A method for optimizing the performance of a ring roller mill based on an oscillating mill

Abstract

The application discloses a kind of ring roller grinding performance optimization method based on pendulum mill, belongs to pendulum mill optimization technical field.In order to the problem that the pendulum mill designed at present fails to guarantee to have higher finished product rate in short time, the pendulum mill to be optimized is first carried out primary grinding simulation test and total grinding simulation test, according to grinding times and corresponding finished product rate, it is determined that optimization direction is to improve primary finished product rate or multiple finished product rate, further in combination with the relationship between the wear degree of grinding roller and grinding ring and clearance, the shape of grinding roller is optimized;Then single factor simulation analysis is carried out to determine the optimization value of the single factor to be fixed, and the single factor simulation analysis includes shovel angle single factor simulation analysis, feed amount single factor simulation analysis and spindle speed single factor simulation analysis;With the optimization value of the single factor to be fixed as fixed factor, the other two factors as variables, based on response surface analysis, the optimization results of the other two factors are determined with finished product rate as target.

Description

Technical Field

[0001] This invention belongs to the field of pendulum mill optimization technology, and relates to an optimization method for pendulum mills. Background Technology

[0002] The main body of a pendulum mill is the primary mechanical structure used for material grinding. The main body of a pendulum mill mainly includes multiple components such as a perforated frame (1), feed inlet (2), central shaft (3), air inlet (4), suspension cover (5), grinding ring (6), grinding rollers (7), scraper (8), and base (9). Figure 1 As shown. During operation, the transmission system is responsible for transmitting energy to the central shaft, which in turn drives the pendulum frame to rotate. As the pendulum frame rotates, the grinding roller device moves around the central shaft and swings outward under the action of centrifugal force. This movement allows the grinding roller to apply pressure to the grinding ring, thereby generating a grinding effect between the grinding roller and the grinding ring. This is also the main working area for material processing in the pendulum mill. The material falling from the feed inlet first enters the grinding roller and grinding ring area. After being captured by the grinding roller, it undergoes the first crushing and grinding. The qualified powder produced is blown to the classification zone by the air field of the main air duct; while the material that does not reach the classification fineness falls downward into the shovel area and is thrown back to the grinding zone by the shovel rotating with the central shaft for secondary or multiple grinding to finally form the finished product.

[0003] In actual operation, the grinding rollers and grinding rings are initially in a zero-gap state when installed, and this gap gradually disappears as wear occurs during production. Once a stable working state is reached, the material thrown by the scraper forms a dynamic material layer between the grinding rollers and grinding rings. This dynamic layer reduces equipment vibration and has a beneficial effect on grinding. The particles in the material layer contact each other and transmit grinding force through friction, continuously reducing the material to achieve the final gradation size. Furthermore, as the wear of the grinding rollers and grinding rings intensifies, a gradually increasing gap forms between them until they reach their wear limit and are replaced.

[0004] Existing pendulum mills are all designed and developed using a forward-engineering approach. In this process, the basic dimensions are determined based on the equipment's operating conditions and environmental requirements. Further design is then carried out based on these basic dimensions, including the actual components and accessories. Therefore, existing solutions are not designed with yield as the goal. Instead, the yield is adjusted by changing the grinding time to meet the actual yield requirements. As a result, the currently designed pendulum mills cannot guarantee a high yield in a short period of time. The performance of the ring roller mill lacks standardized and detailed optimization methods, and a standardized and systematic optimization process has not been formed. Summary of the Invention

[0005] This invention addresses the problem that current pendulum mill designs lack standardized and systematically optimized methods for handling the grinding performance of ring rollers, thus failing to guarantee a high yield rate in a short period of time.

[0006] A method for optimizing the performance of ring roller mills based on pendulum mills includes the following steps:

[0007] For the pendulum mill to be optimized, firstly, Rocky DEM was used to conduct single-stage grinding simulation tests and total grinding simulation tests. Based on the results of the single-stage grinding simulation, the yield of the first-stage product corresponding to each gap was obtained. Based on the results of the total grinding simulation, the yield of the total grinding product corresponding to each gap was obtained. The gap refers to the gap between the grinding roller and the grinding ring. By comparing the yield of the first-stage grinding simulation results and the yield of the total grinding simulation results for each gap, with the aim of improving efficiency and reducing energy consumption, the optimization direction was determined based on the number of grinding cycles and the corresponding yield: whether to improve the yield of the first-stage product or the yield of multiple cycles. Furthermore, the shape of the grinding roller was optimized by combining the relationship between the wear degree of the grinding roller and the grinding ring and the gap.

[0008] Then, a single-factor simulation analysis based on CFD-DEM is performed, including single-factor simulation analysis of blade angle, single-factor simulation analysis of feed rate, and single-factor simulation analysis of spindle speed. Based on the results of the single-factor analysis, the proposed fixed single factor and its optimized value are determined. The optimized value of the proposed fixed single factor is used as the fixed factor, and the other two factors are used as variables. The response surface of the CFD-DEM simulation is analyzed, and the optimization results of the other two factors are determined with the yield as the objective.

