mill's grinding components. Pressure and temperature sensors are installed at the inlet and outlet pipes of the coal mill to accurately measure parameters such as wind pressure, air pressure, wind temperature, and air temperature at the inlet and outlet. The inlet and outlet pressure data reflects the ventilation conditions and material flow resistance within the coal mill, while the temperature data helps assess the energy conversion efficiency, material dryness, and any abnormalities such as overheating within the mill. Furthermore, pulverized coal concentration sensors and pulverized coal fineness analyzers are installed inside the coal mill or near the outlet. These monitor the concentration and fineness of the pulverized coal in real time, providing accurate information on the grinding effect and output quality of the pulverized coal, ensuring that the pulverized coal supplied to the boiler meets combustion requirements. The data collected by these sensors is aggregated, organized, and preliminarily processed by a specialized data acquisition system. It is then transmitted to the control system in a high-speed and stable manner, providing detailed information on the pulverized coal operating status for subsequent analysis and decision-making.

[0078] Generator load data is primarily acquired through close data connections with the grid dispatching system and the generator unit's own monitoring system. At the grid dispatching level, dedicated communication links and data interfaces are used to receive real-time grid load instructions, including the current required generating load value, load change trends (such as the rate and magnitude of increase or decrease), and load forecasts for the future. These grid dispatch instructions serve as a crucial basis for adjusting the generator unit's operating status, directly impacting the mill's operating load and coal pulverization requirements. Furthermore, the generator unit itself is equipped with comprehensive load monitoring equipment, such as power sensors and frequency sensors, which accurately measure key parameters such as the generator unit's actual generated power and grid frequency. Power data directly reflects the generator unit's current load level, while changes in grid frequency indirectly reflect the grid's supply-demand balance and the generator unit's operational stability within the grid. Furthermore, the generator unit's control system records and analyzes historical load data, including load change curves, average load levels, and load fluctuation ranges over different time periods. This historical data is valuable for predicting future load trends, optimizing generator unit operating strategies, and developing appropriate coal mill control solutions. Through comprehensive analysis of real-time grid dispatch instructions, generator set monitoring data, and historical load data, we can fully and accurately grasp the load-related conditions of the generator set, provide strong support for the precise control of the coal mill, and ensure that the entire power generation system can operate stably and efficiently under different load conditions.

[0079] Step 202: Analyze the load-related data and the operating status data to determine the operating condition of the generator set.

[0080] Specifically, after acquiring generator load data (such as load instructions, generated power, load change rate, and grid frequency) and coal mill operating status data (such as motor current, vibration, inlet and outlet pressures and temperatures, and coal powder concentration and fineness), data integration and preprocessing must first be performed. Data integration consolidates data from different data sources and formats to ensure data integrity and consistency. Next, data preprocessing operations, including data cleaning, filtering, and calibration, are performed. Data cleaning primarily removes outliers, erroneous values, and duplicate values. These anomalies may be caused by sensor failures, communication interference, or other unintended factors. Filtering utilizes digital filtering algorithms (such as low-pass filtering, high-pass filtering, or Kalman filtering) to remove noise, making the data smoother and more accurate, thereby better reflecting actual operating conditions. Calibration corrects sensor data based on known standard or reference values ​​to ensure data accuracy and reliability. For example, temperature and pressure sensors are regularly calibrated using standard thermometers and pressure gauges to ensure that the measured data is consistent with the actual physical quantities. After preprocessing, the clean and accurate data enters the feature extraction stage. For load-related data, features such as the amplitude, rate, frequency, and duration of load changes are extracted. For example, the maximum, minimum, and average values ​​of load changes over a certain period of time, as well as the derivative of the load change (i.e., the rate of change), are calculated. The frequency components of the load changes are analyzed using methods such as the Fast Fourier Transform (FFT) to determine the periodic and random characteristics of the load fluctuations. For coal mill operating status data, features closely related to equipment performance and operating conditions are extracted, such as the mean, variance, and crest factor (the ratio of the current peak to the effective value) of the motor current; the spectral characteristics of the vibration signal (such as the harmonic components of each order and the distribution of vibration energy in different frequency bands); the average and fluctuation range of the inlet and outlet pressure difference; and statistical characteristics of the pulverized coal concentration and fineness (such as the mean, standard deviation, and skewness). These features can comprehensively reflect the operating intensity, stability, material handling capacity, and quality of the coal mill. The extracted load-related features are combined with the coal mill operating status features to construct a feature vector that characterizes the operating conditions of the generator set. For example, the load change rate is combined with the change trend of the pulverizer motor current to determine whether the current operating condition is that the load is increasing rapidly, causing the pulverizer load to increase, or that the load is stable but an abnormality occurs inside the pulverizer (such as coal blockage or component wear), causing the current change.

