KR102280602B1 - Smart transformer and its accuracy diagnosis method - Google Patents

Abstract

The present invention relates to an intelligent forging system capable of cold forging forming a workpiece such as bolts, nuts, or various pins in multiple steps through a series of steps, and a precise diagnosis method thereof, comprising: a punch block in which at least one punch is installed; a die block in which at least one mold is installed to correspond to the punch; a mold-side pressure sensor installed in the mold or a mold assembly in which the mold is installed so as to sense the load applied from the punch; and a control unit that compares the measured pressure signal applied from the mold-side pressure sensor with a pre-input normal range and outputs an abnormal signal when it deviates from the normal range.

Description

Intelligent forging system and its precise diagnosis method {Smart transformer and its accuracy diagnosis method}

The present invention relates to an intelligent forging system and a precision diagnosis method thereof, and more particularly, to an intelligent forging system capable of cold forging forming a workpiece such as a bolt, a nut or various pins in multiple steps through a series of steps and a precision thereof It relates to diagnostic methods.

In general, forging is one of the metal processing methods for forming a material into a desired shape by applying a compressive load. A conventional forging machine used for this purpose includes a die or a die for supporting a workpiece such as a material to be processed, a die block and It has a structure in which a punch block, etc., on which a tool such as a punch is mounted, is provided, and the punch is reciprocally moved to the die block side using a hydraulic pressure or an electric motor to shape the workpiece into a shape corresponding to the shape of the mold. Among these forging machines, the multi-stage forging machine is one in which a plurality of molds are mounted on a die block, and the molds have slightly different specifications according to the arrangement order, so that the mold corresponding to the molded product to be finally obtained is placed last, and the die block has A transfer for transferring the workpiece is installed, and the workpiece is sequentially transferred to each die by the transfer, and is molded step by step by the molds and finally molded into a desired shape by the last mold.

However, in the conventional multi-stage forging machine, a plurality of molds are mounted on a die block, and during a long molding process, a sintering phenomenon in which foreign substances are attached to the inside of the mold such as a carbide tip may proceed, and the carbide tip is The inner surface of the mold may break off, which may occur.

Even if this burning phenomenon or mold breakage occurs in any one of the plurality of molds, it can have a fatal adverse effect on the subsequent process due to the characteristics of multi-stage forging molding. In particular, it is defective in fasteners such as nuts, bolts, or fixing pins. When this occurs, it can be fatal to the safety of vehicles, buildings, structures, etc. fixed with these defective fixtures.

The present invention is intended to solve various problems including the above problems, and by mounting pressure sensors in each mold assembly, abnormalities of each mold can be detected in real time, and the coincidence rate between the measured pressure and the reference value It is possible to detect the lifespan of the mold by considering the change in , and by accumulating deviations, it is possible to prevent the occurrence of defective products at the source by detecting whether the deformation energy received by the workpiece during the multi-stage forging process is exceeded. An object of the present invention is to provide an intelligent forging system capable of detecting even the abnormality of blocks by detecting a signal difference between the pressure sensors and a precise diagnosis method thereof. However, these problems are exemplary, and the scope of the present invention is not limited thereto.

Intelligent forging system according to the spirit of the present invention for solving the above problems, the punch block at least one or more punches are installed; a die block in which at least one mold is installed to correspond to the punch; a mold-side pressure sensor installed in the mold or a mold assembly in which the mold is installed so as to sense the load applied from the punch; and a control unit that compares the measured pressure signal applied from the mold-side pressure sensor with a pre-input normal range and outputs an abnormal signal when it deviates from the normal range.

In addition, according to the present invention, the controller is configured to store information about an expected reference waveform of a normal expected pressure signal, an expected upper limit waveform that is allowed to be high from the expected reference waveform, and an expected lower limit waveform that is allowed to be low from the expected reference waveform. predicted waveform storage; a measured pressure determining unit for determining whether the measured pressure signal is within a normal range between the expected upper limit waveform and the expected lower limit waveform; a normal determination signal output unit for outputting a normal determination signal when the measured pressure signal falls within a normal range between the expected upper limit waveform and the expected lower limit waveform; and an abnormality determination signal output unit configured to output an abnormality determination signal when the measured pressure signal is out of a normal range between the expected upper limit waveform and the expected lower limit waveform.

Further, according to the present invention, the control unit calculates the coincidence rate or the coincidence rate between the measured pressure signal and the expected reference waveform, and measures the change in the coincidence rate or the change in the coincidence rate to predict the lifespan of the mold. It may further include;

In addition, according to the present invention, the workpiece is forged in the primary mold, and then transferred to the secondary mold, and then forged in the secondary mold, and then transferred to the tertiary mold. may be a cold multi-stage forging type punch block in which a plurality of the punches are installed in a line, and the die block may be a cold multi-stage forging type mold block in which a plurality of the molds are installed in parallel to correspond to the punches.

