JP2003112350A - Method for evaluating molding condition of resin molding, method for comparing article shape, and method for evaluating article shape - Google Patents

Abstract

PROBLEM TO BE SOLVED: To objectively evaluate a difference between two shapes. SOLUTION: The method for evaluating the molding conditions of a resin molding comprises a nodal point dealing step of defining dealing of a nodal point between both shape data by using a shape data group made of the coordinate group of the arbitrary number of nodal points in which line segments for shaping the shape are intersected at the shapes of both the object articles (step S10), and an evaluating value calculating step of calculating a root mean square of a distance for connecting the nodal points of both the object articles dealt with the nodal point dealing step as an evaluating value for indicating the difference of the shapes of the two object articles (step S20).

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention numerically represents the difference between the shape of a resin molded body obtained by molding under a predetermined molding condition using a computer system and the ideal shape of an originally desired molded body. Thus, the present invention relates to a molding condition evaluation method for evaluating the deformation of a molded body to which the molding conditions contribute.

Further, the present invention compares each shape of a plurality of resin moldings obtained by molding under different molding conditions with a computer system and an ideal shape of an originally desired molding. The present invention relates to a molding condition evaluation method for evaluating the deformation of a molded body to which each molding condition contributes.
The present invention also relates to an object shape comparison method that uses a computer system to numerically compare the differences in the shapes of two target objects.

The present invention also relates to an object shape evaluation method for evaluating which objects have the closest shapes by comparing the shapes of three or more target objects using a computer system.

[0004]

2. Description of the Related Art As a molded body, a mold corresponding to a desired shape is usually prepared, and a resin as a material is poured into the mold,
It is made by molding under prescribed molding conditions. However, when the molded product is cooled after molding, it tends to warp or deform due to uneven contraction of each part. Such a deformation is unattractive, impairs the product value, and causes a problem that it cannot be assembled on other parts. Furthermore, such deformation also differs depending on the conditions under which the molded product is molded. To address these issues,
Alternatively, it is necessary to evaluate the degree of deformation in order to know the degree of deformation of the molded product.

[0005]

By the way, conventionally, the evaluation of the degree of deformation has been performed by obtaining the displacement between two points or the displacement from the reference plane. For example, it is assumed that an article having a straight cross-sectional shape as shown in FIG. 6 is bent at the point B as a boundary. The displacement amount in this case is the displacement amount δ ₁ at the point C when the line segment AB is used as the reference (FIG. 7), but is the displacement amount δ ₂ at the point A when the line segment BC is used as the reference (FIG. 8). Even if the deformed shape is the same, the amount of displacement differs depending on the reference method, and the evaluation of the degree of deformation is different.

When this evaluation method is applied to determine how close two articles having different shapes are to each other, a virtual image showing two shapes is created, and this virtual image is created. It is common to superimpose each other and evaluate the difference between the two shapes. Even in this case, the evaluation will be different depending on the way of taking a reference point for superimposing the two virtual images.

Therefore, the present invention has been made in view of the above-mentioned actual situation, and makes it possible to evaluate the difference between the two shapes, and in particular, the shapes considering the deformation after molding of the molded body as the two shapes. The object is to provide an object shape evaluation method, a resin molded article deformation evaluation method, and an object shape comparison method, which make it possible to evaluate these two shapes by selecting the desired shape. .

[0008]

In order to solve the above-mentioned problems, a method for evaluating a molding condition of a resin molding according to the present invention is a resin obtained by molding under a predetermined molding condition using a computer system. By expressing the difference in the shape of the molded body from the ideal shape of the originally desired resin molded body,
A method for evaluating a molding condition for evaluating the deformation of a molded product contributed by the molding condition, wherein for each of the shapes of both resin molded products, an arbitrary number of line segments for shaping the shape intersect each other. Using the shape data group consisting of the coordinate groups of the nodes, the root mean square of the distances connecting the corresponding nodes of the two resin moldings, the shape of the resin molding obtained by molding under the predetermined molding conditions It is characterized by having an evaluation value calculation step of calculating as an evaluation value showing a difference from the ideal shape.

Further, after the evaluation value calculation step, the coordinates of each node derived from at least one resin molded body are converted so that the relative position of each node is changed while maintaining the shape of each resin molded body. A second step of calculating the root mean square of the distances connecting the nodes defined by the new coordinate by repeating the operation in the evaluation value calculating step using the coordinate converting step and the new coordinate obtained in the coordinate converting step. The evaluation value calculation step, and after repeating the coordinate conversion step and the second evaluation value calculation step as necessary, from among the evaluation values obtained the number of times the evaluation value is calculated, the minimum evaluation value And the evaluation value determination step of setting the evaluation value as a value for evaluating the difference from the ideal shape of the shape of the resin molded product obtained by molding under the predetermined molding conditions, and determining the evaluation value. Value determined in stages It is preferred to use as an evaluation value for evaluating the molding condition.

Further, the method for evaluating the molding conditions of the resin molding according to the present invention is originally desired for each shape of a plurality of resin moldings obtained by molding under different molding conditions using a computer system. A method for evaluating molding conditions for evaluating the deformation of a molded product to which the molding conditions contribute by expressing the difference from the ideal shape of the resin molded product by a numerical value, which is obtained by molding under different molding conditions described above. By selecting the molding conditions that you want to evaluate from multiple resin moldings, select the shape data consisting of the coordinate group of any number of nodes where the line segments for shaping the shape intersect. And the shape data selected in the evaluation target selection step and the shape data for the ideal shape are used to determine the distance between the nodes that correspond to each other between the two resin moldings. Resin molding corresponding to each evaluation condition and an evaluation value calculation step for calculating an average as an evaluation value indicating a difference from the ideal shape of the shape of the resin molded product obtained by molding under the selected predetermined molding condition From the evaluation value obtained for each shape of the body, the minimum evaluation value is taken out, and the molding condition corresponding to the minimum evaluation value is set as the molding condition for obtaining the resin molded body having the shape closest to the ideal shape. And a molding condition selecting step to be selected.

