Helicopter coating color matching method

Abstract

The invention belongs to the technical field of helicopter industrial design, and particularly relates to a helicopter coating color matching method. Comprising the steps of 1, constructing helicopter coating style perceptual image data A; 2, nine typical color samples are constructed; 3, performing carding to form typical color sample perceptual image data B; 4, establishing a color matching scheme taking the typical color sample as a main color; 5, constructing a core mapping relation between the helicopter coating style and the typical color sample, and forming a helicopter coating color matching scheme database; and step 6, obtaining a coating color matching scheme of a given style based on the mapping relation between the coating style and the typical color.

Description

Technical Field

[0001] This invention belongs to the field of helicopter industrial design technology, and in particular relates to a method for matching colors in helicopter paint. Background Technology

[0002] Helicopter paint schemes have a significant impact on visual appeal, brand recognition, professional image, and user experience. A paint scheme that meets diverse user needs can enhance market competitiveness and user experience. However, current helicopter paint schemes have certain limitations in terms of color matching.

[0003] Currently, coating scheme design mainly relies on personal experience and subjective aesthetic preferences, resulting in low design efficiency and an inability to meet the needs of rapid optimization and iteration. Patent CN117671064B discloses a method for defining the interior color of a transport aircraft. It first divides the visible area inside the transport aircraft into a primary color area and a secondary color area, and then evaluates the overall aesthetic appeal of the color scheme based on aesthetic theory. However, this patent lacks the ability to capture and transform the personalized emotional needs of the target users, and also lacks a systematic database of color matching scheme samples. This leads to a deviation between the scheme and the expectations of the target users, resulting in increased design iterations and a longer development cycle. Patent CN116738717B discloses a product color scheme design method and system based on color imagery transfer. It uses subjective and objective evaluation methods to select excellent color scheme cases and their combinations from various evaluation dimensions, and then expresses the correlation between the product color scheme gene planning influence factors and the evaluation dimensions to form a product color scheme gene planning scheme library. However, this patent extracts a large number of excellent color scheme case samples, resulting in an overly broad range of color choices and insufficient constraints, directly affecting the design's relevance. Furthermore, the method's calculation steps are too complex, leading to low design efficiency and poor knowledge universality and reusability. Summary of the Invention

[0004] Purpose of the invention: To address the problems of existing helicopter paint schemes failing to accurately capture user needs, resulting in low design efficiency and poor knowledge reusability, this invention proposes a helicopter paint scheme color matching method. Based on sensory engineering and color psychology, it constructs a mapping relationship between helicopter paint style dimensions and color samples to assist in design decisions. Simultaneously, it establishes a helicopter paint scheme color matching database to quickly extract helicopter paint scheme color matching solutions that meet user needs.

[0005] This invention provides a method for matching colors in helicopter paint schemes, comprising the following steps: Step 1: Collect text data based on keyword strategy, sort out and extract text related to "user needs" and "product design", and then reorganize it into 7 painting style dimensions through semantic clustering to construct the emotional image data A of helicopter painting style; Step 2: Based on the color wheel, select chromatic and achromatic colors to construct 9 typical color samples; Step 3: Based on 9 typical color samples, combined with color psychology and color imagery scale model, extract the textual data of sensory imagery and sort it into sensory imagery data B of typical color samples; Step 4: Based on 9 typical color samples and referring to Munsell's color harmony theory, establish a color scheme with the typical color samples as the main colors; Step 5: Using the semantic difference method, based on the sensory imagery data A of helicopter paint style and the sensory imagery data B of typical color samples, construct the core mapping relationship between helicopter paint style and typical color samples, and form a helicopter paint color matching scheme database. Step Six: Select preliminary single-color and multi-color paint schemes based on typical colors in the helicopter paint scheme database. Then, combine user-personalized selections to capture their preferred paint style. Based on the mapping relationship between paint style and typical colors, obtain a paint scheme for a given style.

