Illumination perception-based exhibition space light environment parameter optimization regulation and control method and system

Abstract

The invention belongs to the field of exhibition light control, and particularly relates to an exhibition space light environment parameter optimization regulation and control method and system based on illumination perception, and the method comprises the steps: firstly building a three-dimensional model through obtaining exhibition semantic information and spatial constraints, extracting an exhibit light sensitivity level and spatial fluctuation information, and dividing an illumination control region sequence according to the exhibit light sensitivity level and the spatial fluctuation information; fusing the photosensitive damage rate and the importance degree of the exhibit, and determining a dynamic target optical parameter control interval set; the method comprises the following steps: constructing a hierarchical target mapping function of a fusion fit degree, exhibition experience and an energy-saving index, and dynamically setting main and auxiliary control functions in different time periods according to a control index priority factor; and solving the optimal optical parameter set of each time period by adopting an optimization search algorithm, and carrying out inversion to obtain an optical parameter control index. According to the method, self-adaptive balance optimization of the exhibition light environment among multiple targets of cultural relic preventive protection, audience visual experience and system energy-saving efficiency is realized.

Description

Technical Field

[0001] This invention belongs to the field of exhibition lighting control, and particularly relates to a method and system for optimizing and controlling the light environment parameters of exhibition spaces based on illuminance perception. Background Technology

[0002] Currently, exhibition spaces in museums and art galleries generally employ lighting control schemes based on preset scene modes or simple light sensors. This traditional approach suffers from significant drawbacks: inefficient control and a limited range of sensory dimensions. Specifically, existing technologies struggle to adaptively adjust to factors such as the unique light-sensitive characteristics of different types of exhibits, real-time changes in ambient lighting conditions, and dynamically fluctuating visitor density. This leads to a significant conflict between three core dimensions: the safety of cultural relic preservation, visitor comfort, and system energy efficiency. This conflict manifests itself in several ways: the inability to effectively suppress the cumulative photochemical damage caused by the periodic changes in natural light to photosensitive exhibits such as paintings, calligraphy, and textiles; the difficulty in providing sufficient visual clarity for visitors while strictly adhering to the exhibit's illuminance safety thresholds; the lack of a tiered lighting protection strategy based on the exhibit's cultural relic value; and the persistently high energy consumption of the lighting system, requiring substantial manual maintenance. These problems ultimately prevent existing solutions from achieving a dynamic balance between the rigid requirements for exhibit protection and the flexible needs of the visitor experience. They also lack predictive control capabilities based on light damage mechanism models and differentiated buffer management mechanisms for exhibits of different importance, which severely restricts the intelligent development of modern exhibition space lighting environment management. Summary of the Invention

[0003] To address the shortcomings of existing technologies, this invention proposes a method and system for optimizing and controlling the lighting environment parameters of exhibition spaces based on illuminance perception. This method first constructs a three-dimensional model by acquiring semantic information and spatial constraints of the exhibition, and extracts the light sensitivity levels and spatial fluctuation information of exhibits, thereby dividing the illuminance control zone sequence. Then, it integrates the light sensitivity damage rate and the importance of exhibits to determine a dynamic set of target light parameter control intervals. By constructing a hierarchical target mapping function that integrates adaptability, viewing experience, and energy-saving indicators, and dynamically setting primary and secondary control functions for different time periods based on the priority factors of the control indicators, an optimization search algorithm is used to solve for the optimal light parameter set for each time period, and the light parameter control indicators are obtained through inversion. This invention achieves adaptive equilibrium optimization of the exhibition lighting environment among multiple objectives: preventive protection of cultural relics, visitor visual experience, and system energy efficiency.