Further, after the distance calculation step and before the molding condition selection step, at least one resin is changed so as to change the relative position of each node while maintaining the shape of each resin molding. Coordinate conversion step of converting the coordinates of each node from the molded body, using the new coordinates obtained in the coordinate conversion step, repeating the operation in the evaluation value calculation step,
After repeating the second evaluation value calculation step of calculating the mean square of the distances connecting the nodes defined by the new coordinates, and the coordinate conversion step and the second evaluation value calculation step as necessary, the evaluation value From the evaluation values obtained only for the number of times of calculation, the minimum evaluation value is taken out, and the evaluation value is obtained by molding the evaluation value under the predetermined molding conditions selected in the evaluation target selection step. And an evaluation value determining step that is a value for evaluating a difference from the ideal shape of the shape, and in the molding condition selecting step, the value determined in the evaluation value determining step is used to evaluate the molding condition. It is preferable to select a molding condition that is used as an evaluation value and gives a resin molded body having a shape that is closest to the ideal shape.

Further, in any of the above-mentioned methods, the shape data of the resin molding obtained by molding under the molding conditions is the same as the shape of the mold giving the resin molding having the ideal shape. It is preferable that the shape data is based on a virtual shape obtained by performing a predetermined simulation using. Further, in any of the above methods, it is preferable to obtain a virtual image of each shape from the shape data of each shape.

An object shape comparison method according to the present invention is an object shape comparison method which uses a computer system to numerically represent a difference in shape between two target objects.
For each of the shapes of the both target objects, using a shape data group consisting of a coordinate group of an arbitrary number of nodes at which line segments for shaping the shape intersect, the nodes are associated with each other between the shape data. An evaluation in which a node-corresponding step to be defined and a root mean square of distances connecting the nodes of the both target objects associated in the node-corresponding step are calculated as an evaluation value indicating a difference in shape between the two target objects. It is characterized by having a value calculation step.

Further, after the evaluation value calculating step, at least one of the at least one of the nodes is changed so as to change the relative position of each node while maintaining the shape of the target object and the nodes defined in the step of associating the nodes. A coordinate conversion step of converting the coordinates of each node derived from the target object, and using the new coordinates obtained in the coordinate conversion step, the operation in the evaluation value calculation step is repeated, and the new coordinates are defined. After repeating the second evaluation value calculation step of calculating the root mean square of the distances connecting the nodes based on the association, and optionally the coordinate conversion step and the second evaluation value calculation step, evaluation value calculation An evaluation value determination step of extracting the minimum evaluation value from the evaluation values obtained by the number of times performed is provided, and the value determined in the evaluation value determination step is evaluated for the difference in shape between the two target objects. Do It is preferred to use as the evaluation value of the fit.

In the object shape evaluation method according to the present invention, the shapes of three or more target objects are compared with each other using a computer system to evaluate which object has the closest shape. An object shape evaluation method, comprising an object selection step of selecting a pair of a pair of objects whose shape evaluation is desired from the three or more target objects, and a shape of both target objects selected in the object selection step. For each of them, using a shape data group consisting of a coordinate group of an arbitrary number of nodes where the line segments for shaping the shape intersect each other, and defining a node correspondence step between both shape data, , The root mean square of the distances connecting the nodes of the both target objects that are associated in the node association step,
From the evaluation value calculation step of calculating as an evaluation value indicating the difference between the shapes of the two target objects, and the evaluation value obtained for each pair of the shapes of the target objects, the minimum evaluation value is extracted and the minimum evaluation value is obtained. And a combination selecting step in which the pair corresponding to the value is a combination of symmetric objects having the closest shape.

Further, after the distance calculation step and before the combination selection step, the shape of the target object and the nodes defined in the step of associating nodes are maintained while the correspondence of each node is maintained. Repeat the operation in the evaluation value calculation step by using the coordinate conversion step of converting the coordinates of each node derived from at least one target object so as to change the relative position and the new coordinates obtained in the coordinate conversion step. And a second evaluation value calculating step of calculating a root mean square of distances connecting the nodes based on the newly defined coordinates, and if necessary, the coordinate converting step and the second evaluation value calculating step. After repeating, from among the evaluation values obtained only the number of times the evaluation value is calculated, the minimum evaluation value is taken out, and the evaluation value is determined as a value for evaluating the combination of the target objects. Have , In the combination selection step, the value determined by the evaluation value determination steps using as an evaluation value of the combination of the target object, it is preferable to select a combination of symmetric object in which the nearest shape.

Further, in any of the above methods, it is preferable to obtain a virtual image of each shape from the shape data of each shape.

[0018]

BEST MODE FOR CARRYING OUT THE INVENTION The object shape comparison method, the object shape evaluation method, and the resin molded article deformation evaluation method according to the present invention will be described below in detail with reference to the drawings.
The object shape comparison method uses a computer system to numerically represent the difference in shape between two target objects.

Specifically, as shown in FIG. 1, for each of the shapes of the both target objects, a shape composed of a coordinate group of an arbitrary number of nodes at which line segments for shaping the shapes intersect each other. Using the data group, a step of associating nodes that defines the association of nodes between both shape data (step S10)
And an evaluation value calculation step of calculating, as an evaluation value indicating a difference in shape between the two target objects, a root mean square of the distances connecting the nodes of the both target objects that are associated in the node association step (step S20). ) Is included.

In FIG. 1, in step S10, nodes are associated between two pieces of shape data representing the shape of a target object whose shape difference is to be compared. Here, the node means a point where line segments for shaping the object shape intersect each other, and is set by a finite element method or the like. The nodes are
The coordinates are preset for each object, and the coordinates are accumulated in a database or the like as a data group for each object.

In addition to the nodal coordinates, the shape data includes
It includes data on elements that combine multiple nodes, such as triangles, quadrilaterals, and the like. Note that the nodal coordinates include three-dimensional coordinates having a predetermined point as the origin and polar coordinates. As a method of associating, first, an arbitrary node is specified from the first shape data, and each combination of the specified point and each of the nodes included in the other second shape data Calculate the internodal distance based on the coordinates of, and with the combination that minimizes this internodal distance, the specified nodal point from the first shape data and the corresponding second nodal point from the shape data. Correspond to.

