JP2833271B2 - Design equipment - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a design apparatus for displaying a vehicle design on a CRT while confirming a human image of the vehicle.

[0002]

2. Description of the Related Art FIG. 9 shows an example of this type of design apparatus. This is HULIS (Hu
1 is a system configuration diagram of a man living system, and is a design device of a house. That is, in the computer memory, the appearance of the house, the entrance,
Housing design elements for each component such as kitchen, bath, etc.
The evaluation terms such as "relaxing", the knowledge defining the relationship between the evaluation terms, and the knowledge defining the relationship between these evaluation terms and the house design elements are stored as a knowledge database. Then, a human operates evaluation term input means such as a keyboard to input, for example, a limited term of a house design such as "Japanese-style room" representing a design element which is a constituent part of the house, and an image of oneself with respect to the Japanese-style room. When a computer inputs the evaluation term “extensive”, the computer infers a suitable Japanese-style design element from the knowledge database based on the input evaluation term, extracts it, and displays the image on the display means. I have.

[0003] By the way, in the above-described design apparatus, if the technical evaluation terms correspond to the vehicle design, it can be put to practical use as a vehicle design apparatus. Is Japanese Patent Application 1
No. 341129).

[0004] That is, in a memory of a computer, knowledge for defining an evaluation term, a relationship between evaluation terms, and knowledge for defining a relationship between a vehicle design element, an evaluation term, and a vehicle design element are stored. Here, the evaluation terms are shown in FIG.
Are formed with adjective words as shown in the evaluation term column of the table.

[0005] The knowledge defining the relationship between the evaluation terms is the knowledge obtained as defining the relationship between the evaluation terms by collecting the evaluation terms and analyzing the results of preliminary experiments as shown in FIG. is there. This relationship is, for example, the evaluation terms are divided into factors 1 to 10 based on human senses by multivariate analysis such as factor analysis, principal component analysis, etc., and how much each evaluation term is related to each factor is factor loading. Data obtained as (numerical values). It can be said that the loading of each factor is closely related to the term of the close number. This knowledge that defines the relationship between evaluation terms is used to select the most similar term when the input evaluation terms are not in the evaluation term group used in the sensory evaluation experiment described later when using the design device. This is also used for creating a factor axis described later.

As shown in the table of FIG. 11, the vehicle design elements are classified into categories for each item such as the number of meters in the vehicle interior.

The knowledge that defines the relationship between the evaluation terms and the vehicle design elements is obtained as a result of a sensory evaluation experiment as shown in FIG. Specifically, items for evaluation terms and vehicle design elements are selected, vehicle design elements corresponding to each item are shown to an unspecified number of people, and vehicle design elements for each of the evaluation terms that are adjective words are selected. Are collected and analyzed as a partial regression coefficient (correlation coefficient) by multivariate analysis such as quantification theory I or II.

Here, as shown in FIG. 11, the items are the number of meters provided on the instrument panel in the vehicle design element group, the instrument panel and the meter cluster, the meter cluster and the center console, the thickness of the door, and the center cluster. It focuses on overhangs, armrests, and the like.

The number of meters is classified into five categories. That is, a first category provided with one large meter, a second category provided with one large meter and two small meters, a third category provided with one large meter and three small meters, and a large meter 2 A fourth category provided with two large meters and two small meters, and a fifth category provided with two large meters and two small meters.

Items focused on instrument panels and meter clusters are classified into two categories. That is, a first category in which the instrument panel and the meter cluster are integrated, and a second category in which the instrument panel and the meter cluster are separated.

Items focused on the meter cluster and the center console are classified into two categories.
That is, a first category in which the meter cluster and the center console are integrated, and a second category in which the meter cluster and the center console are separated.

Items worn for door thickness are classified into two categories. That is, the first category is a thick door and the second category is a thin door.

Items focused on the overhang of the center cluster are classified into two categories. That is, the first category has a center cluster overhang, and the second category has no center cluster overhang.

Hereinafter, items focusing on armrests and other items are classified into categories.

