A method and system for automatic control of a flour mill manufacturing process

Abstract

The application relates to the technical field of equipment control, and provides a flour mill manufacturing process automatic control method and system.The method comprises the following steps: acquiring a plurality of first information of the flour mill in normal operation; acquiring a plurality of second information of the flour mill at present; analyzing the deviation degree of the current working condition of the flour mill from the normal operation working condition according to the plurality of first information and the plurality of second information, determining whether the flour mill has a grinding abnormality based on the deviation degree, and determining the grinding abnormality reason of the flour mill when the flour mill has the grinding abnormality; the grinding abnormality reason is that a material coating is formed in the flour mill or the grinding medium is worn; and the control information of the flour mill is determined according to the grinding abnormality reason of the flour mill.Through the scheme, the efficiency of control in the flour mill manufacturing process can be improved.

Description

Technical Field

[0001] This application relates to the field of equipment control technology, and in particular to an automated control method and system for the manufacturing process of a grinding mill. Background Technology

[0002] In modern industrial production, the grinding mill, as a core piece of equipment, directly affects the quality of the final product and production costs through its operational stability and efficiency. To achieve efficient and stable production, the automated control system needs to acquire and process various operational data in real time and adjust key parameters based on this information.

[0003] However, in actual continuous operation, grinding mill systems may face some subtle challenges, such as wear of the internal grinding media or material adhesion inside the equipment. These changes often do not immediately trigger traditional alarms, but they continuously affect the equipment's performance and energy consumption. Existing automated control systems often struggle to accurately diagnose the root causes of these hidden internal changes, leading to suboptimal control strategies and consequently causing a series of problems such as decreased production efficiency, increased energy consumption, and accelerated equipment wear. Summary of the Invention

[0004] This application provides an automated control method and system for the manufacturing process of a grinding mill, which aims to solve the problem that existing automated control systems for grinding mills are unable to accurately diagnose the root cause when faced with hidden internal changes such as wear of grinding media or material coatings, resulting in suboptimal control strategies and consequently causing problems such as decreased production efficiency, increased energy consumption, and accelerated equipment wear.

[0005] To achieve the above objectives, this application adopts the following technical solution: In a first aspect, an automated control method for a grinding mill manufacturing process is provided, comprising the following steps: acquiring multiple pieces of first information during normal operation of the grinding mill; the multiple pieces of first information include the normal unit power consumption of the grinding mill's drive motor, the normal feed slurry concentration, the normal output slurry density corresponding to the normal feed slurry concentration, the normal frequency spectrum of the drive motor's power signal, and the normal response lag time, wherein the response lag time is the duration between a first moment and a second moment, the first moment being the moment when the drive motor's power changes, and the second moment being the moment after the first moment when the output slurry density changes; acquiring multiple pieces of current information of the grinding mill... The second information includes the current frequency spectrum of the drive motor's power signal, the current power of the drive motor, the current feed slurry flow rate, the current feed slurry concentration, the current output slurry density, and the current response lag time. Based on the first and second information, the deviation between the current operating condition and the normal operating condition of the grinding mill is analyzed. Based on the deviation, it is determined whether there is a grinding abnormality in the grinding mill. If a grinding abnormality exists, the cause of the grinding abnormality is determined. The cause of the grinding abnormality is the formation of a material coating inside the mill or wear of the grinding media. The control information of the grinding mill is determined based on the cause of the grinding abnormality.

[0006] Furthermore, based on multiple first and second pieces of information, the deviation between the current operating condition and the normal operating condition of the grinding mill is analyzed. Based on the degree of deviation, it is determined whether there is a grinding abnormality in the grinding mill. If a grinding abnormality is found, the cause of the abnormality is determined, including: using the ratio of the first value to the normal response lag time as the response time deviation; the first value is the difference between the current response lag time and the normal response lag time; determining the current unit energy consumption of the grinding mill based on the current power, the current feed slurry flow rate, and the current output slurry density; using the ratio of the second value to the normal unit energy consumption as the energy deviation; the second value is the difference between the current unit energy consumption and the normal unit energy consumption; and determining the drive motor... The sum of energy in the preset high-frequency range of the normal frequency spectrum of the power signal is taken as the normal energy sum, and the sum of energy in the preset high-frequency range of the current frequency spectrum of the power signal of the drive motor is taken as the current energy sum; the ratio of the third value to the normal energy sum is taken as the energy deviation; the third value is the difference between the current energy sum and the normal energy sum; the correlation deviation is determined based on the normal feed slurry concentration, the normal output slurry density corresponding to the normal feed slurry concentration, the current feed slurry concentration, and the current output slurry density; based on the response time deviation, the power deviation, the correlation deviation, and the energy deviation, it is determined whether there is a grinding abnormality in the grinding mill, and when there is a grinding abnormality in the grinding mill, the cause of the grinding abnormality is determined.

[0007] Based on the above, the current unit energy consumption of the grinding mill is further determined according to the current power, the current feed slurry flow rate, and the current output slurry density, including: using the product of the current feed slurry flow rate and the current output slurry density as the fourth value; and using the ratio of the current power to the fourth value as the current unit energy consumption of the grinding mill.

[0008] In some preferred embodiments, the correlation deviation is determined based on the normal feed slurry concentration, the normal output slurry density corresponding to the normal feed slurry concentration, the current feed slurry concentration, and the current output slurry density. This includes: using the ratio of the time derivative of the normal feed slurry concentration to the time derivative of the normal output slurry density as the normal grinding correlation; using the ratio of the time derivative of the current feed slurry concentration to the time derivative of the current output slurry density as the current grinding correlation; and using the difference between the current grinding correlation and the normal grinding correlation as the correlation deviation.

[0009] Furthermore, based on the response duration deviation, electrical energy deviation, correlation deviation, and energy deviation, it is determined whether the grinding mill has a grinding abnormality. If a grinding abnormality is found, the cause of the grinding abnormality is determined, including: determining whether the electrical energy deviation continuously increases within a preset duration, and whether the average rate of change of the electrical energy deviation is greater than a preset first electrical energy deviation change threshold; determining whether the response duration deviation continuously increases within a preset duration, and whether the average rate of change of the response duration deviation is greater than a preset first response duration deviation change threshold; determining whether the energy deviation continuously increases within a preset duration, and whether the average rate of change of the energy deviation is greater than a preset energy deviation change threshold; determining whether the correlation deviation continuously decreases within a preset duration, and whether the average rate of change of the correlation deviation is greater than a preset first correlation deviation change threshold. If all of these are true, it is determined that the grinding mill has a grinding abnormality; otherwise, it is determined that the grinding mill does not have a grinding abnormality. If a grinding abnormality is found, the cause of the grinding abnormality is determined.

[0010] Based on the above, when a grinding mill has a grinding abnormality, the cause of the grinding abnormality is determined, including: determining whether the average rate of change of the correlation deviation within a preset time period is less than a preset second correlation deviation change threshold; if the preset second correlation deviation change threshold is greater than a preset first correlation deviation change threshold; if so, the cause of the grinding abnormality is determined to be wear of the grinding media.

[0011] In some implementation schemes, when a grinding abnormality occurs in the grinding mill, the cause of the grinding abnormality is determined, including: determining whether the average rate of change of the response duration deviation is greater than a preset second response duration deviation change threshold; if the preset second response duration deviation change threshold is greater than a preset first response duration deviation change threshold; if so, the cause of the grinding abnormality is determined to be the formation of a material coating inside the grinding mill.

