JPH10146724A - Electric discharge machining control device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To perform machining under an always optimal machining condition by providing a means to change a numeric value to define a membership function corresponding to qualitative expression according to progress of machining, according to progress of the machining. SOLUTION: A machining progress degree detecting part 9 detects a machining progress degree after maching is started. Here, a machining depth is used as the machining progress degree. The relationship between the machining progress degree and a value to define a membership function is stored in a membership function defining part 11. A numeric value to define the membership function is changed by a membership function editing part 10 according to the machining progress degree, and is controlled so that machining can be performed under a proper machining condition.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an electric discharge machining control device for controlling an electric discharge machine.

[0002]

2. Description of the Related Art FIG. 10 is a flowchart showing a process of determining machining conditions in an electric discharge machining control device. FIG.
The process indicated by 0 uses fuzzy control as a means for setting the processing condition to an appropriate value according to the processing state. In the fuzzy control, determination conditions such as the processing state and the current value of the processing condition are described. It has a fuzzy rule consisting of an antecedent part and a consequent part describing the execution contents based on the judgment result of the antecedent part, and the antecedent part and the consequent part are expressed by a membership function.

In the fuzzy control in the electric discharge machining control device, first, a machining state, a current value of the machining condition, and the like, which are conditions for determining the antecedent part, are detected (step S101). Then, a fuzzy operation is performed on each item to calculate the reliability (step S102). If you find the reliability of the antecedent,
The fuzzy operation of the consequent part is performed (step S103). When the fuzzy calculation is completed, the processing conditions are changed based on the result (step S104).

FIG. 11 is a block diagram showing an example of the configuration of a conventional electric discharge machining control device. A conventional electric discharge machining control device includes a machining state detection unit 1 for detecting a machining state at each time point.
An execution processing condition storage unit 2 for storing processing conditions set at each time, a membership function storage unit 3 for storing a membership function for fuzzy inference, and a fuzzy rule storage unit for storing fuzzy rules 4, a fuzzy operation unit 5 that performs fuzzy inference using the processing state and processing conditions at each time point, a processing condition output unit 6 that determines processing conditions to be output from the result of the fuzzy operation, and a processing condition output unit 6. A machining power supply control unit 7 controls a machining power supply based on output information, and an electrode position control unit 8 controls an electrode position based on information from the machining condition output unit 6.

Here, fuzzy control of a die sinking electric discharge machine in which a ratio of a short-circuit pulse to the total number of pulses (hereinafter referred to as a short-circuit ratio) is input and a jump distance is output is considered.
FIG. 12 shows the fuzzy rule. 13 is a membership function corresponding to "high short-circuit rate" and "low short-circuit rate", FIG. 14 is a membership function corresponding to "short jump distance" and "long jump distance", and FIG. It is a membership function corresponding to "increase the jump distance" and "decrease the jump distance". Now, it is assumed that the short-circuit rate is 70% and the jump distance is 1 mm. FIG.
Since the reliability of “high short-circuit rate” is 1.0 from the membership function of FIG. 1 and the reliability of “short jump distance” is 1.0 from the membership function of FIG.
The reliability of the antecedent part of fuzzy rule 1 of 2 is 1.0
It is. Also, the reliability for “low short-circuit rate” is 0,
Since the reliability for “long jump distance” is 0, the reliability for the antecedent of fuzzy rule 2 is 0. When the output of the jump distance is obtained by the truncation method using the reliability value of the antecedent part of the fuzzy rule 1 and the fuzzy rule 2, the output of the jump distance is +0.6.
Therefore, the jump distance is changed to 1.6 mm.

[0006] It is assumed that the short-circuit rate becomes 10% by this change. Since the reliability for “high short-circuit rate” is 0 and the reliability for “short jump distance” is 0.4,
The reliability of the antecedent part of fuzzy rule 1 is 0.
Further, the reliability of “low short-circuit rate” is 1.0 and the reliability of “long jump distance” is 0.6, so the reliability of the antecedent of fuzzy rule 2 is 0.6.
It is. Since the output of the jump distance -0.3 is obtained from the membership functions of both consequent parts, the jump distance is changed to 1.3 mm.

