Spectral scoring method, apparatus, device and medium based on lighting scene

Abstract

The present application belongs to the technical field of LED lighting, and provides a spectrum scoring method, device, equipment and medium based on a lighting scene. The method comprises obtaining a target spectrum of a target LED and a standard spectrum of a standard illuminant; obtaining a corresponding similarity deviation interval according to the spectral characteristics of the standard spectrum in each preset wavelength interval. Scene information of the target LED is obtained and an adjustment factor of each preset wavelength interval is obtained accordingly, the adjustment factor is used to adjust each similarity deviation interval, and a target similarity deviation interval corresponding to the lighting scene is obtained. Finally, the spectral similarity of the target spectrum is obtained by combining the spectral similarity and the target similarity deviation interval. The spectral characteristics and similarity deviation of each wavelength interval under different scenes are comprehensively considered, the evaluation of the spectral performance of the LED product is specified, the customized evaluation can be performed according to the requirements of different scenes, the accuracy and applicability of the spectral evaluation result are improved, and a method is provided for the design and optimization of the LED lighting product.

Description

[0001] This application is a divisional application of the invention patent application with the application date of March 26, 2024, the invention name of "Evaluation method, device and equipment based on spectral similarity and medium", the application number of 2024103472559. TECHNICAL FIELD

[0002] The present application relates to the field of LED lighting technology, and in particular to a spectral scoring method, device, equipment and medium based on lighting scene. BACKGROUND

[0003] In the field of light-emitting semiconductor lighting, LED has been widely used as a high-efficiency and energy-saving light source. However, due to the diversity and complexity of LED spectrum, it is crucial to evaluate the quality and performance of LED products. Spectral similarity is an index to evaluate the similarity between two spectra, which is usually used to compare the color quality of different light sources or judge the matching degree of spectra. In the fields of lighting, plant growth, etc., accurate evaluation of spectral similarity is crucial to ensure the required light quality.

[0004] The existing spectral similarity calculation scheme mainly compares the spectral shape and amplitude, often ignoring the spectral feature information and the different requirements for spectral similarity in different wavelength intervals under different lighting scenes, so the method in the related art has certain limitations in evaluating the color quality of LED light source, resulting in inaccurate evaluation results of the spectrum. SUMMARY

[0005] Therefore, the embodiments of the present application provide a spectral scoring method, device, equipment and medium based on lighting scene, to solve the problem that the existing spectral similarity calculation scheme does not consider the spectral features and related factors of the lighting scene, resulting in inaccurate evaluation results.

[0006] In a first aspect, the embodiments of the present application provide a spectral scoring method based on lighting scene, the method comprising:

[0007] Obtaining the relative spectrum of the target LED and the relative spectrum of the standard illuminant, denoted as target spectrum and standard spectrum respectively;

[0008] According to the spectral features of the standard spectrum in each preset wavelength interval, the similarity deviation interval corresponding to each preset wavelength interval is obtained; wherein each preset wavelength interval has no intersection and belongs to the visible light wavelength range, and the similarity deviation interval corresponding to different preset wavelength intervals is different;

[0009] Obtaining the scene information of the target LED lighting scene, and obtaining the adjustment factor corresponding to each preset wavelength interval according to the scene information;

[0010] adjusting each of the similarity deviation intervals according to the adjustment factor, to obtain a target similarity deviation interval corresponding to the lighting scene;

[0011] According to the spectral similarity of each of the preset wavelength intervals and the corresponding target similarity deviation interval, a spectral similarity score of the target spectrum of the target LED is obtained.

[0012] Preferably, the preset wavelength intervals include a red wavelength interval of 622-700 nm, an orange wavelength interval of 597-622 nm, a yellow wavelength interval of 577-597 nm, a green wavelength interval of 492-577 nm, a cyan wavelength interval of 475-492 nm, a blue wavelength interval of 450-475 nm, and a violet wavelength interval of 400-450 nm.

[0013] Preferably, the step of obtaining a similarity deviation interval corresponding to each of the preset wavelength intervals according to the spectral characteristics of the standard spectrum in each of the preset wavelength intervals comprises:

[0014] obtaining the spectral characteristics of the standard spectrum in each of the preset wavelength intervals;

[0015] According to the spectral energy distribution, the spectral gradient angle, and the human eye visibility, a first deviation threshold and a second deviation threshold corresponding to each of the preset wavelength intervals are determined, wherein the first deviation threshold is a negative number, used to represent the maximum deviation allowed when the light intensity of the target spectrum in the corresponding preset wavelength interval is lower than that of the standard spectrum; the second deviation threshold is a positive number, used to represent the maximum deviation allowed when the light intensity of the target spectrum in the corresponding preset wavelength interval is higher than that of the standard spectrum;

[0016] According to the first deviation threshold and the second deviation threshold, a similarity deviation interval corresponding to each of the preset wavelength intervals is obtained.

[0017] Preferably, the step of obtaining the scene information of the target LED lighting scene and obtaining an adjustment factor corresponding to each of the preset wavelength intervals according to the scene information comprises:

[0018] obtaining the scene information of the target LED lighting scene;

[0019] According to the scene information, a first threshold adjustment factor and a second threshold adjustment factor corresponding to each of the preset wavelength intervals are obtained; wherein the first threshold adjustment factor is used to adjust the first deviation threshold of the preset wavelength interval, and the second threshold adjustment factor is used to adjust the second deviation threshold of the preset wavelength interval.

[0020] Preferably, the step of obtaining the first threshold adjustment factor and the second threshold adjustment factor corresponding to each of the preset wavelength intervals according to the scene information comprises:

[0021] According to the scene information, the preset wavelength intervals are screened to obtain key wavelength intervals;

[0022] According to the scene information, the first threshold adjustment factor and the second threshold adjustment factor of each of the key wavelength intervals are set;

[0023] The first threshold adjustment factor and the second threshold adjustment factor of the preset wavelength intervals other than the key wavelength intervals are both set to 1.

[0024] Preferably, the step of screening the preset wavelength intervals according to the scene information to obtain key wavelength intervals comprises:

[0025] When the scene information indicates that the lighting scene is a classroom scene, the obtained key wavelength intervals include a green wavelength interval 492-577 nm and a blue wavelength interval 450-475 nm;

[0026] When the scene information indicates that the lighting scene is an office scene, the obtained key wavelength intervals include a green wavelength interval 492-577 nm and a yellow wavelength interval 577-597 nm;

[0027] When the scene information indicates that the lighting scene is factory lighting, the obtained key wavelength intervals include a blue wavelength interval 450-475 nm.

[0028] Preferably, the step of obtaining the spectral similarity score of the target spectrum of the target LED according to the spectral similarity of each of the preset wavelength intervals and the corresponding target similarity deviation interval comprises:

[0029] It is judged whether the spectral similarity of the preset wavelength interval belongs to the corresponding target similarity deviation interval;

[0030] If yes, the similarity score of the preset wavelength interval is a preset score, wherein the preset score is a positive number;

[0031] Otherwise, the similarity score of the preset wavelength interval is zero;

[0032] According to the similarity score of each of the preset wavelength intervals, a similarity score of the target LED is obtained.