[0004] To achieve the above objectives, the present invention provides the following technical solution: Methods for optimizing and controlling the lighting environment parameters of exhibition spaces based on illuminance perception include: Obtain exhibition theme information and environmental parameter information of the exhibition space, wherein the exhibition theme information includes at least semantic information of the exhibition theme and the importance of the exhibits; Based on the exhibition theme information, a target light parameter control interval set is determined for each exhibition theme. The target light parameter control interval set includes at least a target illuminance control interval, a target color temperature control interval, and a target color rendering index control interval. Based on the target light parameter control interval set for each exhibition theme, the environmental parameters of each theme area, the importance of exhibits, and the exhibition period, light parameter control indicators for each area are generated; the light parameter control indicators include luminous flux deviation and spectral power distribution deviation; the environmental parameters include at least natural illuminance and spatial pedestrian density. The light parameter control index of the partition is input into a preset adaptive control algorithm to generate optimized control instructions for the lighting equipment in each area of ​​the exhibition space; The optimized control command is executed to drive the lighting equipment so that the light environment parameters of the exhibition space meet the target light parameter control range set.

[0005] Specifically, the process of determining the target light parameter control interval set for each exhibition theme includes: By acquiring information on the exhibition themes within the exhibition space, the boundary constraints corresponding to each exhibition theme, and the location and maximum effective working range of each lighting device, and combining this with modeling algorithms, a three-dimensional model of the exhibition is obtained. Based on the exhibition theme information, extract the light sensitivity level information of the exhibits under the corresponding exhibition theme and the light sensitivity level fluctuation information at different locations; Based on the light sensitivity level fluctuation information, the boundary constraints corresponding to each exhibition theme, the location of each lighting device, and the real-time effective working range, the three-dimensional model of the exhibition is divided into grids using a grid algorithm to obtain the exhibition illuminance control area sequence; wherein the real-time effective working range is the area size of the region where the lighting device meets the target light parameters for the corresponding time period under rated power.

[0006] The process of determining the target light parameter control interval set for each exhibition theme also includes: Based on the semantic information of the exhibition theme of each exhibition illuminance control area, extract the text information of the light sensitivity level and protection requirements of the exhibits corresponding to each exhibition illuminance control area; Based on the light sensitivity level and protection requirements of the current exhibits, combined with a preset light parameter mapping table, a set of basic target light parameter intervals is set for the current exhibition illuminance control area. The set of basic target light parameter intervals includes a basic interval for target illuminance parameters, a basic interval for target color temperature parameters, a basic interval for target color rendering index parameters, and an illuminance-color temperature coupling mapping function established based on the Krutov effect matching principle. Based on the light sensitivity level of each exhibit, the curves of change in light parameters and the degree of damage to the exhibit are obtained by controlling the variable method. These curves include: luminous flux-illuminance-exhibit damage rate change curve, spectral power distribution-color temperature-exhibit damage rate change curve, and spectral power distribution-color rendering index-exhibit damage rate change curve.

[0007] Specifically, the process of determining the target light parameter control interval set for each exhibition theme also includes: Based on the change curve of each light parameter change and the degree of damage to the exhibit, the photosensitive damage rate and the corresponding damage change direction of the exhibit corresponding to each exhibition illuminance control area are obtained. Simultaneously, based on the semantic and value information of the exhibits corresponding to the exhibition illumination control area, combined with the expert evaluation system, the importance of the exhibits in the exhibition illumination control area is obtained; Based on the light-sensitive damage rate and the importance of the exhibits in each exhibition illumination control area, the length of the light parameter buffer zone is determined; at the same time, based on the corresponding damage change direction, the buffer start point corresponding to each basic target light parameter interval is determined. Based on the basic target optical parameter range, buffer length, and buffer start point, the target optical parameter control range set is obtained.

[0008] Specifically, the process of generating the optical parameter control indices for the partition includes: Based on the rate of photosensitive damage and the importance of the exhibits, a priority factor for control indicators is constructed. Collect exhibit suitability indicators, visitor experience indicators, energy saving indicators, illuminance, colorimetry, color rendering index, luminous flux deviation, spectral power distribution deviation, and corresponding exhibition time periods for each exhibition illuminance control area, and construct a hierarchical target mapping function. The hierarchical target mapping function includes a full-time hierarchical suitability mapping function, a time-segmented hierarchical visitor experience mapping function, and a time-segmented hierarchical energy saving mapping function. The exhibition time periods include working hours and rest periods. When the priority factor of the control indicator is greater than the preset threshold of the priority factor of the control indicator and the current exhibition period is a working period, the full-time hierarchical adaptation mapping function is set as the first constraint main control function for the entire exhibition period, and the time-segmented hierarchical viewing experience mapping function is set as the second constraint auxiliary function for the working period. When the current exhibition period is a rest period, the time-segmented hierarchical energy-saving mapping function is set as the second constraint auxiliary function.

