Alumina ball mill monitoring method and system

Abstract

This invention discloses a monitoring method and system for alumina ball mills, belonging to the field of alumina production technology. The method includes the following steps: 1. Acquiring historical data of the ball mill; 2. Obtaining a calculation formula for the unit wear value ΔR of steel balls by training on the historical data; 3. Calculating the unit wear value ΔR of steel balls of various sizes; 4. Calculating the particle size R′ of steel balls of various sizes after wear on the same day; 5. Calculating the volume V′ of steel balls of various sizes after wear on the same day; 6. Calculating the filling rate F of the ball mill after wear on the same day; 7. Calculating the corresponding addition quantity of steel balls of various sizes using the filling rate F obtained in step 6 and the set steel ball ratio. The system includes a data acquisition module, a data processing module, and a data display module. This invention solves the problem of existing technologies requiring manual monitoring of the steel ball condition in ball mills and the formulation of ball addition plans, effectively improving the grinding quality and efficiency of ball mills and reducing energy consumption.

Description

Technical Field

[0001] This invention belongs to the field of alumina production technology, specifically relating to a monitoring method and system for alumina ball mills. Background Technology

[0002] Alumina production is an indispensable part of aluminum smelting, and ball mills are the main industrial equipment in the raw material processing of alumina production. Through the impact and collision of steel balls, bauxite is crushed and ground into relatively uniform fine particles, providing qualified raw materials for subsequent processes and ensuring product quality. The particle size and uniformity of the ore during grinding can be controlled by adjusting equipment parameters and controlling the amount of steel balls of each particle size, as well as the mill filling rate. The quantity and particle size of the added steel balls directly affect the grinding effect and energy consumption. Currently, alumina companies typically rely on manual monitoring of the steel balls and experience to formulate ball-addition plans. However, this method is susceptible to the limitations of experienced technicians, leading to inconsistent grinding results. Furthermore, an unreasonable distribution of steel ball quantity and particle size increases energy consumption. Therefore, it is necessary to propose an automated monitoring method or system to replace manual monitoring, thereby improving alumina production quality and reducing energy consumption. Summary of the Invention

[0003] The purpose of this invention is to provide a monitoring method and system for alumina ball mills, which can dynamically monitor the wear of steel balls of various sizes in the alumina ball mill and provide real-time data on the wear, weight, particle size distribution, and ball addition amount of each size of steel ball in the ball mill. This solves the problem of existing technologies requiring manual monitoring of the steel ball condition and formulation of ball addition plans, and can effectively improve the grinding quality and efficiency of the ball mill while reducing energy consumption.

[0004] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0005] A method for monitoring an alumina ball mill includes the following steps:

[0006] Step 1: Obtain historical data from the ball mill;

[0007] Step 2: By training on the historical data obtained in Step 1, obtain the formula for calculating the unit wear value ΔR of the steel ball: Where k is the wear coefficient, b1 and b2 are wear constants, and R is the particle size of the steel ball before wear;

[0008] Step 3: Collect the ball size and quantity of each batch of balls added during ball mill operation, and calculate the unit wear value ΔR of steel balls of each size using the calculation formula obtained in Step 2;

[0009] Step 4: Calculate the particle size R′ of each steel ball after wear on the same day based on the unit wear value ΔR calculated in Step 3. t represents the daily grinding output of the ball mill;

[0010] Step 5: Based on the particle size R′ calculated in Step 4, calculate the volume V′ of each particle size steel ball after wear on that day;

[0011] Step 6: Sum the volumes V′ calculated in Step 5 to obtain the total volume V of each size of steel ball after wear on that day. 总 V 总 Divide by the ball mill volume V 机 To obtain the filling rate F of the ball mill after wear on that day;

[0012] Step 7: Calculate the number of steel balls of each particle size to be added based on the filling rate F obtained in Step 6 and the set steel ball ratio.