[0033] In a second aspect, an embodiment of the present application provides a spectrum scoring device based on a lighting scene, the device comprising:

[0034] The spectrum acquisition module is configured to acquire a relative spectrum of the target LED and a relative spectrum of a standard illuminant, and the relative spectrum of the target LED and the relative spectrum of the standard illuminant are respectively denoted as a target spectrum and a standard spectrum;

[0035] The deviation interval acquisition module is configured to acquire a similarity deviation interval corresponding to each preset wavelength interval according to a spectral feature of the standard spectrum in each preset wavelength interval; wherein, the preset wavelength intervals are non-intersected and belong to a visible light wavelength range, and the similarity deviation intervals corresponding to different preset wavelength intervals are different;

[0036] The scene acquisition module is configured to acquire scene information of the target LED lighting scene, and acquire an adjustment factor corresponding to each preset wavelength interval according to the scene information;

[0037] The adjustment module is configured to adjust each similarity deviation interval according to the adjustment factor, to obtain a target similarity deviation interval corresponding to the lighting scene;

[0038] The scoring module is configured to acquire a spectral similarity score of the target spectrum of the target LED according to a spectral similarity of each preset wavelength interval and the target similarity deviation interval corresponding to each preset wavelength interval.

[0039] In a third aspect, an embodiment of the present application provides an electronic device, comprising: at least one processor, at least one memory, and computer program instructions stored in the memory, when the computer program instructions are executed by the processor, the method of the first aspect in the above-mentioned embodiments is implemented.

[0040] In a fourth aspect, an embodiment of the present application provides a storage medium having computer program instructions stored thereon, when the computer program instructions are executed by a processor, the method of the first aspect in the above-mentioned embodiments is implemented.

[0041] In summary, the beneficial effects of the present application are as follows:

[0042] The lighting scene based on the spectrum scoring method, device, equipment and storage medium provided by the embodiment of the application, the relative spectrum of the target LED and the standard illuminator is obtained, and is recorded as the target spectrum and the standard spectrum respectively, so that the spectrum distribution of them is accurately understood, and the basic data is provided for subsequent similarity evaluation; the spectrum characteristics of each preset wavelength interval are determined to determine the similarity deviation interval, which helps to establish a reasonable evaluation system and fully considers the spectrum characteristics of different wavelength intervals. The scene information of the target LED lighting scene is obtained, and the adjustment factor corresponding to each preset wavelength interval is obtained accordingly, so that each similarity deviation interval is adjusted according to the adjustment factor, and the target similarity deviation interval corresponding to the lighting scene is obtained. Therefore, the spectrum evaluation can be more accurately performed by combining different lighting scenes, and the score is more convincing. Finally, the LED spectrum similarity score of the target LED target spectrum can be obtained by combining the spectrum similarity of each preset wavelength interval and the target similarity deviation interval. This score comprehensively considers the spectrum characteristics and similarity deviation of each wavelength interval under different lighting scenes, and specifically evaluates the spectrum performance of the LED lighting product, can be customized according to the requirements of different application scenarios, improves the accuracy and applicability of the spectrum evaluation result, and provides a method for the design and optimization of the LED lighting product. BRIEF DESCRIPTION OF DRAWINGS

[0043] In order to more clearly illustrate the technical solutions of the embodiments of the application, the drawings needed to be used in the embodiments of the application will be briefly introduced below. For those skilled in the art, other drawings can also be obtained on the premise of not creating labor, and these are within the protection scope of the application.

[0044] Figure 1 The flowchart of the evaluation method based on the spectrum similarity of the embodiment of the application.

[0045] Figure 2 The flowchart of the embodiment of the application based on the spectrum feature to obtain the similarity deviation interval.

[0046] Figure 3 The structure diagram of the evaluation device based on the spectrum similarity of the embodiment of the application.

[0047] Figure 4 The structure diagram of the electronic device of the embodiment of the application. DETAILED DESCRIPTION

[0048] The features and exemplary embodiments of the various aspects of the present application will be described in detail below with reference to the drawings. The following detailed description is merely intended to teach a person skilled in the art how to make and use the best mode of the present application and is not intended to limit the scope of the application. The following examples are merely illustrative of the present application and are not intended to limit the scope of the present application.

[0049] It should be noted that the relationship terms such as first and second, and the like, are used herein merely to distinguish one entity or action from another, and are not necessarily required to be taken in a particular order. Also, the terms "include", "comprise" or any other variations thereof are intended to cover a non-exclusive inclusion, so that processes, methods, articles, or apparatuses including a series of elements not only include those elements, but also include other elements not explicitly listed, or further include inherent elements of such processes, methods, articles, or apparatuses. Without more limitations, the elements defined by the statement "comprise" do not exclude the presence of additional identical elements in the processes, methods, articles, or apparatuses that include the elements.

[0050] Embodiment 1

[0051] Please refer to Figure 1 The embodiment of the present application provides an evaluation method based on spectral similarity. The method comprises the following steps:

[0052] S1, obtaining the relative spectrum of a target light-emitting semiconductor and the relative spectrum of a standard illuminant, denoted as a target spectrum and a standard spectrum, respectively;

[0053] Specifically, to evaluate the spectral similarity of the target light-emitting semiconductor and the standard illuminant, the spectra of both are first needed to be obtained, wherein the standard illuminant is a standard spectrum used for comparison, usually specified by the International Organization for Standardization or other industry standards; the target light-emitting semiconductor refers to the light-emitting semiconductor light source to be evaluated or compared, which can be a full-spectrum LED device or other types of LED devices, in the LED lighting industry, different types of LED devices have different spectral characteristics, for example, a full-spectrum LED device can emit light in the entire visible spectrum, while other LED devices can only emit light in a specific wavelength range, and the quality and performance evaluation of LED lighting products needs to consider whether the emitted spectrum is similar to that of the standard light source. The standard illuminant usually represents an ideal spectral distribution, such as the D40 standard light source representing a daylight spectrum of white light. By comparing with the standard illuminant, the spectral characteristics of the target light-emitting semiconductor can be evaluated to determine its quality and performance.

[0054] The data of the target spectrum and the standard spectrum are obtained by a spectrometer or other spectral testing equipment, and the target spectrum and the standard spectrum are usually presented in the form of wavelength and relative light intensity, thereby providing the basic data of the LED device to be evaluated and the standard illuminant, and providing the basis for subsequent spectral similarity evaluation.

[0055] S2, obtaining the deviation value between each preset wavelength interval according to the target spectrum and the standard spectrum, wherein each preset wavelength interval has no intersection and belongs to the visible light wavelength range;

[0056] Specifically, the preset wavelength interval is a wavelength range determined in advance for analyzing spectral characteristics, which is usually divided into different ranges according to color or other characteristics, and each preset wavelength interval has no intersection and belongs to the visible light wavelength range, and according to the spectral deviation calculation formula, the deviation value of the target spectrum and the standard spectrum in each preset wavelength interval can be calculated;

[0057] In a preferred embodiment, the preset wavelength interval includes a red wavelength interval of 622-700 nm, an orange wavelength interval of 597-622 nm, a yellow wavelength interval of 577-597 nm, a green wavelength interval of 492-577 nm, a cyan wavelength interval of 475-492 nm, a blue wavelength interval of 450-475 nm, and a violet wavelength interval of 400-450 nm, wherein the red wavelength interval includes a first red wavelength interval of 680-700 nm, a second red wavelength interval of 650-680 nm, and a third red wavelength interval of 622-640 nm.

