JPS61204070A - Automatic controller for operating sorter at maximum capacity and method thereof and abnormality detector - Google Patents

Abstract

(57) [Summary] This bulletin contains application data before electronic filing, so abstract data is not recorded.

Description

[Detailed Description of the Invention] Industrial Application Field This invention provides an abnormality detection device that detects and transmits an abnormality inside a classifier, and a method for using the classifier at the highest point of its ability to sieve the classifier. The present invention relates to an automatic control device and method for a classifier that can increase production and save energy consumption.

Conventional technology Many wire sieves, for example, are used as powder and granule classifiers in powder and granule processes, but these machines have a closed structure, and conventionally, they have to be disassembled when inspecting internal wJ, etc. Perform inspection. This causes the line to stop and requires a great deal of effort to disassemble. In addition, it is very complicated to take detailed measures to deal with changes in the properties of the powder or granular material that occur due to variations in the particle size or moisture content of the supplied powder or granular material, or changes in outside air conditions. It takes a lot of time to measure the properties of particles. In addition, since all rope sieve machines place emphasis on maintaining classification accuracy, the maximum capacity of the rope sieve machine is
The same mesh sieve machine is often used between 0% and 80%.

However, the problem that the invention seeks to solve! #l When using the sieve machine at its maximum capacity, be careful not to accidentally exceed its maximum capacity and thereby cause fine powder to mix with the coarse powder side and significantly reduce its classification efficiency. Workers must take extraordinary care. There was a problem in that it was virtually impossible to use this at the same maximum capacity.

Also, when detecting abnormalities in the classifier such as the above-mentioned screen breakage, the process is progressing from the time of occurrence until it is discovered, resulting in a large amount of loss, as it is discovered when the phenomenon becomes fairly clear. There was a problem.

Means to solve problems The present invention will be explained below based on the drawings.

FIG. 1 is a diagram showing the basic concept of this invention. In FIG. 1, the wire sieve machine is composed of a vibration R1 using a motor or the like and a wire sieve 2.

In Figure 1,! 1 sieve 2 is equipped with a type of 1iIJ3. Therefore,! The fine powder at the bottom of the sieve 1213 is discharged from the discharge hole 4, and the coarse powder at the top of the sieve is discharged from the discharge port 5.

On the other hand, the powder 6 to be classified is fed from the hopper 7 via the feeder 8 into the wire sieve 2 through the input port 9 of the wire sieve 2. On the other hand, flowmeters 10 and 11 for powder and granular material are installed at the discharge ports 4 and 5, so that the flow rate under the sieve and above the sieve discharged from the discharge ports 4 and 5 can be measured. The detected values of flowmeters 10 and 11 are introduced into a controller 12.

The controller 12 has a function of determining the ratio of the detected value of the illll meter 011 and detecting a difference from the target value. At the same time, it has a function of transmitting an operation signal to the feeder 8 to instruct the feeder 8 to increase or decrease its feed amount. In addition, if the ratio of flow rates under the sieve and on the screen changes beyond the allowable difference of the set value, abnormalities such as screen clogging abnormality, screen tear abnormality, input material abnormality, etc. are displayed.

Operation In FIG. 1, if the flow rate of the powder and granular material 60 input from the feeder 8 to the input port 9 is less than the maximum capacity of the wire sieve 2,
The ratio of the detected values of the flowmeters 10 and 11 shows a constant normal value.

This is because the particle size distribution of the granular material 60 does not normally change, so the ratio between the bottom and top of the sieve does not change. However, if the powder 6 is supplied in excess of the maximum capacity of the wJ sieve 2,
As described above, since more fine powder is mixed into the sieve, the ratio of the detected values of the flowmeters 10 and 11 becomes smaller than a certain normal value.