Subsequently, similar calculation is performed for points other than the points that have already been associated with each other. However, associating the second nodes with each other can reduce the amount of calculation as compared with associating the first nodes. That is, when the designated node is determined in a certain shape, the relative position (coordinate) of each node is determined in the shape data for indicating the shape, and thus the designated position is determined based on this coordinate. Multiple other nodes close to the node are also automatically determined.

Therefore, one node that is close to the specified node is extracted from the first shape data, and the node that is associated with the node specified in the first shape data is associated with the second shape data. Take out multiple nodes. The above calculation is performed for the combination consisting of one node from the first shape data and a plurality of nodes from the second shape data to calculate the inter-node distance, and the combination with the minimum inter-node distance, The second node extracted from the first shape data is associated with the corresponding node from the second shape data. In this way, when the association of two nodes between the two shape data is completed, the previous nodes can be automatically associated.

At this time, the shape of each object can be reproduced by a virtual image using the coordinates of the node group forming the shape data, and can be displayed on, for example, a display means or output by an output means such as a printer. preferable. By doing so, it becomes possible to visually confirm the difference between the object shapes with each other using the virtual image together with the calculation result in step S20.

In step S20, the distance between the corresponding nodes in the two object shapes is calculated, the root mean square of the distances is calculated, and the flow proceeds to step S30. Also, when the coordinates of the nodes are represented by three-dimensional coordinates, the root mean square is
For example, the value obtained below.

[0026]

[Equation 1]

Here, dx _i , dy _i and dz _i indicate the displacement of each coordinate component between the i-th nodes. Further, n indicates the total number of nodes. The value is not limited to this, and may be a value obtained by the following formula, for example. In the formula, dx _i , dy _i , dz _i
And n are the same as defined for the above formula.

[0028]

[Equation 2]

In step S30, the root mean square of the internodal distances calculated in step S20 is stored in a predetermined storage means such as a memory, and the process proceeds to step S40. In step S40, it is determined whether or not the relative positions of the same objects to be compared are changed and the root mean square of the distances between the nodes is obtained again. Further, when the virtual image of each object is used, it may be determined whether or not the superimposing method of the virtual images is changed.

If the result of this determination is Yes, that is, if the relative positions of the nodes are changed or the virtual images are superposed on each other and a new root mean square of the inter-node distances is to be obtained, the process proceeds to step S50. If the determination result is No, that is, if the relative positions of the nodes are not changed, or if the virtual images are superposed on each other and the root mean square of the distances between the nodes is not calculated, the process proceeds to step S60.

As this determination method, for example, determination may be made by a person such as an operator every time the calculation of the root mean square is completed. Further, for example, steps S20 to S30
It is also possible to set in advance how many times the processes up to are performed, advance to step S50 until this number is cleared, and to proceed to step S60 when cleared.

In step S50, at least one of the nodes derived from the target object (hereinafter referred to as "a group of nodes derived from the target object") is changed so as to change the relative position of each node while maintaining the shape of each target object. Convert coordinates. That is, in the node group derived from the target object, the relative positions of the nodes are changed so that only the relative positions between the corresponding nodes in the shapes of the two objects to be calculated in step S20 are not changed. Perform coordinate conversion.

When each shape is reproduced in the virtual image, the virtual image is rotated or moved so that the virtual image is fixed at a desired place when the virtual image is accommodated, and the fixed image is dealt with. The node may be a new node coordinate. Also, after coordinate conversion in step S50, the process returns to step S20. In step S20, the obtained new coordinates are used to calculate the root mean square of the distances connecting the nodes defined by the new coordinates (first Second evaluation value calculation step), and the process proceeds to step S30. In step S30, as described above, the obtained new root mean square value is accumulated,
In step S40, the above determination is performed.

In step S60, the minimum value is extracted from the root mean square accumulated in step S30, and the comparison operation regarding the difference between the two object shapes is completed. That is,
This minimum value is an index showing the difference between the two object shapes. The smaller this value is, the closer the two object shapes are. Further, the object shape evaluation method uses a computer system to compare the shapes of three or more target objects with each other and evaluate which object has the closest shape.

Specifically, as shown in FIG. 2, an object selecting step (step S8) of selecting a pair of a pair of objects for which shape evaluation is desired from the three or more target objects, and the object selecting step. For each shape of both target objects selected in the step, using the shape data group consisting of the coordinate group of any number of nodes where the line segments for shaping the shape intersect, the nodes between both shape data are used. And the difference between the shapes of the two target objects as the root mean square of the distances connecting the nodes of the target objects, which are matched in the node correspondence step (step S10). Evaluation value calculation step (step S
20), and the minimum evaluation value is extracted from the evaluation values obtained for each pair of the shapes of the target object, and the pair corresponding to the minimum evaluation value is a combination of symmetrical objects having the closest shape. And a combination selection step (step S100).

In FIG. 2, in step S5, it is judged whether or not there is a plurality of shape data desired to be compared with the database in which the object shape is registered in advance. If the determination result is NO, the comparison operation is ended. If the determination result is YES, the process proceeds to step S8. In step S8, two objects desired to be compared are selected from a group of three or more target objects. That is, the shape data corresponding to the shape of the object to be compared is specified by selecting the object.

Steps S10, S20, S30, S4
At 0, S50, and S60, as shown in FIG. 1 and described above, the index indicating the shape difference of the set of objects selected at step S8 is extracted. In step S70, the index (minimum evaluation value) indicating the shape difference of the set of objects extracted in step S60 is stored in a predetermined storage unit, for example, a memory, and the process proceeds to step S80.

In step S80, it is determined whether or not the index (minimum value) indicating the difference in the object shape has been extracted for all the combinations of the groups of the target objects. This example calculates the total number of combinations when taking out two of a plurality of target objects _(n C _{2: n} represents the total number of the object) and is extracted in the step S60 and the number accumulated in the step S70 This can be done by determining whether or not the number of the calculated indexes (minimum value) matches.