[0012] Furthermore, the control information of the grinding mill is determined based on the cause of the grinding abnormality, including: determining whether the cause of the grinding abnormality is wear of the grinding media; when the cause of the grinding abnormality is wear of the grinding media, determining whether the average rate of change of the electrical energy deviation is greater than a preset second electrical energy deviation threshold; if the preset second electrical energy deviation threshold is greater than a preset first electrical energy deviation threshold; if the average rate of change of the electrical energy deviation is less than or equal to the preset second electrical energy deviation threshold, determining the control information of the grinding mill to reduce the feed slurry flow rate of the grinding mill based on a preset first interval duration and a preset first adjustment step size; if the average rate of change of the electrical energy deviation is greater than the preset second electrical energy deviation threshold, determining the control information of the grinding mill to notify maintenance personnel to replace the new grinding media.

[0013] Based on the above, the control information of the grinding mill is determined according to the cause of the grinding abnormality, including: determining whether the cause of the grinding abnormality is the formation of a material coating inside the mill; when the cause of the grinding abnormality is the formation of a material coating inside the mill, determining whether the average rate of change of the correlation deviation is greater than a preset third correlation deviation change threshold; the preset third correlation deviation change threshold is greater than a preset second correlation deviation change threshold; when the average rate of change of the correlation deviation is greater than the preset third correlation deviation change threshold, determining the control information of the grinding mill to increase the amount of slurry dispersing additive added to the slurry based on a preset second interval duration and a preset second adjustment step size; when the average rate of change of the correlation deviation is less than or equal to the preset third correlation deviation change threshold, determining the control information of the grinding mill to increase the moisture content in the slurry based on a preset third interval duration and a preset third adjustment step size.

[0014] Secondly, this application also discloses an automated control system for a grinding mill manufacturing process, comprising: an acquisition device and a processing device; the acquisition device is used to acquire multiple first pieces of information during normal operation of the grinding mill; the multiple first pieces of information include the normal unit power consumption of the grinding mill's drive motor, the normal feed slurry concentration, the normal output slurry density corresponding to the normal feed slurry concentration, the normal frequency spectrum of the drive motor's power signal, and the normal response lag time, wherein the response lag time is the duration between a first moment and a second moment, the first moment being the moment when the drive motor's power changes, and the second moment being the moment after the first moment when the output slurry density changes; the acquisition device is used to acquire information about the grinding mill... The current second information includes the current frequency spectrum of the drive motor's power signal, the current power of the drive motor, the current feed slurry flow rate, the current feed slurry concentration, the current output slurry density, and the current response lag time. A processing device is used to analyze the deviation between the current operating condition and the normal operating condition of the grinding mill based on the first and second information, determine whether there is a grinding abnormality based on the deviation, and determine the cause of the grinding abnormality when it exists. The cause of the grinding abnormality is the formation of a material coating inside the mill or wear of the grinding media. The processing device is used to determine the control information of the grinding mill based on the cause of the grinding abnormality.

[0015] Beneficial effects The automated control method for the manufacturing process of a grinding mill disclosed in this application acquires multiple first pieces of information during normal operation of the grinding mill and multiple current second pieces of information, and analyzes the deviation between the current operating condition and the normal operating condition based on this information. This method can intelligently determine whether there are grinding abnormalities in the grinding mill, and if abnormalities are found, accurately diagnose the specific causes of the grinding abnormalities, such as the formation of material coatings inside the mill or wear of the grinding media. Finally, based on the diagnosed causes of the grinding abnormalities, the system can determine and execute corresponding control information.

[0016] This technical solution effectively solves the problem in existing automated control systems for grinding mills of accurately diagnosing hidden internal problems (such as grinding media wear or material coating formation). By introducing comparative analysis of multi-dimensional data (including the unit power consumption of the drive motor, the concentration of the feed slurry, the density of the output slurry, the power signal frequency spectrum, and the response lag time), this application can capture subtle changes inside the mill from multiple perspectives, thereby achieving early detection and precise location of grinding anomalies. This method avoids misjudgments and suboptimal control strategies caused by the lack of direct sensing in traditional systems, significantly improving the accuracy and real-time performance of grinding mill operating status diagnosis.

[0017] Accordingly, this application provides more targeted control and maintenance recommendations for grinding mills, thereby effectively reducing energy consumption, extending equipment lifespan, and improving production efficiency and product quality. For example, when grinding media wear is diagnosed, the system can suggest replacing the media or adjusting operating parameters; when material coating is diagnosed, the amount of mineral slurry dispersant or moisture content can be adjusted. This intelligent diagnostic and control mechanism enables the grinding mill to always operate at its optimal state, overcoming the problem of blind adjustment caused by the inability to distinguish between grinding media wear and material coating in existing technologies, thus achieving significant economic benefits and technological advantages. Attached Figure Description

[0018] Figure 1 A flowchart illustrating an automated control method for the manufacturing process of a grinding mill provided in this application; Figure 2 A flowchart illustrating another automated control method for the manufacturing process of a grinding mill provided in this application; Figure 3 This application provides a schematic diagram of the structure of an automated control system for the manufacturing process of a grinding mill. Detailed Implementation

[0019] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. The components of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0020] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0021] In modern industrial production, grinding mills, as core equipment, directly impact the quality of the final product and production costs through their operational stability and efficiency. To achieve efficient and stable production, automated control systems need to acquire and process various operational data in real time and adjust key parameters accordingly. However, during actual continuous operation, grinding mill systems may face some subtle challenges, such as wear of internal grinding media or material adhesion within the equipment. These changes often do not immediately trigger traditional alarms but continuously affect equipment performance and energy consumption. Existing automated control systems often struggle to accurately diagnose the root causes of these hidden internal changes, leading to suboptimal control strategies and consequently, a series of problems including decreased production efficiency, increased energy consumption, and accelerated equipment wear.

[0022] In this regard, such as Figure 1 As shown, this application proposes an automated control method for the manufacturing process of a grinding mill, comprising the following steps: S101. Obtain multiple first-level information during normal operation of the grinding mill.

[0023] The first pieces of information include the normal unit power consumption of the mill's drive motor, the normal feed slurry concentration, the normal output slurry density corresponding to the normal feed slurry concentration, the normal frequency spectrum of the drive motor's power signal, and the normal response lag time. The response lag time is the time between the first moment and the second moment. The first moment is the moment when the drive motor's power changes, and the second moment is the moment after the first moment when the output slurry density changes.

[0024] S102, Obtain multiple second pieces of information about the current grinding mill.

[0025] Several pieces of secondary information include the current frequency spectrum of the drive motor's power signal, the current power of the drive motor, the current feed slurry flow rate, the current feed slurry concentration, the current output slurry density, and the current response lag time.

[0026] S103. Analyze the deviation between the current working condition and the normal operating condition of the grinding mill based on multiple first information and multiple second information, determine whether there is a grinding abnormality in the grinding mill based on the degree of deviation, and determine the cause of the grinding abnormality when there is a grinding abnormality in the grinding mill.

[0027] The abnormal grinding is caused by the formation of a material coating inside the mill or wear of the grinding media.

[0028] S104. Determine the control information of the grinding mill based on the cause of the grinding abnormality.

[0029] This application acquires multiple pieces of first information during the normal operation of the grinding mill and multiple pieces of current second information. Based on this information, it analyzes the deviation between the current operating condition and the normal operating condition of the grinding mill, thereby determining whether there is a grinding abnormality and its specific cause. Then, it determines the corresponding control information based on the cause of the grinding abnormality. This method can effectively identify hidden problems inside the grinding mill, such as wear of the grinding media or the formation of material coatings, thus achieving more precise and intelligent automated control. It avoids misjudgments and suboptimal control caused by the lack of in-depth diagnosis in traditional systems, significantly improving the operating efficiency and stability of the grinding mill.

[0030] To better understand the technical solution proposed in this application, some key terms involved will be explained first.

[0031] "First information" refers to a series of benchmark data collected during the normal operation of the grinding mill. These data reflect the performance parameters of the equipment under ideal operating conditions. Specifically, this includes the normal unit power consumption of the drive motor, the normal feed slurry concentration, the normal output slurry density corresponding to the normal feed slurry concentration, the normal frequency spectrum of the drive motor's power signal, and the normal response lag time. This normal operating data serves as a reference standard for subsequently judging whether the current operating condition of the grinding mill is abnormal.