[0007]

In the prior art, the membership function corresponding to each qualitative expression is fixed irrespective of the progress of machining, so that when the machining state becomes unstable, the machining state becomes stable. The processing conditions are changed as described above, and when the processing state is stabilized, the processing conditions are restored regardless of the progress of the processing. However, appropriate processing conditions change as the processing progresses. In the above example of the control of the jump distance of the die sinking electric discharge machine, the jump distance is increased when the short-circuit rate increases, and the jump distance is shortened when the short-circuit rate decreases. However, the appropriate jump distance depends on the processing depth. To continue processing in a stable state even when the processing proceeds to a deep position, make the jump distance longer than the processing at the time when the processing is not deep. There is a need.
Therefore, the jump distance may be shortened when the short-circuit rate becomes low if the processing has not progressed so deeply, but the jump distance may be reduced when the processing has progressed to a certain depth, even if the short-circuit rate becomes low. It is better not to shorten the distance. However, when the processing conditions are returned to the original state regardless of the progress of the processing as in the conventional technique, the processing state becomes unstable immediately.

[0008]

SUMMARY OF THE INVENTION The present invention relates to a method for determining an appropriate machining condition according to the progress of machining in an electric discharge machining control device for controlling an electric discharge machine. In the first invention, by changing the numerical value defining the membership function corresponding to the qualitative expression according to the progress of processing, the plurality of membership functions are prepared in the second invention, and By switching the membership function according to the progress, the third invention is achieved by performing an arithmetic operation process on input values such as a processing state and a current value of a processing condition input to the antecedent part according to the progress of the processing. You.

According to the present invention, since appropriate processing conditions are determined in accordance with the progress of processing, processing can be continued in a stable state regardless of the progress of processing.

[0010]

FIG. 1 is a block diagram showing a configuration of an electric discharge machining control apparatus according to a first aspect of the present invention. The same parts as those in the related art are denoted by the same reference numerals, and description thereof is omitted.
The electrical discharge machining control apparatus according to the first aspect of the present invention includes a machining progress detection unit 9 for detecting a machining progress, and a membership function editing unit for changing a numerical value defining a membership function according to the progress of machining. A membership function definition unit for storing a relationship between a machining progress degree and a value defining a membership function;

The processing progress detecting section 9 detects the processing progress after the processing is started. Here, the processing depth is used as the processing progress degree. The relationship between the machining progress and the value defining the membership function is determined by the membership function definition unit 1
1 is stored. For example, assuming that the fuzzy rule of FIG. 12 is used, the membership functions corresponding to “short jump distance” and “long jump distance” are represented by
Is defined by the variables DMA and DMB. If the relationship between the processing depth and DMA and DMB is determined as shown in FIG. 3, when the processing depth is 5 mm, the value of DMA is 1 and the value of DMB is 2, and the membership function is shown in FIG.
become that way. When the processing depth is 20 mm, DM
Since the values of A and DMB are 2.0 and 3.0, the membership function is as shown in FIG.

Consider again the fuzzy control of the Die-sinker EDM which takes as input the short-circuit rate for the total number of pulses and outputs the jump distance. The fuzzy rules are the ones in Fig. 12,
The membership functions corresponding to “high short-circuit rate” and “low short-circuit rate” are those in FIG. 13, and the membership functions corresponding to “increase the jump distance” and “short the jump distance” are those in FIG. Use Now the short circuit rate is 7
It is assumed that 0% and the jump distance is 1 mm. The working depth is assumed to be 5 mm. The membership functions corresponding to "short jump distance" and "long jump distance" are shown in FIG.
It becomes 4. The reliability for “high short-circuit rate” is 1.0 from the membership function of FIG. 13, and the reliability for “short jump distance” is 1.0 from the membership function of FIG.
Therefore, the reliability of the antecedent part of the fuzzy rule 1 of FIG. 12 is 1.0. Further, the reliability of “lower short-circuit rate” is 0, and the reliability of “jump distance is longer” is 0, so the reliability of the antecedent of fuzzy rule 2 is 0. When the output of the jump distance is obtained by the truncation method using the value of the reliability of the antecedent part of the fuzzy rule 1 and the fuzzy rule 2, the output of the jump distance is +
0.6. Therefore, the jump distance is changed to 1.6 mm.

It is assumed that the short-circuit rate is reduced to 10% by this change. Since the reliability for “high short-circuit rate” is 0 and the reliability for “short jump distance” is 0.4,
The reliability of the antecedent part of fuzzy rule 1 is 0.
Further, the reliability of “low short-circuit rate” is 1.0 and the reliability of “long jump distance” is 0.6, so the reliability of the antecedent of fuzzy rule 2 is 0.6.
It is. Since the output of the jump distance -0.3 is obtained from the membership functions of both consequent parts, the jump distance is changed to 1.3 mm.