[0058] Specifically, the purpose of setting the preset wavelength interval is to consider the main colors of the visible spectrum, and different color wavelength ranges are distinguished respectively. By dividing the visible spectrum into wavelength intervals of different colors such as red, orange, yellow, green, cyan, blue, and purple, the similarity between the target spectrum and the standard spectrum can be more accurately compared.

[0059] Further, different wavelength intervals correspond to different colors of the spectrum, with obvious spectral characteristics. This subdivision can better capture the differences in the spectrum, helping to accurately assess the spectral similarity; dividing the visible spectrum into wavelength intervals of different colors helps to quantitatively compare the similarity between different colors. This quantitative comparison can provide more specific information to guide the design and manufacture of LED devices; and the spectral intervals of red, orange, yellow, green, cyan, blue, and purple cover the main range of the visible spectrum, suitable for most spectral comparison scenarios, with wide applicability.

[0060] In an embodiment, the spectral deviation calculation formula is expressed as follows: wherein, is the wavelength value, M is the deviation value, and are the lower limit value and the upper limit value of the corresponding preset wavelength interval, respectively, is the target spectrum, is the standard spectrum.

[0061] Specifically, the target spectrum and the standard spectrum These two variables represent the target spectrum and the standard spectrum to be evaluated respectively. The preset wavelength interval refers to the spectral wavelength range set in advance according to specific requirements or standards, which is used to divide the spectrum into different intervals. In the spectral deviation calculation, the target spectrum and the standard spectrum are compared within each preset wavelength interval; the deviation is a measure of the difference between the target spectrum and the standard spectrum within each preset wavelength interval. When the deviation value is positive, it means that the light intensity of the target spectrum in that interval is higher than that of the standard spectrum. By checking the positive and negative of the deviation value, we can understand the difference direction between the target spectrum and the standard spectrum in different wavelength intervals, thereby better evaluating their similarity.

[0062] S3, according to the spectral characteristics of the standard spectrum in each preset wavelength interval, obtain the similarity deviation interval corresponding to each preset wavelength interval, wherein the spectral characteristics include: spectral energy distribution, spectral gradient angle, and different preset wavelength intervals corresponding to the similarity deviation interval of the human eye visibility rate are different;

[0063] Specifically, the deviation interval is used to determine the allowable similarity deviation range between the target spectrum and the standard spectrum, and the main purpose of setting different deviation intervals for each preset wavelength interval is to consider the different spectral characteristics of different wavelength intervals;

[0064] Since the setting of the deviation threshold is usually a more general process, it depends more on the spectral characteristics of the standard illuminant, therefore, the similarity deviation interval is set based on the spectral characteristics of the standard illuminant as a reference, including but not limited to spectral peaks and valleys, spectral polarization properties and spectral frequency characteristics, the peaks and valleys in the spectrum reflect the mutation of light intensity at certain specific wavelengths, the position and amplitude of these peaks and valleys can be used to measure the characteristics of the spectrum, thereby affecting the similarity evaluation of the spectrum; the polarization property of the spectrum refers to the orientation of the vibration direction of the light to the direction of the light propagation. In some cases, the polarization property of the spectrum may affect the similarity of the spectrum, and therefore can be considered in the similarity evaluation; the frequency characteristics of the spectrum describe the frequency distribution of the light wave, including the proportion of high frequency and low frequency components. The frequency characteristics of the spectrum can also be used as one of the important indicators for evaluating the similarity of the spectrum;

[0065] Considering the above spectral characteristics and possible other factors, suitable ranges are determined through analysis and experimental verification to ensure that the target spectrum has sufficient similarity with the standard spectrum within this interval, which can more comprehensively evaluate the similarity between the target spectrum and the standard spectrum, and further determine the similarity deviation interval to achieve more accurate spectral similarity evaluation.

[0066] Preferably, referring to Figure 2 , the step of obtaining the similarity deviation interval corresponding to each of the preset wavelength intervals according to the spectral characteristics of the standard spectrum in each of the preset wavelength intervals comprises:

[0067] S31, obtaining the spectral characteristics of the standard spectrum in each of the preset wavelength intervals;

[0068] Specifically, the spectral energy distribution is the energy distribution of light in a specified wavelength range, i.e. the shape and amplitude of the spectral curve, and the spectral energy distribution is one of the key parameters for describing the spectral characteristics, which can reflect the relationship between the intensity and wavelength of light; the spectral gradient angle refers to the slope or rate of change between adjacent wavelength points on the spectral curve. It reflects the change speed of the spectrum at different wavelengths, and is very important for understanding the transition and change trend of the spectrum;

[0069] The spectral energy distribution can be obtained by measuring the light intensity of the standard spectrum at different wavelengths using a spectral radiometer or spectral analysis instrument, processing the measured spectral data, and calculating the light intensity or radiant energy distribution at each wavelength. The spectral gradient angle represents the rate of change or slope of the spectrum at different wavelengths, which can be obtained by calculating the difference in spectral intensity at adjacent wavelengths. The human eye visibility is expressed in the standard CIE1931 colorimetric chart, and the human eye visibility data at each wavelength can be obtained by consulting the CIE1931 colorimetric standard.

[0070] S32, according to the spectral energy distribution, the spectral gradient angle and the human eye visibility, determine the first deviation threshold and the second deviation threshold corresponding to each of the preset wavelength interval, wherein the first deviation threshold is a negative number, used to represent the maximum deviation allowed when the light intensity of the target spectrum in the corresponding preset wavelength interval is lower than the standard spectrum; the second deviation threshold is a positive number, used to represent the maximum deviation allowed when the light intensity of the target spectrum in the corresponding preset wavelength interval is higher than the standard spectrum, the absolute value of the first deviation threshold is greater than or equal to the absolute value of the second deviation threshold;

[0071] Specifically, the first deviation threshold and the second deviation threshold are determined to evaluate the similarity or deviation degree between the target spectrum and the standard spectrum. These thresholds are determined according to the spectral characteristics (spectral energy distribution, spectral gradient angle) of the standard spectrum and the human eye visibility, to ensure that the light intensity of the target spectrum in each preset wavelength interval has sufficient similarity with the standard spectrum;

[0072] The spectral energy distribution reflects the intensity distribution of light at different wavelengths. When determining the first deviation threshold and the second deviation threshold, the spectral energy distribution of the standard spectrum can be used to determine the light intensity level of the target spectrum in each wavelength interval. This has the advantage of setting the threshold according to the overall brightness of the standard spectrum, ensuring that the difference in light intensity between the target spectrum and the standard spectrum does not exceed the acceptable range.