When an input means such as a keyboard is operated and an adjective as an evaluation term is input, a vehicle design element is inferred and extracted from a knowledge database by the operation of a computer.
2. An image is displayed as shown in FIG. This example shows a case where “sick” and “sporty” are input as evaluation terms. Therefore, a designer or the like can obtain a design diagram by inputting evaluation terms according to his or her own image.

[0016]

However, in such a design device, by inputting an adjective as an evaluation term, the relation between the evaluation term and the design element corresponds to the evaluation term of the partial regression coefficient, and each item is used. Since the category indicating the maximum value is uniquely extracted and the image is displayed as a design drawing of the entire vehicle interior, there is a problem that interaction with each design image cannot be considered. For this reason, each design element is adapted to the design image, but the overall design balance may not match the image.

Accordingly, the present invention has made it possible to output a design drawing in consideration of the interaction of a plurality of design elements constituting a design object with a design image.

[0018]

[0019]

[Means for Solving the Problems] In order to solve the above-mentioned problems
As shown in FIG. 1, the invention according to claim 1 is a method of expressing the degree of influence in relation to a plurality of evaluation elements representing a design image of a design object and a plurality of design elements constituting the design object. A first knowledge database CL5, a second knowledge database CL6 provided for each evaluation element and indicating the degree of influence of a predetermined evaluation element on the mutual relationship between design elements, and an input for inputting an evaluation element Means C
L2 and a first design element having a high degree of influence from the first knowledge database CL5 based on the input evaluation element, and from the first knowledge database CL5 and the second knowledge database CL6, the specified design element is specified. To determine the degree of influence in consideration of the interaction of each of the other design elements, specify a second design element having a strong influence among the degrees of influence, and determine the other design elements by identifying the first and second design elements. A degree of influence taking into account the interaction of each design element is determined, a third design element having a high degree of influence among the degrees of influence is determined, and a means CL3 for inferring a design diagram and outputting the inferred design figure are output. Output means CL4.

[0020]

When an evaluation element is input by the input means CL2, the inference means CL3 infers a design diagram from the knowledge database CL1 in consideration of the interaction of the design element with the design image, and outputs the design diagram by the output means CL4.

[0021]

Embodiments of the present invention will be described below with reference to the drawings.

FIG. 2 shows a schematic configuration diagram of one embodiment. This design device is composed of a computer 1, a keyboard 3 as an input device, and a CRT 5 as a display device.

The computer 1 has a knowledge database C
L1, that is, a memory M as a first knowledge database CL5 and a second knowledge database CL6, and a CPU 7 as design diagram inference means CL3.

Here, in the memory M, a plurality of evaluation factors 9 as evaluation factors for expressing a design image of the vehicle interior, a vehicle design element 11, and a degree of influence are represented by a relationship between the evaluation factors and the design elements. A knowledge 13 and a knowledge 15 representing the degree of influence of a predetermined evaluation factor on the relationship between design elements are stored.

The evaluation factor 9 is constituted by design image factors such as “high-grade feeling factor” exemplified in the evaluation factor column in the chart of FIG.

As shown in the chart of FIG. 3, the vehicle design elements 11 are classified into categories for each element such as the interior color tone of the vehicle interior.

The knowledge 13 representing the degree of influence by the relationship between the evaluation factor and the design element indicates the extent to which the category j of the item i of each design element affects the evaluation factor by a numerical value {Xij}. It is indicated by a value from 0 to 1 as shown in the table of FIG.

The knowledge 15 representing the degree of influence of the predetermined evaluation factors on the relationship between the design elements is determined based on the relevance of the design element k when the design element k is determined as the interior configuration. The degree of influence that produces an image by taking in the element n as an interior configuration is represented by a numerical value {Ykn} in the form of a matrix as an interaction relevance, and is represented by a value from 0 to 1 as shown in the chart of FIG. Things. Also, the same two design elements k and n
, The value may be different even with a numerical value {Ynk} (row and column are reversed).

Here, the items focus on the interior color tone, instrument color tone, seat color tone and the like in the vehicle design element group 11, as shown in FIG. 3, for example.

The indoor colors are classified into two categories, dark and light. Hereinafter, items focusing on instrument colors and other items are classified into categories.

The keyboard 3 constitutes an input means CL4 for inputting the evaluation factor 9.