If the determination result is YES, that is, if it is determined that the indexes indicating the differences in the object shapes have been extracted for all the combinations of objects, the process proceeds to step S100. If the determination result is NO, that is, if it is determined that the indexes indicating the differences in the object shapes have not been extracted for all the combinations of the objects, the process proceeds to step S90, and the unevaluated combinations in the comparison target object group. And returns to step S10, for the new combination identified in step S90,
By performing the processing shown in steps S10 to S70,
An index (minimum value) indicating the difference in object shape in the combination is obtained.

In step S100, the smallest one of the least mean square values, which is the index of the difference in the object shape for each combination extracted in step S60 and accumulated in step S70, is extracted, and the combination corresponding to this index is extracted. , Is selected as the combination showing the closest shape in the group of target objects. Here, using a resin molded body as an object to be compared,
Evaluating the shape of the resin molded product, especially molding, by comparing the shape that will actually be obtained by molding (called "predicted shape") and the ideal shape that is originally desired (called "ideal shape") It is possible to evaluate the molding conditions of the resin molded product by evaluating the deformation of the resin molded product that may vary depending on the conditions.

The evaluation of the molding conditions of this resin molding constitutes one aspect of the present invention. In the deformation evaluation method for a resin molded product according to the present invention, the shape (predicted shape) that may be actually obtained by molding is molding conditions such as resin material,
The position and number of openings (gates) for pouring this resin material into the molding die, the temperature when pouring the resin material into the gate, the molding time, the molding temperature, and a plurality of constraint points that are convenient for calculation are determined. A shape obtained based on a result of performing a predetermined warp analysis simulation, for example, a warp analysis according to a program such as MF / WARP (trade name).

The originally desired ideal shape (ideal shape) is a final shape of a desired resin molded body, for example, a shape obtained based on a die used. Specifically, it is obtained by multiplying the shape made by the cavity of the mold by 1 / mold making magnification. Here, the mold manufacturing ratio refers to the ratio of the shape made by the cavity of the mold to the product shape, in consideration of the shrinkage rate at the time of molding the resin.

For example, when molding is performed using polypropylene, the mold cavity is expected to shrink by about 1%, so the cavity of the mold is manufactured with 1.01 times the product shape. Therefore, the ideal shape for molding using polypropylene can be obtained by multiplying the shape made by the cavity of the mold by 1 / 1.01≈0.99.

Here, examples of the shape of the resin molded body for comparison include the shape of a vehicle instrument panel, a predetermined container, a predetermined housing for electronic equipment, and the like. In the above method, as shown in FIG. 3, in step S5, it is determined whether or not there is an ideal shape and a predicted shape desired to be compared in a database in which the ideal shape and the predicted shape of the resin molded body are registered in advance. To be determined. If this determination result is YES,
It proceeds to step S208. If the determination result is NO, the process proceeds to step S210, and the shape data of the resin molded body to be examined, that is, either the ideal shape data or the predicted shape data is obtained by the above-described simulation, and the process proceeds to step S215. The stored shape data is stored in the database, and the process returns to step S205 again.

In step S208, one combination of the ideal shape data of the resin molding desired to be evaluated and the predicted shape data is selected, and the process proceeds to step S220. In step S220, the distance between the corresponding nodes in the two shapes, that is, the ideal shape and the predicted shape, is calculated, and the root mean square of the distances is calculated.
Proceed to. Since the ideal shape and the predicted shape are data obtained by simulation based on the same mold, the correspondence between nodes is determined between the shape data at the time of calculating each shape data.

When the coordinates of the nodes are represented by three-dimensional coordinates, the root mean square is, for example, the value obtained below.

[0047]

[Equation 3]

Here, dx _i , dy _i , and dz _i indicate the displacement of each coordinate component between the i-th nodes. Further, n indicates the total number of nodes. The value is not limited to this, and may be a value obtained by the following formula, for example. In the formula, dx _i , dy _i , dz _i
And n are the same as defined for the above formula.

[0049]

[Equation 4]

In step S230, step S220
The mean square of the internodal distance calculated in
For example, it is stored in the memory and the process proceeds to step S240. In step S240, it is determined whether the relative positions of the ideal shape data and the predicted shape data are changed and the root mean square of the distances between the nodes is obtained again. Further, as will be described later, when virtual images of each shape are used, it may be determined whether or not the superimposing method of virtual images is changed.

If the result of this determination is Yes, that is, if the relative positions of the nodes are changed or the virtual image is superposed, and the new root mean square of the internodal distances is obtained, the operation proceeds to step S250. If the determination result is No, that is, if the relative positions of the nodes are not changed, or if the virtual images are superposed on each other and the root mean square of the distances between the nodes is not calculated, the process proceeds to step S260.

As this determination method, for example, determination may be made by a person such as an operator every time the calculation of the root mean square is completed. Also, for example, steps S220 to S2
It is also possible to preset how many times the processes up to 30 are to be performed, advance to step S250 until this number is cleared, and proceed to step S260 when cleared.

In step S250, each node derived from at least one shape data (hereinafter referred to as "node group derived from target object") so that the relative position of each node is changed while maintaining the ideal shape and the predicted shape itself. ) Coordinates are converted. That is, in the node group derived from each shape data, the coordinate conversion of the node is performed so that only the relative position between the corresponding nodes in the two shape data is changed without changing the relative position of each other.

When each shape is reproduced in the virtual image, the virtual image is rotated or moved so that the virtual image is fixed at a desired place when the virtual image is contained, and the virtual image is fixed. The node may be a new node coordinate. In addition, after coordinate conversion in step S250, the process returns to step S220. In step S220, the root mean square of the distances connecting the nodes defined by the new coordinates is calculated using the obtained new coordinates (first Second evaluation value calculation step), and the process proceeds to step S230. Step S23
At 0, as described above, the obtained new root mean square value is accumulated, and the process proceeds to step S240 to make the above determination.

In step S260, step S230
The minimum value is extracted from the root mean square accumulated in step S8, and the comparison operation regarding the difference between the ideal shape of the resin molded body and the predicted shape selected in step S8 ends. That is, this minimum value is an index indicating the difference between the predicted shape and the ideal shape. Note that the smaller this value is, the closer the predicted shape is to the ideal shape.