[0073] The spectral gradient angle represents the rate of change of the spectrum with respect to wavelength, i.e. the slope of the spectrum. By analyzing the spectral gradient angle of the standard spectrum, the spectral variation of the target spectrum in each wavelength interval can be determined. This helps to determine the size and direction of the first deviation threshold and the second deviation threshold, ensuring that the similarity evaluation takes into account the trend of spectral change, so as to more accurately judge the similarity between the target spectrum and the standard spectrum.

[0074] The human eye visibility reflects the sensitivity of the human eye to light at different wavelengths. Considering the perception characteristics of the human eye, the threshold in the similarity evaluation can be adjusted according to the human eye visibility of the standard spectrum, so that the evaluation result is more consistent with the actual situation perceived by the human eye. This ensures that the similarity evaluation is more realistic and reliable, and better reflects the sensitivity of the human eye to spectral differences.

[0075] By comprehensively considering the three parameters, the characteristics of the spectrum can be more comprehensively understood, and the first deviation threshold and the second deviation threshold can be determined according to the characteristics of the standard spectrum. In this way, it helps to ensure that the similarity evaluation is more objective and accurate, and more in line with the actual situation of human eye perception, thereby improving the ability to judge the similarity of the target spectrum and the standard spectrum;

[0076] The first deviation threshold is a negative number, which represents the maximum deviation allowed when the light intensity of the target spectrum is lower than that of the standard spectrum in the preset wavelength interval. In other words, when the light intensity of the target spectrum is lower than that of the standard spectrum, the absolute value of the deviation should not exceed the first deviation threshold;

[0077] The second deviation threshold is a positive number, which represents the maximum deviation allowed when the light intensity of the target spectrum is higher than that of the standard spectrum in the preset wavelength interval. In contrast to the first deviation threshold, when the light intensity of the target spectrum is higher than that of the standard spectrum, the absolute value of the deviation should not exceed the second deviation threshold;

[0078] The absolute value of the first deviation threshold is greater than or equal to the absolute value of the second deviation threshold, in order to ensure that the deviations in both directions are properly considered. The larger absolute value of the first deviation threshold means that we are more tolerant of the situation where the light intensity is lower than the standard spectrum, i.e., we allow the light intensity of the target spectrum to be lower than the standard spectrum to a certain extent. The human visual system is highly adaptable to light, and even in relatively dark environments, we can adapt and carry out normal activities. Therefore, a certain degree of light deficiency may not significantly affect our normal activities and experience, while excessive light may cause glare or visual discomfort, and even affect health. In contrast, relatively dark light conditions usually do not cause discomfort or health problems;

[0079] The relatively small absolute value of the second deviation threshold means that we are relatively less tolerant of the situation where the light intensity is higher than the standard spectrum. Excessive light may cause glare, visual discomfort, and even headaches, affecting visual comfort and health. Excessive light may also affect people's overall perception of the environment and the quality of experience, such as overly bright light making the environment appear harsh or unnatural. In addition, excessively high light intensity will result in unnecessary waste of energy, which is not in line with the principles of energy conservation and emission reduction. In the case where the light intensity is already sufficient to meet the demand, continuing to increase the light intensity will only increase unnecessary energy consumption.

[0080] Preferably, the step of determining the first deviation threshold and the second deviation threshold corresponding to each of the preset wavelength intervals according to the spectral energy distribution, the spectral gradient angle, and the human eye visibility comprises:

[0081] S321, according to a preset first deviation threshold calculation formula, the first deviation threshold of each preset wavelength interval is obtained, wherein the expression of the first deviation threshold calculation formula is as follows: In the formula, is a wavelength value, T1 is the first deviation threshold, represents the spectral energy distribution of the wavelength , represents the spectral gradient angle of the wavelength , represents the human eye visibility of the wavelength , a1 is the first coefficient, which is used to represent the influence degree of the spectral energy distribution and the spectral gradient angle on the first deviation threshold, b1 is the second coefficient, which is used to represent the influence degree of the human eye visibility on the first deviation threshold;

[0082] Specifically, the first deviation threshold represents the maximum deviation allowed by the target spectrum when the light intensity in the preset wavelength interval is lower than the standard spectrum. Therefore, in this formula, the increase of the spectral energy distribution will cause the increase of the first deviation threshold, because when the spectral energy distribution increases, it means that the light intensity in a certain wavelength interval increases. In the spectral similarity evaluation, if the light intensity of the target spectrum in a certain preset wavelength interval is lower than the standard spectrum, it means that the target spectrum is insufficient in this interval. In order to ensure the rigor and reliability of the evaluation, it is necessary to set the first deviation threshold to tolerate this deficiency. When the spectral energy distribution increases, it means that the light intensity of the target spectrum in this interval increases, so the tolerance of the spectral deficiency should also increase accordingly to adapt to this change. Therefore, with the increase of the spectral energy distribution, the first deviation threshold also increases to ensure the accuracy and rationality of the evaluation;

[0083] The spectral gradient angle represents the change rate of the spectrum, that is, the degree of change of the light intensity between adjacent wavelengths. When the spectral gradient angle increases, it means that the light intensity of the target spectrum in a certain wavelength interval has changed greatly, that is, the change rate of the spectrum is large. In the spectral similarity evaluation, if the light intensity of the target spectrum in a certain preset wavelength interval changes greatly, a larger deviation threshold needs to be set to accommodate this change to ensure the accuracy and rationality of the evaluation. Therefore, when the gradient spectral angle increases, the first deviation threshold also increases to adapt to the large change rate of the target spectrum, ensuring the rigor of the evaluation.

[0084] The human eye visibility represents the sensitivity of the human eye to light of different wavelengths, i.e. the degree of visual impact of light of different wavelengths on the human eye. When the human eye visibility increases, it means that the human eye is more sensitive to the region of the spectral energy distribution, i.e. it is easier to perceive light of these wavelengths. In the spectral similarity evaluation, if the light intensity of the target spectrum is low in a certain preset wavelength interval, but the human eye has high sensitivity to light of this wavelength interval, a smaller deviation threshold needs to be set to accommodate this sensitivity to ensure the objectivity and accuracy of the evaluation.

[0085] α1 is a first coefficient, which represents the influence of the spectral energy distribution and the gradient spectrum angle on the first deviation threshold. When α1 increases, it means that the degree of attention to the spectral energy distribution and the gradient spectrum angle increases, so that the adjustment of the deviation threshold is more sensitive.

[0086] β1 represents the inverse influence of the human eye visibility on the first deviation threshold. When β1 increases, it means that the influence of the human eye visibility on the first deviation threshold is weakened, i.e. the evaluation of the spectral similarity depends more on the energy distribution and the gradient angle.