[0009] Specifically, the process of generating the optical parameter control indices for the partition also includes: Using the first constraint main control function and the second constraint auxiliary control function of the working period as the objective function, and combining the target light parameter control interval set as the constraint search interval, the search algorithm is optimized to first search the target light parameter control interval set that maximizes the first constraint main control function and minimizes the exhibit damage rate. When the search is completed, the second target light parameter control interval set that maximizes the second constraint auxiliary function during the working period is searched in the first target light parameter control interval set, which is used as the first local target light parameter control interval set of the current exhibition illumination control area during the working period. Using the first constraint main control function and the second constraint auxiliary control function of the rest period as the objective function, and combining the target light parameter control interval set as the constraint search interval, the search algorithm is optimized to first search the first target light parameter control interval set that maximizes the first constraint main control function and minimizes the exhibit damage rate. When the search is completed, the second target light parameter control interval set that minimizes the second constraint auxiliary function during the rest period is searched in the first target light parameter control interval set, which is used as the second local target light parameter control interval set of the current exhibition illumination control area during the rest period. Based on the first or second local target light parameter control interval set of the current exhibition illuminance control area, combined with the all-time hierarchical adaptation degree mapping function, the light parameter control index of the current exhibition illuminance control area during the working period is obtained by inversion.

[0010] Specifically, the hierarchical objective mapping function is constructed by combining a first-level objective variable layer (comprising the total exhibition evaluation score, exhibit suitability index, visitor experience index, and energy-saving index), a second-level objective light parameter variable layer (comprising illuminance, chromaticity, and color rendering index), and a third-level light parameter control index variable layer (comprising luminous flux deviation and spectral power distribution deviation) with a gradient boosting regression tree. The total exhibition evaluation score is obtained by combining exhibit suitability index, visitor experience index, and energy-saving index with a comprehensive fuzzy evaluation algorithm. The construction and training process of the hierarchical objective mapping function includes: Using exhibit suitability index as dependent variable and illuminance, chromaticity, and color rendering index as independent variables, the gradient boosting regression tree algorithm is used to obtain the first factor weights of illuminance, chromaticity, and color rendering index on exhibit suitability index. The first factor weights are then mapped to the target variable layer and the target light parameter variable layer in the all-time hierarchical suitability mapping function as the first inversion mapping weight sequence. The luminous flux deviation and spectral power distribution deviation are respectively obtained as the second factor weights of luminance, chromaticity and color rendering index. The second factor weights are then mapped between the target light parameter variable layer and the light parameter control index variable layer in the full-time hierarchical adaptation mapping function, as the second inversion mapping weight sequence.

[0011] The exhibition space light environment parameter optimization and control system based on illuminance perception includes: a data acquisition module, a target parameter determination module, and a decision module; The data acquisition module is used to acquire exhibition theme information and environmental parameter information of the exhibition space. The exhibition theme information includes at least exhibition theme semantic information and the importance of exhibits. The target parameter determination module determines a set of target light parameter control intervals for each exhibition theme based on the exhibition theme information. The set of target light parameter control intervals includes at least a target illuminance control interval, a target color temperature control interval, and a target color rendering index control interval. The decision module generates light parameter control indicators for each exhibition theme based on the target light parameter control interval set for each exhibition theme and the environmental parameters, exhibit importance, and exhibition time period for each theme area. The light parameter control indicators include luminous flux deviation and spectral power distribution deviation. The environmental parameters include at least natural illuminance and spatial pedestrian density.

[0012] Specifically, the light environment parameter optimization and control system also includes an instruction generation module and an execution module; The instruction generation module is used to input the light parameter control index of the partition into a preset adaptive control algorithm to generate optimized control instructions for the lighting equipment in each area of ​​the exhibition space. The execution module is used to execute the optimization and control instructions to drive the lighting equipment so that the light environment parameters of the exhibition space meet the target light parameter control range set.

