Method for monitoring abnormal conditions of wet return rate in a balling process
By collecting data from the screening system and establishing an abnormal operation model, the wet return rate of the pelletizing process can be monitored in real time, which solves the problem of discontinuous changes in wet return rate and improves the stability of green pellet quality and the quality of finished pellets.
Patent Information
- Application Number
- CN202411509564.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-28
- Publication Date
- 2026-08-25
- Estimated Expiration
- 2044-10-28
AI Technical Summary
In existing technologies, the wet return rate changes discontinuously during the pelletizing process of ore pellets, resulting in fluctuations in the weight of green pellets that affect the quality of the finished pellets, making it impossible to predict and adjust in advance.
By collecting data from the screening system, an abnormal operation model is established. The wet return rate is analyzed using normal distribution and descriptive statistics. An operation monitoring chart is drawn to monitor and warn of abnormal situations in real time, and the pelletizing process parameters are adjusted in a timely manner.
It enables continuous monitoring and early warning of wet return rate, improves the stability of green pellet quality, reduces green pellet weight fluctuation, and enhances the quality of finished pellets.
Smart Images

Figure CN119464701B_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of steel technology, and in particular relates to a method for monitoring abnormal wet return rate in the pelletizing process. Background Technology
[0002] Currently, the main raw material structure used in blast furnace ironmaking is sintered ore plus pellets. As an important component of blast furnace ironmaking raw materials, pellets have irreplaceable advantages such as uniform particle size and high total iron content. In the pellet production process, iron concentrate is pelletized and screened. Green pellets that meet the particle size requirements enter the roasting process, while those that do not meet the requirements become wet return ore and are returned to the batching and pelletizing process. The proportion of wet return ore in the amount of material entering the pelletizer is the wet return rate. Because the pelletizing process in the pelletizer is mainly monitored manually and is labor-intensive, and the main factors affecting the wet return rate include the pelletizing properties of the incoming material and moisture content, these factors are constantly changing, but manual sampling and monitoring of the pelletizing process is discontinuous. This leads to significant fluctuations in the wet return rate during daily production, resulting in fluctuations in the weight of green pellets entering the roasting process and affecting the quality of the finished pellets. Currently, the main method for monitoring pelletizing efficiency is for operators to periodically screen the green pellets produced by the pelletizing machine each shift to determine their quality and make corresponding adjustments. This monitoring is discontinuous and adjustments are only made when green pellet data exceeds the acceptable range, creating a "monitoring vacuum" between sampling points, making advance prediction and adjustment impossible. To address these issues, this method utilizes the proportion and trend of large and small particle size return ore to determine necessary adjustments, thereby accelerating the reaction speed and strengthening the process control of green pellet quality. Summary of the Invention
[0003] To address the aforementioned technical problems, the present invention aims to provide a method for collecting wet return production data and establishing an abnormal operation model in the pelletizing process of ore pelletizing, thereby providing early warning and judgment on abnormal situations in the continuous operation data of wet return rate, and then giving adjustment measures.
[0004] To solve the above-mentioned technical problems, the present invention adopts the following technical solution:
[0005] This invention provides a method for monitoring abnormal wet return rates during the pelletizing process, comprising the following steps:
[0006] A. Collect the hourly average data of each belt conveyor after screening in the screening system and the total amount of material entering the pelletizer at the same time;
[0007] B. The weight of the returned balls on the receiving belt after the first screen (number: SF6-3, which screens out powder <8mm after the granulator) is divided by the proportion of all materials entering the granulator at the same time. This proportion is defined as the SF6-3 rate, which mainly reflects the powder proportion.
[0008] C. The percentage of returned balls removed by the second SF3 double-layer roller screen divided by all materials entering the pelletizer at the same time is defined as the SF3 rate. It mainly reflects the percentage of particles >16mm and the percentage of particles <8mm that are broken due to insufficient strength after SF6-3 screening.
[0009] D. The total wet return rate is SF6 rate plus SF3 rate;
[0010] E. Collect hourly average data of SF6 rate and SF6-3 rate during the pelletizing process;
[0011] F. Perform descriptive statistics and normality verification on the operational data;
[0012] G. Determine the criteria for judging abnormal distribution based on the distribution pattern of the operating data; if the distribution is normal, use the probability density function of the normal distribution to calculate the values of the two tails with a probability of 5% as the normal operating range; if the distribution is not normal, take the 5th quantile and the 95th quantile as the upper and lower limits of normal operation.