The CPU 7 determines whether the memory M (the first knowledge database CL 1, the second knowledge database
Is inferred using the knowledge database CL2).

The CRT 5 constitutes an output means CL4 for outputting the inferred design drawing, and displays the design drawing as an image.

FIG. 5 is a block diagram based on the configuration of FIG.

With the configuration shown in FIG. 2, the evaluation factors 9 and vehicle design elements 11 set in advance, the knowledge 13 indicating the degree of influence in the relationship between the evaluation factors and the design elements, and each design element for a predetermined evaluation factor Knowledge 15 or the like representing the degree of influence in the relationship between the two is stored in the memory M of the computer 1. Then, when the keyboard 3 is operated to input, for example, a factor k as the evaluation factor 9 (17), the CPU 13 operates the knowledge 13 representing the degree of influence in the relationship between the evaluation factor and the design element, and a predetermined evaluation factor. From the knowledge 15 indicating the degree of influence in relation to each design element, a combination of categories most suitable for the input factor is inferred and extracted (1).
9), and the result is displayed on the CRT 5 (21).

Next, the inference method in the block (19) is performed based on, for example, a flowchart shown in FIG.

First, the degree of influence (numerical value) of the design element on the evaluation factor input in step S1 is, for example, as shown in FIG.
Are extracted from the knowledge 13 representing the strength of the influence in the relationship between the evaluation factors and the design elements shown in the table of FIG. Then, in step S2, the category having the largest value among the degrees of influence of all the categories is extracted, and the first category as the optimal design element for the input factor is determined.

Next, steps S3 → S4 → S5 → S6
The process is executed in the order of → S7 → S8 → S9 → S10, and the second category as the optimal design element for the input factor is determined. At this time, in step S4, for example, the first category determined in step S2 from the knowledge 15 representing the degree of influence of the predetermined evaluation factors shown in the chart of FIG. , Interaction interaction degrees (numerical values) of all remaining categories are extracted. Then, the first category as the optimal design element which has been determined by multiplying the value of the interaction relevance of each category by the value of the influence of each category on the input factor extracted in step S2 is considered. The value of the degree of influence on the input factor is calculated. Then step S
At 5, the inconsistency check is performed on the influence values of all the categories calculated in step S4. That is, when the influence values of all the categories of a certain item become 0 with respect to the input factor values of all the categories in consideration of the interaction of the design elements determined by the immediately preceding step, in step S4. This means that the calculated impact values are inconsistent. In this case, the process proceeds to step S7 described below.

On the other hand, if there is no contradiction, step S6
Then, the category having the largest value among the degrees of influence taking into account the interaction calculated in step S4 is extracted, and the second category as the optimal design element for the input factor is determined (step S10). ).

If there is a contradiction, the process proceeds to step S7, and steps S8 and S9 are executed in this order. Step S
In step 8, the degree of influence is determined in consideration of the interaction calculated immediately before, and the category having the next largest value among the degrees of influence is extracted (step S9). Then, the extracted category is determined as a second category as an optimal design element for the input factor (step S10).

Next, it is determined whether or not the categories of all items have been determined in step S11.

If there is an undetermined item, the process proceeds to step S4 via step S12, and step S5 →
The process is repeatedly executed until all the categories are determined in the order of S6 → S7 → S8 → S9 → S10, and when all the categories are determined, this flow ends.

When it is desired to display the next candidate for the displayed input factor of the vehicle interior on the screen, the category having the second largest value among the degrees of influence of the design elements on the evaluation factor extracted in step S1 is selected. It is extracted by determining this category as the first category for the input factor (step S2), and performing the same steps as described above.

Next, the above-mentioned inference method will be described with a specific example. Here, for example, the input factor is “luxury”, and the items constituting the interior to be displayed are “indoor color”,
Three cases of “instrument tone” and “sheet tone” and two categories of <dark color> and <light color> will be described with reference to the flowchart of FIG.