[0009] Furthermore, in determining whether to improve the yield of a single mill or the yield of multiple mills based on the number of milling cycles and the corresponding yield, the optimization direction is to improve the yield of a single mill.

[0010] Furthermore, when optimizing the shape of the grinding roller by considering the relationship between the wear degree of the grinding roller and the grinding ring and the gap, the shape of the grinding roller is optimized to a tire-shaped grinding roller or a frustum-shaped grinding roller.

[0011] Furthermore, the grinding rollers and grinding rings are made of high-manganese steel.

[0012] Furthermore, based on the results of the single-factor analysis, the proposed fixed single factor is the blade angle.

[0013] Furthermore, the optimal value for the single factor to be fixed as the blade angle is 35°.

[0014] Furthermore, based on the response surface analysis of CFD-DEM simulation, the optimization results for the other two factors with the yield as the objective were determined to be a feed rate of 12t / h and a spindle speed of 74.5rpm.

[0015] Beneficial effects:

[0016] This invention first performs single-factor analysis, and based on the characteristics of single-factor analysis, determines a fixed single factor, and uses two other factors as variables. The analysis is performed based on the response surface of CFD-DEM simulation, and the optimization results of the other two factors are determined with the yield as the target. Therefore, this invention can optimize the process of improving the yield of the pendulum mill in the shortest time, which is conducive to improving the quality of the optimization of the ring roller mill performance of the whole machine. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the main structure of a certain type of swing mill.

[0018] Figure 2 This is a diagram showing the wear limit state of the grinding roller.

[0019] Figure 3 This is a graph showing the collision frequency between particles and the grinding roller.

[0020] Figure 4 This is the energy spectrum of the cumulative impact power of the material and the grinding ring.

[0021] Figure 5 This is a graph showing the change in the total mass of the particles.

[0022] Figure 6 This is a graph showing the particle size distribution.

[0023] Figure 7 This is the energy spectrum of the cumulative impact power of the material and the grinding ring.

[0024] Figure 8 This is a graph showing the change in the total mass of particles.

[0025] Figure 9 This is a graph showing the particle size distribution.

[0026] Figure 10 This is a wear contour map of the component.

[0027] Figure 11 This is a graph showing the stress curve of the grinding roller.

[0028] Figure 12 This is a graph showing the wear of the grinding rollers.

[0029] Figure 13 Wear contour maps of grinding rollers of different shapes.

[0030] Figure 14 This represents the particle size distribution of grinding rollers with different shapes.

[0031] Figure 15 This is a graph showing the wear of the grinding rollers.

[0032] Figure 16 This is a schematic diagram of the blade angle.

[0033] Figure 17 This is a distribution diagram of the proportion of each particle size range after 8 seconds of single-factor simulation of the shovel angle.

[0034] Figure 18 This is a graph showing the wear of the grinding rollers.

[0035] Figure 19 Simulation diagrams of particle trajectories under different blade angles.

[0036] Figure 20 The images show the wear state of the grinding roller before and after simulation at different blade angles.

[0037] Figure 21 This is a graph showing the distribution percentage of each particle size range after 8 seconds of single-factor simulation of the feed rate.

[0038] Figure 22 This is the energy spectrum of the cumulative impact power of the material and the grinding ring.

[0039] Figure 23 The distribution percentage of each particle size range after 8 seconds of single-factor simulation of spindle speed.

[0040] Figure 24 This is a diagram showing the impact frequency of particles and the grinding ring.

[0041] Figure 25 This is the surface plot of the grinding rate response. Detailed Implementation Specific implementation method one:

[0043] This embodiment is a method for optimizing the performance of ring roller milling based on a pendulum mill, including the following steps:

[0044] Based on the actual operation of the mill, the installed state is that the grinding rollers and grinding rings have zero clearance; when the pendulum mill is operating stably, the material thrown by the scraper forms a dynamic material layer with flow characteristics between the grinding rollers and grinding rings, with a material layer thickness of 3mm, 5mm, and 8mm; the wear limit of the grinding rollers is 25mm. Figure 2 (This represents the wear limit state of the grinding roller). In the simulation, the gaps between the grinding roller and the grinding ring were set to 0, 3, 5, 8, and 25 mm, respectively. The material properties set in the simulation experiment are shown in Table 1.

[0045] Table 1 Material parameters of the simulation model

[0046]

[0047] Simulation analysis was performed using DEM software. In the DEM software, the particle crushing model used was the Ab-T10 model, which incorporated specific impact energy (ep). impThe concept of impact energy refers to the sum of work done by all contact forces acting on a particle at a given moment. Impact energy includes both elastic energy and dissipated energy in the normal direction. Depending on the normal contact model used (which is suitable for simulating non-cohesive and dry granular materials), the dissipated energy is either plastic or viscous. Furthermore, the elastic component of tangential energy transfer is also considered in the calculation. To break the particle, the specific impact energy should be greater than the particle's minimum breaking energy, e. min The minimum breaking energy is as follows:

[0048]

[0049] In the formula, e min,ref The reference minimum specific energy value for this material is set at 5 J / kg for limestone; L ref For reference particle size, Rocky DEM sets it to 25.4 mm by default; L is the particle diameter, set to 25 mm.