In step S270, step S260
The index (minimum value of the evaluation value) indicating the difference between the predicted shape and the ideal shape extracted in step 1 is stored in a predetermined storage unit, for example, a memory, and the process proceeds to step S280. Step S2
At 80, whether or not there is any unevaluated shape among the predicted shapes to be compared with the ideal shape selected at step S208,
That is, it is determined whether or not all predicted shapes have been evaluated.

If this determination result is YES, that is, if all the predicted shapes have been evaluated, the process proceeds to step S300. If the determination result is NO, that is, if there is an un-evaluated predicted shape, the process proceeds to step S290 to identify the un-evaluated predicted shape data, return to step S220, and regarding the new predicted shape identified in step S290, By performing the processing shown in steps S220 to S270,
An index (minimum value) indicating the difference between the predicted shape and the ideal shape is obtained.

In step S300, step S260
In the least square mean value which is an index of the difference between the predicted shape and the ideal shape accumulated in step S270, and the predicted shape corresponding to this index is the shape closest to the ideal shape. Select as there is. That is, the molding condition that gives the predicted shape is the molding condition for obtaining the shape closest to the ideal shape.

As a means for realizing the object shape comparison method as shown in FIG. 1, for example, there is one having a configuration as shown in FIG. The operation of each configuration will be described below, but the operation corresponding to each step in FIG. 1 is indicated by the step number in parentheses. In FIG. 4, the input unit 10 inputs a predetermined command for operating the shape data extraction unit 121 and the coordinate conversion unit 128. As this command input, for example, shape data indicating an object shape to be compared to be sent to the shape data extraction unit 121 is specified from the database 30,
The specified nodes are associated (step S10).
Command for inputting, and a first determination unit 127 described later
The command input for performing the coordinate conversion operation (step S50) of the coordinate conversion unit 128, which will be described later, in response to the determination result from the above.

The shape data extracting unit 121 accesses the database 30 according to the command input from the input unit 10 and extracts two shape data to be compared. Furthermore, the nodes of these two shape data are associated (step S10). Information about which node and which node are associated with each other is sent to the root mean square calculation unit 125.

Here, the node means a point at which line segments for shaping the object shape intersect each other, and is set by a finite element method or the like. The nodes are preset for each object, and the coordinates are set as a data group for each object in the database 3
Accumulate to 0. Further, in the shape data, in addition to the node coordinates, an element combining a plurality of nodes, for example, a triangle,
Includes data on quadrilaterals, etc. Note that the nodal coordinates include three-dimensional coordinates having a predetermined point as the origin and polar coordinates.

At this time, although not shown, an image reproducing means for reproducing the shape of each object by a virtual image is provided by using the nodal coordinates of each shape data to create image data,
It is preferable that this image data is displayed on, for example, a display unit or output by an output unit such as a printer. By doing so, it becomes possible to visually confirm the overlapping degree of the mutual object shapes together with the result of the calculation (step S20) described later by using the virtual image.

The root mean square calculation unit 125 calculates the distance between the corresponding nodes in the two object shapes, and calculates the root mean square of the distances (step S20). Further, the calculated root mean square value is sent to the root mean square accumulating unit 40, and data indicating that the calculation process is completed is sent to the first discriminating unit 127. The root mean square accumulation unit 40 accumulates the root mean square value calculated by the root mean square calculation unit 125 (step S30). At this time, it is preferable that an address is set for each accumulated root mean square value and a specific root mean square value can be taken out by referring to this address.

The first discriminating section 127 discriminates whether or not to obtain the root mean square of the distances between the nodes by changing the relative positions of the same objects to be compared with each other (step S50).
Further, when the virtual image of each object is used, it is determined whether or not the superimposing method of the virtual images is changed. If the result of this determination is Yes, that is, if the relative position of the nodes is changed or the virtual image superposition method is changed to obtain the root mean square of the new internodal distance, the coordinates of each node before coordinate conversion are calculated. It is sent to the coordinate conversion unit 128. If the determination result is No, that is, if the relative positions of the nodes are not changed, or if the virtual image superposition method is changed and the root mean square of the inter-node distance is not calculated, the minimum value extraction unit 129 Send data to that effect.

As this discrimination method, for example, each time the calculation of the root mean square is completed, the first discrimination unit 127 changes the input unit 1
It is also possible to send information prompting input of whether or not to perform coordinate conversion to 0, and have a person such as an operator operating the input unit 10 input any of the information. Alternatively, for example, the number of times the calculations in steps S20 to S30 are performed is set in advance as a threshold value, and the coordinate conversion unit 128 is made to perform coordinate conversion while the threshold value is not exceeded (step S
50) and when the threshold value is exceeded, the minimum value extraction unit 129
Send data prompting to extract the minimum value as described later.

The coordinate conversion unit 128 changes each relative position of the paired nodes between the shape data while maintaining the shape of each target object (hereinafter referred to as "target node"). The coordinate of "node group derived from the object") is converted. That is, in the node group derived from the target object, the relative positions of the nodes are changed so that only the relative positions between the corresponding nodes in the shapes of the two objects handled by the root mean square calculation unit 125 are not changed. Perform coordinate conversion.

When the coordinate conversion is performed, the input unit 1
Data that prompts the user to input how to convert the coordinates from 0 may be sent from the first determination unit 127 to the input unit 10. By doing so, the person who operates the input unit 10 performs an operation of rotating and moving at least one of the virtual images when the shape of each target object is reproduced using the virtual image, and the coordinate conversion is performed. The unit 128 can configure the system to calculate post-operation nodal coordinates.

After the coordinate conversion by the coordinate conversion unit 128, the process returns to the process by the root mean square calculation unit 125. Here, the mean square of the distances connecting the corresponding nodes defined by the new coordinates after the conversion process is calculated. Calculate (second evaluation value calculation stage). The minimum value extraction unit 129 extracts the minimum value among the root mean square values accumulated by the root mean square accumulation unit 40 (step S60). That is, this minimum value is an index indicating the difference between the two object shapes. The smaller this value is, the closer the two object shapes are. The extracted minimum value is sent to the output unit 50.