[0013] H. Draw an operation monitoring chart of wet return rate in the pelletizing process based on the judgment criteria determined in step H.
[0014] I. Make corresponding adjustments based on the abnormal situations reported in the graph: SF6 exceeding the upper limit and SF6-3 exceeding the upper limit indicates that the green pellet size is too small and there is too much powder; if the SF6 rate is within the normal range but shows an increasing trend for more than 5 hours, it indicates that the wet reversion rate is constantly increasing. It is necessary to judge whether the green pellet size is too large or too small by checking the SF6-3 rate and SF3 rate at the corresponding time.
[0015] If the SF6-3 ratio is continuously increasing, it indicates that the green pellet size is gradually decreasing and the proportion of green pellets <8mm is increasing; if the SF3 ratio is gradually increasing and the SF6-3 ratio does not change significantly or gradually decreases, it indicates that the overall green pellet size is increasing, and water reduction is required in the pelletizing machine.
[0016] If the SF3 ratio is gradually increasing and the SF6-3 ratio is also increasing, it indicates that the overall green pellet size is gradually decreasing, and water needs to be added to the pelletizing machine; if the SF6 ratio is below the lower limit, it indicates that the pelletizing effect is good and no adjustment is needed.
[0017] Furthermore, in step E, the collection time is 80-120 hours.
[0018] Furthermore, in step E, 100 hours are collected.
[0019] Furthermore, abnormal production data during start-up and shutdown are not included in the statistics.
[0020] Furthermore, this method can take timely measures to stabilize the yield of raw pellets in case of abnormal situations.
[0021] Compared with the prior art, the beneficial technical effects of the present invention are as follows:
[0022] This invention collects operational data on the wet return rate during normal pelletizing processes to determine the normal operating range of the wet return rate. In daily production, by creating scatter plots and combining this data with the operating ranges of the SF6 and SF6-3 rates, it is possible to determine whether the pelletizing process is operating normally and identify any major problems. This allows for timely measures to stabilize green pellet production in response to abnormal situations. Attached Figure Description
[0023] The present invention will be further described below with reference to the accompanying drawings.
[0024] Figure 1 This is a normal distribution graph;
[0025] Figure 2 A scatter plot of SF6 ratio;
[0026] Figure 3 This is a scatter plot of the SF6-3 rate. Detailed Implementation
[0027] A method for monitoring abnormal wet return rates during the pelletizing process includes:
[0028] A. Descriptive statistics and Anderson-darling normality tests were performed on the SF6 rate after eliminating the effects of start-up and shutdown. The p-value was 0.176 > 0.05. The descriptive statistics and the p-value of the normality test indicate that the SF6 rate follows a normal distribution with a mean of 0.30153 and a standard deviation of 0.04284.
[0029] B. Based on the probability density function of the normal distribution, the SF6 rate under normal conditions (90%) is calculated to be between 0.2311 (23.11%) and 0.3720 (37.20%). Figure 1 As shown in the figure, the operating range is a symmetrical distribution area with the mean as the axis of symmetry. The above area (23.11%-37.20%) is defined as the normal operating range of SF6 rate.
[0030] C. Descriptive statistics and Anderson-darling normality tests were performed on the SF6-3 rate after eliminating the effects of start-up and shutdown. The p-value was 0.308 > 0.05. The descriptive statistics and the p-value of the normality test indicate that SF6-3 follows a normal distribution with a mean of 0.066417 and a standard deviation of 0.030236.
[0031] D. Based on the probability density function of the normal distribution, the SF6-3 rate under normal conditions is distributed between 0.01668 and 0.1162 at 90%, and the operating range is a symmetrical distribution area with the mean. The above area is defined as the normal operating range of the SF6-3 rate.
[0032] E. Plot the SF6 rate and SF6-3 rate during normal production operation on a graph showing the normal operating limits.
[0033] F. Abnormal Warning:
[0034] from Figure 2 and Figure 3 The two scatter plots show that:
[0035] From 8:00 AM to 1:00 PM, the SF6 rate continuously increased for 5 consecutive hours, and the corresponding SF6-3 rate also continuously increased. This indicates that although the overall wet return rate is within the normal range, it has been rising continuously for 5 hours, mainly due to the increase in the SF6-3 rate of particles <8mm. This suggests that the raw material moisture is continuously drying out, resulting in smaller pellet size, requiring the addition of water.