[0050] Based on the Rocky DEM, a primary grinding simulation experiment was conducted: material falls into the main unit from the feed inlet, first entering the grinding roller and grinding ring areas where it is captured and crushed, known as primary grinding; subsequently, material that does not meet the fineness standard and uncrushed material falls downward into the shovel area and is thrown by the shovel, undergoing further or multiple grinding processes to finally reach the finished product fineness, known as shovel-throwing grinding. The combined effect of primary grinding and throwing grinding is called total grinding. Through primary grinding, some material reaches the finished product fineness, effectively reducing the energy consumption of secondary or multiple throwing processes. To study the primary grinding efficiency of the above five gaps, the grinding roller was kept at a constant speed of 82 rev / min in the simulation, while the shovel remained stationary (ignoring the influence of shovel-throwing on grinding efficiency). The feed particles were polygonal ore with a diameter of 25 mm; the feed time was 3 seconds, the total mass was 10 kg, and the simulation experiment lasted for 5 seconds. Considering simulation costs, the target finished product particle size was set to 5 mm.

[0051] Then, a total grinding simulation test was conducted: In order to study the total grinding effect and further reveal the superimposed effect of the shovel throwing action on the grinding of materials, the speed of both the shovel and the grinding roller was set to 82 rev / min, using the same setting parameters as the first grinding, only extending the grinding simulation test to 10s to ensure that the material was fully ground.

[0052] As grinding components, grinding rollers and grinding rings bear large alternating stress loads. Generally, the service life of grinding rollers is required to be no less than 500 hours and the service life of grinding rings is no less than 1000 hours. Both are easily worn parts and need to be replaced regularly when they reach their service limits.

[0053] Rocky DEM uses the Archard wear criterion, and the wear values ​​are as follows:

[0054] A*dh=B*dw

[0055] In the formula, A is the structural surface area, m 2 h is the wear depth in meters; W is the shearing work in j-liters; B is the wear rate in meters. 3 / J.

[0056] The wear condition was studied, and the grinding rollers and grinding ring were made of wear-resistant high-manganese steel with a volume / shear work ratio of 5e×10. -7 The surface mesh of the grinding roller and grinding ring is densified to a size of 5mm in order to extract accurate wear data.

[0057] Analysis of simulation results of a single grinding process:

[0058] Extract information on the collision frequency between particles and a certain grinding roller, such as... Figure 3 As shown, during the material's descent, it first collides with the grinding rollers and grinding ring. The grinding rollers rotate continuously at high speed to ensure that the material falling from the feed inlet is captured in time and crushed and ground in one pass. In the figure, as the gap between the grinding rollers and grinding ring decreases, the collision frequency increases significantly with time, reaching as high as 1.4 × 10⁻⁶ in the 0mm gap model. 5 HzHz; As the gap between the grinding roller and the grinding ring increases, the collision frequency between the material and the grinding roller decreases sequentially; The collision frequency of the model with a 25mm gap is only 6200 times / s at most. Observing the simulation results, since the material size is similar to the gap size, some material falls directly without being captured by the grinding roller and the grinding ring.

[0059] The energy spectrum of the collision between the extracted material and the grinding ring is shown (the 25mm gap is ignored in the statistics). Energy characterizes the physical system's ability to do work, while power describes the rate at which work is done. The breakage of a single material is mainly determined by the sum of the energy level of a single collision and the total collision power. A high single collision energy allows for effective material breakage, and the number of broken pieces is related to the total power at that energy level. A low single collision energy may not allow for complete breakage in one go, but numerous collisions at lower energy levels can repeatedly accumulate damage, eventually leading to effective breakage. Figure 4 As shown, when the energy is 1.0 × 10 -4 -4.4×10 -3 Within the J range, the impact power remains relatively high. The impact power decreases as the gap increases from 0mm to 8mm, with impact powers of 19kW and 12kW for 3mm and 5mm gaps, respectively. When the gap increases to 8mm, the impact power decreases significantly to 0.65kW. Higher impact power corresponds to faster crushing and better results. Energy greater than 4.4 × 10⁻⁶ -3 After J, the impact power corresponding to each gap model begins to decrease; when the energy increases to 1J, the cumulative power is basically zero, proving that there are fewer high-energy particles.

[0060] See the simulation of particle mass change after one grinding. Figure 5 In all five simulation experiments, after 3 seconds of feeding, the particle mass showed a decreasing trend. After 4 seconds, the particles were basically crushed, and the total mass tended to stabilize. Rocky software, by default, does not count particles smaller than a preset size after grinding. The finished product size was set to 5mm in the simulation, therefore particles smaller than 5mm were not counted. Relative to the total feeding mass of 10kg, the yield rate K is introduced:

[0061]

[0062] In the formula, m1 is the mass of particles with a diameter of 0-5mm after crushing; M is the total mass of particles.

[0063] Based on the calculation of yield K, the yield of the first pass is 77.2% for the 0mm gap model, 5mm, and 8mm gap models are 53.1%, 21.4%, and 6.1% respectively, and the yield of the first pass for the 25mm gap model is only 1.7%. As the gap between the grinding roller and grinding ring increases, the yield of the first pass decreases significantly, that is, the grinding efficiency of the equipment decreases.