[0032] "Second information" refers to the various data collected in real time by the grinding mill under its current operating state, used for comparison and analysis with the first information. Specifically, it includes the current frequency spectrum of the drive motor's power signal, the current power of the drive motor, the current feed slurry flow rate, the current feed slurry concentration, the current output slurry density, and the current response lag time.

[0033] "Response lag time" is a key time parameter, defined as the duration between a first moment and a second moment. The first moment is when the power of the drive motor changes, while the second moment is when the density of the ore slurry exiting the mill changes after the first moment. This parameter reflects the mill's response speed to power changes and is an important indicator for evaluating grinding efficiency and internal conditions.

[0034] "Grinding abnormalities" refer to abnormal grinding conditions that occur during the operation of a grinding mill, which may lead to decreased grinding efficiency, increased energy consumption, or unstable product quality. This application mainly focuses on two causes of grinding abnormalities: the formation of material coatings inside the mill and wear of the grinding media. Material coatings refer to the adhesion of fine particles in the slurry to the surface of the grinding media (such as steel balls) or liners inside the mill, forming a covering that affects the grinding effect. Wear of the grinding media refers to the gradual reduction in size or loss of original shape of the grinding media due to friction during long-term operation, thereby reducing grinding efficiency.

[0035] The core of the automated control method for the manufacturing process of grinding mill proposed in this application lies in achieving accurate diagnosis and intelligent control of grinding abnormalities through in-depth analysis of grinding mill operating data.

[0036] Several methods can be employed to obtain key information about a grinding mill during normal operation. For example, after the mill is first put into operation or undergoes a major overhaul, and to ensure it is in optimal operating condition, sensors and data acquisition systems can continuously monitor and record various operating parameters over a period of time. These parameters include the unit energy consumption of the drive motor, the concentration of the feed slurry, the density of the output slurry, the frequency spectrum of the drive motor's power signal, and the response lag time. Statistical analysis of these data yields statistical characteristics such as averages and standard deviations, serving as a benchmark for "normal" operation.

[0037] Another approach is to manually trigger data acquisition during mill operation when operators or experts determine that the mill is in a stable and efficient operating state. This data is then stored as the primary information for normal operation. For example, a dedicated "normal operating condition record" mode can be set up. In this mode, the system automatically collects and stores the normal unit energy consumption of the drive motor, the normal feed slurry concentration, the normal output slurry density corresponding to the normal feed slurry concentration, the normal frequency spectrum of the drive motor's power signal, and the normal response lag time. The response lag time can be obtained by monitoring the time required for the output slurry density to stabilize when the drive motor power undergoes a slight change.

[0038] To acquire various secondary information about the grinding mill, the system needs to continuously collect the mill's current operating data in real time. This can be achieved by installing various sensors on the mill, such as power sensors to measure the current power of the drive motor, flow meters to measure the current feed slurry flow rate, concentration meters to measure the current feed slurry concentration, and density meters to measure the current output slurry density. Simultaneously, by performing spectral analysis on the drive motor power signal, the current frequency spectrum of the drive motor power signal can be obtained. The current response lag time can be obtained by monitoring the time difference between changes in drive motor power and changes in output slurry density in real time. This real-time data is continuously transmitted to the control system for processing.

[0039] In analyzing the deviation between the current operating condition and the normal operating condition of the grinding mill based on multiple primary and secondary information sources, determining whether there is a grinding abnormality based on the degree of deviation, and identifying the cause of the grinding abnormality when it exists, various data analysis methods can be employed. For example, the currently collected secondary information can be directly compared with pre-stored primary information to calculate the absolute or relative deviation of various parameters. When these deviations exceed preset thresholds, it is considered that the grinding mill may have a grinding abnormality. Specifically, the difference between the current unit energy consumption and the normal unit energy consumption, the difference between the current feed slurry concentration and the normal feed slurry concentration, and the difference between the current response lag time and the normal response lag time can be calculated, etc.

[0040] Furthermore, the system can compare and analyze the current frequency spectrum and normal frequency spectrum of the drive motor's power signal, for example, calculating their energy differences in the high-frequency or low-frequency range. When these deviations reach a certain level, the system will issue a preliminary judgment of grinding anomaly. After confirming the existence of grinding anomaly, the system will further analyze the patterns and trends of these deviations to determine the specific cause of the grinding anomaly, such as the formation of a material coating inside the mill or wear of the grinding media.

[0041] Regarding the determination of control information for the grinding mill based on the causes of grinding abnormalities, once the specific cause of the abnormality is identified, the system generates corresponding control information according to a preset control strategy. For example, if the cause of the abnormality is the formation of a material coating inside the mill, the control information might include adjusting the slurry concentration, increasing the amount of dispersant added, or changing the mill's operating parameters to remove the coating. If the cause of the abnormality is wear of the grinding media, the control information might include recommending replacement of the grinding media, adjusting the slurry flow rate into the mill, or changing the mill's rotational speed to compensate for the decrease in grinding efficiency. This control information can be sent directly to the mill's actuators or used to notify operators for intervention in the form of alarms and suggestions.

[0042] The automated control method for the manufacturing process of a grinding mill proposed in this application systematically acquires multiple first pieces of information and multiple current second pieces of information of the grinding mill during normal operation, and analyzes the degree of deviation between the current working condition and the normal operating condition of the grinding mill based on this information, thereby determining whether there is a grinding abnormality in the grinding mill and its specific cause, and then determining the corresponding control information based on the cause of the grinding abnormality.

[0043] Specifically, during the operation of the grinding mill, the system first continuously acquires primary information such as the normal unit power consumption of the drive motor, the normal feed slurry concentration, the normal output slurry density corresponding to the normal feed slurry concentration, the normal frequency spectrum of the drive motor's power signal, and the normal response lag time. This information serves as the benchmark for the normal operation of the grinding mill. Simultaneously, the system acquires secondary information in real time, including the current frequency spectrum of the drive motor's power signal, the current power of the drive motor, the current feed slurry flow rate, the current feed slurry concentration, the current output slurry density, and the current response lag time.

[0044] Next, the system compares and analyzes the real-time acquired second information with the preset first information to calculate the degree of deviation of various parameters. For example, by comparing the current response lag time with the normal response lag time, the current unit power consumption with the normal unit power consumption, the current frequency spectrum of the drive motor power signal with the normal frequency spectrum, and the correlation between the current feed slurry concentration and the output slurry density and the normal conditions, the system quantifies the degree of deviation between the current operating condition and the normal operating condition of the grinding mill.

[0045] Based on these deviations, the system can intelligently determine whether there is a grinding abnormality in the grinding mill. For example, when the response lag time increases significantly, the unit power consumption continues to rise, the power signal frequency spectrum changes in the high-frequency band, and the correlation between the feed slurry concentration and the output slurry density decreases, the system will determine that there is a grinding abnormality in the grinding mill.

[0046] Once a grinding anomaly is identified, the system will further analyze the patterns and trends of these deviations to determine the specific cause of the anomaly. For example, if the response lag time and unit power consumption increase simultaneously and continuously, and the power signal frequency spectrum shows a significant decrease in energy at high frequencies, it may indicate wear of the grinding media; if the correlation between the feed slurry concentration and the output slurry density decreases sharply, and the response lag time increases significantly, it may indicate the formation of a material coating inside the mill.

[0047] Finally, based on the identified cause of the grinding anomaly, the system generates corresponding control information. For example, if the grinding media is worn, the system may suggest adjusting the feed slurry flow rate or notifying maintenance personnel to replace the grinding media; if a material coating forms inside the mill, the system may suggest increasing the moisture content of the slurry or adding a slurry dispersant. This control information can guide operator intervention or be directly executed by the automated control system to promptly correct grinding anomalies and ensure the stable and efficient operation of the grinding mill.