[0036] As can be seen from the running time at 16:00, the SF6 rate exceeded the upper limit of the 90% operating range. However, the SF6-3 rate of <8mm was within the range between the average and the upper limit, indicating that both SF6-3 and SF3 were relatively high. This was mainly due to the large amount of <8mm powder, which resulted in a large amount of SF6-3 being returned to the ore. There was also a large amount of <8mm SF3 being screened out. We need to pay attention to the moisture content of the raw materials and the strength of the green pellets.
[0037] The SF6-3 rate at 20 points exceeds the control limit and the total wet return rate of SF6 is close to the limit, indicating that there are too many small-diameter green pellets. We need to pay attention to the moisture content and the thickness of the bottom of the pelletizer. It may be that the moisture content is too low or the bottom of the pelletizer collapses, resulting in more pellets with a diameter of <8mm exiting the pelletizer. Water needs to be added to the pelletizer's pellet tray.
[0038] The fact that the SF6-3 rate at point 26 exceeds the lower control limit indicates that fewer small-diameter green pellets were removed by screening. It is possible that the overall green pellets are too large. However, considering that the total wet return rate (SF6 rate) at point 26 is within the normal range, the possibility of excessively large green pellets is ruled out. This indicates that the pelletizing situation is good and no adjustment is needed.
[0039] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made by those skilled in the art to the technical solutions of the present invention without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.
Claims
1. A method for monitoring abnormal wet return rate during the pelletizing process, characterized in that, The steps include the following: A. Collect the hourly average data of each belt conveyor after screening in the screening system and the total amount of material entering the pelletizer at the same time; B. The percentage obtained by dividing the weight of returned balls on the receiving belt after the SF6-3 sieve in the pelletizer by the total amount of material entering the pelletizer at the same time is defined as the SF6-3 rate, which mainly reflects the proportion of powder with a particle size of <8mm. C. The percentage of returned balls removed by the second SF3 double-layer roller screen divided by all materials entering the pelletizer at the same time is defined as the SF3 rate. It mainly reflects the percentage of particles >16mm and the percentage of particles <8mm that are broken due to insufficient strength after SF6-3 screening. D. The total wet return rate is SF6 rate plus SF3 rate; E. Collect hourly average data of SF6 rate and SF6-3 rate during the pelletizing process; F. Perform descriptive statistics and normality verification on the operational data; G. Determine the criteria for judging abnormal distribution based on the distribution pattern of the operating data; if the distribution is normal, use the probability density function of the normal distribution to calculate the values of the two tails with a probability of 5% as the normal operating range; if the distribution is not normal, take the 5th quantile and the 95th quantile as the upper and lower limits of normal operation. H. Draw an operation monitoring chart of wet return rate in the pelletizing process based on the judgment criteria determined in step G; I. Make corresponding adjustments based on the abnormal situations reported in the graph: SF6 exceeding the upper limit and SF6-3 exceeding the upper limit indicates that the green pellet size is too small and there is too much powder; if the SF6 rate is within the normal range but shows an increasing trend for more than 5 hours, it indicates that the wet reversion rate is constantly increasing. It is necessary to judge whether the green pellet size is too large or too small by checking the SF6-3 rate and SF3 rate at the corresponding time. If the SF6-3 ratio is continuously increasing, it indicates that the green pellet size is gradually decreasing and the proportion of green pellets <8mm is increasing; if the SF3 ratio is gradually increasing and the SF6-3 ratio does not change significantly or gradually decreases, it indicates that the overall green pellet size is increasing, and water reduction is required in the pelletizing machine. If the SF3 ratio is gradually increasing and the SF6-3 ratio is also increasing, it indicates that the overall green pellet size is gradually decreasing, and water needs to be added to the pelletizing machine; if the SF6 ratio is below the lower limit, it indicates that the pelletizing effect is good and no adjustment is needed.
2. The method for monitoring abnormal wet return rate in the pelletizing process according to claim 1, characterized in that, In step E, the collection time is 80-120 hours.
3. The method for monitoring abnormal wet return rate in the pelletizing process according to claim 1, characterized in that, In step E, 100 hours are collected.
4. The method for monitoring abnormal wet return rate in the pelletizing process according to claim 1, characterized in that, Abnormal production data during start-up and shutdown are not included in the statistics.
Citation Information
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