[0064] Particle size distribution is used to evaluate the particle size after grinding. The particle size distribution of [0-5], [5-10], [10-15], [15-20], and [20-25] mm particles is extracted sequentially. Figure 6 As shown, except for the 25mm gap, the particle size proportions of the 0mm, 3mm, 5mm, and 8mm gap models in the range [5-15]mm increase sequentially, while the proportions in the [15-25]mm range remain basically consistent. This indicates that increasing the gap can produce more finer particles, but the yield trend is opposite. Overall, increasing the gap between the grinding roller and grinding ring leads to a significant decrease in the first-pass yield. However, the number of fine particles in the [5-15]mm range increases with the increase in gap. These particles need to be further ground under the throwing force of the scraper to achieve the final fineness of the finished product, thus consuming more energy. Therefore, it can be concluded that increasing the first-pass grinding yield is an effective way for pendulum mills to achieve high efficiency and low energy consumption.

[0065] Analysis of overall milling simulation results:

[0066] In the overall grinding simulation, the blade rotates synchronously with the spindle, allowing us to capture the combined effects of primary grinding and blade throwing. The energy spectrum of the impact power between the material and the grinding ring is statistically analyzed. Figure 7 The impact power distribution under different energies is compared with that of a single grinding operation. When the energy is 1.0 × 10⁻⁶, the impact power distribution is as follows: -4 -4.4×10 -3Within the J range, the impact power is at its highest, resulting in better crushing performance. Impact power decreases as the gap increases. At this point, the impact power for 3mm is 20kW, 1.6kW higher than single-stage crushing; the impact power for 5mm increases by 0.9kW; and the impact power also increases accordingly for 8mm.

[0067] See particle mass change Figure 8 Compared to a single-stage grinding simulation, the particle mass of the models in each gap decreased more significantly under the throwing action of the shovel. The finished product breakage rate was calculated, and compared to single-stage grinding, the breakage rates of the 0mm, 3mm, 5mm, and 8mm gap models improved by 1.3%, 12.5%, 7.6%, and 0.7%, respectively, while the 25mm model showed no improvement. The increased finished product rate demonstrates that the shovel's throwing action produces an effective secondary and multiple grinding effect. The gap between the grinding rollers and grinding rings formed by a dynamic material layer of a certain thickness facilitates greater material capture during shovel throwing, resulting in more efficient grinding. The particle size distribution of the five groups of experiments is shown below. Figure 9 Observe the mass ratio of the fineness range. It is consistent with the law of one-time grinding. When the gap increases, more fine particles with a particle size of [5-15] mm can be produced. When there is a gap (3 mm, 5 mm and 8 mm gap model), the proportion of coarse particles with a particle size of [15-25] mm is very small.

[0068] Based on the above analysis, the optimization direction is determined to improve the yield per pass, which is actually determined to optimize the yield per pass with the fewest possible grinding passes. Then, based on this optimization direction, the wear degree of the grinding roller and grinding ring is analyzed, and the shape of the grinding roller is optimized by combining the wear degree of the grinding roller and grinding ring with the gap.

[0069] In this embodiment, based on the study of wear conditions, two improved grinding roller structures (tire-type grinding roller and frustum-type grinding roller) are proposed. The grinding roller and grinding ring are made of wear-resistant high-manganese steel, with a volumetric / shear work ratio of 5e×10. -7 The surface mesh of the grinding roller and grinding ring is densified to a size of 5mm to extract accurate wear data.

[0070] To study the wear of grinding rollers and grinding rings, wear contour maps of the simulated components were extracted, such as... Figure 10 As shown, (a) is the grinding ring and (b) is the grinding roller. The wear-prone areas of the grinding roller and grinding ring are more concentrated in the middle area. Compare the wear photos of the grinding roller provided by the company ( Figure 2 The simulation results are consistent with the actual wear of the grinding roller.

[0071] Extracting the instantaneous stress of a certain grinding roller, such as Figure 11As shown in the figure, the spindle speed is 105 rev / min, corresponding to a grinding roller rotation period of 0.57 s, which matches the time interval of the six peak values ​​in the figure. Stress changes occur when the grinding roller moves from its initial position to below the feed inlet (starting from 0.65 s). As the grinding roller passes below the feed inlet, it can capture and grind the falling material; particle grinding and crushing requires significant stress. Since the scraper does not rotate, the grinding stress drops rapidly after the grinding roller leaves the position below the feed inlet, resulting in a periodic stress variation. Because the continuous feeding time is 3 s, the average of the first four peak values ​​is taken. The average stresses corresponding to the 0 mm, 3 mm, 5 mm, and 8 mm gap models are 0.78 MPa, 0.65 MPa, 0.54 MPa, and 0.41 MPa, respectively. The smaller the gap, the greater the grinding roller stress, the higher the grinding efficiency per cycle, and the greater the stress value, the greater the wear on the grinding roller.