In addition, according to the present invention, the mold-side pressure sensor may include: a first sensor installed in the primary mold or the primary mold assembly; a second sensor installed in the secondary mold or the secondary mold assembly; and a third sensor installed in the tertiary mold or the tertiary mold assembly, wherein the control unit calculates a deviation rate or degree of deviation between the measured pressure signal measured by the first sensor and the expected reference waveform and calculating a deviation rate or degree of deviation between the measured pressure signal measured by the second sensor and the expected reference waveform, and a deviation rate or degree of deviation between the measured pressure signal measured by the third sensor and the expected reference waveform a deviation accumulation unit that calculates , and calculates a cumulative sum of the deviation rates or the deviation degrees; a cumulative pressure determining unit that determines whether the cumulative total value is within a normal range; a normal accumulation signal output unit for outputting a normal accumulation determination signal when the accumulated sum value falls within the normal range; and an abnormal accumulation signal output unit for outputting an abnormal accumulation determination signal when the measured total value is out of the normal range.

In addition, according to the present invention, the mold assembly includes a carbide tip having a cavity into which a workpiece is inserted so as to correspond to the punch, a supporter supporting the lower surface of the carbide tip, and the outer diameter of the carbide tip and the supporter a mold comprising a bushing surrounding the face; and a spacer in which an upper surface of the mold is in contact with a lower surface of the supporter and a lower surface of the bushing so that the pressure of the mold is transmitted, and a vertical groove is formed on one side in a direction perpendicular to the pressure direction of the mold. The mold-side pressure sensor may include a piezo element inserted into the vertical groove of the spacer and converting the pressure transmitted to the spacer into a current form.

In addition, according to the present invention, the punch or the punch side pressure sensor installed in the punch assembly is installed; Further comprising, the control unit may compare the measured pressure signal applied from the punch-side pressure sensor with a pre-input normal range and output an abnormal signal when it is out of this range.

On the other hand, the precision diagnosis method of the intelligent forging system according to the spirit of the present invention for solving the above problems, a punch block in which at least one punch is installed, a die block in which at least one mold is installed to correspond to the punch, the punch In order to sense the load applied from the mold, the mold side pressure sensor installed in the mold or the mold assembly in which the mold is installed and the measured pressure signal applied from the mold side pressure sensor are compared with the pre-input normal range, and if it deviates from the normal range, abnormal In the precise diagnosis method of an intelligent forging system comprising a control unit for outputting a signal, an expected reference waveform of a normal expected pressure signal, an expected upper limit waveform that is allowed to be high from the expected reference waveform, and an expected lower limit that is allowed to be low from the expected reference waveform an expected waveform storage step of storing information about the waveform; a measured pressure determination step of determining whether the measured pressure signal falls within a normal range between the expected upper limit waveform and the expected lower limit waveform; a normal determination signal output step of outputting a normal determination signal when the measured pressure signal falls within a normal range between the expected upper limit waveform and the expected lower limit waveform; an abnormality discrimination signal output step of outputting an abnormality discrimination signal when the measured pressure signal is out of a normal range between the expected upper limit waveform and the expected lower limit waveform; and a mold life prediction step of calculating a coincidence rate or coincidence rate between the measured pressure signal and the expected reference waveform, and predicting the lifespan of the mold by measuring a change in the coincidence rate or a change in the coincidence rate.

In addition, according to the present invention, the mold-side pressure sensor may include: a first sensor installed in the primary mold or the primary mold assembly; a second sensor installed in the secondary mold or the secondary mold assembly; and a third sensor installed in the tertiary mold or the tertiary mold assembly, wherein a deviation rate or degree of deviation between the measured pressure signal measured by the first sensor and the expected reference waveform is calculated, and the second calculating a deviation rate or degree of deviation between the measured pressure signal measured by the second sensor and the expected reference waveform, and calculating a deviation rate or degree of deviation between the measured pressure signal measured by the third sensor and the expected reference waveform, a deviation accumulation step of calculating a cumulative sum of the deviation rates or the deviation degrees; a cumulative pressure determination step of determining whether the cumulative total value is within a normal range; a normal accumulation signal output step of outputting a normal accumulation determination signal when the accumulated sum value falls within the normal range; and an abnormal accumulation signal output step of outputting an abnormal accumulation determination signal when the measured total value is out of the normal range.