Next, consider the case where the working depth is 20 mm. FIG. 4 shows membership functions corresponding to “short jump distance” and “long jump distance”. Similarly, it is assumed that the short-circuit rate is 70% and the jump distance is 1 mm. Since the reliability of “high short-circuit rate” is 1.0 from the membership function of FIG. 13 and the reliability of “short jump distance” is 1.0 from the membership function of FIG. 14, the fuzzy rule of FIG. The reliability of the antecedent of 1 is 1.0. The reliability for “low short-circuit rate” is 0, and the reliability for “long jump distance” is 0.
Therefore, the reliability of the antecedent part of the fuzzy rule 2 is 0. When the output of the jump distance is obtained by the truncation method using the reliability value of the antecedent part of the fuzzy rule 1 and the fuzzy rule 2, the output of the jump distance is +0.6. Therefore, the jump distance is changed to 1.6 mm.

[0015] It is assumed that the short-circuit rate becomes 10% by this change. Since the reliability for "high short-circuit rate" is 0 and the reliability for "short jump distance" is 1.0,
The reliability of the antecedent part of fuzzy rule 1 is 0.
Also, the reliability of “low short-circuit rate” is 1.0 and the reliability of “long jump distance” is 0, so the reliability of the antecedent of fuzzy rule 2 is 0. Since the output 0 of the jump distance can be obtained from the membership functions of both consequent parts, the jump distance is kept at 1.6 mm. As described above, according to the first aspect of the present invention, by changing the value defining the membership function in accordance with the degree of processing progress, it is possible to control to perform processing under appropriate processing conditions.

FIG. 5 is a block diagram showing a configuration of an electric discharge machining control apparatus according to a second aspect of the present invention. The same parts as those in the prior art and the first invention are denoted by the same reference numerals, and description thereof is omitted. The second electric discharge machining control device according to the present invention includes a membership function storage unit 12 for storing a plurality of membership functions for each qualitative expression, and a qualitative expression for each qualitative expression according to the machining progress. A membership function selection unit 13 for selecting a membership function is provided.

The membership function storage unit 12 stores a plurality of membership functions for each qualitative expression. For example, as membership functions for qualitative expressions such as “short jump distance” and “long jump distance”, three membership functions are prepared as shown in FIGS. 14, 6, and 7, respectively. Then, the membership function selection unit 13 selects an appropriate one from the three membership functions according to the processing progress. For example, when the processing depth is less than 10 mm, FIG. 14 is selected, when the processing depth is 10 mm or more and less than 15 mm, FIG. 6 is selected, and when the processing depth is 15 mm or more, FIG. Shall be selected.

Here, too, consider a fuzzy control of a sinking electric discharge machine in which the short-circuit rate with respect to the total number of pulses is inputted and the jump distance is outputted. The processing depth is used as the processing progress. The fuzzy rules correspond to those in FIG. 12 and the membership functions corresponding to “high short-circuit rate” and “low short-circuit rate” correspond to those in FIG. 13 to “increase the jump distance” and “decrease the jump distance”. The membership function corresponding to FIG. 15 is used. Now, it is assumed that the short-circuit rate is 70% and the jump distance is 1 mm. Assuming that the machining depth is 5 mm, the membership functions corresponding to “short jump distance” and “long jump distance” are as shown in FIG. Since the reliability of “high short-circuit rate” is 1.0 from the membership function of FIG. 13 and the reliability of “short jump distance” is 1.0 from the membership function of FIG. 14, the fuzzy rule of FIG. The reliability of the antecedent of 1 is 1.0. The reliability for “low short-circuit rate” is 0, and the reliability for “long jump distance” is 0.
Therefore, the reliability of the antecedent part of the fuzzy rule 2 is 0. When the output of the jump distance is obtained by the truncation method using the reliability value of the antecedent part of the fuzzy rule 1 and the fuzzy rule 2, the output of the jump distance is +0.6. Therefore, the jump distance is changed to 1.6 mm.

It is assumed that the short-circuit rate becomes 10% by this change. Since the reliability for “high short-circuit rate” is 0 and the reliability for “short jump distance” is 0.4,
The reliability of the antecedent part of fuzzy rule 1 is 0.
Further, the reliability of “low short-circuit rate” is 1.0 and the reliability of “long jump distance” is 0.6, so the reliability of the antecedent of fuzzy rule 2 is 0.6.
It is. Since the output of the jump distance -0.3 is obtained from the membership functions of both consequent parts, the jump distance is changed to 1.3 mm.