[0048] The automated control method for the grinding mill manufacturing process proposed in this application has significant advantages and innovations compared to existing technologies. Traditional automated control systems often struggle to accurately diagnose the root causes of hidden problems such as wear of grinding media or the formation of material coatings inside the grinding mill. This leads to suboptimal control strategies, resulting in a series of problems including decreased production efficiency, increased energy consumption, and accelerated equipment wear. For example, when wear of grinding media leads to a decrease in grinding efficiency, the system may misinterpret it as "the ore entering the mill becoming more difficult to grind" or "insufficient grinding action," thus initiating suboptimal compensation strategies, such as blindly increasing or decreasing the feed rate or increasing the water supply. These seemingly reasonable adjustments do not actually address the root cause of the problem; instead, they may accelerate equipment wear, increase energy consumption, and lead to a decrease in the particle size stability of the produced slurry.

[0049] This application, by comprehensively acquiring multiple primary and secondary information sources during normal operation of the grinding mill, particularly analyzing the frequency spectrum and response lag time of the drive motor's power signal, enables a deeper understanding of the grinding mill's internal operating status. By comparing this multi-dimensional information, the system can accurately analyze the deviation between the grinding mill's current operating condition and its normal operating condition, and based on this, determine whether grinding abnormalities exist. More importantly, this application can further determine the specific cause of the grinding abnormality, such as the formation of a material coating inside the mill or wear of the grinding media. This deep diagnostic capability is not possessed by existing technologies.

[0050] By accurately identifying the causes of grinding abnormalities, this application can determine the control information of the grinding mill based on the specific cause, thereby achieving more targeted and effective automated control. For example, when it is determined that the grinding media is worn, the system can suggest replacing the grinding media or adjusting the flow rate of the slurry entering the mill; when it is determined that a material coating has formed, the system can suggest increasing the moisture content in the slurry or adding a slurry dispersant. This cause-based intelligent control avoids the drawbacks of blindly adjusting parameters in traditional systems, significantly improving the operating efficiency of the grinding mill, reducing energy consumption, and extending the service life of the equipment. Therefore, this application has significant technological advancements in the field of grinding mill automation control.

[0051] Specifically, based on multiple pieces of primary and secondary information, the deviation between the current operating condition and the normal operating condition of the grinding mill is analyzed. Based on the degree of deviation, it is determined whether there is a grinding abnormality in the grinding mill. If a grinding abnormality is found, the cause of the abnormality is determined, including the following steps: The ratio of the first value to the normal response lag time is used as the response time deviation; the first value is the difference between the current response lag time and the normal response lag time; the current unit energy consumption of the grinding mill is determined based on the current power, the current feed slurry flow rate, and the current output slurry density; the ratio of the second value to the normal unit energy consumption is used as the energy deviation; the second value is the difference between the current unit energy consumption and the normal unit energy consumption; the sum of energy in the preset high-frequency range of the normal frequency spectrum of the drive motor power signal is used as the normal energy sum, and the power signal of the drive motor... The total energy within the preset high-frequency range in the current frequency spectrum is taken as the current total energy; the ratio of the third value to the normal total energy is taken as the energy deviation; the third value is the difference between the current total energy and the normal total energy; the correlation deviation is determined based on the normal feed slurry concentration, the normal output slurry density corresponding to the normal feed slurry concentration, the current feed slurry concentration, and the current output slurry density; based on the response time deviation, electrical energy deviation, correlation deviation, and energy deviation, it is determined whether there is a grinding abnormality in the grinding mill, and when there is a grinding abnormality in the grinding mill, the cause of the grinding abnormality is determined.

[0052] The response time deviation is used to quantify changes in the response characteristics of the grinding mill. Specifically, the first value is defined as the difference between the current response lag time and the normal response lag time. This difference reflects the change in the time required for the density of the slurry exiting the mill to stabilize after a power change. Using the ratio of this first value to the normal response lag time as the response time deviation allows for a relativistic assessment of the degree of deviation in the response lag time.

[0053] Furthermore, the current unit energy consumption of the grinding mill is determined as the ratio of the current power to the product of the current feed slurry flow rate and the current output slurry density. This unit energy consumption characterizes the electrical energy required per unit output (determined by both the feed slurry flow rate and the output slurry density) and is a key indicator for measuring the energy efficiency of the grinding mill. Based on this, the energy deviation is calculated as the ratio of a second value to the normal unit energy consumption, where the second value is the difference between the current unit energy consumption and the normal unit energy consumption, thus quantifying the deviation of the grinding mill's energy efficiency.

[0054] Furthermore, energy deviation is used to assess changes in the frequency spectrum of the drive motor power signal within the high-frequency range. Specifically, the sum of energy within a preset high-frequency range in the normal frequency spectrum of the drive motor power signal is defined as the normal energy sum, while the sum of energy within the preset high-frequency range in the current frequency spectrum of the drive motor power signal is defined as the current energy sum. The preset high-frequency range typically refers to the vibration frequency range related to grinding processes such as impact and friction within the mill. The third value is defined as the difference between the current energy sum and the normal energy sum, and the energy deviation is the ratio of the third value to the normal energy sum, used to reflect abnormal changes in the grinding state within the mill.

[0055] Furthermore, the correlation deviation is used to assess changes in the correlation between the feed slurry concentration and the output slurry density. This deviation assesses the stability of the grinding process by comparing the interaction between the feed slurry concentration and the output slurry density under normal operating conditions and the current operating conditions.

[0056] This application's solution introduces four key indicators—response time deviation, electrical energy deviation, energy deviation, and correlation deviation—to achieve multi-dimensional and quantitative analysis of the deviation between the current operating condition and the normal operating condition of the grinding mill. Response time deviation reflects changes in the material's residence time within the mill, which may be related to changes in material flow characteristics caused by the formation of material coatings inside the mill or wear of the grinding media. Electrical energy deviation is directly related to the grinding mill's energy efficiency; when the mill's internal conditions are abnormal, such as increased material coatings or wear of the grinding media, it typically leads to a decrease or fluctuation in energy efficiency.

[0057] Energy deviation analyzes the energy changes of the drive motor power signal in the high-frequency range to capture subtle changes in the grinding process, such as impact and friction, within the mill. These changes are important physical characteristics of grinding media wear or material coating formation. Correlation deviation assesses the stability and efficiency of the grinding process by examining the dynamic relationship between the feed slurry concentration and the output slurry density. By comprehensively considering these deviations, it is possible to more fully and accurately identify whether there are grinding abnormalities in the mill and further distinguish the specific causes of these abnormalities, such as the formation of material coatings inside the mill or wear of the grinding media.

[0058] like Figure 2 As shown, this application further proposes the following steps for determining the current unit energy consumption of the grinding mill based on the current power, the current feed slurry flow rate, and the current output slurry density: S201. The product of the current feed slurry flow rate and the current discharge slurry density is taken as the fourth value.

[0059] S202. The ratio of the current power to the fourth value is taken as the current unit power consumption of the grinding mill.

[0060] Specifically, the fourth value can be understood as the effective mass flow rate of material passing through the grinding mill per unit time under the current operating conditions, reflecting the actual load on the grinding mill. The current feed slurry flow rate refers to the volume or mass of slurry entering the grinding mill per unit time, while the current output slurry density reflects the consistency of the slurry after grinding. Multiplying the two aims to comprehensively consider the amount of material entering the grinding mill and its effective concentration or density inside the mill, thereby more accurately characterizing the actual processing capacity of the grinding mill.

[0061] The current unit energy consumption of the grinding mill refers to the electrical energy consumed by the grinding mill in processing a unit mass or volume of material under its current operating conditions. A standardized and comparable energy consumption index can be obtained by calculating the ratio of the current power of the drive motor to the fourth value mentioned above. Current power refers to the actual output power of the drive motor at the current moment, representing the energy input required for the operation of the grinding mill.