[0087] S322, according to the preset second deviation threshold calculation formula, the second deviation threshold of each preset wavelength interval is obtained, wherein the expression of the second deviation threshold calculation formula is as follows: In the formula, α2 is a third coefficient for representing the influence of the spectral gradient angle on the second deviation threshold; β2 is a fourth coefficient for representing the influence of the spectral gradient angle on the second deviation threshold; γ2 is a fifth coefficient for representing the influence of the human eye visibility on the second deviation threshold;

[0088] Specifically, when the spectral energy distribution increases, it means that the light intensity in a certain wavelength interval is relatively high. In the spectral similarity evaluation, if the light intensity of the target spectrum in a certain preset wavelength interval is higher than that of the standard spectrum, but the spectral energy distribution of this wavelength interval is more extensive, i.e. the spectral distribution range is wider, a smaller second deviation threshold needs to be set to keep the light intensity of the target spectrum in this interval still higher than that of the standard spectrum;

[0089] The increase of the spectral gradient angle represents the larger change rate of the spectrum in a certain wavelength range, i.e. the steeper slope of the spectrum. In the spectral similarity evaluation, if the slope of the target spectrum in a certain preset wavelength interval is larger, i.e. the gradient spectrum angle is larger, it means that the change rate of the spectrum in this interval is faster.

[0090] When the gradient spectrum angle increases, a larger deviation is needed to accommodate the spectrum with a faster rate of change. Because a larger gradient spectrum angle means that the spectrum changes more sharply in the wavelength range, a larger deviation is needed to allow the difference between the target spectrum and the standard spectrum. Therefore, as the gradient spectrum angle increases, the second deviation threshold value can increase to adapt to the rate of change of the target spectrum, ensuring more accurate and reliable evaluation results.

[0091] An increase in the human eye visibility indicates an increase in the sensitivity of the human eye to light at a certain wavelength, i.e., the human eye is more sensitive to light at that wavelength. In the spectral similarity evaluation, if the human eye visibility of the target spectrum increases in a certain preset wavelength interval, i.e., the human eye is more sensitive to light in this interval, it means that the change in light intensity in this interval can be more easily perceived by the human eye.

[0092] When the human eye visibility increases, the tolerance of the deviation of the target spectrum decreases to more accurately reflect the sensitivity of the human eye to spectral differences. Because a higher human eye visibility means that the human eye is more sensitive to spectral differences, a smaller deviation is needed to ensure that the difference between the target spectrum and the standard spectrum is not perceived by the human eye. Therefore, when the human eye visibility increases, the second deviation threshold value can be reduced to better reflect the perception ability of the human eye to spectral differences, thereby improving the accuracy and reliability of the spectral similarity evaluation.

[0093] The coefficient α2 represents the degree of influence of the gradient spectrum angle on the second deviation threshold value. When α2 increases, it means that the importance of the gradient spectrum angle increases, making the adjustment of the deviation threshold value more sensitive.

[0094] The two exponents γ2 and β2 represent the inverse influence of the spectral energy distribution and the human eye visibility on the second deviation threshold value, respectively. When γ2 and β2 increase, it means that the influence of the spectral energy distribution and the human eye visibility on the second deviation threshold value decreases, i.e., the evaluation of spectral similarity depends more on the spectral gradient angle.

[0095] The first coefficient, the second coefficient, the third coefficient, the fourth coefficient, and the fifth coefficient are obtained by statistical analysis of historical spectrum test data.

[0096] Specifically, a sufficient amount of historical spectral test data is collected, including comparison data between target spectra and standard spectra. These data should cover a variety of different spectral characteristics and conditions to ensure the comprehensiveness and accuracy of the analysis. The required spectral features are extracted from the historical spectral data, including spectral energy distribution, gradient spectral angle, and human eye visibility, etc. These features can be extracted and calculated by mathematical methods or professional tools. Statistical analysis is performed on the extracted spectral features to explore their relationships and their impact on spectral similarity evaluation. Various statistical methods such as correlation analysis, regression analysis, factor analysis, etc. can be used to determine the correlation and impact of the features on the similarity evaluation results. Based on the results of statistical analysis, mathematical models or fitting methods can be used to fit the values of the first coefficient, the second coefficient, the third coefficient, the fourth coefficient, and the fifth coefficient. These coefficient values can best describe the relationship between spectral features and similarity evaluation.

[0097] S33, according to the first deviation threshold and the second deviation threshold, obtaining the similarity deviation interval corresponding to each preset wavelength interval.

[0098] Specifically, according to the calculated first deviation threshold and the second deviation threshold, the similarity deviation interval of each preset wavelength interval can be obtained. Each preset wavelength interval may have different spectral characteristics, such as spectral energy distribution, wavelength range, etc. By setting different similarity deviation intervals according to these characteristics, the similarity between the target spectrum and the standard spectrum can be evaluated more precisely. This way, instead of simply considering the entire spectrum as a whole, more detailed analysis and evaluation can be performed for different wavelength ranges. Different wavelength ranges may have different types of spectral problems, such as significant spectral shift or intensity abnormalities in certain wavelength ranges. By setting different similarity deviation intervals, these problem areas can be better identified and corrected or adjusted accordingly, improving the spectral quality of LED devices. By setting different similarity deviation intervals according to these spectral characteristics, the similarity between the target spectrum and the standard spectrum can be evaluated more precisely. This way, instead of simply considering the entire spectrum as a whole, more detailed analysis and evaluation can be performed for different wavelength ranges.

[0099] In a specific embodiment, the similarity deviation interval corresponding to the first red light interval is (-0.6, 0.11), the similarity deviation interval corresponding to the second red light interval is (-0.38, 0.10), the similarity deviation interval corresponding to the third red light interval is (-0.2, 0.19), the similarity deviation interval corresponding to the orange light wavelength interval is (-0.16, 0.16), the similarity deviation interval corresponding to the yellow light wavelength interval is (-0.19, 0.19), the similarity deviation interval corresponding to the green light wavelength interval is (-0.26, 0.1), the similarity deviation interval corresponding to the cyan light wavelength interval is (-0.39, 0.1), the similarity deviation interval corresponding to the blue light wavelength interval is (-0.46, 0.18), and the similarity deviation interval corresponding to the purple light wavelength interval is (-1, 1).

[0100] These similarity deviation intervals provide specific indicators for spectral similarity evaluation, which can help analysts understand the similarity between the target spectrum and the standard spectrum, thereby better evaluating the spectral quality. The upper and lower limits of each interval determine the allowed similarity deviation range, making the evaluation result more accurate and reliable.

[0101] In an embodiment, after the step S33, the method further comprises:

[0102] S34, obtaining application scenario information of the target light-emitting semiconductor;

[0103] Specifically, this step obtains the application scenario information of the target light-emitting semiconductor, and the application scenario includes the environment and conditions in which the light source will be applied, such as indoor lighting, outdoor lighting, etc. The indoor lighting includes but is not limited to classroom lighting, office lighting, factory lighting, living room lighting, and bedroom lighting. The application scenario information can be obtained through the product specification or technical document of the target light-emitting semiconductor. The product specification and technical document usually provide detailed information about the light-emitting semiconductor, including its applicable scenarios, performance characteristics, optoelectronic parameters, etc. By reading the product specification and technical document, one can understand which scenarios and application fields the light-emitting semiconductor is suitable for. Different application scenarios have different requirements for the spectral similarity of different wavelength intervals, so understanding the application scenario can better adjust the parameters of the similarity evaluation.