Next, consider the case where the working depth is 20 mm. FIG. 4 shows membership functions corresponding to “short jump distance” and “long jump distance”. Similarly, it is assumed that the short-circuit rate is 70% and the jump distance is 1 mm. Since the reliability of “high short-circuit rate” is 1.0 from the membership function of FIG. 13 and the reliability of “short jump distance” is 1.0 from the membership function of FIG. 14, the fuzzy rule of FIG. The reliability of the antecedent of 1 is 1.0. The reliability for “short short-circuit rate” is 0, and the reliability for “long jump distance” is 0.
Therefore, the reliability of the antecedent part of the fuzzy rule 2 is 0. When the output of the jump distance is obtained by the truncation method using the reliability value of the antecedent part of the fuzzy rules 1 and 2, the output of the jump distance is +0.6. Therefore, the jump distance is changed to 1.6 mm.

It is assumed that the short-circuit rate becomes 10% by this change. Since the reliability for "high short-circuit rate" is 0 and the reliability for "short jump distance" is 1.0,
The reliability of the antecedent part of fuzzy rule 1 is 0.
Also, the reliability of “low short-circuit rate” is 1.0 and the reliability of “long jump distance” is 0, so the reliability of the antecedent of fuzzy rule 2 is 0. Since the output 0 of the jump distance can be obtained from the membership functions of both consequent parts, the jump distance is kept at 1.6 mm. As described above, the same effect as that of the first invention can be obtained in the second invention of the present invention.

FIG. 8 is a block diagram showing a configuration of an electric discharge machining control apparatus according to a third aspect of the present invention. The same parts as those of the prior art and the first and second inventions are denoted by the same reference numerals, and description thereof will be omitted. The electric discharge machining control device according to a third aspect of the present invention performs an arithmetic operation on a value representing the machining state detected by the machining state detection unit 1 and a current value of the machining condition stored in the execution machining condition storage unit 2. An input arithmetic processing unit 14 is provided. The input value arithmetic operation processing unit 14 performs an arithmetic operation process corresponding to the degree of processing on the value representing the processing state and the current value of the processing condition, which are input to the antecedent part. For example, a value corresponding to the machining depth is subtracted from the current value of the jump distance as shown in FIG.

As in the past, a fuzzy control of a die sinking electric discharge machine in which the short-circuit rate with respect to the total number of pulses is input and the jump distance is output is considered. The processing depth is used as the processing progress. The fuzzy rules correspond to those in FIG. 12, and the membership functions corresponding to “high short-circuit rate” and “low short-circuit rate” correspond to those in FIG. 13, and correspond to “short jump distance” and “long jump distance”. The membership functions shown in FIG. 14 are used, and those shown in FIG. 15 are used as the membership functions corresponding to “increase the jump distance” and “decrease the jump distance”. Now, it is assumed that the short-circuit rate is 70% and the jump distance is 1 mm. Assuming that the processing depth is 5 mm, since the subtraction value of the jump distance is 0 from FIG. 9, the jump distance is treated as 1 mm as it is. Therefore, the reliability of “high short-circuit rate” is 1.0 from the membership function of FIG. 13, and the reliability of “short jump distance” is 1.0 from the membership function of FIG. The reliability of the fuzzy rule 1 for the antecedent is 1.0. The reliability for “low short-circuit rate” is 0, and the reliability for “long jump distance” is 0.
Therefore, the reliability of the antecedent part of the fuzzy rule 2 is 0. When the output of the jump distance is obtained by the truncation method using the reliability value of the antecedent part of the fuzzy rule 1 and the fuzzy rule 2, the output of the jump distance is +0.6. Therefore, the jump distance is changed to 1.6 mm.

It is assumed that the short-circuit rate becomes 10% by this change. Since the reliability for “high short-circuit rate” is 0 and the reliability for “short jump distance” is 0.4,
The reliability of the antecedent part of fuzzy rule 1 is 0.
Further, the reliability of “low short-circuit rate” is 1.0 and the reliability of “long jump distance” is 0.6, so the reliability of the antecedent of fuzzy rule 2 is 0.6.
It is. Since the output of the jump distance -0.3 is obtained from the membership functions of both consequent parts, the jump distance is changed to 1.3 mm.