[0072] Figure 12 The radial wear variation of the grinding rollers in each group of tests is shown. The wear of the grinding rollers increases in a stepwise manner. After 3 seconds of feeding, the growth trend of wear slows down; after about 5 seconds, particle crushing is completed, and the wear of the grinding rollers tends to stabilize. The wear of grinding rollers with gaps of 0mm, 3mm, 5mm, and 8mm are 2.36μm, 2.35μm, 2.00μm, and 1.23μm, respectively. The gap size is inversely proportional to the wear of the grinding rollers; the smaller the gap, the greater the wear. To improve the wear condition of the grinding rollers, a jig-shaped grinding roller and a frustum-shaped grinding roller were designed. Figure 13 The diagram shows different grinding roller structures and their corresponding wear area cloud maps. Among them, (a) shows the original grinding roller form of the mill, (b) shows the tire-shaped grinding roller, and (c) shows the frustum-shaped grinding roller, with a cylinder at the bottom and a frustum structure on top of the cylinder.

[0073] The particle size distribution of the three sets of grinding rollers with different shapes is as follows: Figure 14 Compared to cylindrical grinding rollers, frustum-shaped grinding rollers increased the first-pass yield by 1.8%, while the average particle size after crushing decreased slightly. Conversely, tread-shaped grinding rollers decreased the first-pass yield by 5.2%, indicating that frustum-shaped grinding rollers provided relatively better grinding performance.

[0074] Extract the wear variation pattern in the radial direction of grinding rollers of various shapes, as follows: Figure 15 As shown, the wear amounts of the tire-shaped grinding roller and the frustum-shaped grinding roller are 2.84 μm and 1.36 μm, respectively. Both the tire-shaped grinding roller and the frustum-shaped grinding roller can effectively reduce wear, but based on the overall grinding efficiency analysis, the frustum-shaped grinding roller performs better overall.

[0075] Then, a single-factor simulation analysis based on CFD-DEM is performed:

[0076] (1) Single-factor simulation analysis of blade angle:

[0077] In a single-factor simulation with the blade angle as the variable, the spindle speed was set to 82 rev / min, the feed rate was set to the actual production feed rate of 15 t / h (particle mass was 33.3 kg in the 8-s simulation), and the blade angle was set to 25°, 30°, 35°, and 40° based on the company's actual production experience. Figure 16 As shown, an 8-second simulation was completed. After the simulation, the particle parameters of the crushed material and the wear parameters of the grinding rollers were exported from the DEM, as shown in Table 2. (The shovel is shown in the image.) Figure 16 As shown.

[0078] The particle crushing process significantly increases computational burden during computer simulation. Therefore, the minimum particle size that can be crushed must be defined in the simulation configuration (the minimum crushing particle size set in this study is 5 mm) to ensure that particles smaller than this size are not included in further calculations during the simulation. Using DEM software, the total mass of these excluded small particles is calculated and used as the mass of the final product particles.

[0079] Table 2 Single-factor analysis of blade angle

[0080]

[0081] Table 2 shows the single-factor results for the blade angle. When analyzing the effect of blade angle changes on the average particle size in the simulation results, it was observed that the average particle size increased with increasing blade angle. The differences between groups were small, with the average particle sizes in the main unit being 10.35 mm, 10.4 mm, 10.52 mm, and 10.96 mm, respectively. The particle yield showed an upward trend, with a significant difference between the 30° and 35° blade angle groups. The yield increased from 74.5% to 78.2%, demonstrating a significant optimization effect. Within the range of 35° to 40°, the wear increased from 6.33 μm to 7.4 μm as the blade angle increased. Figure 17 To simulate the distribution of particles in different size ranges after 8 seconds, particles in the [5-15] mm range constituted the majority, with the 40° scraper showing the highest proportion in the [15-25] mm large particle size range. Considering component lifespan and energy conservation, although the 40° scraper had the highest yield, the improvement in yield was not significant compared to the 35° scraper, while the wear of the grinding roller increased substantially. Therefore, the 35° scraper was used in the single-factor analysis of the scraper.

[0082] The scraper is an important component used to deliver materials to the grinding area between the grinding roller and the grinding ring for grinding. The angle of the scraper, that is, the angle between the scraper and the horizontal plane, directly affects the force on the material on the grinding roller, thus affecting the wear of the grinding roller. Figure 18The wear distribution of the scraper at different angles shows that the wear of the grinding roller increases in a stepwise manner with the increase of the feed rate. The wear of the grinding roller is the largest at 40°, at 7.4μm, while the wear is the smallest at 25°, at 5.95μm. Figure 19 The particle movement trajectory and grinding roller wear are observed when the scraper angle is 25° and 40°. At a 25° scraper angle, as... Figure 19 In (a), the material experiences more concentrated force at the lower position of the grinding roller, reducing the vertical impact force on the roller and thus relatively reducing wear. Furthermore, with a 25-degree scraper, the material's residence time on the grinding roller is shorter, which is not conducive to thorough grinding and thus reduces grinding efficiency. With a 40-degree scraper, as... Figure 19 In (b), the material experiences more uniform force on the grinding roller. An increased blade angle means stronger cutting force and greater impact on the grinding roller, leading to increased wear. The material is delivered to the grinding area promptly by the blade, resulting in more dispersed force on the grinding roller. Furthermore, with a 40° blade, the material stays on the grinding roller for a longer time, facilitating thorough grinding and improving grinding efficiency.