[0081] Using the constructed operating condition feature vectors, operating condition judgment and classification are performed using a pre-established operating condition judgment model or algorithm. A common approach is rule-based judgment, where a series of operating condition judgment rules are summarized based on expert experience and historical operating data. For example, if the load change rate exceeds a certain threshold and the pulverizer motor current continues to rise, while the vibration amplitude is within the normal range, the generator set is judged to be in a condition of rapid load increase and normal pulverizer response. If the load is relatively stable, but the pulverizer inlet and outlet pressure differential continues to increase and the coal fineness becomes coarser, the pulverizer may be experiencing poor ventilation or wear on grinding components. Another approach employs machine learning algorithms, such as support vector machines (SVMs), neural networks (NNs), or decision trees (DTs), for operating condition classification. First, the machine learning model is trained using a large amount of historical operating data to learn the inherent patterns and regularities of data features under different operating conditions. The feature vectors extracted in real time are then fed into the trained model, which automatically determines the current operating condition of the generator set based on this knowledge. For example, a trained neural network model can output corresponding operating condition categories based on input load and coal mill status characteristics, such as normal operation, deep peak-shaving, and fault warning conditions. This approach can accurately and timely determine the operating conditions of the generator set at different times, providing a reliable basis for subsequent precise control and optimized operation.

[0082] Step 203: Generate a control instruction for the coal mill according to the operating condition, so as to adjust the internal circulation rate of the coal mill based on the control instruction.

[0083] Specifically, after determining the operating conditions of the generator set, the control system will conduct an in-depth analysis of the conditions to determine the most suitable control strategy to generate control instructions for the coal mill. For different operating conditions, such as normal and stable operating conditions, deep peak-shaving conditions (large load fluctuations and at a low level), coal type switching or conditions with large changes in coal quality, the system has pre-set corresponding control strategy libraries. Under normal and stable operating conditions, the system will adopt a feedback control-based strategy based on the set load target value and the current operating parameters of the coal mill. For example, by comparing the deviation between the actual load and the target load, as well as the difference between the current internal circulation rate of the coal mill, coal powder fineness and other parameters and the ideal values, the amount that needs to be adjusted is calculated and the corresponding control instructions are generated. In deep peak-shaving conditions, if the load drops rapidly, the system will quickly switch to a strategy based on feedforward-feedback composite control. Based on the rate and magnitude of load reduction, the extent to which the internal circulation rate of the pulverizer needs to be reduced is predicted in advance. Fine-tuning is performed in conjunction with feedback signals (such as the pulverized coal concentration at the pulverizer outlet and the boiler combustion status), generating control instructions to quickly reduce the dynamic separator speed, hot air flow, and feed rate to avoid excessive pulverization and energy waste in the pulverizer. When a coal type is switched or the coal quality changes significantly, the system selects a strategy optimized for the new coal type from the control strategy library based on its characteristics (such as volatile matter, moisture, ash content, grindability, etc.). For example, for coal with low volatile matter, the dynamic separator speed will be reduced to make the pulverized coal finer. At the same time, the hot air temperature and flow will be adjusted to improve the drying effect and ignition performance of the pulverized coal. This generates corresponding control instructions and adjusts the operating parameters of the pulverizer to meet the grinding and combustion requirements of the new coal type.