In step S1, the influence of the design element on the input factor "luxury" is extracted from the knowledge 13 representing the strength of the influence in the relationship between the evaluation factor and the design element. In this example, as shown in the table of FIG. 3, the numerical values of each category are extracted as surrounded by a solid line. And step S
In step 2, the category having the maximum value among the degrees of influence of all the categories is extracted. In this example, the category <dark color> of the item “indoor color tone” is selected at 1.0. In the chart of FIG. 3, the numerical values are indicated by surrounding them with a solid triangle. In this way, “the interior color tone is dark” is determined as the first design element as the optimal design element for the input factor “luxury”.

Next, at step S4, the category "dark color" of the item "indoor color tone" determined at step S2 from the knowledge 15 representing the degree of influence of the predetermined evaluation factors on the relationship between the respective design elements. against, the rest of the element "Installation tone" category <dark> and <bright>, and the category of items "sheet color tone" and <dark> is interaction relevance of <bright> are extracted. In this example, as shown in the table of FIG. 4, the numerical values of each category are extracted as surrounded by a solid line.

The relationship between the interaction relevance of each category extracted in this way and the influence of each category on the input factor “luxury” extracted in step S2 is as follows if the latter is enclosed in parentheses. Become. That is, the category “dark color” of the item “instrument tone”... 0.4 (0.
4), <bright color>... 0.0 (0.8), category of item “sheet color” <dark color>... 0.3 (0.6),
Same <bright color>... 0.3 (0.4).

Then, the interaction relevance of each category is multiplied by the degree of influence on the input factor “luxury”, and the influence of each item on the design element “dark interior tone” is considered for “luxury”. The degree is calculated. That is, the category of the item “instrument
Dark> 0.16 (0.4 × 0.4), same <light>
… 0.0 (0.0 × 0.8), item “sheet color tone”
Of Katekori <dark color> ... 0.18 (0.3 x 0.6),
Same as <bright color>... 0.12 (0.3 × 0.4).

Next, in step S5, step S5
It is determined whether or not there is any contradiction regarding the degree of influence of all the categories calculated in step 4. In this example, since there is no inconsistency, the process proceeds to step S6, and the category having the maximum value among the influences of all the categories in consideration of the interaction calculated in step S4 is extracted. In this example, the category <dark color> of the item “sheet color tone” is selected at 0.18. Then, "the color tone of the sheet is dark" is determined as the second design element of the optimal design element relating to the input factor "luxury" (step S10).

Next, it is determined whether or not the categories of all items have been determined in step S11. In this example, since the category of the item “instrument tone” has not been determined, the process shifts to step S4 via step S12.

In step S4, the category <dark color> of the remaining item "instrument" for the category <dark color> of the item "sheet color" determined in step S10.
And <light color> are extracted. In this example, as shown in the table of FIG. 4, the values of the category are extracted as surrounded by a broken line.

With respect to the interaction relevance of the category <dark color> of the item "instrument" extracted in this way and the input factor "luxury", the influence in consideration of the interaction of the category <dark> of the item "indoor color". The relationship between degrees and parentheses is as follows. That is, the category <dark color> of the item “instrument tone”... 0.2
(0.16) and <bright color>... 0.8 (0.0).

Then, by multiplying the interaction relevance of each category by the influence of each category on the input factor "luxury", the design elements "dark in room color" and "dark in sheet color" for "luxury" are multiplied. Is calculated taking into account the interaction of That is, the category <dark color> of the item “instrument tone”... 0.036 (0.2 × 0.
16), <Light color>... 0.0 (0.8 × 0.0).

Then, the process proceeds to steps S5 and S6, and in step S6, the category having the maximum value among the degrees of influence of each category in consideration of the interaction calculated in step S4 is extracted. In this example, the category <dark color> of the item “instrument tone” is selected at 0.036. Then, “dark tone of instrument” is determined as the third design element as the optimal design element for the input factor “luxury” (step S10).

In this manner, the design factors relating to the input factor “luxury” are “dark in the room”, “dark in the seat”, and “dark in the instrument”, and the design between the design elements is determined. A design drawing can be output in consideration of interaction with an image. Therefore, it is possible to output a design drawing that matches the design image as a whole, not to mention individual design elements.

FIG. 7 is a block diagram according to another embodiment of the present invention.