[0104] S35, obtaining first threshold adjustment factors and second threshold adjustment factors corresponding to each of the preset wavelength intervals according to the application scenario;

[0105] According to the acquired application scene information, the first threshold adjustment factor and the second threshold adjustment factor corresponding to each preset wavelength interval can be determined. These adjustment factors are used to adjust the similarity deviation interval appropriately according to the application scene. For example, in an indoor lighting scene, for some wavelength intervals, the environmental feeling of comfort is not particularly critical, and it can be expected to tolerate greater deviation, while for some wavelength intervals, the spectral similarity can be more important, and the similarity deviation interval can be reduced;

[0106] In an embodiment, the step S35 specifically comprises:

[0107] S351, filtering the preset wavelength intervals according to the application scene to obtain a key wavelength interval;

[0108] In this step, the key wavelength interval is selected according to the specific application scene. These wavelength intervals have special importance in this scene and are crucial to achieve a specific lighting effect. For different scenes, different wavelength intervals may be concerned because they have an important influence on people's perception and comfort in the scene, and different application scenes have different requirements for spectral characteristics. Only adjusting the threshold value of the key wavelength interval can better meet the needs of different scenes, thereby improving the adaptability and flexibility of the LED lighting system;

[0109] For example, but not limited to, for a classroom scene, the key wavelength interval includes a green wavelength interval (492-577 nm) and a blue wavelength interval (450-475 nm), the green wavelength interval helps to improve students' attention and concentration, and the blue wavelength interval can enhance clarity and alertness;

[0110] For an office scene, the key wavelength interval includes a green wavelength interval (492-577 nm) and a yellow wavelength interval (577-597 nm), the green wavelength interval helps to improve the attention and work efficiency of employees, and the yellow wavelength interval helps to create a warm and comfortable atmosphere;

[0111] For factory lighting, the key wavelength interval includes a blue wavelength interval (450-475 nm), and the blue wavelength interval is beneficial to improve alertness and work efficiency;

[0112] S352, according to the application scene information, setting the first threshold adjustment factor and the second deviation adjustment factor for each key wavelength interval;

[0113] The first and second threshold adjustment factors are set for each key wavelength interval. These factors are used to adjust the calculation of the spectral similarity score to take into account the importance of the specific wavelength interval to the scene.

[0114] S353. Set the first threshold adjustment factor and the second threshold adjustment factor of the preset wavelength range outside the key wavelength range to 1;

[0115] In this step, first and second threshold adjustment factors are set for each key wavelength range. These factors are used to adjust the calculation of the spectral similarity score to take into account the importance of specific wavelength ranges to the scene;

[0116] For example, rather than limiting it, for the green light wavelength range in office lighting scenarios, a first threshold adjustment factor might be increased to ensure that the light intensity of the target light-emitting semiconductor is below a certain level to provide sufficiently bright lighting, which helps improve employee attention and work efficiency. For the yellow light wavelength range, a second threshold adjustment factor might be adjusted to ensure sufficiently soft and warm lighting.

[0117] In one specific embodiment, when the scene information is classroom lighting, the first threshold adjustment factor for the green light wavelength range is 1.2 and the second threshold adjustment factor is 0.9; the first threshold adjustment factor for the blue light wavelength range is 0.9 and the second threshold adjustment factor is 1.1.

[0118] This setting increases the tolerance of the target light-emitting semiconductor to light intensities exceeding the standard spectrum. In classroom lighting scenarios, this results in slightly higher tolerance for spectral deviations in the green light wavelength range and slightly lower tolerance for blue light wavelengths. This adjustment helps optimize lighting effects, making classroom light more suitable for learning and concentration. Increasing tolerance in the green light wavelength range provides softer lighting, helping to reduce eye strain and improve student focus; while decreasing tolerance in the blue light wavelength range reduces blue light stimulation of the retina, helping to alleviate visual fatigue and improve student comfort and learning efficiency.

[0119] When the scene information is office lighting, the first threshold adjustment factor for the red light wavelength range is 1.1 and the second threshold adjustment factor is 0.95; the first threshold adjustment factor for the blue light wavelength range is 0.95 and the second threshold adjustment factor is 1.05.

[0120] This setting helps improve the comfort and suitability of light in office lighting scenarios. Increasing tolerance for the red light wavelength range makes the light softer, which helps reduce eye fatigue and improve employee productivity. Conversely, reducing tolerance for the blue light wavelength range reduces eye irritation, helping to reduce visual fatigue and improve the comfort of the work environment.

[0121] When the scene information is factory lighting, the first threshold adjustment factor for the yellow light wavelength range is 1.2 and the second threshold adjustment factor is 0.9; the first threshold adjustment factor for the green light wavelength range is 1.1 and the second threshold adjustment factor is 0.95.

[0122] In factory lighting scenarios, increasing the tolerance of the yellow wavelength interval can provide warmer and more comfortable lighting, helping to create a more suitable work environment. Slightly reducing the tolerance of the green wavelength interval can make the lighting brighter, helping to improve worker alertness and productivity.

[0123] When the scene information is living room lighting, the first threshold adjustment factor of the blue wavelength interval is 0.9, and the second threshold adjustment factor is 1.1; the first threshold adjustment factor of the green wavelength interval is 1.1, and the second threshold adjustment factor is 0.95.

[0124] In living room lighting scenarios, increasing the tolerance of the green wavelength interval can provide softer and more comfortable lighting, making the space more suitable for relaxation and entertainment. Reducing the tolerance of the blue wavelength interval can reduce eye irritation, helping to reduce visual fatigue and improve comfort.

[0125] When the scene information is bedroom lighting, the first threshold adjustment factor of the red wavelength interval is 1.2, and the second threshold adjustment factor is 0.9; the first threshold adjustment factor of the yellow wavelength interval is 1.1, and the second threshold adjustment factor is 0.95.

[0126] In bedroom lighting scenarios, increasing the tolerance of the red wavelength interval can create a more warm and comfortable atmosphere, helping to promote sleep. At the same time, increasing the tolerance of the yellow wavelength interval can also provide softer and more comfortable lighting, helping to relax the body and mind and enter a sleep state.

[0127] S36, adjusting each of the similarity deviation intervals according to the first threshold adjustment factor and the second factor adjustment factor;

[0128] Specifically, the first and second threshold adjustment factors of the non-key wavelength intervals are set to 1, which is to maintain the similarity scores of these wavelength intervals unaffected by additional adjustments in the calculation

[0129] According to different application scenarios, the threshold adjustment factors of the key wavelength intervals are adjusted to make the spectral similarity scores more suitable for the needs of specific scenarios. This customized adaptability can improve the accuracy and reliability of the evaluation.

[0130] By adjusting the threshold adjustment factors according to actual needs, the evaluation process is more in line with actual use, thereby improving the accuracy of the evaluation. In particular, the adjustment of the key wavelength intervals can more accurately reflect the similarity of the spectrum in the important wavelength range.

[0131] By adjusting only the threshold adjustment factor of the key wavelength interval and setting the adjustment factors of other wavelength intervals to 1, the calculation resources and time cost can be saved, and the evaluation efficiency can be improved.