[0062] The proposed solution defines a fourth value as the product of the current feed slurry flow rate and the current output slurry density. This fourth value is used as the denominator, and the current power of the drive motor is used as the numerator to calculate the current unit energy consumption of the grinding mill. This calculation method aims to establish a more accurate energy consumption model that comprehensively reflects the energy efficiency of the grinding mill under specific material throughput and material conditions during actual operation. This standardized calculation eliminates the interference caused by fluctuations in feed slurry flow rate or output slurry density on energy consumption assessment, making energy consumption data under different operating conditions comparable, thus providing more reliable basic data for subsequent operating condition deviation analysis.

[0063] Through the above technical solutions, the current unit energy consumption of the grinding mill can be calculated and quantified more accurately. This precise calculation method helps improve the accuracy of grinding mill operating condition analysis, making the judgment of grinding abnormalities more reliable. In addition, the acquisition of standardized energy consumption indicators also provides solid data support for the evaluation and optimization of grinding mill operating efficiency, thereby helping to achieve refined and automated control of the grinding mill manufacturing process.

[0064] This application further proposes a method for determining the correlation deviation based on the normal feed slurry concentration, the normal output slurry density corresponding to the normal feed slurry concentration, the current feed slurry concentration, and the current output slurry density.

[0065] Specifically, the correlation deviation is determined based on the normal feed slurry concentration, the normal output slurry density corresponding to the normal feed slurry concentration, the current feed slurry concentration, and the current output slurry density, including: The ratio of the time derivative of the normal feed slurry concentration to the time derivative of the normal output slurry density is taken as the normal grinding correlation; the ratio of the time derivative of the current feed slurry concentration to the time derivative of the current output slurry density is taken as the current grinding correlation; and the difference between the current grinding correlation and the normal grinding correlation is taken as the correlation deviation.

[0066] The time derivative can be understood as the rate of change of a physical quantity over time. For example, the time derivative of the normal feed slurry concentration refers to the trend and rate of change of the feed slurry concentration over time under normal mill operation; the time derivative of the normal output slurry density refers to the trend and rate of change of the output slurry density over time under normal mill operation. Similarly, the time derivatives of the current feed slurry concentration and the current output slurry density refer to the trends and rates of change of the feed slurry concentration and the output slurry density over time under the current operating conditions of the mill. These time derivatives can be obtained by differential calculation of historical data or by numerical differentiation of real-time sensor data.

[0067] Normal grinding correlation refers to the degree of association between changes in feed slurry concentration and changes in output slurry density under normal grinding mill operating conditions. Current grinding correlation refers to the degree of association between changes in feed slurry concentration and changes in output slurry density under the current operating conditions of the grinding mill. This dynamic association can be quantified by calculating the ratio of their time derivatives. Correlation deviation is obtained by comparing the difference between current grinding correlation and normal grinding correlation, reflecting the degree to which the dynamic correlation between feed slurry concentration and output slurry density deviates from the normal state during the current grinding process of the grinding mill.

[0068] This application's solution, by introducing the concept of time derivative, can more precisely capture the intrinsic correlation between the dynamic changes in the feed slurry concentration and the output slurry density of a grinding mill under different operating conditions. Traditionally, only the difference between instantaneous or average values ​​may be considered, but these static indicators are insufficient to fully reflect the dynamic characteristics of the grinding process. By calculating the correlation between normal grinding and the current grinding, and further calculating their difference as the correlation deviation, this solution can effectively quantify the degree of deviation between the dynamic response characteristics of the grinding mill process and the normal state. This deviation in dynamic correlation is often an early signal of changes in the grinding state inside the mill, such as the formation of material coatings or wear of grinding media. These anomalies affect the response of changes in feed slurry concentration to changes in output slurry density.

[0069] This application further proposes a method for determining whether a grinding mill has a grinding abnormality, and when a grinding abnormality is found, determining the cause of the grinding abnormality, comprising: The system determines whether the energy deviation continuously increases within a preset time period, and whether the average rate of change of the energy deviation is greater than a preset first energy deviation change threshold; whether the response time deviation continuously increases within a preset time period, and whether the average rate of change of the response time deviation is greater than a preset first response time deviation change threshold; whether the energy deviation continuously increases within a preset time period, and whether the average rate of change of the energy deviation is greater than a preset energy deviation change threshold; and whether the correlation deviation continuously decreases within a preset time period, and whether the average rate of change of the correlation deviation is greater than a preset first correlation deviation change threshold. If all of these conditions are met, the system determines that the grinding mill has a grinding abnormality; otherwise, it determines that the grinding mill does not have a grinding abnormality. If the grinding mill has a grinding abnormality, the system determines the cause of the grinding abnormality.

[0070] Specifically, the above judgment process aims to improve the accuracy and robustness of grinding anomaly detection through multi-dimensional and dynamic indicator analysis. The "preset duration" refers to a time window for observing the changing trends of various deviations. Its setting should be sufficient to capture the typical development process of grinding anomalies while avoiding overreaction to short-term, instantaneous fluctuations. For example, this preset duration can be empirically set based on the specific model of the grinding mill, the characteristics of the processed materials, and historical operating data, typically ranging from several minutes to several hours.

[0071] "Continuous increase" or "continuous decrease" means that within the aforementioned preset time period, the corresponding deviation value exhibits a continuous upward or downward trend, rather than occasional fluctuations. This trend is an important signal that grinding anomalies are gradually forming or worsening. For example, its persistence can be determined by performing moving average processing or trend fitting on the deviation data.

[0072] The "average rate of change" is used to quantify the speed and magnitude of the deviation within a preset time period, reflecting the urgency of the abnormal development. This average rate of change can be obtained by calculating the ratio of the total change in deviation within the preset time period to the preset time period.

[0073] The "Preset First Threshold for Electrical Energy Deviation," "Preset First Threshold for Response Time Deviation," "Preset First Threshold for Energy Deviation," and "Preset First Threshold for Correlation Deviation" are pre-defined threshold values ​​used to define what level of change is considered abnormal. These thresholds are typically calibrated based on the data fluctuation range of the grinding mill under normal operating conditions and expert experience to ensure that only significant changes exceeding the normal range are identified as abnormal.

[0074] When all the above judgment conditions—namely, electrical energy deviation, response time deviation, and energy deviation—continuously increase within a preset time period and their average rate of change is greater than their respective preset thresholds, while the correlation deviation continuously decreases within a preset time period and its average rate of change is greater than a preset first correlation deviation change threshold, then it is comprehensively determined that the grinding mill has a grinding abnormality. If all these conditions are not met, it is considered that the grinding mill currently does not have a grinding abnormality. Once a grinding abnormality is determined, the system will further initiate the process of determining the cause of the grinding abnormality.

[0075] This application's solution, by introducing the judgment of deviation change trends and rates, can more accurately identify whether there are grinding abnormalities in the grinding mill. Traditional anomaly detection methods may only rely on whether the instantaneous value of the deviation exceeds a certain fixed threshold, which is easily affected by fluctuations in normal operating conditions, leading to false alarms or missed alarms. This application, however, by monitoring the continuous change trends and average rates of multiple key deviations over a preset time period and combining this with preset thresholds for comprehensive judgment, can effectively filter out short-term noise and instantaneous disturbances, thus more reliably capturing systemic changes caused by real anomalies such as the formation of material coatings inside the mill or wear of grinding media. This multi-indicator, dynamic judgment mechanism makes anomaly detection more sensitive and has higher anti-interference capabilities.

[0076] This application further proposes methods for determining the cause of grinding abnormalities in a grinding mill, including: Determine whether the average rate of change of correlation deviation within a preset time period is less than a preset second correlation deviation change threshold; if the preset second correlation deviation change threshold is greater than a preset first correlation deviation change threshold; if so, determine that the grinding abnormality of the grinding mill is caused by wear of the grinding media.