The output unit 50 is, for example, a display or a printer, and outputs the minimum value. Further, the object shape evaluation method for selecting two objects to be compared from a group of three or more objects as shown in FIG. 2 is realized by using a device having a configuration as shown in FIG. It will be possible.

The operation of each component will be described below.
Step numbers are shown in parentheses for operations corresponding to the steps in FIG. 5, in the input unit 15, a predetermined command for operating the shape data extraction unit 122 and the coordinate conversion unit 128 is input, as in the input unit 10 of FIG. As this command input, as this command input, for example, shape data indicating an object shape to be compared for sending to the shape data extraction unit 121 is specified from the database 30, and the specified nodes are associated ( The command input for step S10) and the command input for performing the coordinate conversion operation (step S50) of the coordinate conversion unit 128 described later in response to the determination result from the first determination unit 127 described later are included.

In the shape data extraction unit 122, the input unit 15
It is determined whether or not the two shape data specified in step S5 are stored in the database 30 (step S5), and the two shape data specified in the database 30 are stored in the same manner as the shape data extraction unit 121 in FIG. After extraction (step S8), nodes are associated with these two shape data (step S10). In addition, the information about which node is associated with which of these two shape data is associated with the root mean square calculation unit 1
Sent to 25.

In the database 30, as described above,
The coordinates of the nodes preset for each object are accumulated as a data group for each object, that is, shape data. At this time, as described above, using the nodal coordinates of each shape data, although not shown, an image reproducing means for reproducing the shape of each object by a virtual image is provided to create image data,
It is preferable that this image data is displayed on, for example, a display unit or output by an output unit such as a printer. By doing so, it becomes possible to visually confirm the overlapping degree of the mutual object shapes together with the result of the calculation (step S20) described later by using the virtual image.

The root mean square calculation unit 125 calculates the distance between the corresponding nodes in the two object shapes, and calculates the root mean square of the distances (step S20). Further, the calculated root mean square value is sent to the root mean square accumulating unit 45, and data indicating that the calculation process is completed is sent to the first discriminating unit 127. The root mean square accumulation unit 45 accumulates the root mean square value calculated by the root mean square calculation unit 125 (step S30). At this time, it is preferable that an address is set for each accumulated root mean square value and a specific root mean square value can be taken out by referring to this address.

As described above, the first discriminating unit 127 discriminates whether or not to obtain the root mean square of the distances between the nodes by changing the relative positions of the same objects to be compared with each other (step S50). ). Further, when the virtual image of each object is used, it is determined whether or not the superimposing method of the virtual images is changed. If the result of this determination is Yes, that is, if the relative position of the nodes is changed or the virtual image superposition method is changed to obtain the root mean square of the new internodal distance, the coordinates of each node before coordinate conversion are calculated. It is sent to the coordinate conversion unit 128. If the determination result is No, that is, if the relative positions of the nodes are not changed, or if the virtual image superposition method is changed and the root mean square of the inter-node distances is not calculated, the minimum value extraction unit 130 Send data to that effect.

As described above, the coordinate conversion unit 128 changes each relative position of the pair of nodes between each shape data while maintaining the shape of each target object, so that each node derived from at least one target object is changed. (Hereinafter, "node group derived from target object"
() Is converted. Further, when performing this coordinate conversion, data that prompts the input unit 15 to input how to convert the coordinates may be sent from the first determination unit 127 to the input unit 15. By doing so, the person who operates the input unit 15 performs an operation of rotating and moving at least one of the virtual images when the shape of each target object is reproduced using the virtual image, and the coordinate conversion is performed. The unit 128 can configure the system to calculate post-operation nodal coordinates.

After the coordinate conversion by the coordinate conversion unit 128, the process returns to the process by the mean square calculation unit 125. Here, the mean square of the distances connecting the corresponding nodes defined by the new coordinates after the conversion process is calculated. Calculate (second evaluation value calculation stage). In addition, as described above, the minimum value extraction unit 130 extracts the index (minimum value) of the difference between the shapes of the set of target objects extracted by the shape data extraction unit 122 (step S60), and then the appropriate value. The minimum value is accumulated in the accumulating unit (step S70), and the data to that effect is sent to the second discriminating unit 132. A memory may be separately provided as the appropriate storage unit, but it is preferable to use the above-mentioned root mean square storage unit 45 from the viewpoint of reducing the number of components. When the root mean square accumulating unit 45 is used, a part of the root mean square accumulating unit 45 may be separately allocated to the minimum value accumulating area, or a part of the root mean square accumulating unit 45 stores the address of the root mean square value corresponding to the minimum value. It may be configured such that when a selection request is made from the selecting unit 134, which will be described later, by allocating to the area to be stored, the corresponding address is taken out and the target minimum value can be extracted using this address.

The second discriminating section 132 discriminates whether or not there is an unevaluated combination of comparison target objects. That is, it is determined whether or not an index (minimum value) indicating a difference in object shape has been extracted for all combinations of the group of target objects (step S80). This example calculates the total number of combinations when taking out two of a plurality of target objects _(n C _{2: n} represents the total number of the object) and is extracted with the number and the minimum value extractor 130, the root mean This can be performed by determining whether or not the number of indexes (minimum value) stored in the storage unit 45 matches. Specifically, with the total number of combinations as a threshold,
By comparing this value with the number of minimum values, when the number of minimum values reaches the threshold value, it can be determined that the minimum value has been extracted for all combinations of target objects.

Further, when there is a combination of target objects for which the minimum value has not been calculated, data requesting a selection command for the combination is sent to the input unit 15. In the input unit 15,
When this data is sent, a further combination is selected (step S90). Further, when it is determined that the minimum value has been extracted for all combinations of target objects, the selection unit 1
The data to that effect is sent to 34.

The selection unit 134 is the minimum value extraction unit 130.
The smallest minimum value is selected and extracted from the minimum values extracted in step S100. In the case of the present embodiment, the root mean square accumulating unit 45 is accessed to take out the smallest minimum value (index value). The extracted minimum index value is sent to the output unit 50. Here, by using the resin molded body as the object to be compared, by comparing the predicted shape that would be actually obtained by molding and the originally desired ideal shape and the ideal shape, It is possible to evaluate the shape, especially the deformation of the resin molded body which may vary depending on the molding conditions.