Next, consider the case where the working depth is 20 mm. Similarly, short circuit rate is 70%, jump distance is 1mm
And From FIG. 9, the subtraction value of the jump distance is 1 mm
Therefore, the fuzzy operation is performed with the jump distance set to 0 mm. The reliability for “high short-circuit rate” is 1.0 from the membership function of FIG. 13, and the reliability for “short jump distance” is 1.0 from the membership function of FIG.
Therefore, the reliability of the antecedent part of the fuzzy rule 1 of FIG. 12 is 1.0. Further, the reliability of “lower short-circuit rate” is 0, and the reliability of “jump distance is longer” is 0, so the reliability of the antecedent of fuzzy rule 2 is 0. When the output of the jump distance is obtained by the truncation method using the value of the reliability of the antecedent part of the fuzzy rule 1 and the fuzzy rule 2, the output of the jump distance is +
0.6. Therefore, the jump distance is changed to 1.6 mm.

It is assumed that the short-circuit rate becomes 10% by this change. The reliability of “high short circuit rate” is 0, and the jump distance is 0.6 obtained by subtracting 1 mm from the current value of 1.6 mm.
mm, the reliability of “short jump distance” is 1. Therefore, the reliability of the antecedent part of fuzzy rule 1 is zero. Also, the reliability of “low short-circuit rate” is 1.0 and the reliability of “long jump distance” is 0, so the reliability of the antecedent of fuzzy rule 2 is 0. Since the output 0 of the jump distance can be obtained from the membership functions of both consequent parts, the jump distance is kept at 1.6 mm. Thus, Invention 3
In this case, the same effects as those of the first and second aspects can be obtained. In the present embodiment, the jump distance has been described as an object, but the arithmetic operation processing can be similarly applied to all items regardless of the antecedent part and the consequent part.

[0027]

As described above, according to the electric discharge machining control apparatus of the present invention, since appropriate machining conditions are determined in accordance with the progress of machining, machining can always be performed under optimal machining conditions.

[Brief description of the drawings]

FIG. 1 is a block diagram showing an example of an electric discharge machining control device according to a first invention of the present invention.

FIG. 2 is a diagram illustrating an example of a membership function related to a jump distance.

FIG. 3 is a diagram showing an example of values defining a membership function in the first invention.

FIG. 4 is a diagram illustrating an example of a membership function relating to a jump distance.

FIG. 5 is a block diagram showing an example of an electric discharge machining control device according to a second invention of the present invention.

FIG. 6 is a diagram illustrating an example of a membership function relating to a jump distance.

FIG. 7 is a diagram illustrating an example of a membership function relating to a jump distance.

FIG. 8 is a block diagram showing an example of an electric discharge machining control device according to a third aspect of the present invention.

FIG. 9 is a diagram illustrating an example of an arithmetic operation amount with respect to a jump distance.

FIG. 10 is a flowchart showing a flow of processing in the electric discharge machining control device.

FIG. 11 is a diagram showing an example of an electric discharge machining control device according to a conventional technique.

FIG. 12 is a diagram illustrating an example of a fuzzy rule.

FIG. 13 is a diagram illustrating an example of a membership function related to a short-circuit rate.

FIG. 14 is a diagram illustrating an example of a membership function related to a jump distance.

FIG. 15 is a diagram illustrating an example of a membership function related to a jump distance.

[Explanation of symbols]

1 processing state detection unit, 2 execution processing condition storage unit, 3
Membership function storage unit, 4 Fuzzy rule storage unit, 5 Fuzzy operation unit, 6 Processing condition output unit,
7 Machining power control unit, 8 Electrode position control unit, 9 Machining progress detecting unit, 10 Membership function editing unit,
11 Membership function definition part, 12 Membership function storage part, 13 Membership function selection part, 14
Input value arithmetic processing unit.

Claims (3)

[Claims] 1. An electric discharge machine for controlling an electric discharge machine by expressing a consequent part describing a determination condition such as a machining state and a consequent part describing execution contents based on a result of determination of the antecedent part in a fuzzy set. An electric discharge machining control device, characterized in that the control device comprises means for changing a numerical value defining a membership function corresponding to a qualitative expression in accordance with the progress of machining. 2. An electric discharge machine for controlling an electric discharge machine by expressing a consequent part describing a determination condition such as a machining state and a consequent part describing an execution content based on a result of determination of the antecedent part in a fuzzy set. The electric discharge machining, characterized in that the control device is provided with a means for preparing a plurality of membership functions for one qualitative expression and switching a membership function assigned to the qualitative expression as the machining progresses. Control device. 3. An electric discharge machining control device for controlling an electric discharge machine based on an antecedent part in which a determination condition such as a machining state is described and a consequent part in which an execution result based on the determination result of the antecedent part is described. An electric discharge machining control device comprising means for performing an arithmetic operation process on an input value such as a machining state or a current value of a machining condition to be input to an antecedent part according to the progress of machining.