According to some embodiments of the present invention made as described above, by mounting pressure sensors on each mold assembly, abnormalities of each mold can be detected in real time, and changes in the coincidence rate between the measured pressure and the reference value can be detected. It is possible to detect the life of the mold by taking this into account, and by accumulating deviations, it is possible to fundamentally prevent the occurrence of defective products by detecting whether the deformation energy that the workpiece receives during the multi-stage forging process is exceeded, and the pressure sensor between the die block and the punch block. It has the effect of detecting even the abnormality of blocks by detecting the signal difference of Of course, the scope of the present invention is not limited by these effects.

1 is an external perspective view of an intelligent forging system according to some embodiments of the present invention.
Figure 2 is a cross-sectional view of the intelligent forging system of Figure 1;
3 is an enlarged cross-sectional view showing an enlarged die block of the intelligent forging system of FIG. 2 .
4 is a perspective view illustrating a mold assembly of the intelligent forging system of FIG. 3 .
FIG. 5 is a partially cut-away perspective view showing a mold assembly of the intelligent forging system of FIG. 4 .
FIG. 6 is a graph illustrating an example of a measured pressure signal detected by a pressure sensor on a mold side of the intelligent forging system of FIG. 2 .
7 is a block diagram illustrating a control unit of the intelligent forging system of FIG. 2 .
8 is a flowchart illustrating a precision diagnosis method of an intelligent forging system according to some embodiments of the present invention.
9 and 10 are photographs showing the breakage of the mold according to the sintering phenomenon, such as a cemented carbide tip generated in the mold of the conventional forging machine.
11 to 15 are diagrams showing step-by-step examples of numerical analysis diagrams and load graphs during step-by-step molding of the intelligent forging system according to some embodiments of the present invention.

Hereinafter, several preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings.

Examples of the present invention are provided to more completely explain the present invention to those of ordinary skill in the art, and the following examples may be modified in various other forms, and the scope of the present invention is as follows It is not limited to an Example. Rather, these embodiments are provided so as to more fully and complete the present disclosure, and to fully convey the spirit of the present invention to those skilled in the art. In addition, in the drawings, the thickness or size of each layer is exaggerated for convenience and clarity of description.

Throughout the specification, when referring to one component, such as a film, region, or substrate, being located "on," "connected to," "stacked with," or "coupled to," another component, the one component. It may be construed that an element may be directly in contact with, “on,” “connected to,” “stacked with,” or “coupled to,” another element, or that there may be other elements intervening therebetween. On the other hand, when it is stated that one element is located "directly on," "directly connected to," or "directly coupled to," another element, it is construed that there are no other elements interposed therebetween. do. Like numbers refer to like elements. As used herein, the term “and/or” includes any one and any combination of one or more of those listed items.

Although the terms first, second, etc. are used herein to describe various members, parts, regions, layers and/or parts, these members, parts, regions, layers and/or parts are limited by these terms so that they It is self-evident that These terms are used only to distinguish one member, component, region, layer or portion from another region, layer or portion. Accordingly, a first member, component, region, layer or portion discussed below may refer to a second member, component, region, layer or portion without departing from the teachings of the present invention.

Also, relative terms such as "above" or "above" and "below" or "below" may be used herein to describe the relationship of certain elements to other elements as illustrated in the drawings. It may be understood that relative terms are intended to include other orientations of the element in addition to the orientation depicted in the drawings. For example, if an element is turned over in the figures, elements depicted as being on the face above the other elements will have orientation on the face below the other elements. Thus, the term “top” by way of example may include both “bottom” and “top” directions depending on the particular orientation of the drawing. If the element is oriented in a different orientation (rotated 90 degrees relative to the other orientation), the relative descriptions used herein may be interpreted accordingly.

The terminology used herein is used to describe specific embodiments, not to limit the present invention. As used herein, the singular forms may include the plural forms unless the context clearly dictates otherwise. Also, as used herein, “comprise” and/or “comprising” refers to the presence of the recited shapes, numbers, steps, actions, members, elements, and/or groups of those specified. and does not exclude the presence or addition of one or more other shapes, numbers, movements, members, elements and/or groups.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of the present invention will be described with reference to the drawings schematically illustrating ideal embodiments of the present invention. In the drawings, variations of the illustrated shape can be expected, for example depending on manufacturing technology and/or tolerances. Accordingly, embodiments of the inventive concept should not be construed as limited to the specific shape of the region shown in the present specification, but should include, for example, changes in shape caused by manufacturing.

1 is an external perspective view of an intelligent forging system 100 according to some embodiments of the present invention, and FIG. 2 is a cross-sectional view of the intelligent forging system 100 of FIG. 1 .

First, as shown in FIGS. 1 and 2 , the intelligent forging system 100 according to some embodiments of the present invention includes a punch block 10 in which at least one punch P is installed, and the punch ( A die block 20 in which at least one mold M is installed to correspond to P), and the mold M or a mold in which the mold M is installed so as to sense the load applied from the punch P A control unit 40 that compares the mold-side pressure sensor S1 installed in the assembly 30 and the measured pressure signal applied from the mold-side pressure sensor S1 with a pre-input normal range and outputs an abnormal signal when it is out of this range may include.