[0013] Compared with the prior art, the beneficial effects of the present invention are: This invention addresses the shortcomings of existing technologies by constructing a 3D model of the exhibition and extracting information on light sensitivity level fluctuations. It establishes a sequence of illuminance control zones based on grid division, achieving refined spatial-scale light environment management. By integrating light sensitivity damage rate and exhibit importance, it determines the target light parameter control interval set, forming a differentiated protection strategy. It innovatively constructs a hierarchical target mapping function with a three-layer variable structure, using a gradient boosting regression tree algorithm to obtain the inversion mapping weight sequence between each layer, establishing a quantifiable mapping relationship from control parameters to evaluation indicators. Employing a multi-objective optimization algorithm based on time-period characteristics, it prioritizes ensuring the viewing experience during working hours and optimizing energy-saving indicators during off-peak hours, while consistently ensuring that exhibit suitability indicators meet protection requirements. Through simulation training of the refined hierarchical target mapping function, it achieves multi-dimensional comprehensive evaluation and adaptive control of the exhibition light environment, effectively improving the scientific and systematic nature of light environment parameter optimization and providing an intelligent lighting solution for exhibition spaces that balances artifact protection, viewing experience, and energy consumption control. Attached Figure Description

[0014] Figure 1 This is a flowchart of the method for optimizing and controlling the light environment parameters of an exhibition space based on illuminance perception, as described in Embodiment 1 of the present invention. Figure 2 This is a schematic diagram of the target optical parameter control range in Embodiment 1 of the present invention; Figure 3 This is a block diagram of the exhibition space light environment parameter optimization and control system based on illuminance perception, which is the second embodiment of the present invention. Detailed Implementation

[0015] Example 1 Please see Figure 1 The present invention provides an embodiment of a method for optimizing and controlling the light environment parameters of an exhibition space based on illuminance perception, comprising the following steps: S1. Obtain exhibition theme information and environmental parameter information of the exhibition space, wherein the exhibition theme information includes at least semantic information of the exhibition theme and the importance of the exhibits; S2. Based on the exhibition theme information, determine the target light parameter control interval set for each exhibition theme. The target light parameter control interval set includes at least the target illuminance control interval, the target color temperature control interval, and the target color rendering index control interval. S3. Based on the target light parameter control interval set for each exhibition theme and the environmental parameters, exhibit importance, and exhibition time period of each theme area, generate light parameter control indicators for each area; the light parameter control indicators include luminous flux deviation and spectral power distribution deviation; the environmental parameters include at least natural illuminance and spatial pedestrian density; S4. Input the light parameter control index of the partition into the preset adaptive control algorithm to generate optimized control instructions for the lighting equipment in each area of ​​the exhibition space; the adaptive control algorithm in this embodiment is preferably a fuzzy control algorithm. S5. Execute the optimization control command to drive the lighting equipment so that the light environment parameters of the exhibition space meet the target light parameter control range set.