[0132] In summary, the overall process of S34 to S36 improves the accuracy and reliability of the evaluation by customizing the threshold adjustment factor, while saving the calculation resources, thereby providing an effective method and tool for the spectral similarity evaluation between the target light-emitting semiconductor and the standard illuminant.

[0133] S4, according to the spectral similarity of each of the preset wavelength intervals and the corresponding similarity deviation interval, obtaining the spectral similarity score between the target light-emitting semiconductor and the standard illuminant.

[0134] Specifically, according to the spectral similarity and the similarity deviation interval of each of the preset wavelength intervals calculated in the foregoing, the spectral similarity score between the target light-emitting semiconductor and the standard illuminant can be calculated. This score reflects the degree of similarity between the target spectrum and the standard spectrum in the entire spectral range, and can quickly and accurately evaluate the spectral quality, providing a basis for quality control and optimization of LED devices.

[0135] Preferably, the standard illuminant is standard illuminant D40, which is a specific spectral power distribution artificial light source whose spectral curve is adjusted to simulate the spectral characteristics of natural daylight. D40 is widely used in colorimetric research and experiments as one of the standard illuminants, and its relative spectral power distribution is relatively close to the spectral characteristics of natural daylight, and is particularly suitable for simulation and experiments in indoor lighting environments.

[0136] The step of obtaining the spectral similarity score between the target light-emitting semiconductor and the standard illuminant according to the spectral similarity of each of the preset wavelength intervals and the corresponding similarity deviation interval comprises:

[0137] S41, judging whether the spectral similarity of the preset wavelength interval belongs to the corresponding similarity deviation interval;

[0138] For each preset wavelength interval, the relationship between the spectral similarity of the target spectrum and the standard spectrum in the interval and the similarity deviation interval is compared. If the similarity of the target spectrum falls within the similarity deviation interval, it means that the target spectrum has sufficient similarity with the standard spectrum in the interval, and they can be considered similar. If the similarity of the target spectrum exceeds the similarity deviation interval, it means that the difference between the target spectrum and the standard spectrum in the interval exceeds the tolerance range and is considered dissimilar.

[0139] S42, if it belongs, the similarity score of the preset wavelength interval is a preset score, wherein the preset score is a positive number.

[0140] If the similarity of the target spectrum falls within the similarity deviation interval, a preset score is assigned to the similarity score of the preset wavelength interval. This preset score is usually a positive number, indicating the similarity of the target spectrum to the standard spectrum in this interval.

[0141] S43, otherwise, the similarity score of the preset wavelength interval is zero;

[0142] If the similarity of the target spectrum exceeds the similarity deviation interval, the similarity score of the preset wavelength interval is set to zero, indicating that the similarity of the target spectrum to the standard spectrum in this interval is not enough to be considered similar.

[0143] S44, according to the similarity score of each preset wavelength interval, the similarity score of the target light-emitting semiconductor is obtained.

[0144] For all preset wavelength intervals, their similarity scores are weighted and summed to obtain the overall similarity score of the target light-emitting semiconductor. This overall score represents the overall similarity of the target spectrum to the standard spectrum.

[0145] Embodiment 2

[0146] Please refer to Figure 3 , the embodiment of the present application provides an evaluation device based on spectral similarity, the device comprises:

[0147] A spectrum acquisition module is used to acquire the relative spectrum of the target light-emitting semiconductor and the standard illuminator, which are denoted as the target spectrum and the standard spectrum, respectively.

[0148] A deviation value calculation module is used to acquire the deviation value between each preset wavelength interval according to the target spectrum and the standard spectrum, wherein each preset wavelength interval has no intersection and belongs to the visible light wavelength range.

[0149] A deviation interval acquisition module is used to acquire the similarity deviation interval corresponding to each preset wavelength interval according to the spectral characteristics of the standard spectrum in each preset wavelength interval, wherein the similarity deviation intervals corresponding to different preset wavelength intervals are different.

[0150] A similarity evaluation module is used to acquire the spectral similarity score between the target light-emitting semiconductor and the standard illuminator according to the spectral similarity of each preset wavelength interval and the corresponding similarity deviation interval.

[0151] It should be noted that the modules and units in the evaluation device based on the spectral similarity in this embodiment one by one correspond to the steps in the evaluation method based on the spectral similarity in the foregoing embodiment, and therefore the specific embodiments of this embodiment can refer to the embodiments of the spectral similarity evaluation based on the spectral characteristics, which will not be described here again.

[0152] Embodiment 3

[0153] In addition, in combination with Figure 1 The evaluation method based on the spectral similarity of the described embodiments of the application can be implemented by an electronic device. Figure 4 A hardware structure schematic diagram of an electronic device provided by an embodiment of the application is shown.

[0154] The electronic device can include a processor and a memory having computer program instructions stored therein.

[0155] Specifically, the processor can include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the application.

[0156] The memory can include a mass storage for data or instructions. By way of example and not limitation, the memory can include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. Where appropriate, the memory can include removable or non-removable (or fixed) media. Where appropriate, the memory can be internal or external to the data processing apparatus. In certain embodiments, the memory is non-volatile solid-state memory. In certain embodiments, the memory includes read-only memory (ROM). Where appropriate, this ROM can be mask-programmed ROM, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), electrically alterable ROM (EAROM), or flash memory, or a combination of two or more of these.

[0157] The processor reads and executes the computer program instructions stored in the memory to implement any one of the evaluation methods based on the spectral similarity in the foregoing embodiments.

[0158] In one example, the electronic device can further include a communication interface and a bus. Wherein, as Figure 4 As shown, the processor 401, the memory 402, and the communication interface 403 are connected through the bus 410 and complete communication with each other.

[0159] The communication interface is mainly used for realizing the communication between the modules, devices, units and / or equipment in the embodiments of the present application.

[0160] The bus includes hardware, software, or both, that couples components of an electronic device to one another in which the bus can include, for example, but not limited to, an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand (IB) interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or another suitable bus or a combination of two or more of these. Where appropriate, the bus can include one or more buses. Although the present embodiments describe and show a particular bus, the present application contemplates any suitable bus or interconnect.

[0161] Embodiment 4

[0162] In addition, in combination with the evaluation method based on the spectral similarity in the above embodiments, the present embodiment can provide a computer readable storage medium to realize. The computer readable storage medium has computer program instructions stored thereon; the computer program instructions are executed by the processor to realize any one of the evaluation methods based on the spectral similarity in the above embodiments.

[0163] In summary, the present embodiment provides an evaluation method, device, equipment and storage medium based on the spectral similarity.

[0164] It needs to be clear that the present application is not limited to the specific configurations and processes described above and shown in the drawings. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present application is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps, after understanding the spirit of the present application.

[0165] The functional blocks shown in the structural block diagrams described above can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application specific integrated circuits (ASICs), appropriate firmware, plug-ins, functional cards, and the like. When implemented in software, the elements of the present application are program or code segments that are used to perform the required tasks. The program or code segments can be stored in a machine-readable medium or transmitted through a data signal carried in a carrier wave over a transmission medium or communication link. A "machine-readable medium" includes any medium that can store or transport information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, and the like. The code segments can be downloaded via computer networks such as the Internet, intranets, and the like.