Here, it is assumed that the supply amount of the granular material 6 is 60% of the maximum capacity of the wire sieve 2. At this point, the controller 12 instructs the feeder 8 to increase the amount of powder and granular material 6 fed by 15% according to the instructions of the built-in program. Thereafter, the ratio of the detected values of the flowmeters 10 and 11 after a predetermined period of time, for example, one minute, is determined and compared with a preset normal value. If no abnormality is found, the feeder 8 is further instructed to increase the supply amount by 15%. Similarly to the above, the controller calculates the ratio of the detected values and compares it with the normal value, and if no abnormality is found, the controller further reduces the amount of supplied ci of the powder/granular material 6 by 1.
The feeder 8 is commanded to increase by 5%. At this point, the controller 12 detects that the ratio of the detected values of both flowmeters 10 and 11 deviates from the normal value, and instructs the feeder 8 to reduce the amount of powder and granular material 6 fed by 7.5%. do. Similarly, after confirming that the ratio of the detection values of both flow meters 10 and 11 is a normal value, the controller 12 starts supplying the powder 6 to the feeder 8 in 3.
Order to increase by 75%. By repeating such operations, the controller automatically maintains the maximum capacity of the wire sieve 2 for supplying the powder and granular material 6.

The above is a method for automatically maintaining the maximum capacity when there is no variation in the particle size distribution of the powder or granular material 60.

Generally, the particle size distribution of powder and granular material 60 varies within a range of 1 to 2%, so a tolerance within a certain range is set for the ratio of the flow rate above the sieve to the flow rate under the sieve, and the setting tolerance (for example, 60± 3%), the supply amount is increased by 5% in the same manner as described above, and the input flow rate is increased until it exceeds the set tolerance. Then, the steady input flow rate is fixed to the value immediately before the input flow rate that exceeds the set tolerance. In addition, by measuring the flow rate above the sieve and the flow rate under the sieve after a certain period of time or at any time, detecting the ratio of both flow rates, and repeating the above method, the sieve machine can always be operated near its maximum capacity despite slight fluctuations in the particle size distribution. becomes possible.

With the above method, the feed rate may gradually decrease when the sieve is operated near its maximum capacity, but this is due to clogging of the sieve screen, and in this case, the lower limit of the throughput can be reduced. This setting is displayed as clogging abnormality or particle size distribution abnormality (particle size is coarse).

Furthermore, if the flow rate under the sieve increases more than the set value compared to the flow rate above the sieve, an abnormality is detected as a broken screen or an abnormality in the particle size distribution of the feed material (the particle size has become finer), and an abnormality is displayed.

On the other hand, it is clear that the above function can be achieved by determining the flow rate input from the feeder 8 and the flow rate under the sieve or above the sieve instead of the ratio of the flow rates under the sieve and above the sieve.

Embodiment FIGS. 1 and 2 are embodiments of this invention.
Since the figures have already been explained, FIG. 2 will be explained. l1l
T3 is equipped with meshes 4 and 15 of two different meshes. The first stage mesh 15 has a coarser mesh than the next stage mesh 14. The powder and granular material 6 fed into the input port 16 from the feeder 8 is classified by the net 14 and the net 15, and then sent to each discharge port 18.1.
9 and 20. At the same time, the flow rate is measured by flow meter 2.
1, 22 and 23, and the detected values are introduced into the controller 24. Here, since the target of the automatic control device and method for maximum capacity operation of the mesh sieve machine is the first stage Wi15, the controller 24 takes the ratio of the detected values of the flowmeters 22 and 23 and calculates the ratio set in advance. Compare with a certain normal value.

If the two match, the controller 24 instructs the feeder 8 to increase the supply by 5%. After one minute, the flowmeters 22 and 23
The ratio of the detected values is taken, and if no difference from a certain normal value is recognized, the feeder is instructed to increase the supply by an additional 5%. After repeating this and eventually confirming that the ratio of the detected values of the two flowmeters 22 and 23 differs from a certain normal value, the controller 24 instructs the feeder 8 to reduce the supply by 3%. . By repeating this in sequence, this classifier system will always continue to operate at its maximum capacity. Here, the flow meter 21
The detected value was used for an alarm to detect an abnormality in the wire sieve 13. In FIG. 1, the net 3 corresponds to the first stage net. Further, instead of the feeder shown in FIGS. 1 and 2, a loss-in-weight type or a feedback automatic control type quantitative feeder shown in FIGS. 3 and 4 may be provided. This case has the advantage of being able to supply powder and granules with higher precision than a single feeder, but it also has the disadvantage of being more expensive. In either case, it is still a supply machine here. FIG. 3 is an explanatory diagram of a loss-in-weight type quantitative feeder. The powder and granular material 6 is supplied from the supply hopper 25 by a supply machine, and the amount is determined in advance by the controller 1.
2 matches the commanded feeder. That is, the controller 27 automatically controls the feeder 8 so that the rate of weight loss of the powder or granular material in the feed hopper 25 detected by the load cell 26 matches the feed amount commanded by the controller 12. Of course, in this case, the powder 6 is not discharged from the hopper 7 via the feeder 28.