In this embodiment, as an evaluation element, for example, an adjective word as an evaluation term expressing a design as shown in the table of FIG. 10 is input (31), and the input evaluation term is evaluated as an evaluation term and an evaluation factor. Is decomposed into evaluation factors from the relationship database 33 (35), and the relationship between each design element with respect to the knowledge indicating the degree of influence in the relationship between the evaluation factors and the design elements shown in FIG. 3 and the predetermined evaluation factors shown in FIG. Then, a database of the relationship between terms and design elements is created from the knowledge 37 indicating the degree of influence (39). Next, considering the weight of each evaluation factor for each evaluation term (see FIG. 10), using a knowledge 41 representing the degree of influence of the relationship between each design element with respect to the evaluation factor, a relation database between design elements related to input terms (FIG. 4) (43). Then, using this database, inference and display similar to 19 and 21 in FIG.
7). Therefore, in this embodiment, by inputting the evaluation terms, a design diagram can be output in consideration of the interaction between the design elements.

FIG. 8 is a block diagram according to still another embodiment of the present invention.

In this embodiment, a certain design element can be fixed, and the category can be corrected from the design drawing displayed on the CRT 5. This embodiment fixes elements that greatly contribute to the design image, and changes the elements other than the fixed elements when the output design drawing is different from the image.
It is designed to match the image. For example, the design element to be fixed includes a handle.

First, an evaluation factor is input (51), and then a fixed design element is input (53). Then, using the relational database 55 between the evaluation factor and the design element,
The database of the relationship between the evaluation factor and the design element accompanying the fixation of the design element is changed (57). In FIG. 3 and FIG. 4, when the "indoor color tone" is fixed to "dark color", the numerical value corresponding to this is deleted so that "indoor color tone is dark" is not included in the calculation in the inference process. Then, using the knowledge 59, inference and display similar to 19 and 21 in FIG.
1, 63). If the displayed design drawing does not match the image, the category of the element other than the fixed design element is changed (65). This change is also made in the same manner as described above in consideration of the interaction between design elements.

[0061]

As is clear from the above, according to the present invention, it is possible to output a design drawing in consideration of the interaction of the design image between design elements from the input evaluation elements, which is suitable for the image of the vehicle interior. You can get a design drawing.

[Brief description of the drawings]

FIG. 1 is a configuration diagram of the present invention.

FIG. 2 is a schematic configuration diagram of one embodiment.

FIG. 3 is a chart showing an example of knowledge representing the degree of influence in relation to an evaluation factor and a design element.

FIG. 4 is a chart showing an example of knowledge indicating the degree of influence of a predetermined evaluation factor on the relationship between design elements;

FIG. 5 is a block diagram of one embodiment.

FIG. 6 is a flowchart of the inference method in FIG. 5;

FIG. 7 is a block diagram according to another embodiment.

FIG. 8 is a block diagram according to another embodiment.

FIG. 9 is a block diagram according to a conventional example.

FIG. 10 is a diagram of knowledge defining a relationship between evaluation terms.

FIG. 11 is a diagram of knowledge that defines an association between an evaluation term and each item of a vehicle design element.

FIG. 12 is an explanatory diagram illustrating an example of image display.

FIG. 13 is an explanatory diagram illustrating an example of an image display.

[Explanation of symbols]

 CL1, knowledge database CL2 input means CL3 design diagram inference means CL4 output means CL5 first knowledge database CL6 second knowledge database

Continuation of the front page (58) Field surveyed (Int.Cl. ⁶ , DB name) G06F 17/50 JICST file (JOIS)

Claims (1)

(57) [Claims] 1. Expressing a design image of a design target
Multiple evaluation elements and multiple data
First knowledge indicating the degree of influence in relation to the Zine element
Database and specified evaluation requirements for each evaluation element
The degree of influence of the interaction between design elements
Input a second knowledge database representing the
Input means, and the first knowledge from the input evaluation element.
Identify the first design elements with high impact from the database
First knowledge database and second knowledge data
From the base, each of the other
Find the degree of influence taking into account the interaction of the
Identify the second design element with the strongest influence in the sound intensity,
From the identification of the first and second design elements, the other design
The influence that takes into account the interaction of the
Identify the third design element with the strongest impact in the design
Means for inferring in-drawings and outputting inferred design drawings
A design device comprising: