CN112800610A - Emotion-based modeling method for influence factors of indoor space lighting system - Google Patents

Emotion-based modeling method for influence factors of indoor space lighting system Download PDF

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CN112800610A
CN112800610A CN202110142170.3A CN202110142170A CN112800610A CN 112800610 A CN112800610 A CN 112800610A CN 202110142170 A CN202110142170 A CN 202110142170A CN 112800610 A CN112800610 A CN 112800610A
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emotion
rendering index
illumination
equation
color rendering
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陆蔚华
梁芯蕊
郭琦
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Nanjing University of Aeronautics and Astronautics
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Abstract

The invention discloses a method for modeling influence factors of an indoor space lighting system based on emotion, which comprises the steps of selecting illumination, color temperature and color rendering index as the influence factors of the indoor lighting system, carrying out single-factor control variable experiments, establishing a matrix of emotion feedback of a user to a lighting environment in each group of experiments, establishing a relational curve between the influence factors and the emotion and a fitting equation between the influence factors, and finally fitting a k-th-order surface equation of the illumination, the color temperature, the color rendering index and the emotion by using a least square method to determine an optimal solution and an optimal interval range. According to the invention, the color rendering index is introduced as an influence factor when the relation between the lighting system and the user emotion is researched, so that the model is more scientific and objective; in industrial design, mathematical means are used for analysis and prediction, the rationality of the design of the lighting system is evaluated, and the subjectivity and the fuzziness of artificial judgment are avoided.