[0006] In summary, the beneficial effects of the present invention are as follows: This invention proposes a method for helicopter paint scheme color matching, applicable to the design of user-demand-oriented helicopter paint scheme color matching solutions. It addresses current problems in helicopter paint scheme design, such as the inability to accurately capture and translate user needs, low design efficiency, and poor knowledge reusability. This method has been successfully applied to a certain type of helicopter and can be applied to other helicopters in the future, demonstrating significant engineering application value. Attached Figure Description

[0007] Figure 1 A flowchart of a helicopter paint scheme color matching method; Figure 2 A preliminary schematic diagram of the helicopter paint scheme. Figure 3 A diagram illustrating the user's preferred paint style; Figure 4 A diagram illustrating the selection of user-preferred paint styles; Figure 5 A schematic diagram of color schemes for helicopter paint jobs. Detailed Implementation

[0008] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings.

[0009] This invention proposes a method for matching colors in helicopter paint schemes, which solves the problems of inaccurate capture and transformation of user needs, low design efficiency, and poor knowledge reusability in the current helicopter paint scheme design process.

[0010] A method for matching helicopter paint scheme colors firstly involves analyzing user needs based on sensory engineering to construct sensory imagery data A for helicopter paint scheme styles; then, using color psychology, constructing sensory imagery data B for typical color samples, and combining color harmony theory to determine the color scheme scheme with each typical color sample as the main color; next, based on data A and data B, using semantic difference method, constructing the core mapping relationship between helicopter paint scheme styles and typical color samples, and building a database of paint scheme color matching schemes suitable for helicopters; finally, determining a single-color paint scheme based on the typical color samples of the mapping relationship, and determining a multi-color paint scheme based on the database.

[0011] A method for matching colors in helicopter paint schemes, such as Figure 1 As shown, it includes the following steps: Step 1: Collect text data based on keyword strategy, sort out and extract text related to "user needs" and "product design", and then reorganize it into 7 painting style dimensions through semantic clustering to construct the emotional imagery data A of helicopter painting style. 1) Using open text retrieval on the Internet, combined with keyword strategies such as "aircraft paint evaluation" and "appearance design sense", text was collected to obtain the set of retrieved texts, as shown in Table 1.

[0012] Table 1. Collection of Retrieved Texts

[0013] 2) Extract and identify five key evaluation dimensions that are strongly related to user needs from the retrieved text collection Table 1, including “visual appeal”, “functionality”, “brand value”, “emotional resonance” and “innovation”, and include all texts in the corresponding dimensions to form a key evaluation dimension text classification table, as shown in Table 2.

[0014] Table 2 Key Evaluation Dimensions Text Classification

[0015] 3) Remove negative evaluation terms and overly vague terms that are irrelevant to the positive goals of helicopter painting design, and extract texts that are strongly related to product design and have clear guiding significance. The selected helicopter painting design texts are shown in Table 3.

[0016] Table 3. Text Screening for Helicopter Painting Design

[0017] 4) Using the results of questionnaire surveys and in-depth interviews, we collected feedback and suggestions from target users on helicopter paint schemes, extracted high-frequency words such as "attack" and "powerful", and supplemented them to form a text collection on helicopter paint schemes, as shown in Table 4.

[0018] Table 4. Text Collection for Helicopter Painting

[0019] 5) Unify the part-of-speech of all texts in the text collection for helicopter painting, and divide them into seven painting style dimensions according to the criteria of "emotional tendency", "visual feeling" and "style type": "modern and fashionable style", "natural and comfortable style", "traditional and elegant style", "dynamic and powerful style", "unique and individual style", "technological and future style" and "military and majestic style", forming the emotional imagery data A of helicopter painting style, as shown in Table 5.

[0020] Table 5. Data on the Emotional Imagery of Helicopter Painting Styles

[0021] Step 2: Based on the color wheel, select chromatic and achromatic colors to construct 9 typical color samples. Combine color psychology and color imagery scale model to extract emotional imagery text data and sort them into emotional imagery data B of typical color samples. At the same time, refer to Munsell's color harmony theory to establish a color scheme with typical color samples as the main color.