[0083] according to Figure 19 By analyzing the particle trajectory at different blade angles, the wear state of the grinding roller at each blade angle can be obtained, such as... Figure 20 As shown, (a) is the original grinding roller, (b) is the wear of the grinding roller under the 25° scraper, and (c) is the wear of the grinding roller under the 40° scraper. After the particles have undergone one grinding and two grinding processes by the scraper, compared with the original grinding roller, the grinding roller under the 25° scraper angle has more uniform wear and no significant unevenness. The upper part of the grinding roller under the 40° scraper angle has more severe wear. This is because the excessively high scraper angle causes the particles that are thrown during the second grinding process to preferentially pass through the upper part of the grinding roller for grinding, thus leading to this phenomenon.

[0084] (2) Single-factor simulation analysis of feed rate:

[0085] In the single-factor simulation with the feed rate as the variable, the blade angle was set to 30°, the spindle speed was set to 82 (rev / min), and the feed rate was set to 15, 20, and 25 t / h respectively based on the actual production experience of the enterprise (the particle mass in the 8s simulation was 33.3 kg, 44.4 kg, and 55.5 kg respectively) to complete the 8s simulation.

[0086] Table 3 Single-factor analysis of feed rate

[0087]

[0088] The feed rate directly affects the grinding efficiency of a pendulum mill. Ideally, the grinding efficiency of a pendulum mill is directly proportional to the feed rate. The larger the feed rate, the higher the grinding efficiency. This is because when the feed rate increases, the pendulum mill has more material to grind, thus improving grinding efficiency. However, this does not mean that the feed rate can be increased indefinitely. When the feed rate exceeds the load-bearing capacity of the pendulum mill, the equipment will experience overload, leading to a decrease in grinding efficiency. Conversely, if the feed rate is too small, although high-quality products can be obtained, production efficiency will be greatly reduced, failing to meet production needs. Therefore, reasonably controlling the feed rate is key to improving the grinding efficiency of a pendulum mill. As shown in Table 3, the single-factor analysis results of the blade angle show that with the increase of the feed rate, the yield rate shows a gradual downward trend, at 74.5%, 66.4%, and 58.9%, respectively. The wear of the grinding rollers shows an upward trend, while the change in the average particle size is not significant and has little impact. Figure 21 To simulate the distribution ratio of each particle size range after 8s, particles with a diameter of [5-15]mm accounted for the majority, and the feed rate of 15t / h had the highest proportion in the large particle size range of [15-25]mm and the lowest proportion of 53.69% in the small particle size range of [5-10]mm.

[0089] In the simulation, the shovel and the main shaft rotate synchronously, allowing us to obtain the influence of particles with different feed rates on the grinding ring under the throwing action of the shovel. The energy spectrum of the impact power between the material and the grinding ring is statistically analyzed. Figure 22 The impact power distribution is shown for different energies, when the energy is 1.0 × 10⁻⁶. -4 -4.4×10 -3 Within the J range, the impact power is at its highest, resulting in better crushing performance. The impact power increases with the increase of the feed rate. At this point, the impact power of a feed rate of 20t / h is 35kW, which is 6kW higher than that of a feed rate of 15t / h, and the maximum impact power of a feed rate of 25t / h is 40kW.

[0090] (3) Single-factor simulation analysis of spindle speed:

[0091] A pendulum mill mainly consists of a base, support frame, main shaft, grinding rollers, and adjustment device. When the main shaft rotates at high speed, it drives the grinding rollers to oscillate through gear transmission, causing the material to be squeezed and ground between the grinding rollers and the grinding ring, thereby achieving the purpose of pulverization. Therefore, the main shaft speed has a significant impact on the grinding effect of the pendulum mill.

[0092] Spindle speed is one of the key parameters for the grinding effect of a pendulum mill. Generally speaking, the higher the spindle speed, the faster the grinding rollers oscillate, and the longer the material spends grinding between the grinding rollers and the grinding ring, resulting in a better grinding effect. However, excessively high spindle speeds can also cause the material to pass through the grinding rollers and grinding ring too quickly, preventing sufficient grinding and thus reducing the grinding effect. Therefore, selecting an appropriate spindle speed is crucial for improving the grinding effect of a pendulum mill.

[0093] The spindle speed also significantly affects the energy consumption of a pendulum mill. Generally, the higher the spindle speed, the faster the grinding rollers oscillate, resulting in greater friction during grinding and higher energy consumption. However, as the spindle speed increases, the grinding time between the grinding rollers and the grinding disc shortens, relatively reducing energy consumption per unit time. Therefore, while ensuring grinding efficiency, appropriately increasing the spindle speed can reduce the energy consumption of a pendulum mill.

[0094] The spindle speed also has a certain impact on the service life of a rotary mill. Excessively high spindle speeds will accelerate wear between the grinding rollers and the grinding disc, leading to a shorter equipment lifespan. Furthermore, excessively high spindle speeds will increase equipment vibration and noise, affecting stable operation. Therefore, when selecting the spindle speed, the wear and service life requirements of the equipment should be fully considered.