[0166] It should also be noted that the exemplary embodiments mentioned in the present application describe some methods or systems based on a series of steps or devices. However, the present application is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiments, or in an order different from that in the embodiments, or several steps can be performed simultaneously.

[0167] The above description is merely a specific implementation of the present application. Those skilled in the art can clearly understand the specific working processes of the above-described system, modules and units for the convenience and brevity of description, which can refer to the corresponding processes in the foregoing method embodiments, which will not be described here. It should be understood that the protection scope of the present application is not limited thereto, and any person skilled in the art can easily think of various equivalent modifications or replacements within the technical range disclosed by the present application, and these modifications or replacements should be covered within the protection scope of the present application.

Claims

1. A spectral scoring method based on lighting scenes, characterized in that, The method includes: Obtain the relative spectrum of the target LED and the relative spectrum of the standard illuminator, and denote them as the target spectrum and the standard spectrum, respectively; Based on the target spectrum and the standard spectrum, the deviation values ​​between each preset wavelength interval are obtained, wherein there is no overlap between each preset wavelength interval and they belong to the visible light wavelength range; Based on the spectral characteristics of the standard spectrum in each preset wavelength range, the similarity deviation range corresponding to each preset wavelength range is obtained, including: The spectral characteristics of the standard spectrum in each of the preset wavelength ranges are obtained; wherein, the spectral characteristics include: spectral energy distribution, spectral gradient angle, and human visual visibility. Based on the spectral energy distribution, spectral gradient angle, and human visual visibility, a first deviation threshold and a second deviation threshold are determined for each of the preset wavelength intervals; wherein, the first deviation threshold is a negative number, used to characterize the maximum allowable deviation when the light intensity of the target spectrum in the corresponding preset wavelength interval is lower than that of the standard spectrum; the second deviation threshold is a positive number, used to characterize the maximum allowable deviation when the light intensity of the target spectrum in the corresponding preset wavelength interval is higher than that of the standard spectrum. Based on the first deviation threshold and the second deviation threshold, the similarity deviation interval corresponding to each preset wavelength interval is obtained; wherein, the similarity deviation intervals corresponding to different preset wavelength intervals are different; Obtain scene information of the target LED lighting scene; based on the scene information, obtain a first threshold adjustment factor and a second threshold adjustment factor corresponding to each preset wavelength range; adjust each similarity deviation range based on the first threshold adjustment factor and the second threshold adjustment factor to obtain the target similarity deviation range corresponding to the lighting scene. Based on the spectral similarity of each preset wavelength range and the corresponding target similarity deviation range, a spectral similarity score between the target LED and the standard illuminator is obtained.

2. The spectral scoring method based on lighting scenes according to claim 1, characterized in that, The preset wavelength ranges include the red light wavelength range of 622~700nm, the orange light wavelength range of 597~622nm, the yellow light wavelength range of 577~597nm, the green light wavelength range of 492~577nm, the cyan light wavelength range of 475~492nm, the blue light wavelength range of 450~475nm, and the violet light wavelength range of 400~450nm.

3. The spectral scoring method based on lighting scenes according to claim 1, characterized in that, The step of obtaining the first threshold adjustment factor and the second threshold adjustment factor corresponding to each of the preset wavelength ranges based on the scene information includes: Based on the scene information, the preset wavelength range is filtered to obtain the key wavelength range; Based on the scenario information, set a first threshold adjustment factor and a second threshold adjustment factor for each of the key wavelength ranges; Set both the first threshold adjustment factor and the second threshold adjustment factor of the preset wavelength range outside the key wavelength range to 1.

4. The spectral scoring method based on lighting scenes according to claim 3, characterized in that, The step of filtering the preset wavelength range based on the scene information to obtain the key wavelength range includes: When the scene information indicates that the lighting scene is a classroom scene, the key wavelength range obtained includes the green light wavelength range of 492~577nm and the blue light wavelength range of 450~475nm; When the scene information indicates that the lighting scene is an office scene, the key wavelength range obtained includes the green light wavelength range of 492~577nm and the yellow light wavelength range of 577~597nm; When the scene information indicates that the lighting scene is factory lighting, the key wavelength range obtained includes the blue light wavelength range of 450~475nm.

5. The spectral scoring method based on lighting scenes according to any one of claims 1-4, characterized in that, The step of obtaining a spectral similarity score for the target LED based on the spectral similarity of each preset wavelength range and the corresponding target similarity deviation range includes: Determine whether the spectral similarity of the preset wavelength range belongs to the corresponding target similarity deviation range; If it belongs to the range, the similarity score of the preset wavelength range is the preset score, wherein the preset score is a positive number; Otherwise, the similarity score for the preset wavelength range is zero; The similarity score of the target LED is obtained based on the similarity score of each preset wavelength range.

6. A spectral scoring device based on a lighting scene, characterized in that, The device includes: The spectrum acquisition module is used to acquire the relative spectrum of the target LED and the relative spectrum of the standard illuminator, which are denoted as the target spectrum and the standard spectrum, respectively. The deviation value calculation module is used to obtain the deviation value between each preset wavelength interval based on the target spectrum and the standard spectrum, wherein there is no overlap between each preset wavelength interval and they belong to the visible light wavelength range; The deviation interval acquisition module is used to acquire the similarity deviation interval corresponding to each preset wavelength interval based on the spectral characteristics of the standard spectrum in each preset wavelength interval, including: The spectral characteristics of the standard spectrum in each of the preset wavelength ranges are obtained; wherein, the spectral characteristics include: spectral energy distribution, spectral gradient angle, and human visual visibility. Based on the spectral energy distribution, spectral gradient angle, and human visual visibility, a first deviation threshold and a second deviation threshold are determined for each of the preset wavelength intervals; wherein, the first deviation threshold is a negative number, used to characterize the maximum allowable deviation when the light intensity of the target spectrum in the corresponding preset wavelength interval is lower than that of the standard spectrum; the second deviation threshold is a positive number, used to characterize the maximum allowable deviation when the light intensity of the target spectrum in the corresponding preset wavelength interval is higher than that of the standard spectrum. Based on the first deviation threshold and the second deviation threshold, the similarity deviation interval corresponding to each preset wavelength interval is obtained; wherein, the similarity deviation intervals corresponding to different preset wavelength intervals are different; Obtain scene information of the target LED lighting scene; based on the scene information, obtain a first threshold adjustment factor and a second threshold adjustment factor corresponding to each preset wavelength range; adjust each similarity deviation range based on the first threshold adjustment factor and the second threshold adjustment factor to obtain the target similarity deviation range corresponding to the lighting scene. The similarity evaluation module is used to obtain a spectral similarity score between the target LED and the standard illuminator based on the spectral similarity of each preset wavelength range and the corresponding target similarity deviation range.

7. An electronic device, characterized in that, include: At least one processor, at least one memory, and computer program instructions stored in the memory, which, when executed by the processor, implement the method as described in any one of claims 1-5.

8. A storage medium storing computer program instructions thereon, characterized in that, When the computer program instructions are executed by a processor, the method as described in any one of claims 1-5 is implemented.

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