[0077] Specifically, correlation deviation refers to the degree of deviation in the correlation between the normal feed slurry concentration, the corresponding normal output slurry density, the current feed slurry concentration, and the current output slurry density. When the grinding media wears down, the grinding efficiency inside the mill decreases, leading to a weakening of the correlation between the feed slurry concentration and the output slurry density, i.e., a decrease in correlation deviation. The preset duration refers to a period of time used to observe the trend of correlation deviation changes; for example, it can be set to several hours or days to ensure that the observed changes are continuous rather than instantaneous fluctuations.

[0078] The preset second correlation deviation change threshold is a pre-defined value used to determine whether the decrease in correlation deviation is sufficient to indicate wear of the grinding media. This threshold is typically determined through historical data analysis, expert experience, or experimental testing to ensure it can effectively distinguish wear of the grinding media from other abnormal conditions. The preset second correlation deviation change threshold is set to be greater than the preset first correlation deviation change threshold. This means that when judging wear of the grinding media, the requirement for a more significant decrease in correlation deviation is stricter; a more significant decrease is needed to be considered as wear of the grinding media, thereby improving the accuracy of the judgment.

[0079] This application's solution addresses the problem in the aforementioned technical framework where it's difficult to accurately distinguish between grinding media wear and other abnormal causes when grinding anomalies occur, by introducing a further assessment of the average rate of change of the correlation deviation. When grinding media wears down, the grinding efficiency inside the mill gradually decreases, leading to a significant weakening of the correlation between the concentration of the feed slurry and the density of the output slurry. This weakening of the correlation is reflected in a continuous decrease in the correlation deviation, and its average rate of change is less than a relatively large preset second correlation deviation change threshold.

[0080] By setting a second, higher threshold for correlation deviation than the first threshold, and determining whether the average rate of change of correlation deviation is less than this second threshold, the correlation change pattern unique to grinding media wear can be captured more accurately. This mechanism allows the system to distinguish grinding media wear from other abnormal conditions that may cause a decrease in correlation deviation but to varying degrees, thus providing a more accurate basis for subsequent control or maintenance decisions.

[0081] This application further proposes methods for determining the cause of grinding abnormalities in a grinding mill, specifically including: Determine whether the average rate of change of the response duration deviation is greater than the preset second response duration deviation change threshold; if the preset second response duration deviation change threshold is greater than the preset first response duration deviation change threshold; if so, determine that the grinding abnormality of the grinding mill is caused by the formation of a material coating inside the mill.

[0082] Specifically, the average rate of change of response time deviation refers to the rate at which the response time deviation changes over a period of time. Response time deviation reflects the degree of time lag between changes in drive motor power and changes in the density of the ore output from the mill, deviating from normal conditions. When a material coating forms inside the mill, the grinding environment inside the mill changes significantly. For example, the adhesion of material to the mill inner wall or the surface of the grinding media alters the material's flow characteristics and grinding efficiency, resulting in a significantly prolonged response time to the effect of power changes on the density of the ore output from the mill, and a more drastic trend in the change.

[0083] Therefore, by monitoring the average rate of change of response duration deviation, this dynamic change caused by the material coating can be effectively captured. The preset second response duration deviation change threshold is set to be greater than the preset first response duration deviation change threshold. This aims to provide a more stringent judgment standard to distinguish the more significant response duration change trend caused by the material coating, thereby improving the accuracy of the diagnosis.

[0084] This application's solution, by introducing a judgment on the average rate of change of response duration deviation and setting a higher preset second response duration deviation change threshold, can more accurately identify the specific grinding anomaly caused by the formation of a material coating inside the mill. When a material coating forms inside the mill, the adhesion of material to the grinding media or the inner wall of the mill hinders the normal grinding process, leading to an increase in the residence time of the material inside the mill and a sluggish response to changes in drive motor power. This sluggishness is not simply an increase in response duration, but rather manifests as a continuous increase in response duration deviation at a faster rate. By comparing the average rate of change of response duration deviation with a relatively high preset second response duration deviation change threshold, this unique dynamic characteristic caused by the material coating can be effectively captured, thereby distinguishing the material coating from other grinding anomalies (such as grinding media wear).

[0085] Based on the aforementioned automated control method for the grinding mill manufacturing process, the control information for the grinding mill is determined according to the causes of grinding abnormalities, including: Determine whether the grinding abnormality of the grinding mill is caused by wear of the grinding media; if the grinding abnormality is caused by wear of the grinding media, determine whether the average rate of change of the electrical energy deviation is greater than a preset second electrical energy deviation threshold; if the preset second electrical energy deviation threshold is greater than a preset first electrical energy deviation threshold; if the average rate of change of the electrical energy deviation is less than or equal to the preset second electrical energy deviation threshold, determine that the control information of the grinding mill is to reduce the feed slurry flow rate of the grinding mill based on a preset first interval duration and a preset first adjustment step size; if the average rate of change of the electrical energy deviation is greater than the preset second electrical energy deviation threshold, determine that the control information of the grinding mill is to notify maintenance personnel to replace the new grinding media.

[0086] Specifically, when a grinding mill is found to have a grinding abnormality, and the cause of the abnormality is wear of the grinding media, it is necessary to further assess the severity of the wear in order to take appropriate control measures. Wear of the grinding media refers to the gradual wear of the grinding media (such as steel balls, steel rods, etc.) inside the grinding mill due to prolonged operation, leading to a decrease in grinding efficiency. To assess the degree of wear, this application introduces the average rate of change of electrical energy deviation as a key indicator. Electrical energy deviation reflects the degree of deviation of the unit electrical energy consumption of the grinding mill from the normal value, and its average rate of change reflects the speed of this deviation trend.

[0087] Furthermore, a preset second energy deviation change threshold is set to distinguish between slight and severe wear of the grinding media. This preset second energy deviation change threshold is greater than the preset first energy deviation change threshold, indicating a more significant abnormal change in energy consumption. When the average rate of change of energy deviation is less than or equal to the preset second energy deviation change threshold, it indicates relatively mild wear of the grinding media. In this case, the control information of the grinding mill is determined to reduce the feed slurry flow rate based on a preset first interval duration and a preset first adjustment step size. Reducing the feed slurry flow rate can alleviate the load on the grinding mill, thereby compensating to some extent for the decrease in grinding efficiency caused by grinding media wear, slowing down the wear process, and maintaining stable operation of the grinding mill. The preset first interval duration and preset first adjustment step size are used to guide the frequency and amplitude of flow rate adjustment, ensuring the smoothness and effectiveness of the adjustment process.

[0088] However, when the average rate of change of electrical energy deviation exceeds the preset second threshold for electrical energy deviation, it usually indicates that the wear of the grinding media has reached a relatively severe level, and simply adjusting the feed slurry flow rate is no longer effective in solving the problem. In this case, the control information for the grinding mill is determined to notify maintenance personnel to replace the grinding media. This measure aims to completely resolve the problem of low grinding efficiency caused by severe wear and avoid potential equipment damage or product quality degradation due to continued operation.

[0089] This application's solution achieves differentiated control strategies by finely distinguishing the degree of wear of grinding media, a specific cause of grinding anomalies. When grinding media wear occurs in a grinding mill, its grinding efficiency decreases. To maintain the same grinding effect, the drive motor may need to consume more electrical energy, or the grinding effect may deteriorate with the same energy consumption, which is reflected in a continuous increase in the electrical energy deviation. By monitoring the average rate of change of the electrical energy deviation, the severity of wear can be quantified. A smaller average rate of change indicates that the wear is in its early or slight stage. At this time, reducing the feed slurry flow rate can effectively reduce the load on the grinding mill, decrease the wear rate of the grinding media, and maintain a certain grinding effect, thereby extending the service life of the grinding media and avoiding unnecessary downtime.