[0084] Based on the selected control strategy, the control system begins generating specific control commands for the coal mill. These commands adjust the operating parameters of several key components of the coal mill, such as the dynamic separator speed, hot air control valve opening, coal feeder feed rate, and roller loading pressure. For example, when the internal circulation rate of the coal mill needs to be increased, the control system calculates the required speed increase based on the current operating conditions and the pre-set control logic. This speed increase is converted into a corresponding control signal (such as an analog voltage or digital pulse signal) and transmitted to the dynamic separator's drive motor controller, which adjusts the speed accordingly. Simultaneously, for the hot air control valve, the system calculates the appropriate opening change based on the operating conditions and generates control commands to adjust the hot air flow and temperature. During the generation of control commands, the system also optimizes the command parameters. Taking into account the inter-coupling relationships between the coal mill components and the system's dynamic response characteristics, the control parameters in the control commands are optimized by establishing precise mathematical models or employing intelligent optimization algorithms (such as genetic algorithms and particle swarm optimization). For example, when adjusting the speed of the dynamic separator and the opening of the hot air control door, the rate and timing of change are optimized to ensure that while increasing the internal circulation rate, the pressure balance and temperature distribution within the pulverizer are maintained, avoiding system instability or coal powder quality degradation caused by improper parameter adjustment. Furthermore, based on the pulverizer's real-time operational feedback data (such as motor current changes, vibration, and inlet and outlet pressure fluctuations), control instructions are corrected and optimized in real time to ensure their accuracy and effectiveness.

[0085] The generated control instructions are transmitted to the various actuators in the coal mill via a high-speed, reliable communication network. Within the coal mill, each actuator rapidly executes the instructions after receiving them. For example, the dynamic separator's drive motor precisely adjusts its speed based on the speed control instruction, changing the separator's rotational speed and thereby adjusting the coal pulverization efficiency and the coal mill's internal circulation rate. The hot air control door's actuator adjusts its opening based on the opening control instruction, precisely regulating the hot air flow and temperature. The coal feeder's speed regulator adjusts the raw coal feed rate based on the feed rate control instruction to ensure an appropriate feed rate for the coal mill. During the execution of the instructions, sensors within the coal mill continuously monitor the actual operating parameters of each component (such as the actual speed of the dynamic separator, the actual hot air flow and temperature, and the actual feed rate) and transmit this feedback data to the control system in real time. The control system monitors and evaluates the execution of the control instructions based on this feedback data. If it is found that the actual execution result deviates from the expected target, the control system will immediately readjust the control instructions to form a closed-loop control to ensure that the internal circulation rate of the pulverizer can be accurately and stably adjusted according to the predetermined requirements, so as to achieve a good match between the operating conditions of the pulverizer and the generator set, and improve the operating efficiency and stability of the entire power generation system.

[0086] Furthermore, as an implementable manner of the embodiment of the present disclosure, generating the control instruction of the coal mill according to the operating condition includes:

[0087] generating a control instruction for a dynamic separator in the coal mill according to the operating conditions;

[0088] And / or, according to the operating conditions, hot air flow adjustment data and temperature adjustment data of the coal mill are determined, and control instructions for the hot air adjustment door of the coal mill are generated.

[0089] Specifically, control instructions for the dynamic separator in the coal mill are generated based on the operating conditions: First, control instructions for the dynamic separator in the coal mill are generated based on the determined operating conditions. Under normal operation and stable load conditions, the difference between the current internal circulation rate of the coal mill and the ideal internal circulation rate under these conditions is compared. The required speed adjustment for the dynamic separator is calculated based on the current speed of the dynamic separator and relevant parameters such as the fineness of the pulverized coal. Corresponding control instructions are then generated to maintain stable material circulation and pulverized coal output quality within the coal mill. When the load is rapidly increasing, the pulverized coal discharge rate of the coal mill must be rapidly increased to meet the boiler load requirements. Based on a pre-defined model of the relationship between load and dynamic separator speed and the current load fluctuation range, the required speed increase of the dynamic separator is determined. Corresponding control instructions are generated to increase the rotation speed of the dynamic separator, allowing unqualified pulverized coal to return to the coal mill for further grinding more quickly, thereby improving the internal circulation rate and ensuring that more qualified pulverized coal can be delivered to the boiler in a timely manner. In conditions where the load drops rapidly, the speed of the dynamic separator that should be reduced is calculated according to the load drop amplitude according to the established adjustment strategy, and a control instruction is generated to reduce its speed, avoid excessive grinding, reduce the internal circulation rate, and make the powder output of the coal mill adapt to the demand after the load is reduced.