When the powder and granular material 6 in the supply hopper 25 is reduced to a predetermined amount, the supply machine 28 starts supplying. In this case, until the feed hopper 25 is filled with a predetermined amount of powder or granular material 6, automatic control by the controller 27 is not performed and the feeder 8 continues to feed at the value immediately before the automatic control was stopped. In other words, this is the turning point of control.

On the other hand, in the feedback automatic control type quantitative feeder shown in FIG. Configure automatic control circuit. In this case, compared to the former case, there is an advantage that it is possible to follow the commands of the controller 120 more quickly and that there is no break point in control.

Therefore, other special feeders can also be used as long as they can follow the commands from the controller 12.

As described in detail of the invention, the classification work is automatically performed at the maximum capacity of the classifier system, which has the significant effect of increasing production and reducing energy consumption per unit of production. We can expect that. At the same time, since everything is operated automatically, it is thought to greatly contribute to labor savings.

On the other hand, abnormalities in the classifier can be automatically detected as soon as they occur. Therefore, there are advantages in that production losses can be reduced and dangerous situations can be prevented in advance. Also, if one were to consider doing this manually, the benefits would be much more accurate and less expensive to achieve.

Furthermore, a simpler method than the method shown in FIG. 1 is also conceivable. That is, for example, this is an example in which only the flow meter 10 for under-sieving, the controller 12, and the feeder 8 are provided. In this case, as explained in the embodiment section, the controller 12 instructs the feeder 8 to increase the supply by an appropriate percentage. On the other hand, if the flow meter IO detects an increase in the flow rate by an appropriate percentage, the controller 12 further instructs the feeder 8 to increase the supply by an appropriate percentage.

Thus, if the flow meter IO does not detect an increase in flow rate despite the same command, the controller 12 will command a reduction in supply. Thus, similar to the above, this classifier system is
It will always continue to operate at maximum capacity. On the other hand, even though the supply amount of the feeder 8 has not increased, the flow rate = t1
If 0 detects an increase in the flow rate, it means that 1!13 is damaged or some other abnormality has been detected, and an abnormality alarm will be issued. Also, a flowmeter I+ can be used instead of the flowmeter IO. In this case, the increase/decrease in the flow rate detected by the flowmeter 11 will be somewhat different from that of the flowmeter IO.

It is possible to achieve similar objectives.

[Brief explanation of the drawing]