Also in this case, the molding condition of the resin molding can be evaluated by operating the device as described above by using the device as shown in FIG. 4 or FIG. The database 30 stores both the ideal shape data and the predicted shape data of the resin molded body as described above. If the shape data of the predicted shape to be evaluated does not exist in the database 30, the shape data is obtained using an appropriate simulation means (not shown in FIGS. 4 and 5) (step S210), and the database is obtained. It is necessary to store the data in 30 (step S215).

For example, when the apparatus shown in FIG. 5 is used, the input unit 15 inputs a command for specifying the ideal shape and predicted shape data of the resin molded body desired to be evaluated, and the shape data extracting unit 122. Then, the specified ideal shape data and predicted shape data are extracted from the database 30 (step S208). The mean square calculator 125 calculates the mean square of the distances between the nodes corresponding to the ideal shape data and the predicted shape data (step S2).
20), the calculated root mean square is stored in the root mean square storage unit 45 (step S230).

In the first discriminating unit 127, the mean square calculating unit 1
In response to the calculation of the root mean square in 25, it is determined whether or not the coordinate conversion is performed to change the relative position between the same predicted shape and the ideal shape (step S240). When coordinate conversion is performed, the coordinate conversion unit 128 performs constant coordinate conversion (step S250). If not,
The minimum value extraction unit 130 accesses the root mean square storage unit 45 to extract the minimum root mean square value (minimum value) (step S260), and stores this minimum value in an appropriate storage means (step S270). ). This suitable storage means may be the same as that described above.

In the second discriminating unit 132, the minimum value extracting unit 13
After the minimum value was extracted at 0, did all other predicted shapes (shapes obtained based on different molding conditions using the same mold as the mold giving the ideal shape) evaluated? The input unit 15 is requested to determine whether or not (step S
280). When the unevaluated predicted shape remains in the database 30, the input unit 15 is instructed to specify the unevaluated predicted shape, and the input unit 15 inputs a command to specify the unevaluated predicted shape. (S29
0). Further, in the case where all the predicted shapes in the database 30 are evaluated, although not shown, the minimum value (index value) from the input unit 15 to the selection unit 134 as described above is used.
Request to make a choice.

The selecting section 134 selects and takes out the smallest index value from the index values accumulated in the root mean square accumulating section 45 (step S300). Here, it is preferable to send to the output unit 50 molding conditions for obtaining a predicted shape that gives the extracted index value. The output unit 50 outputs the sent information. As described above, according to the present invention,
It is possible to objectively express how close two objects are in shape.

Further, shape data obtained by fixing (constraining) an arbitrary number of points on two objects to be compared are
Since the relative positions of the object shapes are changed and re-evaluation is performed, the conventional re-evaluation is performed again by changing the fixed point, and different results are obtained despite the same evaluation target. That inconvenience disappears. Also, when two similar shapes are taken out from a group of three or more objects, the object shapes are compared for the arbitrarily taken out combinations, a predetermined numerical value is obtained, and the difference in shape is used by using that numerical value. Therefore, it is possible to objectively make a subjective judgment.

Further, by setting one of the ideal shapes desired as the resin molded body as the object of comparison and the other predicted shape of the resin molded body obtained based on the actually set molding conditions, a predetermined molding is performed. It is possible to express numerically how close the predicted shape of the resin molded body obtained under the conditions is to the ideal shape. Furthermore, it becomes possible to objectively judge and select a molding condition that gives a shape that is the closest to the ideal shape from the predicted shapes of the resin molded body obtained under each of several assumed molding conditions.

It should be understood that a configuration which is appropriately modified without departing from the object of the present invention also belongs to the scope of the present invention.

[0088]

According to the present invention, it is possible to evaluate the difference between two shapes, and in particular, two shapes can be selected by selecting a shape in consideration of the deformation of the molded body after molding and an intended shape. It is possible to provide a deformation evaluation method for a resin molded body, an object shape evaluation method, and an object shape comparison method that enable evaluation of these two shapes.

[Brief description of drawings]

FIG. 1 is a flowchart illustrating an embodiment of an object shape comparison method according to the present invention.

FIG. 2 is a flowchart illustrating an embodiment of an object shape evaluation method according to the present invention.

FIG. 3 is a flowchart illustrating an embodiment of a method for evaluating deformation of a resin molded body according to the present invention.

FIG. 4 is a block diagram showing one embodiment of an apparatus for performing the method of the present invention.

FIG. 5 is a block diagram showing another embodiment of an apparatus for carrying out the method of the present invention.

FIG. 6 is a cross-sectional view of an evaluation target article.

FIG. 7 is a diagram showing a displacement amount after deformation.

FIG. 8 is a diagram showing displacement amounts with different references.

Claims (11)