[0013] Furthermore, the historical data includes: the start-up time of the ball mill, the initial quantity and weight of steel balls of each particle size, the time, quantity, and weight of steel balls added to the ball mill of each particle size, the quantity and weight of discarded steel balls, the daily feed rate of the ball mill, the grinding time, the quantity and weight of steel balls after grinding, and the volume of the ball mill.

[0014] Furthermore, in step 2, the historical data obtained in step 1 is divided into a training set and a test set. A fitting algorithm is used to train the training set to obtain the calculation formula for ΔR. Then, the obtained ΔR calculation formula is tested using the test set.

[0015] Furthermore, in step 5, the volume V of each steel ball before wear on the same day is calculated based on the particle size R of the steel ball before wear, and the weights G and G′ of each steel ball before and after wear on the same day are calculated based on the volumes V and V′ respectively.

[0016] Furthermore, in step 5, based on the particle size R′ calculated in step 4, the steel balls of each particle size after wear on that day are divided into intervals according to the particle size range, and the number and weight percentage of steel balls in different intervals are counted.

[0017] Furthermore, in step 5, a pie chart is used to display the percentage of steel balls in each interval in terms of both quantity and weight.

[0018] Furthermore, in step 5, the distribution of the number and weight of steel balls of specific particle sizes in each interval is displayed using a normal distribution diagram.

[0019] Furthermore, in step 7, a threshold range is set for the fill rate F. When the fill rate F exceeds the threshold range, an early warning is issued.

[0020] The present invention also provides an alumina ball mill monitoring system, including a data acquisition module, a data processing module and a data display module;

[0021] The data acquisition module is used to acquire the operating data of the ball mill and send the operating data to the data processing module; the operating data includes historical data and real-time data.

[0022] The data processing module is used to train on historical data from the ball mill to obtain the calculation formula for the unit wear value ΔR of the steel balls. Then, based on the calculation formula of ΔR and the ball feeding information for each batch during ball mill operation, it calculates the unit wear value ΔR of steel balls of each size. Furthermore, it calculates the particle size R′ and volume V′ of each size of steel ball after wear on that day, and finally calculates the total volume V of each size of steel ball after wear on that day. 总 Divide by the ball mill volume V 机 The filling rate F of the ball mill after wear on that day was obtained; finally, the corresponding addition quantity of steel balls of each particle size was calculated by using the calculated filling rate F and the set steel ball ratio.

[0023] The data display module receives the calculation results from the data processing module and converts them into charts for display. Furthermore, when the fill rate F calculated by the data processing module exceeds or falls below a set threshold, it automatically calculates the required steel ball ratio, generates an early warning command, and sends it to the data display module, which then executes the warning operation.

[0024] By adopting the above technical solution, the present invention has the following beneficial effects:

[0025] 1. This invention can dynamically monitor steel balls of various sizes in an alumina ball mill and provide real-time data on wear, weight, particle size distribution, and ball addition amount for each size. This ensures that the ball mill maintains optimal operating conditions and economic efficiency, effectively improving grinding quality and efficiency while reducing energy consumption. It replaces traditional manual monitoring methods and solves the problem of existing technologies requiring manual monitoring of ball conditions and formulation of ball addition plans.

[0026] 2. This invention proposes a scheme that uses artificial intelligence to automatically analyze and determine the wear amount of steel balls in a ball mill and the amount of steel balls of various particle sizes to add. This scheme can optimize the ratio of steel balls and the filling rate of the ball mill to ensure that the grinding effect reaches the best state, the grinding particle size is more uniform and stable, and the raw materials are better for subsequent processes, which is beneficial to the efficiency of subsequent processes and product quality.

[0027] 3. This invention displays data using charts such as pie charts and normal distribution graphs, making it easier for staff to view detailed parameters and wear trends of steel balls of various sizes, ensuring accurate monitoring of the ball mill's operating status. Furthermore, it can automatically issue warnings when the filling rate exceeds or falls below a set threshold, which helps improve the accuracy of ball mill ball feeding. Attached Figure Description

[0028] Figure 1 This is a schematic diagram of the main operation flow of the present invention; Detailed Implementation

[0029] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0030] like Figure 1 As shown, a method for monitoring an alumina ball mill includes steps 1-7.