FIG. 1 is a diagram used to explain the invention in detail, but at the same time, it also shows an embodiment together with FIG. Moreover, FIGS. 3 and 4 are reference diagrams as a quantitative feeder for the powder and granular material 6. In the figure, 1: Vibration source 2: ial sieve 3: Screen 4: Discharge port 5: Discharge port 6: Powder 7: Hopper 8: Feeder 9: Input port 10: Flowmeter 1M flowmeter 12 Controller I3 : Rope sieve 14: Net 15: Net 16: Inlet 18: Outlet
19: 1 outlet 20: 2 outlets
1: Flowmeter 22: Flowmeter 23; Flowmeter 24
: Controller 25: Supply hopper 26: 1 code cell 27: Controller 28: Supply machine 2
9: Flow rate meter 1st group O 2 Method of writing correction) 1. Display of the case Patent Application No. 44439 of 1985 2, Title of the invention Automatic control device for maximum capacity operation of a classifier and its method and abnormality detection device 3 Relationship between the person making the amendment and the case Patent applicant 4゜Amendment Subject: Description 5, Contents of amendment: As attached, Description 1: Title of the invention: Automatic control device for maximum capacity operation of classifier and its method, and abnormality detection device 2, Claim 1: First-stage mesh of classifier A function to determine the difference between the ratio of the flow rate of any two of the flow rate under the sieve and the flow rate above the sieve or the flow rate input to the classifier and a preset normal value, and supply of powder and granules to the classifier based on the difference. A maximum capacity operation automatic control device for a classifier, characterized by having a function of instructing the machine to increase or decrease the supply. 2. The current supply amount of the feeder that supplies powder and granules to the classifier is automatically increased by a predetermined percentage, and as a result, A) the flow rate under the sieve and above the sieve of the first stage of the classifier, or the If the ratio of any two flow rates among the flow rates input to the classifier does not differ from a preset normal value, the feed rate is further automatically increased by the predetermined percentage. B) If any of the flow rates under and above the sieve of the first-stage screen of the classifier or the flow rate input to the classifier is different from the preset IIE normal 11α in the ratio of the second stream, then the supply amount is automatically reduced by the predetermined percentage or a fraction thereof. A method of achieving maximum capacity operation of the classifier by performing the following operations. :(6) A function that calculates the difference between the ratio of the flow rate of any two of the flow rates to the bottom of the sieve and the sieve E of the classifier, or the current input to the classifier, and a preset normal value, and detects abnormalities based on the difference. An abnormality detection device for a classifier characterized by the function of emitting a signal. 4. Of the flow rate under or above the sieve of the first stage of the classifier,
A function to determine the difference between the amount of increase or decrease in any of the flow rates and a preset normal increase or decrease, and a function to instruct the feeder that supplies powder and granules to the classifier to increase or decrease the supply based on the difference. The highest capacity automatic control device for classifier operation, which is characterized by: 5. Automatically increase the current supply amount of the feeder that supplies powder and granular material to the classifier by a predetermined percentage, and the result is: If there is no difference between the amount of increase in any of the flow rates and the normal increase amount set in advance, the supply amount is further automatically increased by the predetermined percentage. 1 () If the amount of increase in the flow rate of any one of the flow rates of the lower sieve, sieve, and L of the first stage of the classifier is different from the normal increase amount set in advance, record the supply amount in L. It is automatically reduced by a predetermined percentage or a fraction thereof. A method of achieving maximum capacity operation of the classifier by performing the following operations. 6. Features include a function to determine the difference between the flow rate under or above the sieve of the classifier and a preset normal value, and a function to issue an abnormal signal based on the difference. Abnormality detection device for classifier. : 3. Detailed explanation of the invention Industrial field of application This invention uses an abnormality detection device that detects and transmits an abnormality inside the classifier, and a classifier with the highest capacity for sieving. The present invention relates to an automatic control device and method for a classifier, thereby increasing production and saving energy consumption. Conventional technology For example, many wire sieves are used as a classifier for powder and granular materials in the powder and granular material process, but these machines have a closed structure, and conventionally, when inspecting the internal screens, etc., they have to be disassembled. Perform inspection. This causes the line to stop and requires a great deal of effort to disassemble. In addition, it is very complicated to take detailed measures to deal with changes in the properties of the powder or granular material that occur due to variations in the particle size or moisture content of the supplied powder or granular material, or changes in outside air conditions. It takes a lot of time to measure the properties of particles. Furthermore, since all of the 5pii machines place emphasis on maintaining classification accuracy, the wire sieve machine is often used at 60% to 80% of the maximum capacity of the wire sieve machine. Problems to be Solved by the Invention However, if you try to use the mesh machine at its maximum capacity, if you always accidentally exceed its maximum capacity, fine powder will get mixed into the coarse powder side, reducing its classification efficiency. Workers must take extraordinary