[0090] Generate control instructions for the mill's hot air damper based on operating conditions: Similarly, the mill's hot air flow and temperature control data are determined based on operating conditions, and control instructions for the hot air damper are generated. If the coal type changes and the new coal type has a higher moisture content, the required increase in hot air flow and temperature is calculated based on the drying heat required for the new coal type and the current ventilation conditions within the mill. Control instructions for the hot air damper are generated. By adjusting the hot air damper opening, the hot air flow and temperature are increased to ensure sufficient drying of the raw coal within the mill and maintain optimal grinding and internal circulation conditions. In conditions of fluctuating loads, such as increased load, the appropriate increase in hot air flow and temperature is determined based on the load changes and the mill's current hot air parameters to accelerate the mill's internal circulation rate and improve pulverized coal discharge. Corresponding control instructions are generated to increase the hot air damper opening, allowing more heat-rich hot air to enter the mill, facilitating rapid drying, conveying, and internal circulation of the pulverized coal. On the contrary, when the load decreases, the corresponding adjustment strategy is used to calculate the values ​​by which the hot air flow and temperature need to be reduced, and a control instruction is generated to close the hot air adjustment door, reduce the hot air supply, avoid energy waste caused by excessive hot air and adverse effects on the operation of the coal mill, and make the circulation rate in the coal mill match the load change.

[0091] It should be noted that the embodiments of the present disclosure may include multiple steps. For the convenience of description, these steps are numbered, but these numbers do not limit the execution time slots or execution order between the steps; these steps can be implemented in any order, and the embodiments of the present disclosure do not limit this.

[0092] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0093] Figure 4 A schematic block diagram of an example electronic device 400 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are provided as examples only and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0094] like Figure 4As shown, the device 400 includes a computing unit 401, which can perform various appropriate actions and processes according to a computer program stored in a ROM (Read-Only Memory) 402 or a computer program loaded from a storage unit 408 into a RAM (Random Access Memory) 403. Various programs and data required for the operation of the device 400 can also be stored in the RAM 403. The computing unit 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An I / O (Input / Output) interface 405 is also connected to the bus 404.

[0095] Various components in device 400 are connected to I / O interface 405, including an input unit 406, such as a keyboard, mouse, etc.; an output unit 407, such as various types of displays, speakers, etc.; a storage unit 408, such as a magnetic disk, optical disk, etc.; and a communication unit 409, such as a network card, modem, wireless communication transceiver, etc. Communication unit 409 allows device 400 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0096] The computing unit 401 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, a CPU (Central Processing Unit), a GPU (Graphic Processing Unit), various specialized AI (Artificial Intelligence) computing chips, various computing units that run machine learning model algorithms, a DSP (Digital Signal Processor), and any suitable processor, controller, microcontroller, etc. The computing unit 401 performs the various methods and processes described above, such as the variable load regulated milling method. For example, in some embodiments, the variable load regulated milling method can be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 408. In some embodiments, part or all of the computer program can be loaded and / or installed on the device 400 via the ROM 402 and / or the communication unit 409. When the computer program is loaded into the RAM 403 and executed by the computing unit 401, one or more steps of the method described above can be performed. Alternatively, in other embodiments, the computing unit 401 may be configured to execute the aforementioned load-variable pulverizing method by any other appropriate means (for example, by means of firmware).

[0097] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application-Specific Standard Products), SOCs (System on Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special-purpose or general-purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0098] The program code for implementing the method of the present disclosure can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device so that when the program code is executed by the processor or controller, the functions / operations specified in the flow chart and / or block diagram are implemented. The program code can be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0099] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or apparatus. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or apparatus, or any suitable combination of the foregoing. More specific examples of machine-readable storage media may include an electrical connection based on one or more wires, a portable computer disk, a hard disk, RAM, ROM, EPROM (Electrically Programmable Read-Only-Memory) or flash memory, optical fiber, CD-ROM (Compact Disc Read-Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0100] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0101] The systems and techniques described herein can be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: LAN (Local Area Network), WAN (Wide Area Network), the Internet, and blockchain networks.