Here, for example, the intelligent forging system 100 according to some embodiments of the present invention is a kind of equipment that can cold forge a workpiece such as a bolt, a nut, or various pins in multiple steps through a series of steps. can

However, the present invention is not necessarily limited to multi-stage cold forging, and can be applied to all forging equipment having the punch block 10 and the die block 20 described above.

More specifically, for example, the workpiece 1 is first forged in the primary mold M1, transferred to the secondary mold M2, and secondarily forged in the secondary mold M2. , the punch block 10 is a cold multi-stage forging type punch block in which a plurality of the punches P1, P2, and P3 are installed in a line so as to be transferred to the tertiary mold M3, and the die block 20 ) may be a cold multi-stage forging mold block in which a plurality of the molds M1, M2, and M3 are installed side by side to correspond to the punches P1, P2, and P3.

However, the technical idea of the present invention can be applied to all forging equipment of two or more stages, and although three stages are illustrated in the drawings, all of the two stages or more than three stages can be applied to forging equipment.

In addition, for example, as shown in FIGS. 1 and 2 , the mold-side pressure sensor S1 of the intelligent forging system 100 according to some embodiments of the present invention is the primary mold M1 or the The first sensor S11 installed in the primary mold assembly 30, the second sensor S12 installed in the secondary mold M2 or the secondary mold assembly 30, and the tertiary mold M3 ) or a third sensor S13 installed in the tertiary mold assembly 30 may be included.

However, the technical idea of the present invention can be applied to all equipment in which two or more sensors are installed, and although three sensors are exemplified in the drawing, it can be applied to all forging equipment in which two or three or more sensors are installed. .

3 is an enlarged cross-sectional view showing an enlarged die block 20 of the intelligent forging system 100 of FIG. 2 , and FIG. 4 is a perspective view showing the mold assembly 30 of the intelligent forging system 100 of FIG. 3 , FIG. 5 is a partially cut-away perspective view showing the mold assembly 30 of the intelligent forging system 100 of FIG. 4 .

More specifically, for example, as shown in FIGS. 1 to 5 , the mold assembly 30 has a cemented carbide tip 31 in which a cavity into which the workpiece 1 is inserted to correspond to the punch is formed. And, a supporter 32 for supporting the lower surface of the carbide tip 31 and a primary mold (M1) comprising a bushing 33 surrounding the outer diameter surface of the carbide tip 31 and the supporter 32, and The upper surface of the primary mold M1 is in contact with the lower surface of the supporter 32 and the lower surface of the bushing 33 so that the pressure of the primary mold M1 is transmitted, and the primary mold M1 on one side. It may include a spacer 34 in which a vertical groove (G) formed in a direction perpendicular to the pressure direction is formed.

Here, a through hole through which the eject pin 35 of FIGS. 2 and 3 can pass is formed in the primary mold M1, the supporter 32, and the spacer 34, so that after the primary molding, the workpiece (1) may be discharged to the outside of the primary mold (M1).

In addition, the first sensor S11 is inserted into the vertical groove G of the spacer 34 , and a piezo element that converts the pressure transmitted to the spacer 34 into a current form is applied. can

Therefore, when the punch P molds the workpiece 1, a molding load is transmitted to the primary mold M1, which is transmitted to the spacer 34 through the supporter 32, In this case, the first sensor S11 may convert the load applied to the spacer 34 into an electrical signal, that is, a current, and apply it to the controller 40 .

6 is a graph illustrating an example of a measured pressure signal detected by the mold side pressure sensor S1 of the intelligent forging system 100 of FIG. 2 .

For example, as shown in FIG. 6 , the measured pressure signal WW sensed by each of the mold-side pressure sensors S1 gradually increases over time to achieve a peak value, and has a pattern that gradually decreases again.

However, these patterns may vary depending on the type of mold, the use environment, the specification of the workpiece, and the like, and FIG. 6 illustrates the overall trend to help the description.

7 is a block diagram illustrating the control unit 40 of the intelligent forging system 100 of FIG. 2 .

1 to 7 , the controller 40 of the intelligent forging system 100 according to some embodiments of the present invention includes an expected reference waveform W1 of the normal expected pressure signal of FIG. 6 and the The expected waveform storage unit 41 for storing information on the expected upper limit waveform W2 allowed to be high from the expected reference waveform and the expected lower limit waveform W3 allowed to be low from the expected reference waveform, and the measured pressure signal of FIG. 6 . A measured pressure determining unit 42 that determines whether (WW) is within a normal range between the expected upper limit waveform W2 and the expected lower limit waveform W3, and the measured pressure signal WW is the expected upper limit waveform ( If it falls within the normal range A between W2) and the expected lower limit waveform W3, the normal discrimination signal output unit 43 that outputs a normal discrimination signal and the measured pressure signal WW are the expected upper limit waveform W2 and an abnormality discrimination signal output unit 44 for outputting an abnormality discrimination signal when it is outside the normal range A between the and the expected lower limit waveform W3 .