precautions to avoid significant deterioration. There was a problem in that it was virtually impossible to use this at the same maximum capacity. In addition, when detecting abnormalities in the classifier such as the above-mentioned screen breakage, the process is progressing from the time it occurs until it is discovered, resulting in a large amount of loss. There was a problem. Means for Solving the Problems The present invention will be described below with reference to the drawings. FIG. 1 is a diagram illustrating the basic concept of this invention. In FIG. 1, the wire sieve machine is composed of a vibration source 1 using a motor or the like and a screen surface 2. In FIG. 1, a type of net 3 is attached to the screen surface 2. Therefore,! ! The fine powder under the sieve of I3 is discharged from the discharge hole 4, and the coarse powder on the sieve is discharged from the discharge port 5. On the other hand, the powder 6 to be classified is fed from the hopper 7 via the feeder 8 to the screen surface 2 through the inlet 9 of the screen surface 2. On the other hand, flow meters 10 and 11 for powder and granular material are installed at the discharge ports 4 and 5, so that the flow rate under the sieve and above the sieve discharged from the discharge ports 4 and 5 can be measured. The detected values of flowmeters 10 and 11 are introduced into a controller 12. The controller 12 determines the ratio of the detected values of the flowmeters 10 and 11,
It has a function that can detect differences from the target value. At the same time, it has a function of transmitting an operation signal to the feeder 8 to instruct the feeder 8 to increase or decrease its lp-feed amount. Also, under the sieve,
If the flow rate ratio on the mesh changes beyond the tolerance of the set value, the mesh will become clogged! Displays abnormalities such as iI tearing abnormality and input raw material abnormality. Operation In FIG. 1, if the input flow rate of the powder 6 from the feeder 8 to the input port 9 is below the maximum capacity of the mesh surface 2,
The ratio of the detected values of the flowmeters 10 and 11 shows a constant normal value. This is because the particle size distribution of the granular material 6 does not normally change, so the ratio between the bottom and top of the sieve does not change. However, if the granular material 6 is supplied in excess of the maximum capacity of the screen surface 2, as mentioned above, more fine powder will be mixed into the sieve, which will cause the detected values of the flowmeters IO and I+ to decrease. The ratio will be smaller than a certain normal value. Here, it is assumed that the supply amount of the granular material 6 is 60% of the maximum capacity of the mesh surface 2. At this point, the controller 12 instructs the feeder 8 to increase the feed amount of the powder or granular material 6 by +5% according to a command from a built-in program. Thereafter, after a predetermined period of time, for example, 1 minute has elapsed, the ratio between the detected values of the flowmeter 10 and 11 is determined and compared with a preset normal value. If no abnormality is found, the feeder 8 is further instructed to increase the supply amount by 15%. In the same way as above, the ratio of the detected values is calculated and compared with the normal value, and if no abnormality is found, the controller further increases the supply amount of the powder/granular material 6 by 15%.
The feeder 8 is commanded to increase the amount. At this point, the controller 12 determines that the ratio of the detected values of both inflow needles IO and 11 is normal 11α.
This deviation is detected and the feeder 8 is instructed to reduce the feed amount of the powder or granular material 6 by 7.5%. Similarly, after confirming that the ratio of the detection values of both flow placement needles 10 and 11 is a normal value, the controller 12 supplies the powder and granular material 6 to the supply device 8 in 3.
Order to increase by 75%. By repeating such operations, the controller automatically maintains the maximum capacity of the mesh surface 2 for supplying the powder 6. The first method is to automatically maintain the maximum capacity when there is no variation in the particle size distribution of the powder or granular material 6. Generally, the particle size distribution of the powder 6 varies within a range of 1 to 2%, so a tolerance within a certain range is set for the ratio of the flow rate above the sieve to the flow rate under the sieve, and the setting - tolerance (e.g. 60±3%)
If it is, the supply amount is increased by 5% in the same manner as described above, and the input flow rate is increased until it exceeds the set tolerance. Then, the steady input flow rate is fixed to the value immediately before the input flow rate that exceeds the set tolerance. In addition, by measuring the flow rate above the sieve and the flow rate under the sieve after a certain period of time or at any time, detecting the ratio of both flow rates, and repeating the above method, the sieve machine can always be operated near its maximum capacity despite slight fluctuations in the particle size distribution. becomes possible. With the above method, the feed rate may gradually decrease when the sieve is operated near its maximum capacity, but this is due to clogging of the sieve screen, and in this case, the lower limit of the throughput can be reduced. This setting is displayed as clogging abnormality or particle size distribution abnormality (particle size is coarse). Also, if the flow rate under the sieve increases more than the set value as a ratio to the flow rate above the sieve, an abnormality will be detected as a broken screen or an abnormal particle size distribution of particles (the particle size has become finer), and an abnormality will be displayed. On the other hand, it is clear that the above function can be achieved by determining the flow rate input from the feeder 8 and the flow rate under the sieve or above the sieve instead of the ratio of the flow rates under the sieve and above the sieve. Embodiment FIGS. 1 and 2 are embodiments of this invention.