[0022] 1) Select 6 chromatic colors evenly from the color wheel and combine them with 3 achromatic colors to form 9 typical color samples, namely "red, orange, yellow, green, blue, purple, black, white, and gray".

[0023] 2) For the nine typical color samples, color psychology and the standardized color imagery scale space model were used to obtain the corresponding emotional imagery texts from the core dimensions of "hue", "purity", "brightness", "attribute", "feeling", "emotional expression", "cultural association" and "symbolic meaning", as shown in Table 6.

[0024] Table 6. Sensory Imagery Text of Typical Color Samples

[0025] 3) Based on the emotional imagery texts in Table 6, texts related to "product appearance design", "overall style", "color selection" and "visual effect" were selected from the dimensions of "product design relevance", "descriptive accuracy", "design guidance value" and "visual expressiveness", forming the product design related text selection results, as shown in Table 7.

[0026] Table 7. Results of Product Design Related Text Filtering

[0027] Based on color psychology theory, the selected texts in Table 7 were integrated to form typical color sample sensory imagery data B, as shown in Table 8.

[0028] Table 8. Sensory Imagery Data of Typical Color Samples

[0029] 5) Based on Munsell's color harmony theory, each of the nine typical color samples is used as the main color to determine the corresponding five types of color schemes, namely, monochromatic gradient harmony, analogous color harmony, complementary color segmentation harmony, triangular color harmony, rectangular four-color harmony, etc.

[0030] 6) For all determined color schemes, calculate the color difference and contrast (using the internationally recognized WCAG2.1 and CIEDE2000 improved color difference formulas) to select effective color schemes. Then, use the Birkhoff aesthetic evaluation model to evaluate the harmony and suitability of the color schemes. Calculate the aesthetic value M for all effective color schemes and select the color schemes with the highest aesthetic value as typical color sample color matching scheme samples.

[0031] Step 3: Use semantic difference method to construct the core mapping relationship between helicopter paint style and typical color samples.

[0032] 1) Based on data A (7 style dimensions) and data B (9 typical color samples), calculate the semantic similarity W between the style dimensions and the typical color samples. ij See Table 9: (1) In equation (1), A i B represents the text contained in the i-th style dimension of data A; j This represents the text contained in the j-th typical color sample in data B; Num(A i ∩B j ) represents A i and B j Total number of texts; Num(A) i ∪B j ) represents A i and B j The total number of texts contained.

[0033] Table 9 shows the semantic similarity calculation results between data A and data B.

[0034] 2) Rank the semantic similarity for each style dimension, and select W. ij The top 5 typical color samples are used as mappings to the corresponding style dimensions, as shown in Table 10.

[0035] Table 10 Mapping Table of Painting Styles and Typical Colors

[0036] 3) Based on the typical color samples in Table 10, determine the color matching scheme for the corresponding style of monochrome paint, and combine the color matching scheme samples of the typical color samples to determine the color matching scheme for the corresponding style of multicolor paint, forming a helicopter paint color matching scheme database (hereinafter referred to as "paint color database").

[0037] Step 4: Select preliminary single-color and multi-color painting color schemes for typical colors in the painting color database. Then, combine the user's personalized selection to capture their preferred painting style. Based on the mapping relationship between painting style and typical colors, obtain a painting color scheme for the given style.

[0038] 1) Using nine typical colors from the paint color database as base colors, nine pure monochrome paint color schemes were constructed; then, using these nine typical colors as primary colors, the "triangular color matching" schemes from the paint color database were extracted to construct nine multi-color paint color schemes. (See...) Figure 2 .

[0039] 2) Based on user preferences, five helicopter paint scheme color combinations were selected, and the main color of each scheme was extracted. See [link / reference]. Figure 5 .

[0040] 3) Based on the mapping relationship between painting style and typical colors, select the corresponding painting style from the main color extracted in step 2), which mainly includes the following two forms: (a) The primary color appears simultaneously in a certain style dimension, such as Figure 5 As shown, if the three main colors "black", "blue" and "gray" appear simultaneously in the "military and majestic" and "traditional and elegant" paint styles, then these two styles will be selected as the user's preferred styles.