Accordingly, the control unit 40 of the present invention includes an expected reference waveform W1 of a normal expected pressure signal, an expected upper limit waveform W2 that is allowed to be high from the expected reference waveform, and an expected lower limit that is allowed to be low from the expected reference waveform. Storing information on the waveform W3, determining whether the measured pressure signal WW falls within a normal range between the expected upper limit waveform W2 and the expected lower limit waveform W3, and the measured pressure signal WW ) is within the normal range (A) between the expected upper limit waveform (W2) and the expected lower limit waveform (W3), output a normal determination signal, or the measured pressure signal (WW) is the expected upper limit waveform (W2) and If it is out of the normal range A between the expected lower limit waveform W3, a series of steps of outputting an abnormality determination signal may be performed.

Therefore, by mounting a plurality of the mold-side pressure sensors S11, S12, and S13 in each of the mold assemblies 30, abnormalities in each of the molds M1, M2, and M3 are detected in real time. When an abnormality occurs in one or more of the molds M1, M2, and M3, the user or operator is promptly notified of the occurrence of an abnormality in the mold. You can take immediate follow-up action before it causes any harm.

In addition, for example, as shown in FIG. 7 , the control unit 40 calculates a coincidence rate or degree of coincidence between the measured pressure signal WW and the expected reference waveform W1, and determines the change in the coincidence rate or the coincidence degree. It may further include a mold life prediction unit 45 for predicting the life of the mold by measuring the change.

Therefore, for example, if the coincidence rate between the actual measured value and the expected reference value was 99% or more in the first month, but if the coincidence rate decreased by 1% to 98% after one month, if the discrepancy rate at failure decreases by 1% every month to 80%, after 10 months Since the possibility of failure is high, it is possible to respond by predicting the life of the mold in advance, such as preparing the mold in advance after 10 months.

Therefore, it is possible to predict the individual lifespans of each of the molds M1, M2, and M3 in advance in consideration of the change in the coincidence rate between the measurement pressure and the reference value, and perform follow-up measures.

In addition, as shown in FIGS. 1 to 7 , the control unit 40 includes a deviation rate or deviation between the measured pressure signal WW measured by the first sensor S11 and the expected reference waveform W1 . and calculating a deviation rate or deviation K between the measured pressure signal WW measured by the second sensor S12 and the expected reference waveform W1, and the third sensor S13 a deviation accumulator 46 for calculating a deviation rate or degree of deviation between the measured pressure signal WW and the expected reference waveform W1 measured at , a cumulative pressure determining unit 47 that determines whether the cumulative total value is within a normal range, a normal cumulative signal output unit 48 that outputs a normal cumulative discrimination signal when the cumulative total value falls within the normal range, and the measured total value It may further include an abnormal accumulation signal output unit 49 for outputting an abnormal accumulation determination signal when is out of the normal range.

Accordingly, the control unit 40 of the present invention includes the measured pressure signal WW and the expected reference waveform measured by the first sensor S11, the second sensor S12, and the third sensor S13. Calculate the deviation rate or degree of deviation of (W1), respectively, calculate the cumulative sum of these deviation rates or the degree of deviation, determine whether the cumulative sum value is within a normal range, and the cumulative total value falls within the normal range A series of steps of outputting a normal accumulation determination signal or outputting an abnormal accumulation determination signal when the measured total value is out of the normal range may be performed.

Therefore, it is possible to fundamentally prevent the occurrence of defective products by accumulating the deviation between the actual value and the ideal value generated in each mold and detecting whether the deformation energy received by the workpiece in the multi-stage forging process is exceeded.

If the total amount of deformation energy that the workpiece 1 receives in the multi-stage forging process exceeds the normal value, the workpiece 1 does not overcome it and cracks or breaks inside and outside, or is easily damaged by various impact loads, etc. defective products may occur. The present invention can prevent in advance not only the mold, but also such defects of the workpiece.

On the other hand, as shown in Figures 1 and 2, the intelligent forging system 100 according to some embodiments of the present invention, the punch (P) or the punch side installed in the punch assembly in which the punch (P) is installed It may further include a pressure sensor (S2).

Accordingly, the control unit 40 may compare the measured pressure signal applied from the punch side pressure sensor S2 with a pre-input normal range, and output an abnormal signal when it is out of this range.