[0090] When the average rate of change of electrical energy deviation exceeds the preset second threshold for electrical energy deviation, it means that the wear of the grinding media is very severe. Continuing to operate it will not only be inefficient but may also cause further damage to the equipment. At this time, notifying maintenance personnel to replace the grinding media is a more economical and efficient solution, which can quickly restore the normal grinding capacity of the mill. This graded handling mechanism allows the control system to take the most appropriate countermeasures according to the severity of the actual operating conditions.

[0091] This application further proposes to determine the control information of the grinding mill based on the cause of grinding abnormalities, specifically for the situation where a material coating forms inside the grinding mill, and provides a more refined and adaptive control scheme.

[0092] The aforementioned automated control method for the grinding mill manufacturing process determines the control information of the grinding mill based on the cause of the grinding abnormality when a grinding abnormality occurs. This includes: Determine whether the grinding abnormality of the grinding mill is caused by the formation of a material coating inside the mill; when the grinding abnormality is caused by the formation of a material coating inside the mill, determine whether the average rate of change of the correlation deviation is greater than the preset third correlation deviation change threshold; if the preset third correlation deviation change threshold is greater than the preset second correlation deviation change threshold; if the average rate of change of the correlation deviation is greater than the preset third correlation deviation change threshold, determine that the control information of the grinding mill is to increase the amount of slurry dispersant additive added to the slurry based on the preset second interval time and the preset second adjustment step size; if the average rate of change of the correlation deviation is less than or equal to the preset third correlation deviation change threshold, determine that the control information of the grinding mill is to increase the moisture content in the slurry based on the preset third interval time and the preset third adjustment step size.

[0093] Specifically, after determining that the grinding abnormality in the mill is caused by the formation of a material coating inside the mill, it is necessary to further assess the severity or development trend of this coating problem in order to take more precise control measures. The correlation deviation refers to the difference between the normal grinding correlation between the normal feed slurry concentration and the normal output slurry density, and the current grinding correlation between the current feed slurry concentration and the current output slurry density. It reflects the change in the correlation between the feed slurry concentration and the output slurry density during the grinding process. When a material coating forms inside the mill, this correlation may change significantly, causing fluctuations in the correlation deviation. By calculating the average rate of change of the correlation deviation, the speed or severity of material coating formation can be assessed. A preset third correlation deviation change threshold is a key criterion; its value is greater than a preset second correlation deviation change threshold, used to distinguish different severity levels of the material coating problem.

[0094] When the average rate of change of the correlation deviation exceeds the preset third correlation deviation threshold, it indicates that the material coating problem is severe or rapidly deteriorating. At this point, the mill control information is determined to increase the amount of slurry dispersant additive added to the slurry based on a preset second interval duration and a preset second adjustment step size. The slurry dispersant additive effectively improves the rheological properties of the slurry and reduces its viscosity, thereby inhibiting material adhesion to the mill inner wall or grinding media and promoting the peeling off of existing coatings. The preset second interval duration and preset second adjustment step size are used to control the frequency and amount of additive addition each time, achieving smooth and effective adjustment.

[0095] Furthermore, when the average rate of change of the correlation deviation is less than or equal to the preset third correlation deviation change threshold, it indicates that the material coating problem is relatively less severe or in its early stages. In this case, the control information for the grinding mill is determined to increase the moisture content in the slurry based on a preset third interval duration and a preset third adjustment step size. Increasing the moisture content in the slurry can reduce the slurry concentration, improve the slurry's fluidity, thereby reducing material adhesion and helping to alleviate or prevent the formation of material coatings. The preset third interval duration and preset third adjustment step size are also used to control the frequency and amount of moisture increase to avoid excessive impact on the grinding process.

[0096] This application's solution effectively addresses the problems of single or imprecise control measures that may exist in traditional solutions by conducting a detailed assessment of the degree of grinding anomalies caused by the formation of a material coating inside the grinding mill and adopting differentiated control strategies accordingly. Specifically, when a material coating forms inside the mill, the rheological properties of the slurry change, leading to a decrease in the correlation between the slurry concentration entering the mill and the density exiting the mill, and consequently, an increase in the deviation of the correlation. By monitoring the average rate of change of the correlation deviation, the speed and severity of the material coating formation can be reflected in real time.

[0097] When the rate of change exceeds the preset threshold for the third correlation deviation, it indicates a more urgent coating problem. In this case, increasing the amount of slurry dispersant can rapidly improve slurry dispersibility, directly affecting the coating formation mechanism, accelerating coating peeling, and thus quickly restoring grinding efficiency. Conversely, when the rate of change does not reach this threshold, it indicates a relatively mild coating problem. In this case, increasing the water content in the slurry can gently reduce the slurry concentration, improve fluidity, inhibit further coating formation from the source, avoid unnecessary consumption of chemical additives, and achieve more economical and precise control.

[0098] This application also discloses an automated control system for a grinding mill manufacturing process, comprising: an acquisition device and a processing device; the acquisition device is used to acquire multiple pieces of first information during normal operation of the grinding mill; the multiple pieces of first information include the normal unit power consumption of the grinding mill's drive motor, the normal feed slurry concentration, the normal output slurry density corresponding to the normal feed slurry concentration, the normal frequency spectrum of the drive motor's power signal, and the normal response lag time, wherein the response lag time is the duration between a first moment and a second moment, the first moment being the moment when the drive motor's power changes, and the second moment being the moment after the first moment when the output slurry density changes; the acquisition device is used to acquire grinding mill... The mill currently has multiple second pieces of information; these include the current frequency spectrum of the drive motor's power signal, the current power of the drive motor, the current feed slurry flow rate, the current feed slurry concentration, the current output slurry density, and the current response lag time; a processing device is used to analyze the deviation between the current operating condition and the normal operating condition of the mill based on the multiple first and second pieces of information, determine whether there is a grinding abnormality in the mill based on the deviation, and determine the cause of the grinding abnormality when there is a grinding abnormality; the cause of the grinding abnormality is the formation of a material coating inside the mill or wear of the grinding media; the processing device is used to determine the control information of the mill based on the cause of the grinding abnormality.

[0099] It is important to emphasize that the acquisition device can be implemented in various ways. For example, the acquisition device may include a series of physical sensors, such as power sensors, flow meters, concentration meters, and density meters. These sensors are directly installed on the grinding mill and its related pipelines to collect analog or digital signals in real time, such as the power of the drive motor, the flow rate of the feed slurry, the concentration of the feed slurry, and the density of the output slurry. In addition, the acquisition device may also include a data acquisition module, which is responsible for the digital conversion, preprocessing, and transmission of signals from various sensors.

[0100] It is important to emphasize that the processing device may be implemented in a manner that includes one or more processors (such as a central processing unit (CPU), a microcontroller (MCU), or a dedicated digital signal processor (DSP), as well as memory connected to the processors. The memory may store computer program instructions for performing the aforementioned analysis, judgment, and control information determination functions.

[0101] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. An automated control method for the manufacturing process of a grinding mill, characterized in that, Includes the following steps: Acquire multiple pieces of first information during normal operation of the grinding mill; these pieces of first information include the normal unit power consumption of the grinding mill's drive motor, the normal feed slurry concentration, the normal output slurry density corresponding to the normal feed slurry concentration, the normal frequency spectrum of the drive motor's power signal, and the normal response lag time. The response lag time is the time between a first moment and a second moment. The first moment is the moment when the drive motor's power changes, and the second moment is the moment after the first moment when the output slurry density changes. Acquire multiple pieces of secondary information about the grinding mill; these include the current frequency spectrum of the power signal of the drive motor, the current power of the drive motor, the current feed slurry flow rate, the current feed slurry concentration, the current output slurry density, and the current response lag time. Based on multiple primary and secondary information analyses, the degree of deviation between the current operating condition and the normal operating condition of the grinding mill is determined. Based on the degree of deviation, it is determined whether there is a grinding abnormality in the grinding mill. If there is a grinding abnormality in the grinding mill, the cause of the grinding abnormality is determined. The abnormal grinding is caused by the formation of a material coating inside the mill or wear of the grinding media; Determine the control information of the grinding mill based on the cause of the grinding abnormality.