Description

Emotion-based modeling method for influence factors of indoor space lighting system
Technical Field
The invention relates to a modeling method, in particular to a modeling method for the relationship between emotion and illumination space influence factors.
Background
The lighting environment is one of the most important physical environmental factors of people's life and working space, and in recent years, along with the development of social economy and the improvement of people's living standard of matter, along with the continuous improvement of understanding of light, people pay more and more attention to the quality of the lighting environment. The lighting environment has great influence on human emotion, and the ideal lighting environment not only needs to meet the visual and physiological requirements of people, but also needs to meet the psychological requirements of people. As shown in fig. 1, as early as 1941, the coruessov curve was constructed from psychophysical data collected by the netherlands physicist Kruithof, describing regions of luminance level and color temperature that are generally considered comfortable or satisfactory for the viewer. Since Kruithof does not describe an evaluation method, does not have a data verification process, but only evaluates a qualitative range, and there are many influencing factors of the lighting environment, including illuminance, color temperature, color rendering index, glare, illumination angle and direction, etc., it is obviously imperfect to analyze the relationship between the lighting system and human emotion or feelings using only illuminance and color temperature as the influencing factors of the lighting system.
Disclosure of Invention
The purpose of the invention is as follows: the invention aims to provide a modeling method for analyzing the relation between illumination, color temperature, color rendering index and emotion, which comprehensively evaluates the influence of a lighting system on human emotion and has systematicness and scientificity.
The technical scheme is as follows: the invention relates to a method for modeling influence factors of an indoor space lighting system based on emotion, which comprises the following steps of establishing an emotion feedback matrix of a user to a lighting environment by using a product emotion quantification method based on an acoustic parameter method:
(11) setting contrast experiments of illumination, color temperature, color rendering index and emotion;
(12) establishing an emotion feedback matrix of a user to the lighting environment;
(13) respectively establishing fitting equations among emotion, illumination, color temperature and color rendering index;
(14) respectively establishing a fitting equation between each two of the illumination, the color temperature and the color rendering index;
(15) and fitting a k-order surface equation of the emotion values corresponding to the illumination, the color temperature and the color rendering index by using a least square method, and determining an optimal solution and an optimal interval range.
Further, the optimal solution is the point P (Q) on the k-th order surface equation closest to the origin1,Q2,Q3) The optimal interval is the maximum on the k-th-order surface equationThe preferred solution is central, all contain
Figure BDA0002929447360000011
Within the range of a closed curve formed therein, wherein
Figure BDA0002929447360000012
And (3) respectively setting m groups of illumination, color temperature and color rendering index data in the comparison experiment of the step (11), carrying out a control variable experiment of a single factor, and selecting an intermediate value for other two influencing factors.
The fitting equation in the step (13) is a Gaussian equation.
The fitting equation in the step (14) is an nth-order polynomial equation.
Has the advantages that: (1) a model of comprehensive influence of the influence factors of the lighting system on emotion is established, and the quality of the lighting environment can be objectively and accurately evaluated, so that the lighting environment design is optimized; (2) the color rendering index is introduced as an influence factor of the lighting system, so that a relation model of the lighting system and emotion is enriched; (3) scientific means are introduced into the field of lighting system design, and informatization construction and development of industrial design industry are promoted.
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FIG. 1 is a prior art Koreux curve;
FIG. 2 is a flow chart of a modeling method of the present invention;
FIG. 3 is a two-dimensional plot of the present invention cut on a k-th fit curve.
Detailed Description
The technical scheme of the invention is further explained by combining the attached drawings.
As shown in fig. 2, the method for modeling influence factors of an indoor space lighting system based on emotion includes the following steps:
(1) experiment of single-factor controlled variable
(11) Selecting an illuminance, a color temperature and a color rendering index as influencing factors of an indoor space lighting system, wherein:
illuminance is the received luminous flux per unit area, denoted by the symbol E, and is given by lx. The formula is as follows:
Figure BDA0002929447360000021
wherein
Figure BDA0002929447360000022
Is the luminous flux, in lm; a is the area in m2。
The color temperature is the color temperature of a light source when the chromaticity of the light source is the same as the chromaticity of the complete radiator at a certain temperature, and the symbol T is usedcExpressed in units of K.
The color rendering index is a value indicating the level of visual perception of an object by a light source under sunlight, and is represented by a symbol Ra. The higher the color rendering, the closer the color rendering index value is to 100, the stronger the color reduction capability of the object, and the easier it is for human eyes to distinguish the colors of the object.
Setting m sets of illumination data { A1,A2……AmSetting m groups of color temperature data { B }1,B2……BmAnd setting m groups of color rendering index data { C1,C2……CmWhere m is odd. In order to explore the influence of a single factor on the emotion of a user, the other two influencing factors select a middle value, 3 x m groups of lighting environments are set, and an experiment is carried out by using a control variable method. To explore the influence of illumination on emotion, m groups of comparison experiments were set: (A)1，B(1+m)/2，C(1+m)/2)、(A2，B(1+m)/2，C(1+m)/2)、......(Am，B(1+m)/2，C(1+m)/2) (ii) a To explore the influence of color temperature on emotion, m groups of comparison experiments were set: (A)(1+m)/2，B1，C(1+m)/2)、(A(1+m)/2，B2，C(1+m)/2)、......((A(1+m)/2，Bm，C(1+m)/2) (ii) a To explore the influence of the color rendering index on emotion, m groups of control experiments were set: (A)(1+m)/2，B(1+m)/2，C1)、(A(1+m)/2，B(1+m)/2，C2)、......(A(1+m)/2，B(1+m)/2，Cm)。
(12) Selecting l music pieces to form an acoustic library, controlling the duration of each music piece to be about 5 seconds, defining the music pieces in the acoustic library by k parameters, and obtaining a parameter matrix P:
Figure BDA0002929447360000031
when the testee is in a lighting environment, three music pieces are randomly played, and the testee selects the music piece which best meets the current lighting environment. After the first selection is completed, three different music pieces are randomly played again, and the testee makes a second selection. After the previous two selections are completed, three different music pieces are randomly played again, and the testee makes a third selection. The 9 music pieces played in the three experiments are different from each other. Finally, the first three selected music pieces are taken as alternatives, the music piece which best meets the current lighting environment is selected, the selected frequency of the music piece is recorded as 0.5, and the selected frequencies of the other two music pieces are recorded as 0.25. After all the testees finish the experiment, obtaining a music piece selected frequency matrix F according to the selection results of all the testees, and calculating the average value of all the frequency matrices
Figure BDA0002929447360000032
Figure BDA0002929447360000033
The user's emotional feedback to the lighting environment is defined as a matrix V:
Figure BDA0002929447360000034
(2) fitting relation curve
(21) According to the experiment in the step (1), the emotional change basically conforms to the normal distribution along with the change of the illumination, the color temperature and the color rendering index.
Emotion to luminance relationship:
Figure BDA0002929447360000035
Figure BDA0002929447360000036
Figure BDA0002929447360000037
wherein A is1Is the amplitude, b1Is a constant term, μ1Is a mean value, σ1 2Is the variance.
Emotion to color temperature relationship:
Figure BDA0002929447360000041
Figure BDA0002929447360000042
Figure BDA0002929447360000043
wherein A is2Is the amplitude, b2Is a constant term, μ2Is a mean value, σ2 2Is the variance.
Emotion to color rendering index relationship:
Figure BDA0002929447360000044
Figure BDA0002929447360000045
Figure BDA0002929447360000046
wherein A is3Is the amplitude, b3Is a constant term, μ3Is a mean value, σ3 2Is the variance.
(22) And fitting a relation curve among the illumination, the color temperature and the color rendering index according to the relation.
Color temperature versus illumination:
T(xE)＝a0+a1xE+a2xE 2+…+anxE n
luminance versus color rendering index:
E(xRa)＝b0+b1xRa+b2xRa 2+…+bnxRa n
color temperature versus color rendering index:
T(xRa)＝c0+c1xRa+c2xRa 2+…+cnxRa n
wherein { a0，a1……an}、{b0，b1……bnAnd { c }and0，c1……cnIs the coefficient of an nth degree polynomial.
(3) Least square method fitting surface equation
Calculating discrete points (Q) according to step (2)1,Q2,Q3) Fitting the fitted surface equation by using a least square method, wherein the k-th surface equation can be expressed as:
Figure BDA0002929447360000047
the formula is shared
Figure BDA0002929447360000048
Item, there are
Figure BDA0002929447360000049
Coefficient of Cij。
(4) Determining an optimal range of intervals
The k-th order surface conforms to multidimensional normal distribution, a point P with the maximum distance from the origin is taken as the optimal solution, the distance from the origin is represented by a symbol R,
Figure BDA0002929447360000051
passing point P (Q)1,Q2,Q3) The cut surface is made to the xy plane, and the resulting two-dimensional curve is shown in FIG. 3. In the experimental science, the 3 σ law of normal distribution is that "almost all" values are within the range of plus or minus three standard deviations of the mean, that is, the probability of 99.7% can be regarded as "almost constant" experimentally, and therefore the optimal solution P (Q) is taken1,Q2,Q3) Is a center, comprising
Figure BDA0002929447360000052
The closed curved surface formed within the range is the optimal interval range: wherein
Figure BDA0002929447360000053
The emotion feedback of the user is good in the optimal interval range, the lighting environment in the state is comfortable, a designer can scientifically design a lighting system of an indoor space according to the optimal interval range, whether the service design is reasonable or not is evaluated, and the most comfortable lighting experience is brought to people.