In addition, the control unit 40 can detect even the abnormality of the blocks by detecting a signal difference between the pressure sensors S1 and S2 between the die block 20 and the punch block 10 .

Therefore, for example, when the signal difference of the pressure sensors S1 and S2 between the die block 20 and the punch block 10 is out of normal value, an abnormal abnormality has occurred in either one or the pressure acts non-uniformly. It can be determined that the user or operator has taken follow-up action.

8 is a flowchart illustrating a precision diagnosis method of the intelligent forging system 100 according to some embodiments of the present invention.

As shown in FIGS. 1 to 8 , the precision diagnosis method of the intelligent forging system 100 according to some embodiments of the present invention, in the diagnosis process of the first mold, is normally performed in the first sensor S11. Information on the expected reference waveform W1 of the expected pressure signal, the expected upper limit waveform W2 that is allowed to be high from the expected reference waveform W1, and the expected lower limit waveform W3 that is allowed to be low from the expected reference waveform W1 The expected waveform storage step (S110) of storing, and the measured pressure signal (WW) measured by the first sensor (S11) is a normal range between the expected upper limit waveform (W2) and the expected lower limit waveform (W3) ( The measured pressure determination step (S120) to determine whether it belongs to A), and to determine whether it belongs to the normal range (S130), and the measured pressure signal (WW) is the expected upper limit waveform (W2) and the expected lower limit waveform (W3) A normal discrimination signal output step (S140) of outputting a normal discrimination signal if it belongs to the normal range (A) between the, and the measured pressure signal (WW) is between the expected upper limit waveform (W2) and the expected lower limit waveform (W3) When out of the normal range (A) of the abnormality discrimination signal output step (S150) of outputting an abnormality discrimination signal, and calculating the agreement rate or degree of agreement between the measured pressure signal and the expected reference waveform (W1), the change in the agreement rate or the It may include a mold life prediction step (S160) of predicting the life of the mold by measuring the change in coincidence.

In addition, for example, in the diagnosis process of the second mold, the expected reference waveform W1 of the normal expected pressure signal from the second sensor S12 and the expected upper limit waveform W2 allowed to be high from the expected reference waveform W1 ) and an expected waveform storage step (S210) of storing information on an expected lower limit waveform (W3) that is allowed to be low from the expected reference waveform (W1), and the measured pressure signal (WW) measured by the second sensor (S12) ) of the measured pressure determination step (S220) to determine whether it belongs to the normal range (A) between the expected upper limit waveform (W2) and the expected lower limit waveform (W3), and to determine whether it belongs to the normal range (S230), the When the measurement pressure signal WW falls within the normal range A between the expected upper limit waveform W2 and the expected lower limit waveform W3, a normal discrimination signal output step S240 of outputting a normal discrimination signal; When the pressure signal WW is out of the normal range A between the expected upper limit waveform W2 and the expected lower limit waveform W3, an abnormality discrimination signal output step S250 of outputting an abnormality discrimination signal and the measured pressure signal and a mold life prediction step (S260) of calculating the coincidence rate or the coincidence degree of the expected reference waveform W1, and predicting the lifespan of the mold by measuring the change in the coincidence rate or the change in the coincidence degree.

In addition, for example, in the diagnostic process of the third mold, the expected reference waveform W1 of the normal expected pressure signal from the third sensor S13 and the expected upper limit waveform W2 allowed to be high from the expected reference waveform W1 ) and an expected waveform storage step (S310) of storing information on an expected lower limit waveform (W3) that is allowed to be low from the expected reference waveform (W1), and the measured pressure signal (WW) measured by the third sensor (S13) ) is measured pressure determination step (S320) to determine whether it belongs to the normal range (A) between the expected upper limit waveform (W2) and the expected lower limit waveform (W3), and to determine whether it belongs to the normal range (S330), the When the measurement pressure signal WW falls within the normal range A between the expected upper limit waveform W2 and the expected lower limit waveform W3, a normal discrimination signal output step (S340) of outputting a normal discrimination signal; When the pressure signal WW is out of the normal range A between the expected upper limit waveform W2 and the expected lower limit waveform W3, an abnormality discrimination signal output step S350 of outputting an abnormality discrimination signal and the measured pressure signal and a mold life prediction step (S360) of calculating the coincidence rate or the coincidence degree of the expected reference waveform W1, and predicting the lifespan of the mold by measuring the change in the coincidence rate or the change in the coincidence rate.