[0031] Step 1: Obtain historical data of the ball mill; wherein, the historical data includes: ball mill start-up time, initial quantity and weight of steel balls of each particle size, time, quantity and weight of steel balls added for each particle size, quantity and weight of discarded steel balls, daily ore feed rate, grinding time, quantity and weight of steel balls after grinding, and ball mill volume.

[0032] Step 2: By training on the historical data obtained in Step 1, obtain the formula for calculating the unit wear value ΔR of the steel ball: Where k is the wear coefficient, b1 and b2 are wear constants, and R is the particle size of the steel ball before wear.

[0033] In the specific implementation process, the historical data obtained in step 1 can be divided into a training set and a test set. A fitting algorithm is used to train the training set to obtain the calculation formula for ΔR, and then the obtained ΔR calculation formula is tested using the test set. Specifically, the proportion of the training set can be larger. For example, three-quarters of the historical data can be used as the training set, and the remaining quarter as the test set. The least squares method is used to train and fit the wear coefficient k and wear constant b on the training set, and the obtained wear coefficient and wear constant are tested using the test set.

[0034] The unit wear value ΔR refers to the length by which the radius of the steel ball's diameter cross-section decreases for every 1000 tons of ore ground. ΔR = RR(w), where R is the radius of the steel ball before unit wear, and R(w) is the radius of the steel ball after unit wear.

[0035] Step 3: Collect the ball size and quantity of each batch of balls added during ball mill operation, and calculate the unit wear value ΔR of steel balls of each size using the calculation formula obtained in Step 2.

[0036] The wear of the initial ball load is calculated from the start-up time, which refers to the first addition of balls when the ball mill starts up or the re-addition of balls after emptying the ball mill. Information for each batch of balls added is recorded, including the particle size, tonnage of balls added, and the number of balls added each time. The daily unit wear value ΔR of the steel balls for that batch is calculated and analyzed using the formula mentioned above. In practice, a minimum particle size for discarded steel balls can be set. Each time balls are selected, technicians discard steel balls smaller than this set particle size. The system automatically marks records where the worn particle size is smaller than this set particle size as deleted, and discarded steel balls will not be included in subsequent calculations and displays.

[0037] Step 4: Calculate the particle size R′ of each steel ball after wear on the same day based on the unit wear value ΔR calculated in Step 3. t represents the daily grinding volume of the ball mill.

[0038] If steel balls of the same batch and size are assumed to wear down to the same degree under the same grinding load, then it can be assumed that the number of batches of steel balls added will result in the number of different particle sizes in the ball mill. The particle size before and after wear can be calculated based on the unit wear value ΔR and the daily feed rate. The particle size before wear on the current day is the particle size after wear calculated on the previous day. The particle size after wear on the current day = particle size before wear - wear value.

[0039] Step 5: Based on the particle size R′ calculated in Step 4, calculate the volume V′ of each particle size steel ball after wear on that day.

[0040] Based on the particle size R of the steel ball before wear, calculate the volume V of each particle size steel ball before wear on that day, and calculate the weight G and G′ of each particle size steel ball before and after wear on that day based on the volume V and V′ respectively. The calculation formula is: weight = volume × steel ball density.

[0041] Based on the particle size R′ calculated in step 4, the steel balls of each particle size after wear on that day are divided into intervals according to the particle size range, and the number and weight percentage of steel balls in different intervals are counted.

[0042] For example, the particle size after wear on the same day is divided into particle size intervals of 10 particle sizes. The resulting particle size intervals are (60-70], (70-80], (80-90], (90-100], (100-110], (110-120], and (120-130]. ​​The number of particle sizes in each interval is statistically analyzed to obtain the weight and quantity of each interval, and then the results are displayed in a chart.