[0095] The spindle speed also affects the stability of the pendulum mill. Excessively high spindle speeds increase vibration and noise, impacting stable operation. Furthermore, excessively high spindle speeds may cause material to pass too quickly between the grinding rollers and the grinding disc, resulting in insufficient grinding and reduced grinding efficiency. Therefore, the stability requirements of the equipment should be fully considered when selecting the spindle speed.

[0096] In the single-factor simulation with spindle speed as the variable, the blade angle was set to 30°, the feed rate was set to the actual feed rate in production of 15t / h (the particle mass in the 8s simulation was 33.3kg), and the spindle speed was set to 62, 72, 82, 92, and 102 (rev / min) respectively according to the actual production experience of the enterprise, and the 8s simulation was completed.

[0097] Table 4 Single-factor analysis of spindle speed

[0098]

[0099] Table 4 shows the single-factor results for spindle speed. It can be observed that as the spindle speed increases, the average particle size after simulation decreases. The average particle sizes in the main unit are 12.43 mm, 11.16 mm, 10.40 mm, 10.35 mm, and 10.26 mm, respectively. The yield of the particles decreases, with significant differences between the 62 rev / min and 82 rev / min speed groups. The yield increases from 74.47% to 77.09% and then decreases again to 74.5%, indicating a maximum yield value within this range. Simultaneously, with increasing spindle speed, the wear of the grinding rollers increases sequentially, rising from 3.37 μm to 6.08 μm. Figure 23 To simulate the distribution ratio of each particle size range after 8s, the particles in the [5-15]mm range accounted for the majority. The 62rev / min rotation speed combination had the lowest proportion in this range. Furthermore, due to the low rotation speed, the particles could not be captured and ground in time. Although the wear of the grinding roller was the lowest, the crushing effect was not ideal, resulting in the 62rev / min rotation speed combination having the highest proportion in the [15-25]mm large particle size range.

[0100] The impact frequency of particles on the grinding ring refers to the number of collisions between particles and the grinding ring per unit time. The impact frequency is closely related to the grinding efficiency, product fineness, and energy consumption of the pendulum mill. Generally, the higher the impact frequency, the higher the grinding efficiency and the finer the product, but the energy consumption also increases accordingly. The impact frequencies of particles on the grinding ring at the lowest, original model, and highest spindle speeds of 62 rev / min, 82 rev / min, and 102 rev / min, respectively, are extracted. Figure 24 As shown, the impact frequency between particles and the grinding ring gradually increases with the increase of the spindle speed. At a speed of 102 rev / min, the impact frequency of particles on the grinding ring reaches as high as 2.1E+07 times / s. The higher the speed of the scraper, the more times the material is thrown towards the grinding ring, and the higher the impact frequency. However, excessively high speeds result in a short residence time of the material on the grinding disc, which is not conducive to material crushing. Therefore, the yield is lowest at a speed of 102 rev / min.

[0101] (4) Based on the characteristics of single-factor analysis, determine the single-factor machine optimization value that needs to be fixed, and use the other two factors as variables to analyze the response surface based on CFD-DEM simulation, and determine the optimization results of the other two factors with the yield as the objective.

[0102] To investigate the crushing efficiency of limestone powder, the spindle speed and feed rate of the main unit were used as optimization parameters, and the crushing efficiency of the pendulum mill was used as the objective function for response surface methodology (RSM) experiments. Based on the parameter range determined through enterprise practice, the Box-Behnken RSM optimization method was employed for scheme design. The optimal blade installation angle was determined to be 35 degrees based on single-factor analysis, and this angle was set at 35° in the RSM experimental design.

[0103] Experimental analysis was conducted using Design-Expert 13 software. The experimental factor levels are shown in Table 5.

[0104] Table 5. Experimental Factor Level Table

[0105]

[0106] Crushing efficiency is an important evaluation indicator in Raymond mill production, and its level directly determines the competitiveness of Raymond mills in the ultrafine powder industry.

[0107] The simulation results for each group are shown in Table 6.

[0108] Table 6 Simulation Tests and Yield Values

[0109]

[0110] The yield rates obtained from the three sets of simulation experiments are shown in Table 6. When the spindle speed is 62 rpm, the yield rate first increases and then decreases with the increase of the feed rate, reaching a maximum of 79.6%. When the spindle speed is 72 rpm, the yield rate decreases, reaching a maximum of 83.1%. Similarly, when the spindle speed is 82 rpm, the yield rate also decreases, reaching a maximum of 82.6%. This indicates that when the spindle speed is constant, an excessive feed rate has a detrimental effect on the overall grinding process, causing the mill to be in an oversaturated state, resulting in a decrease in the yield rate. Conversely, when the feed rate is constant, an excessively high spindle speed causes the particles to remain in the grinding zone for too short a time, also leading to a decrease in the yield rate.

[0111] Table 7 Results of the variance analysis of yield

[0112]

[0113] * Indicates that the factor has a significant impact on the experimental index (P < 0.05).

[0114] Table 7 shows that the main factors affecting the yield η are A, B, AB, and A. 2 B 2 A has a significant impact on the yield of the material (P < 0.05).