[0041] (b) The primary color cannot appear simultaneously in a certain style dimension, such as Figure 4 As shown, among the four main colors of "white", "green", "blue" and "gray", "white", "blue" and "gray" appear in the "technology and future" style, while "green", "blue" and "gray" appear in the "military and majestic" style. The main color types in the above two styles account for 75%, which is significantly higher than other styles. Therefore, these two styles are regarded as user preference styles.

[0042] 4) Select all colors in the given painting style as typical colors. Taking step 3)b) as an example, construct color matching schemes for pure monochrome, mixed monochrome, and multi-color painting respectively, such as... Figure 5As shown. The pure monochrome scheme uses a typical color as the base color to construct five color matching schemes: "green", "blue", "black", "gray" and "white". The mixed monochrome scheme uses "green" and "blue" from the typical colors as the base colors, and combines them with achromatic colors such as "black", "gray" and "white" to construct six color matching schemes: "dark green", "medium green", "light green", "dark blue", "medium blue" and "light blue". The multi-color painting color matching scheme uses the above five pure monochrome and six mixed monochrome as the main colors, and combines them with the "triangular color matching" in the painting color database to construct and obtain 11 color matching schemes.

[0043] The key point of this invention is a helicopter paint scheme color matching method, which is applicable to the design of helicopter paint scheme color matching schemes based on user needs. It can solve the problems of the current helicopter paint scheme design process, such as the inability to accurately capture and transform user needs, low design efficiency, and poor knowledge reusability.

[0044] The helicopter painting color matching method described herein integrates the research methods of sensible ergonomics design and the design theory of color psychology. The mapping relationship must be consistent with local culture and the development of the times, and be updated regularly to ensure its effectiveness; The aforementioned helicopter paint scheme database can be further optimized and converged through user satisfaction surveys.

Claims

1. A method for matching colors in helicopter paint schemes, characterized in that, Includes the following steps: Step 1: Collect text data based on keyword strategy, sort out and extract text related to "user needs" and "product design", and then reorganize it into 7 painting style dimensions through semantic clustering to construct the emotional imagery data A of helicopter painting style; Step 2: Based on the color wheel, select chromatic and achromatic colors to construct 9 typical color samples; Step 3: Based on 9 typical color samples, combined with color psychology and color imagery scale model, extract the textual data of sensory imagery and sort it into sensory imagery data B of typical color samples; Step 4: Based on 9 typical color samples and referring to Munsell's color harmony theory, establish a color scheme with the typical color samples as the main colors; Step 5: Using the semantic difference method, based on the sensory imagery data A of helicopter paint style and the sensory imagery data B of typical color samples, construct the core mapping relationship between helicopter paint style and typical color samples, and form a helicopter paint color matching scheme database. Step Six: Select preliminary single-color and multi-color paint schemes based on typical colors in the helicopter paint scheme database. Then, combine user-personalized selections to capture their preferred paint style. Based on the mapping relationship between paint style and typical colors, obtain a paint scheme for a given style.

2. The helicopter painting color matching method according to claim 1, characterized in that, Step one is as follows: S11 utilizes open text retrieval on the Internet and combines keyword strategies to collect text, resulting in a set of retrieval texts. Keywords must include at least: aircraft paint evaluation and appearance design. S12, extract and identify 5 key evaluation dimensions that are strongly related to user needs from the search text set, including "visual appeal", "functionality", "brand value", "emotional resonance" and "innovation", and include all texts in the search text set into the corresponding dimensions to form a text classification table of key evaluation dimensions; S13, remove negative evaluation terms and overly vague terms that are irrelevant to the positive goals of helicopter paint design from the text classification table of key evaluation dimensions, extract texts that are strongly related to product design and have clear guiding significance, and obtain the selected helicopter paint design texts. S14. Collect feedback and suggestions from target users on helicopter paint schemes, extract high-frequency words, and supplement them to form a text collection for helicopter paint schemes; high-frequency words should at least include "attack" and "majestic". S15 unifies the part-of-speech of all texts in the text collection for helicopter painting and divides them into seven painting style dimensions according to the standards of "emotional tendency", "visual feeling" and "style type": "modern and fashionable style", "natural and comfortable style", "traditional and elegant style", "dynamic and powerful style", "unique and individual style", "technological and futuristic style" and "military and majestic style", forming the emotional imagery data A of helicopter painting style.