[0102] A computer system may include a client and a server. The client and server are generally remote from each other and typically interact via a communication network. This client-server relationship is established by computer programs running on the respective computers, establishing a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host, a host product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosts and VPS services ("Virtual Private Servers" or simply "VPS"). The server may also be a server in a distributed system or a server integrated with blockchain.

[0103] It's important to note that artificial intelligence (AI) is the study of how computers can simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, and planning). This encompasses both hardware and software technologies. AI hardware technologies generally include sensors, specialized AI chips, cloud computing, distributed storage, and big data processing. AI software technologies primarily encompass computer vision, speech recognition, natural language processing, machine learning / deep learning, big data processing, and knowledge graphs.

[0104] The various numerical numbers such as first and second involved in the present disclosure are only for the convenience of description and are not used to limit the scope of the embodiments of the present disclosure, and also indicate the order of precedence.

[0105] The at least one in the present disclosure can also be described as one or more, and the multiple can be two, three, four or more, which is not limited in the present disclosure. In the embodiments of the present disclosure, for a technical feature, the technical features in the technical feature are distinguished by "first", "second", "third", "A", "B", "C" and "D", and there is no order of precedence or size between the technical features described by "first", "second", "third", "A", "B", "C" and "D".

[0106] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this disclosure can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved. This is not limited herein.

[0107] The above specific embodiments do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure shall be included within the scope of protection of this disclosure.

Claims

1. A variable load adjustment pulverizing system, characterized in that: The system includes: a monitoring module, a coal mill, and a control module; The monitoring module is connected to the coal mill and the control module respectively, and is used to monitor the operating status data of the coal mill and send the operating status data to the control module; The control module is connected to the coal mill and the monitoring module respectively, and is used to perform data analysis on the load-related data of the generator set and the operating status data, determine the operating condition of the generator set, and generate control instructions for the coal mill according to the operating condition; The coal mill is connected to the monitoring module and the control module respectively, and is used to adjust the internal circulation rate of the coal mill according to the control instructions.

2. The system according to claim 1, wherein: The system further comprises: a raw coal feeding module; The raw coal feeding module is connected to the coal mill and is used to feed the raw coal to the coal mill. Accordingly, the monitoring module is also used for: The raw coal characteristic data delivered to the coal mill by the raw coal feeding module is monitored, and the raw coal characteristic data is sent to the control module.

3. The system according to claim 2, characterized in that The control module is further configured to: The control strategy is adjusted according to the raw coal characteristic data.

4. The system according to claim 1, wherein: The control module includes: a dynamic separator feedforward submodule; The dynamic separator feedforward submodule is used to generate a control instruction for the dynamic separator in the coal mill according to the operating conditions, so as to control and adjust the internal circulation rate of the coal mill according to the control instruction.

5. The system according to claim 1, wherein: The control module further includes: a hot air regulating door feedforward submodule; The hot air regulating door feedforward submodule is used to determine the hot air flow regulation data and temperature regulation data of the coal mill according to the operating conditions, and generate a control instruction for the hot air regulating door of the coal mill, so as to control and adjust the internal circulation rate of the coal mill according to the control instruction.

6. A variable load regulated pulverizing method, characterized in that: The method comprises: Obtaining coal mill operating status data and generator set load-related data; Performing data analysis on the load-related data and the operating status data to determine the operating condition of the generator set; According to the operating conditions, a control instruction of the coal mill is generated, so as to adjust the internal circulation rate of the coal mill based on the control instruction.

7. The method according to claim 6, characterized in that Generating the control instruction of the coal mill according to the operating condition includes: generating a control instruction for a dynamic separator in the coal mill according to the operating conditions; And / or, according to the operating conditions, hot air flow adjustment data and temperature adjustment data of the coal mill are determined, and control instructions for the hot air adjustment door of the coal mill are generated.

8. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 6 to 7.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to cause the computer to execute the method according to any one of claims 6-7.

10. A computer program product, characterized in that A computer program is included which, when executed by a processor, implements the method according to any one of claims 6 to 7.

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