[0115] The Design Expert software was used to establish response surface curves from the experimental results, such as... Figure 25 When the spindle speed is constant, the yield rate first increases and then decreases as the feed rate decreases; conversely, when the feed rate is constant, the yield rate first increases and then decreases as the spindle speed decreases. The yield rate is higher when the spindle speed is between 72 rpm and 80 rpm. The fitted formula for the yield rate using regression equation fitting is as follows:

[0116] η=82.08-2.95A+0.8333B-2.0AB-2.22A 2 -3.67B 2

[0117] Using the Optimization module in Design Expert software, with the goal of maximizing yield, the optimal combination of optimization parameters was obtained as shown in Table 8.

[0118] Table 8 Response Surface Recommendation Results

[0119]

[0120] Based on the above optimization results and according to the original working conditions of the enterprise, under the premise of ensuring that the output does not decrease, the feed rate of 12t / h, the spindle speed of 74.5rpm, and the yield of 83.3% were selected for verification. The optimal yield of the material was found to be 82.96%, which is 0.41% different from the optimization result.

[0121] This invention may have other embodiments. Without departing from the spirit and essence of this invention, those skilled in the art can make various corresponding changes and modifications according to this invention, but these corresponding changes and modifications should all fall within the protection scope of the appended claims.

Claims

1. A method for optimizing the performance of ring roller milling based on a pendulum mill, characterized in that: Includes the following steps: The main structure of the pendulum mill includes a plum blossom frame (1), a feed inlet (2), a central shaft (3), an air inlet (4), a suspension cover (5), a grinding ring (6), a grinding roller (7), a shovel (8), and a base (9); For the pendulum mill to be optimized, a single grinding simulation test and a total grinding simulation test were first conducted using Rocky DEM. The yield rate for each gap is obtained based on the analysis of the simulation results of a single grinding cycle, and the total yield rate for each gap is obtained based on the analysis of the simulation results of the total grinding cycle. The gap refers to the gap between the grinding roller and the grinding ring. By comparing the yield rate of the single grinding cycle simulation results and the yield rate for each gap obtained from the simulation results of the total grinding cycle, with the aim of improving efficiency and reducing energy consumption, the optimization direction is determined based on the number of grinding cycles and the corresponding yield rate. This is either to improve the yield rate of the single grinding cycle or the yield rate of multiple grinding cycles. Furthermore, the shape of the grinding roller is optimized by combining the relationship between the wear degree of the grinding roller and the grinding ring and the gap. Then, a single-factor simulation analysis based on CFD-DEM is performed, including single-factor simulation analysis of blade angle, single-factor simulation analysis of feed rate, and single-factor simulation analysis of spindle speed. Based on the results of the single-factor analysis, the proposed fixed single factor and its optimized value are determined. The optimized value of the proposed fixed single factor is used as the fixed factor, and the other two factors are used as variables. The response surface of the CFD-DEM simulation is analyzed, and the optimization results of the other two factors are determined with the yield as the objective. Based on Rocky DEM, a grinding simulation test was first conducted: the material fell into the main unit from the feed port and first entered the grinding roller and grinding ring area to be captured and crushed and ground. The shovel did not rotate, which is called the first grinding. Subsequently, the material that did not meet the fineness standard and the uncrushed material fell down into the shovel area and was thrown by the rotating shovel. After being ground again or multiple times, the fineness of the finished product was finally achieved. This is called shovel throwing grinding. The superposition effect of the first grinding and throwing grinding is called the total grinding.

2. The method for optimizing the performance of ring roller milling based on a pendulum mill according to claim 1, characterized in that: The optimization direction is determined based on the number of milling cycles and the corresponding yield rate. In the process of determining whether to improve the yield rate of a single milling cycle or the yield rate of multiple milling cycles, the optimization direction is to improve the yield rate of a single milling cycle.

3. The method for optimizing the performance of ring roller mill based on a pendulum mill according to claim 2, characterized in that: When optimizing the shape of the grinding roller by considering the relationship between the wear degree of the grinding roller and the grinding ring and the gap, the shape of the grinding roller is optimized to a tire-shaped grinding roller.

4. The method for optimizing the performance of ring roller mill based on a pendulum mill according to claim 2, characterized in that: When optimizing the shape of the grinding roller, considering the relationship between the wear degree of the grinding roller and the grinding ring and the gap, the shape of the grinding roller is optimized to a frustum-shaped grinding roller.

5. The method for optimizing the performance of ring roller mill based on a pendulum mill according to claim 1, characterized in that: The grinding rollers and grinding rings are made of high manganese steel.

6. A method for optimizing the performance of ring roller mills based on pendulum mills according to any one of claims 1 to 5, characterized in that: Based on the results of the single-factor analysis, the proposed fixed single factor is the blade angle.

7. The method for optimizing the performance of ring roller mill based on a pendulum mill according to claim 6, characterized in that: The proposed fixed single factor is the blade angle, with an optimal value of 35°.

8. The method for optimizing the performance of ring roller mill based on a pendulum mill according to claim 7, characterized in that: Based on the response surface analysis of CFD-DEM simulation, the optimization results of the other two factors with the yield as the objective were determined to be a feed rate of 12t / h and a spindle speed of 74.5rpm.

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