Claims (6)

1. A method for modeling influence factors of an indoor space lighting system based on emotion comprises the steps of establishing an emotion feedback matrix of a user to a single factor of a lighting environment by using a product emotion quantification method based on an acoustic parameter method, and is characterized by further comprising the following steps:
(11) setting contrast experiments of illumination, color temperature, color rendering index and emotion;
(12) establishing an emotion feedback matrix of a user to the lighting environment;
(13) respectively establishing fitting equations among emotion, illumination, color temperature and color rendering index;
(14) respectively establishing a fitting equation between each two of the illumination, the color temperature and the color rendering index;
(15) and fitting a k-order surface equation of the emotion values corresponding to the illumination, the color temperature and the color rendering index by using a least square method, and determining an optimal solution and an optimal interval range.
2. The method of claim 1, wherein the optimal solution is the point P (Q) on the k-th surface equation closest to the origin1,Q2,Q3)。
3. The method of claim 1, wherein the optimal interval is centered on the optimal solution on the k-th order surface equation and comprises
Figure FDA0002929447350000011
Within the range of a closed curve formed therein, wherein
Figure FDA0002929447350000012
4. The method of claim 1, wherein m sets of illumination, color temperature and color rendering index data are set in the control experiment of step (11), a single-factor control variable experiment is performed, and the other two influencing factors are selected as intermediate values.
5. The method of claim 1, wherein the fitting equation of step (13) is a Gaussian equation.
6. The method of claim 1, wherein the fitting equation of step (14) is an nth order polynomial equation.
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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102507151A (en) * 2011-10-25 2012-06-20 复旦大学 Reading desk lamp evaluation method based on ergonomic experiment
CN103489453A (en) * 2013-06-28 2014-01-01 陆蔚华 Product emotion qualification method based on acoustic parameters
US20160306844A1 (en) * 2015-01-29 2016-10-20 Affectomatics Ltd. Determining a Cause of Inaccuracy in Predicted Affective Response
CN107239738A (en) * 2017-05-05 2017-10-10 南京邮电大学 It is a kind of to merge eye movement technique and the sentiment analysis method of heart rate detection technology
CN109429415A (en) * 2017-08-29 2019-03-05 美的智慧家居科技有限公司 Illumination control method, apparatus and system

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102507151A (en) * 2011-10-25 2012-06-20 复旦大学 Reading desk lamp evaluation method based on ergonomic experiment
CN103489453A (en) * 2013-06-28 2014-01-01 陆蔚华 Product emotion qualification method based on acoustic parameters
US20160306844A1 (en) * 2015-01-29 2016-10-20 Affectomatics Ltd. Determining a Cause of Inaccuracy in Predicted Affective Response
CN107239738A (en) * 2017-05-05 2017-10-10 南京邮电大学 It is a kind of to merge eye movement technique and the sentiment analysis method of heart rate detection technology
CN109429415A (en) * 2017-08-29 2019-03-05 美的智慧家居科技有限公司 Illumination control method, apparatus and system

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
W LU等: "Affective design of products using an audio-based protocol: Application to eyeglass frame", 《INTERNATIONAL JOURNAL OF INDUSTRIAL ERGONOMICS》 *
葛玲玉: "基于声学参数法的产品智能设计方法研究", 《中国优秀博硕士学位论文全文数据库(硕士)工程科技Ⅱ辑》 *
陆蔚华: "户情绪的特征及其评价尺度", 《中国基础科学》 *

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