[0043] Specifically, pie charts display the percentage of steel balls by quantity and weight in each interval, while normal distribution plots show the distribution of the quantity and weight of steel balls of specific sizes in each interval. Clicking on an interval in the chart displays a wear trend graph and detailed table data for that interval over a period of time. Clicking on a particle size in the chart displays a wear trend graph and detailed table data for that particle size over a period of time. The wear trend graph is generated based on the monitoring and prediction of the wear amount of steel balls of each particle size.

[0044] This invention displays data using charts such as pie charts and normal distribution graphs, making it easier for staff to view detailed parameters and wear trends of steel balls of various sizes, thus ensuring accurate monitoring of the ball mill's operating status.

[0045] Step 6: Sum the volumes V′ calculated in Step 5 to obtain the total volume V of each size of steel ball after wear on that day. 总 V 总 Divide by the ball mill volume V 机 The filling rate F of the ball mill after wear on that day is obtained. The filling rate F can be displayed in a chart for easy viewing.

[0046] Step 7: Using the filling rate F obtained in Step 6 and the set steel ball ratio, calculate the corresponding addition quantity of steel balls of each particle size. Furthermore, a threshold range is set for the filling rate F. When the filling rate F exceeds the threshold range, the required steel ball ratio is automatically calculated, and an early warning is issued. This threshold range is set according to the specific parameters of each ball mill model. When the calculated filling rate exceeds the set threshold range, it can be displayed and an early warning is issued using a pie chart and different colors.

[0047] For example, if the threshold range is set to [23%, 27%], when the calculated fill rate exceeds the threshold range, an alert will be issued in the warning box, and the fill rate will be indicated by a bright color. When the fill rate exceeds the upper limit, the fill rate will be displayed in red, prompting technicians to reduce the number of balls added; when it is below the lower limit, the fill rate will be displayed in yellow, prompting users to add balls in time.

[0048] The invention will be further illustrated below with specific data:

[0049] 1. The calculation of the volume and weight of the steel ball before and after wear is as follows:

[0050] (1) For example, the least squares method is used to train and fit the training set to obtain a wear coefficient k of 4 and wear constants b1 of 100 and b2 of 0.01;

[0051] (2) Assume that there are steel balls with four particle sizes of φ110, φ100, φ90 and φ80 in the ball mill, with 15,000, 30,000, 30,000 and 30,000 respectively. The unit wear values ​​of each particle size of the steel balls on the first day of this batch are calculated to be 0.02052, 0.02273, 0.02572 and 0.02989 respectively.

[0052] (3) Assuming the daily ore output is 10,000 tons, the wear-off particle sizes are 0.2052, 0.2273, 0.2572, and 0.2989, and the wear-off particle sizes are 109.7948, 99.7727, 89.7428, and 79.7011 mm, respectively.

[0053] (4) The volumes of steel balls of various sizes before wear, calculated using the volume formula, are: 696909.3817, 523598.3333, 381703.185, and 268082.3467 mm. 3 The volumes of the steel balls after wear were 693015.8973, 520035.5227, 378440.0097, and 265088.0072 mm, respectively. 3 The total volume before and after wear is calculated as the number of units multiplied by the volume of a single unit. The total volumes before wear are 10.45, 15.71, 11.45, and 8.04 m³, respectively. 3 The total volumes after wear are: 10.40, 15.60, 11.35, and 7.95 m³, respectively. 3 .

[0054] (5) Assume the density of the steel ball is 7.8 g / mm³. 3 Based on volume calculations, the weights before wear were 5.43, 4.08, 2.98, and 2.09 kg, respectively, and the weights after wear were 5.41, 4.06, 2.95, and 2.07 kg, respectively.

[0055] 2. Calculation of ball mill filling rate

[0056] Based on the above data, assume that the volume of a ball mill is 240m³. 3 The total volume of all steel balls after wear is calculated as follows: 10.40 + 15.60 + 11.35 + 7.95 = 45.3 m. 3 The calculation of 45.3 / 240 yields a mill filling rate of 18.88%, which is lower than the set threshold range of 23%. The filling rate is displayed in yellow, prompting the user to replenish the balls in time.