[Claims] Claims: 1. By using a computer system to express the difference in the shape of the resin molded body obtained by molding under predetermined molding conditions from the originally desired ideal shape of the resin molded body, A method for evaluating a molding condition for evaluating deformation of a molded product to which a condition contributes, for each of the shapes of both resin molded products, an arbitrary number of nodes at which line segments for shaping the shape intersect with each other. The ideal shape of the shape of the resin molded body obtained by molding the mean square of the distances connecting the corresponding nodes of the both resin molded bodies using the shape data group including the coordinate group under the predetermined molding conditions. The method for evaluating a molding condition of a resin molded article, comprising: an evaluation value calculating step of calculating an evaluation value indicating a difference from 2. After the evaluation value calculation step, the coordinates of each node derived from at least one resin molded body are converted so that the relative position of each node is changed while maintaining the shape of each resin molded body. Using the coordinate conversion step and the new coordinates obtained in the coordinate conversion step, the operation in the evaluation value calculation step is repeated to calculate the root mean square of the distances connecting the nodes defined by the new coordinates. The evaluation value calculation step, and, if necessary, after repeating the coordinate conversion step and the second evaluation value calculation step, from among the evaluation values obtained the number of times the evaluation value is calculated, the minimum evaluation value Take out the
The evaluation value is provided with an evaluation value determination step which is a value for evaluating a difference from the ideal shape of the resin molded body obtained by molding the evaluation value under the predetermined molding condition, and is determined in the evaluation value determination step. The method according to claim 1, wherein the value obtained is used as an evaluation value for evaluating the molding condition. 3. A numerical value indicating the difference between the originally desired shape of the resin molded body and the shape of each of the plurality of resin molded bodies obtained by molding using a computer system under different molding conditions. In the method for evaluating a molding condition for evaluating the deformation of a molded product to which the molding condition contributes, a molding condition desired to be evaluated is selected from a plurality of resin molded products obtained by molding under different molding conditions. By performing an evaluation target selection step of selecting shape data consisting of a coordinate group of an arbitrary number of nodes at which line segments for shaping the shape, and the shape data selected in the evaluation target selection step And using the shape data of the ideal shape, the root mean square of the distance connecting the nodes corresponding to each other of the resin molding,
Evaluation value calculation step for calculating as an evaluation value indicating a difference from the ideal shape of the shape of the resin molded body obtained by molding under the selected predetermined molding condition and the shape of the resin molded body corresponding to each molding condition Molding in which the minimum evaluation value is extracted from the evaluation values obtained for each, and the molding condition corresponding to the minimum evaluation value is selected as the molding condition for obtaining the resin molded body having the shape closest to the ideal shape. A method for evaluating a molding condition of a resin molding, the method comprising a condition selection step. 4. After the distance calculation step and before the molding condition selection step, at least one resin is changed so as to change the relative position of each node while maintaining the shape of each resin molded body. Using the coordinate transformation stage that transforms the coordinates of each node originating from the molded body and the new coordinates obtained in the coordinate transformation stage, repeat the operation in the evaluation value calculation stage to define the nodes defined by these new coordinates. After the second evaluation value calculation step of calculating the root mean square of the distances connecting, and the coordinate conversion step and the second evaluation value calculation step as necessary, the evaluation value calculation is performed the number of times. From the evaluation values that were obtained, take out the minimum evaluation value,
And an evaluation value determination step of setting the evaluation value as a value for evaluating a difference from the ideal shape of the shape of the resin molded body obtained by molding under the predetermined molding condition selected in the evaluation target selection step. In the molding condition selection step, using the value determined in the evaluation value determination step as an evaluation value for evaluating the molding condition, a molding condition that gives a resin molded body having a shape closest to an ideal shape is selected. The method of claim 3, comprising: 5. The shape data of a resin molded body obtained by molding under the molding conditions is subjected to a predetermined simulation by using the same mold shape as the mold that gives the resin molded body having the ideal shape. The method according to claim 1, which is shape data based on a virtual shape obtained by performing the method. 6. The method according to claim 1, wherein a virtual image of each shape is obtained from the shape data of each shape. 7. A method of comparing object shapes, which numerically indicates the difference in shape between two target objects using a computer system, wherein a line for shaping the shape of each of the target objects is provided. Using a shape data group consisting of a coordinate group of an arbitrary number of nodes at which the minutes intersect, a step of associating nodes that defines the correspondence between the two pieces of shape data, and a step of associating in the step of associating nodes An object shape comparison method, comprising: an evaluation value calculation step of calculating a root mean square of distances connecting nodes of the both target objects as an evaluation value indicating a difference in shape of the two target objects. 8. After the evaluation value calculation step, at least one of the at least one of the nodes is changed so as to change the relative position of each node while maintaining the shape of the target object and the nodes defined in the step of associating nodes. The coordinate conversion step for converting the coordinates of each node derived from the target object, and the new coordinates obtained in the coordinate conversion step are used to repeat the operation in the evaluation value calculation step to define the new coordinates. After the second evaluation value calculation step of calculating the root mean square of the distances connecting the nodes based on the association, and if necessary, the coordinate conversion step and the second evaluation value calculation step are repeated, and then the evaluation value calculation is performed. From the evaluation values obtained only the number of times performed, an evaluation value determination step for extracting the minimum evaluation value is provided, and the value determined in the evaluation value determination step is evaluated for the difference in shape between the two target objects. Suta The method of claim 7 which comprises using as the evaluation value. 9. An object shape evaluation method for evaluating which objects have the closest shape by comparing the shapes of three or more target objects with each other using a computer system. An object selecting step of selecting a pair of objects for which shape evaluation is desired from one or more target objects, and a line for shaping the shape of each of the target objects selected in the object selecting step. Using a shape data group consisting of a coordinate group of an arbitrary number of nodes at which the minutes intersect, a step of associating nodes that defines the correspondence between the two pieces of shape data, and a step of associating in the step of associating nodes An evaluation value calculation step of calculating the root mean square of the distances connecting the nodes of the two target objects as an evaluation value indicating the difference between the shapes of the two target objects, and the evaluation obtained for each pair of the shapes of the target objects. And a combination selecting step in which a minimum evaluation value is extracted from the values, and a pair corresponding to the minimum evaluation value is a combination of symmetrical objects having a shape closest to the pair, the evaluation method of the object shape. . 10. After each of the distance calculation steps and before the combination selection step, the shape of the target object and the nodes defined in the node correspondence step are maintained while the correspondence of each node is maintained. Repeat the operation in the evaluation value calculation step by using the coordinate conversion step of converting the coordinates of each node derived from at least one target object so as to change the relative position and the new coordinates obtained in the coordinate conversion step. Then, a second evaluation value calculating step of calculating a root mean square of distances connecting the nodes based on the newly defined coordinates, and the coordinate converting step and the second evaluation value calculating step as necessary. After repeating the above, from the evaluation values obtained only the number of times the evaluation value was calculated, take out the minimum evaluation value,
It has an evaluation value determination step of setting the evaluation value as a value for evaluating the combination of the target objects, and in the combination selection step, the value determined in the evaluation value determination step is used as the evaluation value of the combination of the target objects. make use of,
10. The method according to claim 9, characterized in that the combination of the closest shaped symmetrical objects is selected. 11. The method according to claim 7, wherein a virtual image of each shape is obtained from the shape data of each shape.