3. The helicopter painting color matching method according to claim 2, characterized in that, Step two is as follows: Six chromatic colors are evenly selected from the color wheel and combined with three achromatic colors to form nine typical color samples, namely "red, orange, yellow, green, blue, purple, black, white, and gray".

4. The helicopter painting color matching method according to claim 3, characterized in that, Step three specifically involves: S31, for 9 typical color samples, uses color psychology and a standardized color image scale space model to obtain corresponding emotional image texts from the core dimensions of "hue", "purity", "brightness", "attribute", "feeling", "emotional expression", "cultural association", and "symbolic meaning". S32, based on emotional imagery text, filters out texts related to "product appearance design", "overall style", "color selection" and "visual effect" from the dimensions of "product design relevance", "descriptive accuracy", "design guidance value" and "visual expressiveness", forming the product design related text filtering results; S33, combining color psychology theory, integrates the product design-related text screening results to form typical color sample sensory imagery data B.

5. The helicopter painting color matching method according to claim 4, characterized in that, Step four is as follows: S41. According to Munsell's color harmony theory, each of the nine typical color samples is used as the main color to determine the corresponding five types of color schemes, namely, monochrome gradient harmony, analogous color harmony, complementary color segmentation harmony, triangular color harmony, and rectangular four-color harmony. S42. For the five color schemes, calculate the color difference and contrast, select the effective color schemes, and then use the Birkhoff aesthetic evaluation model to calculate the beauty value M of the effective color schemes. Select the color schemes with the highest beauty value as the color matching scheme samples of the typical color samples.

6. The helicopter painting color matching method according to claim 5, characterized in that, Step five is as follows: S51, based on the sensory imagery data A of helicopter paint scheme style and the sensory imagery data B of typical color samples, calculate the semantic similarity W between the style dimension and the typical color samples. ij : In the formula, A i B represents the text contained in the i-th style dimension of data A; j This represents the text contained in the j-th typical color sample in data B; Num(A i ∩B j ) represents A i and B j Total number of texts; Num(A) i ∪B j ) represents A i and B j The total number of texts contained; S52, perform semantic similarity ranking for each style dimension in data A, and select W. ij The top 5 typical color samples serve as mappings to the corresponding style dimensions; S53. Based on 9 typical color samples, determine the corresponding style of monochrome paint scheme. Combine the color scheme samples of the typical color samples to determine the corresponding style of multicolor paint scheme, forming a helicopter paint scheme database.

7. The helicopter painting color matching method according to claim 6, characterized in that, Step six specifically involves: S61. Using nine typical colors from the helicopter paint color matching scheme database as base colors, nine pure monochrome paint color matching schemes are constructed. Then, using the nine typical colors as main colors, the "triangular color matching" scheme from the helicopter paint color matching scheme database is extracted to construct nine multi-color paint color matching schemes, for a total of 18 paint color matching schemes. S62, based on the user's personal preference, selected 5 helicopter paint schemes from 18 paint schemes, and extracted the main color of each scheme; S63, based on the mapping relationship between painting style and typical colors, the final painting style is selected according to the extracted main color; S64 selects all colors in the final paint style as typical colors and constructs pure monochrome, mixed monochrome and multi-color paint color matching schemes respectively.

8. The helicopter painting color matching method according to claim 7, characterized in that, In S63, the final paint scheme includes the following two forms: If the primary color appears in a certain style dimension, then that style dimension is selected as the user's preferred style. Since the primary color cannot appear in a certain style dimension at the same time, the style dimension with the highest proportion of primary color types is selected as the user's preferred style.

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