Since the figures have already been explained, FIG. 2 will be explained. Mesh tube 1
3 is equipped with nets 14 and 15 of two different mesh sizes. The first stage wJ+5 has a coarser mesh than the next stage tIJ14. The powder and granular material 6 fed into the input port 16 from the feeder 8 is classified by the net 14 and the net I5, and then sent to each discharge port 18.
．． It is discharged from 19 and 20. At the same time, the flow rate is detected by the flowmeters 21, 22 and 23, and the detected value is introduced into the controller 24. Here, since the target of the automatic control device and method for layer high capacity operation of the 1!4 sieve machine is the first stage screen 15, the controller 24 takes the ratio of the detected values of the flow meters 22 and 23, Compare with a certain normal value set in advance. If the two match, the controller 24 instructs the feeder 8 to increase the supply by 5%. After one minute, the flowmeters 22 and 23
The ratio of the detected values is taken, and if no difference from a certain normal value is recognized, the feeder is instructed to increase the supply by an additional 5%. After repeating this process and eventually confirming that the ratio of the detected values of the second flow meter 22 and 23 is different from a certain normal value, the controller 24 instructs the feeder 8 to reduce the supply by 3%. do. By repeating this in sequence, this classifier system will always continue to operate at its maximum capacity. Here, the flow meter 21
The detected value was used for an alarm to detect an abnormality in the screen tube 13. In FIG. 1, the net 3 corresponds to the first stage net. Further, instead of the feeder shown in FIGS. 1 and 2, a loss-in-weight type or a feedback automatic control type quantitative feeder shown in FIGS. 3 and 4 may be provided. This case has the advantage of being able to supply powder and granules with higher precision than a single feeder, but it also has the disadvantage of being more expensive. In either case, it is still a supply machine here. FIG. 3 is an explanatory diagram of a loss-in-weight type quantitative feeder. The powder and granular material 6 is supplied from a supply hopper 25 by a supply machine, and the amount is controlled in advance by a controller]
2 matches the supply amount commanded. That is, the controller 27 automatically controls the feeder 8 so that the rate of weight loss of the powder or granular material in the feed hopper 25 detected by the load cell 26 matches the feed amount commanded by the controller 12. Of course, in this case, the powder 6 is not discharged from the hopper 7 via the feeder 28. When the powder and granular material 6 in the supply hopper 25 is reduced to a predetermined amount, the supply machine 28 starts supplying. In this case, until the feed hopper 25 is filled with a predetermined amount of powder or granular material 6, automatic control by the controller 27 is not performed and the feeder 8 continues to feed at the value immediately before the automatic control was stopped. In other words, this is the turning point of control. On the other hand, in the feedback automatic control type quantitative feeder shown in FIG. Configure automatic control circuit. In this case, compared to the former case, there is an advantage that it is possible to more quickly follow the commands of the controller 12, and there is no possibility of a control failure. Therefore, other special feeders can also be used as long as they can follow the commands from the controller 12. As described in detail of the invention, the classification work is automatically performed at the maximum capacity of the classifier system, which has the significant effect of increasing production and reducing energy consumption per unit of production. We can expect that. At the same time, since everything is operated automatically, it is thought to greatly contribute to labor savings. On the other hand, abnormalities in the classifier can be automatically detected as soon as they occur. Therefore, there are advantages in that production losses can be reduced and dangerous situations can be prevented at the vehicle nose. Also, if one were to consider doing this manually, the benefits would be much more accurate and less expensive to achieve. Furthermore, a simpler method than the method shown in FIG. 1 is also conceivable. That is, for example, this is an example in which only the flow meter 10 for under-sieving, the controller I2, and the feeder 8 are provided. In this case, as explained in the embodiment section, the controller 12 instructs the feeder 8 to increase the supply by an appropriate percentage. On the other hand, if the flow meter 10 detects an increase in the flow rate by an appropriate percentage, the controller 12 further instructs the feeder 8 to increase the supply by an appropriate percentage. Thus, if flow meter 10 does not detect an increase in flow rate despite the same command, controller 12 will command a reduction in supply. Thus, similar to the above, this classifier system is
It will always continue to operate at maximum capacity. On the other hand, even though the supply amount of the feeder 8 has not increased, the flowmeter 10
If it detects an increase in the flow rate, it means that &l 113 is damaged or some other abnormality has been detected, and an abnormality alarm will be issued. Furthermore, a flowmeter II can be used instead of the flowmeter IO. In this case, although the increase/decrease in the flow rate detected by the flowmeter 11 will be somewhat different from that of the flowmeter 10, it is possible to achieve the same purpose. 4. Brief Description of the Drawings Fig. 1 is a drawing used to explain the present invention in detail, and at the same time, together with Fig. 2, it also shows an embodiment. In addition, Figures 3 and 4 show the machine as a quantitative feeder for powder and granular material 6.
7 Nono? That's what it says. In the figure, l: vibration source 2: wire sieve 3: screen 4: discharge port 5: discharge port 6: granular material 7: hopper 8: feeder 9: input port 10: flow meter 11: flow meter 12: controller 1:1:net 18
i+4: Net 15: wJ16: Inlet