Next, the precision diagnosis method of the intelligent forging system 100 according to some embodiments of the present invention is measured by the first sensor S11, the second sensor S12, and the third sensor S13. a deviation accumulation step (S410) of calculating a deviation rate or degree of deviation between the measured pressure signal WW and the expected reference waveform W1, and calculating a cumulative sum of the deviation rates or the deviation degrees; A normal cumulative pressure determination step (S420) of determining whether is within a normal range, determining whether the cumulative total value is within a normal range (S430), and outputting a normal cumulative determination signal if the cumulative total value is within the normal range The step of outputting the accumulated signal ( S440 ) and the step of outputting an abnormal accumulation signal ( S450 ) of outputting an abnormal accumulation determination signal when the measured sum is out of the normal range may be included.

Here, the deviation rates or the deviation degrees can be summed up by the number of sensors, and by comparing the theoretical sum of the intermediate or final stage with the actual sum, it can be determined step by step whether the accumulated strain energy falls within the normal range. .

For example, if the workpiece 1 is within the normal range in the first and second steps, but the amount of deformation is insufficient, it can be determined that no defective product is generated even if the amount of deformation slightly exceeds the normal range in the third step, and vice versa , If the amount of deformation of the workpiece 1 is within the normal range in the first, second, and third orders, but excess energy is accumulated at each step, and the total sum of the final deformation energy exceeds the total normal range, a defective product is generated. It can be predicted that the probability of

9 and 10 are photographs showing the breakage of the mold according to the sintering phenomenon, such as a cemented carbide tip generated in the mold of the conventional forging machine.

As shown in FIGS. 9 and 10 , in the conventional forging machine, it can be confirmed that foreign materials are sintered in the mold so that the cemented carbide tip is damaged or falls off.

11 to 15 are diagrams showing step-by-step examples of numerical analysis diagrams and load graphs during step-by-step forming of an intelligent forging system according to some embodiments of the present invention.

11 to 15, the maximum expected loads and actual pressure measurement graphs of the loads acting on each mold through a total of 5 steps from STEP1 to STEP5 are different, and numerical analysis is performed according to the shape of each step. As shown, since the pressure distributions are all different, theoretical normal graphs can be extracted through these repeated experiments and numerical analysis, and the present invention provides real-time pressure values outside the normal range of these normal graphs or their cumulative sum in real time. It is possible to immediately check the abnormal state of each mold or work piece by detecting it.

Here, the peak value of each load graph may vary depending on the shape of the actual mold or the specification of the workpiece, and the numerical analysis may also vary depending on the numerical analysis method or numerical value.

Although the present invention has been described with reference to the embodiment shown in the drawings, which is merely exemplary, those skilled in the art will understand that various modifications and equivalent other embodiments are possible therefrom. Therefore, the true technical protection scope of the present invention should be determined by the technical spirit of the appended claims.

1: Workpiece
10: punch block
P: punch
P1: 1st punch
P2: 2nd punch
P3: 3rd Punch
20: die block
M: mold
M1: Primary mold
M2: secondary mold
M3: 3rd mold
30: mold assembly
31: carbide tip
32: supporter
33: bushing
34: spacer
35: eject pin
G: vertical groove
S1: mold side pressure sensor
S11: first sensor
S12: second sensor
S13: third sensor
S2: Punch side pressure sensor
40: control unit
W1: Expected reference waveform
W2: Expected upper limit waveform
W3: Expected lower limit waveform
WW: Measured pressure signal
A: normal range
41: expected waveform storage
42: measurement pressure determination unit
43: normal determination signal output unit
44: abnormal determination signal output unit
45: mold life prediction part
46: deviation accumulation part
47: cumulative pressure determination unit
48: normal accumulation signal output unit
49: abnormal accumulation signal output unit
100: intelligent forging system

Claims (9)