[0057] 3. The calculation of the number of steel balls to be added is as follows:

[0058] (1) Assuming the ball ratio for each particle size is: φ130:φ120:φ110:φ100:φ90:φ80:φ70:φ60 = 1:1:2:3:3:3:2:1, when the filling rate is lower than the threshold limit, the following formula is used for calculation: (threshold limit * ball mill volume * proportion of a single particle size - current total volume of that particle size) / volume of a single ball for a single particle size, resulting in ball amounts of 3.75, 3.75, -2.90, -4.35, -0.10, 3.30, 7.5, and 3.75 m³ respectively. 3 A negative value indicates that steel balls of that size do not need to be added.

[0059] (2) The output number of balls added for each particle size is as follows: φ130, φ120, φ80, φ70, and φ60 are added with 3.75, 3.75, 3.30, 7.5, and 3.75 μm respectively. 3 The required number of balls are 3000, 3815, 8947, 38439, and 30520 respectively. The number of balls added = total volume of balls added for that particle size / volume of a single steel ball for that particle size.

[0060] The present invention also provides an alumina ball mill monitoring system, including a data acquisition module, a data processing module, and a data display module.

[0061] The data acquisition module is used to acquire the operating data of the ball mill and send the operating data to the data processing module; the operating data includes historical data and real-time data.

[0062] The data processing module is used to train on historical data from the ball mill to obtain the calculation formula for the unit wear value ΔR of the steel balls. Then, based on the calculation formula of ΔR and the ball feeding information for each batch during ball mill operation, it calculates the unit wear value ΔR of steel balls of each size. Furthermore, it calculates the particle size R′ and volume V′ of each size of steel ball after wear on that day, and finally calculates the total volume V of each size of steel ball after wear on that day. 总 Divide by the ball mill volume V 机 The filling rate F of the ball mill after wear on that day was obtained; finally, the addition quantity of steel balls of each particle size was calculated by using the calculated filling rate F and the set steel ball ratio.

[0063] The data display module receives the calculation results from the data processing module and converts them into charts for display. Furthermore, when the fill rate F calculated by the data processing module exceeds or falls below a set threshold, it automatically calculates the required steel ball ratio and generates an early warning command, which is then sent to the data display module. The data display module then executes the early warning operation.

[0064] This invention dynamically monitors steel balls of various sizes within an alumina ball mill, providing real-time data on wear, weight, particle size distribution, and ball addition levels for each size. This ensures the ball mill maintains optimal operating conditions and economic efficiency, effectively improving grinding quality and efficiency while reducing energy consumption. It replaces traditional manual monitoring, solving the problem of requiring manual monitoring of steel balls and formulation of ball addition plans in existing technologies. This invention proposes a scheme that uses artificial intelligence to automatically analyze and provide data on steel ball wear and the addition amount of steel balls of various sizes. This scheme optimizes the steel ball ratio and ball mill filling rate to ensure optimal grinding performance, resulting in more uniform and stable particle size. This provides better raw materials for subsequent processes, improving efficiency and product quality.

[0065] The above description is a detailed description of the preferred embodiments of the present invention. However, the embodiments are not intended to limit the scope of the patent application of the present invention. All equivalent changes or modifications made under the technical spirit of the present invention should fall within the patent scope covered by the present invention.