Claims (1)

[Scope of Claims] 1. A function to determine the difference between the ratio of any two flow rates among the flow rates under and above the sieve of the first-stage screen of the classifier, or the flow rates input to the classifier, and a preset normal value. and a function of instructing a feeder that supplies powder and granular material to the classifier to increase or decrease the supply based on the difference. 2. The current supply amount of the feeder that supplies powder and granules to the classifier is automatically increased by a predetermined percentage, and as a result, A) the flow rate under the sieve and above the sieve of the first stage of the classifier, or the If the ratio of any two flow rates among the flow rates input to the classifier does not differ from a preset normal value, the feed rate is further automatically increased by the predetermined percentage. B) If the ratio of any two flow rates among the flow rates under and above the sieve of the first-stage screen of the classifier, or the flow rate input to the classifier, is different from the preset normal value, the supply amount should be adjusted as above. Automatically decrease by a predetermined percentage or a fraction thereof. A method of achieving maximum capacity operation of the classifier by performing the following operations. 3. A function that calculates the difference between the ratio of the flow rate of any two of the flow rates to the bottom and top of the sieve of the classifier, or the flow rate input to the classifier and a preset normal value, and generates an abnormal signal based on the difference. An abnormality detection device for a classifier that is characterized by the following functions: 4. A function to determine the difference between the amount of increase/decrease in the flow rate of either the flow rate under the sieve or the flow rate above the sieve of the first stage of the classifier and the preset normal increase/decrease, and based on the difference, to An automatic control device for the highest capacity operation of a classifier, characterized by having a function of instructing a feeder for supplying granules to increase or decrease the feed. 5. Automatically increase the current supply amount of the feeder that supplies powder and granules to the classifier by a predetermined percentage, and as a result, A) Of the flow rate under or above the sieve of the first stage of the classifier, If there is no difference between the amount of increase in any of the flow rates and the normal amount of increase set in advance, the supply amount is further automatically increased by the predetermined percentage. B) If the amount of increase in either the flow rate under the sieve or above the sieve of the first stage of the classifier is different from the normal increase amount set in advance, the supply amount is increased by the above predetermined percentage, or It will automatically decrease by a fraction of that amount. A method of achieving maximum capacity operation of the classifier by performing the following operations. 6. Features include a function to determine the difference between the flow rate under or above the sieve of the classifier and a preset normal value, and a function to issue an abnormal signal based on the difference. Abnormality detection device for classifier.