2. The automated control method for the manufacturing process of a grinding mill according to claim 1, characterized in that, Based on multiple pieces of primary and secondary information, the deviation between the current operating condition and the normal operating condition of the grinding mill is analyzed. Based on the degree of deviation, it is determined whether there is a grinding abnormality in the grinding mill. If a grinding abnormality is found, the cause of the abnormality is determined, including: The ratio of the first value to the normal response lag time is used as the response time deviation; the first value is the difference between the current response lag time and the normal response lag time. The current unit energy consumption of the grinding mill is determined based on the current power, the current feed slurry flow rate, and the current output slurry density. The ratio of the second value to the normal unit energy consumption is used as the energy deviation; the second value is the difference between the current unit energy consumption and the normal unit energy consumption. The sum of energy in the preset high-frequency range of the normal frequency spectrum of the power signal of the drive motor is taken as the normal energy sum, and the sum of energy in the preset high-frequency range of the current frequency spectrum of the power signal of the drive motor is taken as the current energy sum. The ratio of the third value to the normal total energy is used as the energy deviation; the third value is the difference between the current total energy and the normal total energy. The correlation deviation is determined based on the normal feed slurry concentration, the normal output slurry density corresponding to the normal feed slurry concentration, the current feed slurry concentration, and the current output slurry density. Based on the deviation of response time, electrical energy, correlation, and energy, it is determined whether there is a grinding abnormality in the grinding mill, and when a grinding abnormality is found, the cause of the grinding abnormality is determined.

3. The automated control method for the manufacturing process of a grinding mill according to claim 2, characterized in that, The current unit energy consumption of the grinding mill is determined based on the current power, current feed slurry flow rate, and current output slurry density, including: The product of the current feed slurry flow rate and the current output slurry density is used as the fourth value; The ratio of the current power to the fourth value is taken as the current unit power consumption of the grinding mill.

4. The automated control method for the manufacturing process of a grinding mill according to claim 2, characterized in that, The correlation deviation is determined based on the normal feed slurry concentration, the corresponding normal output slurry density, the current feed slurry concentration, and the current output slurry density, including: The ratio of the time derivative of the normal feed slurry concentration to the time derivative of the normal output slurry density is used as the normal grinding correlation. The ratio of the time derivative of the current feed slurry concentration to the time derivative of the current output slurry density is used as the current grinding correlation. The difference between the current grinding correlation and the normal grinding correlation is used as the correlation deviation.

5. The automated control method for the manufacturing process of a grinding mill according to claim 2, characterized in that, Based on the deviations in response time, electrical energy, correlation, and energy, determine whether the grinding mill exhibits grinding abnormalities, and if so, determine the causes of these abnormalities, including: Determine whether the power deviation continues to increase within a preset time period, and whether the average rate of change of the power deviation is greater than a preset first power deviation change threshold. Determine whether the response duration deviation continues to increase within a preset time period, and whether the average rate of change of the response duration deviation is greater than a preset first response duration deviation change threshold. Determine whether the energy deviation continues to increase within a preset time period, and whether the average rate of change of the energy deviation is greater than a preset energy deviation change threshold. Determine whether the correlation deviation continues to decrease within a preset time period, and whether the average rate of change of the correlation deviation is greater than a preset first correlation deviation change threshold. If both are true, it is determined that the grinding mill has a grinding abnormality; otherwise, it is determined that the grinding mill does not have a grinding abnormality. When a grinding mill has a grinding abnormality, determine the cause of the grinding abnormality.

6. The automated control method for the manufacturing process of a grinding mill according to claim 5, characterized in that, When a grinding mill exhibits grinding abnormalities, the cause of the grinding abnormality should be determined, including: Determine whether the average rate of change of correlation deviation within a preset time period is less than a preset second correlation deviation change threshold; the preset second correlation deviation change threshold is greater than a preset first correlation deviation change threshold. If so, the abnormal grinding in the mill is determined to be caused by wear of the grinding media.

7. The automated control method for the manufacturing process of a grinding mill according to claim 5, characterized in that, When a grinding mill exhibits grinding abnormalities, the cause of the grinding abnormality should be determined, including: Determine whether the average rate of change of the response duration deviation is greater than the preset second response duration deviation change threshold; the preset second response duration deviation change threshold is greater than the preset first response duration deviation change threshold; If so, the abnormal grinding in the mill is determined to be caused by a material coating forming inside the mill.

8. The automated control method for the manufacturing process of a grinding mill according to claim 5, characterized in that, The control information of the grinding mill is determined based on the cause of the grinding abnormality, including: Determine whether the grinding abnormality of the grinding mill is caused by wear of the grinding media; When the grinding abnormality of the grinding mill is caused by wear of the grinding media, it is determined whether the average rate of change of the electrical energy deviation is greater than the preset second electrical energy deviation change threshold; the preset second electrical energy deviation change threshold is greater than the preset first electrical energy deviation change threshold. When the average rate of change of electrical energy deviation is less than or equal to the preset second electrical energy deviation change threshold, the control information of the grinding mill is determined to be to reduce the feed slurry flow rate of the grinding mill based on the preset first interval duration and the preset first adjustment step size. When the average rate of change of electrical energy deviation exceeds the preset second electrical energy deviation threshold, the control information of the grinding mill is determined to be to notify maintenance personnel to replace the new grinding media.

9. The automated control method for the manufacturing process of a grinding mill according to claim 6, characterized in that, The control information of the grinding mill is determined based on the cause of the grinding abnormality, including: Determine whether the grinding abnormality of the grinding mill is caused by the formation of a material coating inside the mill; When the grinding abnormality in the grinding mill is caused by the formation of a material coating inside the mill, it is determined whether the average rate of change of the correlation deviation is greater than the preset third correlation deviation change threshold; the preset third correlation deviation change threshold is greater than the preset second correlation deviation change threshold. When the average rate of change of correlation deviation is greater than the preset third correlation deviation change threshold, the control information of the grinding mill is determined to be to increase the amount of slurry dispersing additive added to the slurry based on the preset second interval time and the preset second adjustment step size. When the average rate of change of correlation deviation is less than or equal to the preset third correlation deviation change threshold, the control information of the grinding mill is determined to be to increase the moisture content in the slurry based on the preset third interval duration and the preset third adjustment step size.

10. An automated control system for the manufacturing process of a grinding mill, characterized in that, include: Acquisition device and processing device; Acquisition device, used to acquire multiple first pieces of information about the grinding mill during normal operation; The first pieces of information include the normal unit power consumption of the mill's drive motor, the normal feed slurry concentration, the normal output slurry density corresponding to the normal feed slurry concentration, the normal frequency spectrum of the drive motor's power signal, and the normal response lag time. The response lag time is the time between the first moment and the second moment. The first moment is the moment when the power of the drive motor changes, and the second moment is the moment after the first moment when the output slurry density changes. The acquisition device is used to acquire multiple pieces of second information about the grinding mill at present; the multiple pieces of second information include the current frequency spectrum of the power signal of the drive motor, the current power of the drive motor, the current feed slurry flow rate, the current feed slurry concentration, the current output slurry density, and the current response lag time. The processing device is used to analyze the deviation between the current operating condition and the normal operating condition of the grinding mill based on multiple first information and multiple second information, determine whether there is a grinding abnormality in the grinding mill based on the deviation, and determine the cause of the grinding abnormality when there is a grinding abnormality in the grinding mill. The abnormal grinding is caused by the formation of a material coating inside the mill or wear of the grinding media; The processing device is used to determine the control information of the grinding mill based on the cause of the grinding abnormality.

Images