Claims

1. A method for monitoring an alumina ball mill, characterized in that, Includes the following steps: Step 1: Obtain historical data from the ball mill; Step 2: By training on the historical data obtained in Step 1, obtain the formula for calculating the unit wear value ΔR of the steel ball: Where k is the wear coefficient, b1 and b2 are wear constants, and R is the particle size of the steel ball before wear; the unit wear value ΔR refers to the length of the reduction in radius of the steel ball's diameter section for every 1000 tons of ore ground. Step 3: Collect the ball size and quantity of each batch of balls added during ball mill operation, and calculate the unit wear value ΔR of steel balls of each size using the calculation formula obtained in Step 2; Step 4: Calculate the particle size R′ of each steel ball after wear on the same day based on the unit wear value ΔR calculated in Step 3. t represents the daily grinding output of the ball mill; Step 5: Based on the particle size R′ calculated in Step 4, calculate the volume V′ of each particle size steel ball after wear on that day; Step 6: Sum the volumes V′ calculated in Step 5 to obtain the total volume V of each size of steel ball after wear on that day. 总 V 总 Divide by the ball mill volume V 机 To obtain the filling rate F of the ball mill after wear on that day; Step 7: Calculate the number of steel balls of each particle size to be added based on the filling rate F obtained in Step 6 and the set steel ball ratio.

2. The method for monitoring an alumina ball mill according to claim 1, characterized in that: The historical data includes: the start-up time of the ball mill, the initial quantity and weight of steel balls of each size, the time, quantity, and weight of adding steel balls of each size, the quantity and weight of discarded steel balls, the daily feed rate of the ball mill, the grinding time, the quantity and weight of steel balls after grinding, and the volume of the ball mill.

3. The method for monitoring an alumina ball mill according to claim 1, characterized in that: In step 2, the historical data obtained in step 1 is divided into a training set and a test set. The training set is trained using a fitting algorithm to obtain the calculation formula for ΔR. Then, the obtained ΔR calculation formula is tested using the test set.

4. The method for monitoring an alumina ball mill according to claim 1, characterized in that: In step 5, the volume V of each steel ball before wear is calculated based on the particle size R of the steel ball before wear, and the weights G and G′ of each steel ball before and after wear are calculated based on the volumes V and V′.

5. The method for monitoring an alumina ball mill according to claim 4, characterized in that: In step 5, based on the particle size R′ calculated in step 4, the steel balls of each particle size after wear on that day are divided into intervals according to the particle size range, and the number and weight percentage of steel balls in different intervals are counted.

6. The method for monitoring an alumina ball mill according to claim 5, characterized in that: In step 5, pie charts are used to show the percentage of steel balls in each interval in terms of both quantity and weight.

7. The method for monitoring an alumina ball mill according to claim 6, characterized in that: In step 5, the distribution of the number and weight of steel balls of specific particle sizes in each interval is shown by using a normal distribution plot.

8. The method for monitoring an alumina ball mill according to claim 1, characterized in that: In step 7, a threshold range is set for the fill rate F. When the fill rate F exceeds the threshold range, an early warning is issued.

9. A monitoring system for an alumina ball mill, characterized in that, It includes a data acquisition module, a data processing module, and a data display module; The data acquisition module is used to acquire the operating data of the ball mill and send the operating data to the data processing module; the operating data includes historical data and real-time data. The data processing module is used to train historical data of the ball mill based on the alumina ball mill monitoring method as described in any one of claims 1-8, obtain the calculation formula for the unit wear value ΔR of the steel balls, and then calculate the unit wear value ΔR of steel balls of each particle size according to the calculation formula of ΔR and the ball feeding information of each batch during the operation of the ball mill. Furthermore, it calculates the particle size R′ and volume V′ of each particle size after wear on that day, and then calculates the total volume V of each particle size after wear on that day. 总 Divide by the ball mill volume V 机 The filling rate F of the ball mill after wear on that day was obtained; finally, the addition quantity of steel balls of each particle size was calculated by using the calculated filling rate F and the set steel ball ratio. The data display module receives the calculation results from the data processing module and converts them into charts for display.

10. The alumina ball mill monitoring system according to claim 9, characterized in that: When the fill rate F calculated by the data processing module exceeds or falls below the set threshold range, the required steel ball ratio is automatically calculated, an early warning command is generated and sent to the data display module, and the data display module executes the early warning operation.

Images