A plurality of punches are arranged in a row so that the workpiece is forged in the primary mold, transferred to the secondary mold, forged in the secondary mold, and then transferred to the tertiary mold for cold multi-stage forging Punch blocks installed with;
a die block in which a plurality of molds are installed side by side to correspond to the punches;
a mold-side pressure sensor installed in the mold or a mold assembly in which the mold is installed so as to sense the load applied from the punch; and
A control unit that compares the measured pressure signal applied from the mold-side pressure sensor with a pre-input normal range and outputs an abnormal signal when it is out of this range;
The mold side pressure sensor,
a first sensor installed in the primary mold or the primary mold assembly;
a second sensor installed in the secondary mold or the secondary mold assembly; and
Including; a third sensor installed in the tertiary mold or the tertiary mold assembly;
The control unit is
The deviation rate or degree of deviation between the expected reference waveform of the measured pressure signal measured by the first sensor and the normal expected pressure signal is calculated, and the deviation rate between the measured pressure signal measured by the second sensor and the expected reference waveform, or A deviation accumulation unit that calculates a degree of deviation, calculates a deviation rate or degree of deviation between the measured pressure signal measured by the third sensor and the expected reference waveform, and calculates a cumulative sum of the deviation rates or the degree of deviation ;
a cumulative pressure determining unit that determines whether the cumulative total value is within a normal range;
a normal accumulation signal output unit for outputting a normal accumulation determination signal when the accumulated sum value falls within the normal range; and
an abnormal accumulation signal output unit for outputting an abnormal accumulation determination signal when the accumulated total value is out of the normal range;
Including, intelligent forging system. The method of claim 1,
The control unit is
a predicted waveform storage unit configured to store information on the predicted reference waveform, an expected upper limit waveform that is allowed to be high from the predicted reference waveform, and an expected lower limit waveform that is allowed to be low from the expected reference waveform;
a measured pressure determining unit for determining whether the measured pressure signal is within a normal range between the expected upper limit waveform and the expected lower limit waveform;
a normal determination signal output unit for outputting a normal determination signal when the measured pressure signal falls within a normal range between the expected upper limit waveform and the expected lower limit waveform; and
an abnormality discrimination signal output unit for outputting an abnormality discrimination signal when the measured pressure signal is out of a normal range between the expected upper limit waveform and the expected lower limit waveform;
Including, intelligent forging system. 3. The method of claim 2,
The control unit is
a mold life prediction unit calculating a matching rate or degree of agreement between the measured pressure signal and the expected reference waveform, and predicting a lifespan of the mold by measuring a change in the coincidence rate or a change in the coincidence degree;
Further comprising, an intelligent forging system. delete delete The method of claim 1,
The mold assembly,
A mold comprising: a carbide tip having a cavity into which a workpiece is inserted to correspond to the punch, a supporter supporting a lower surface of the carbide tip, and a bushing surrounding the carbide tip and an outer diameter of the supporter; and
and a spacer having an upper surface in contact with a lower surface of the supporter and a lower surface of the bushing of the mold to transmit the pressure of the mold, and having a vertical groove formed on one side in a direction perpendicular to the pressure direction of the mold.
The mold side pressure sensor,
a piezo element inserted into the vertical groove of the spacer and converting the pressure transmitted to the spacer into a current form;
Including, intelligent forging system. The method of claim 1,
a punch-side pressure sensor installed in the punch or a punch assembly in which the punch is installed;
further comprising,
The control unit is
An intelligent forging system that compares the measured pressure signal applied from the punch side pressure sensor with a pre-input normal range and outputs an abnormal signal when it is out of this range. A punch block in which at least one punch is installed, a die block in which at least one mold is installed to correspond to the punch, and a mold side installed in the mold or a mold assembly in which the mold is installed so as to sense a load applied from the punch In the precision diagnosis method of an intelligent forging system, comprising: a pressure sensor and a control unit that compares the measured pressure signal applied from the mold side pressure sensor with a pre-input normal range and outputs an abnormal signal when it is out of the normal range,
a predicted waveform storing step of storing information on an expected reference waveform of a normal expected pressure signal, an expected upper limit waveform that is allowed to be high from the expected reference waveform, and an expected lower limit waveform that is allowed to be low from the expected reference waveform;
a measured pressure determination step of determining whether the measured pressure signal falls within a normal range between the expected upper limit waveform and the expected lower limit waveform;
a normal determination signal output step of outputting a normal determination signal when the measured pressure signal falls within a normal range between the expected upper limit waveform and the expected lower limit waveform;
an abnormality discrimination signal output step of outputting an abnormality discrimination signal when the measured pressure signal is out of a normal range between the expected upper limit waveform and the expected lower limit waveform; and
A mold life prediction step of calculating a coincidence rate or coincidence rate between the measured pressure signal and the expected reference waveform, and predicting the lifespan of the mold by measuring a change in the coincidence rate or a change in the coincidence rate;
The mold side pressure sensor,
a first sensor installed in the primary mold or the primary mold assembly;
a second sensor installed in the secondary mold or the secondary mold assembly; and
Including; a third sensor installed in the tertiary mold or the tertiary mold assembly;
A deviation rate or degree of deviation between the measured pressure signal measured by the first sensor and the expected reference waveform is calculated, and a deviation rate or degree of deviation between the measured pressure signal measured by the second sensor and the expected reference waveform is calculated. a deviation accumulation step of calculating a deviation rate or degree of deviation between the measured pressure signal measured by the third sensor and the expected reference waveform, and calculating a cumulative sum of the deviation rates or the degree of deviation;
a cumulative pressure determination step of determining whether the cumulative total value is within a normal range;
a normal accumulation signal output step of outputting a normal accumulation determination signal when the accumulated sum value falls within the normal range; and
an abnormal accumulation signal output step of outputting an abnormal accumulation determination signal when the accumulated sum value is out of the normal range;
Further comprising, a precision diagnostic method of an intelligent forging system. delete

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