[0016] It should be further explained that the process of determining the target light parameter control interval set for each exhibition theme in this embodiment includes: S101. Obtain the exhibition theme information, the boundary constraints corresponding to each exhibition theme, and the location and maximum effective working range of each lighting device within the exhibition space, and combine them with the modeling algorithm to obtain the three-dimensional model of the exhibition. It should be further explained that the exhibition theme information in this embodiment includes at least the exhibit type / material, cultural value and cost, exhibit size and form, etc.; among which, the cultural value is judged and marked by the corresponding professionals based on their professional knowledge; the boundary constraints corresponding to an exhibition theme include spatial functional zoning, such as "main exhibition line", "key display cases", "transition corridor", "visitor rest area", "interactive experience area", "entrance hall". Exhibition zoning identification, such as zoning ID and zoning name; spatial physical characteristics, such as wall / ceiling reflectivity, display case glass transmittance and reflectivity, and fixed obstructions within the space; S102. Based on the exhibition theme information, extract the light sensitivity level information of exhibits under the corresponding exhibition theme and the light sensitivity level fluctuation information corresponding to different locations; it should be further explained that, in this embodiment, the process of extracting the light sensitivity level information of exhibits under the corresponding exhibition theme and the light sensitivity level fluctuation information corresponding to different locations includes: S1021. Based on the exhibit types and materials in the exhibition theme information, query the pre-set exhibit type-material-light sensitivity mapping database to obtain the initial light sensitivity level and corresponding reference light parameter safety threshold for each exhibit unit; secondly, based on the exhibit cultural value and preservation status score in the exhibition theme information combined with a correction function constructed by a support vector machine, correct the initial light sensitivity level to obtain the corrected light sensitivity level for each exhibit unit; wherein the exhibit cultural value and preservation status score are evaluated and labeled by professionals in the art according to the exhibits under the corresponding exhibition theme; the exhibit type-material-light sensitivity mapping database is constructed by professionals in the art based on experimental testing and historical data combined with a graph database; S1022. Using the three-dimensional coordinates, optical axis direction vector, and light distribution curve data of each lighting device in the exhibition three-dimensional model as input, the influence weight of the light intensity from all lighting devices on each point in the exhibition three-dimensional space is calculated through a ray tracing simulation algorithm; the influence weights of all lamps are normalized, and a light influence domain model representing the light source of each point in the space is output; it should be further explained that the steps of constructing the light influence domain model in this embodiment include: firstly, establishing a hemispherical ray sampling array starting from the optical center of the lamp, and initializing the luminous flux in each direction according to the angular intensity distribution parameters of the light distribution curve; using an adaptive step ray tracing algorithm to calculate the coordinates of the intersection point between the ray and the scene geometric model, and calculating the illuminance contribution value of the intersection point according to the inverse square law of attenuation; accumulating the illuminance contribution of all effective rays in each voxel unit in the three-dimensional space grid to form an unnormalized initial light intensity field; finally, processing the illuminance data of the entire three-dimensional scene through a maximum-minimum normalization algorithm, mapping the total light influence weight of each spatial point to a continuous interval from zero to one, and obtaining the light influence domain model.

[0017] S1023. Map the corrected photosensitivity level of each exhibit unit to the corresponding exhibit surface spatial position in the three-dimensional exhibition model; for spatial positions outside the exhibit surface, calculate its representative photosensitivity value based on the photosensitivity level of the exhibit surface in the spatial neighborhood using a spatial interpolation algorithm to obtain an initial static photosensitivity distribution matrix covering the entire three-dimensional exhibition space; it should be further noted that the process of generating the initial static photosensitivity distribution matrix in this embodiment includes: First, a regular grid voxel array aligned with the coordinate system of the 3D model is established. The light sensitivity level of each exhibit surface triangular facet is assigned to all voxel units that intersect with it. For blank voxels that do not intersect with any exhibit surface, their geometric center is used as the query point, and neighboring exhibit surface voxels are searched within a preset radius. The inverse distance weighted interpolation algorithm is used to calculate their representative light sensitivity value, where the weight coefficient is inversely proportional to the square of the distance. By traversing and processing all voxel units, a digital light sensitivity distribution matrix covering the entire 3D space of the exhibition is finally constructed.

[0018] S1024. Obtain dynamic spatial pedestrian density data of the exhibition space within a preset time period; superimpose the dynamic spatial pedestrian density data with the illumination influence domain model to simulate the shading effect of pedestrian flow on illumination, generating a dynamic shading model; fuse the dynamic shading model with the initial static light sensitivity distribution matrix to obtain a light sensitivity distribution matrix sequence arranged in chronological order within the preset time period; it should be further explained that the specific steps for simulating the shading effect of pedestrian flow on illumination in this embodiment include: Based on preset human geometric and optical parameters, a mapping function of human flow density and light attenuation is established through Monte Carlo light transmission simulation. Specifically, the human body is simplified into a cylindrical optical model. By calculating the effective projected area ratio under different human flow densities and combining it with the diffuse reflection coefficient of clothing material, a continuous lookup table of light attenuation coefficients is generated. The input of the lookup table is the normalized human flow density value, and the output is the corresponding light attenuation coefficient, with a value range of zero to one.

[0019] The three-dimensional pedestrian density distribution matrix of each time slice is input into the light attenuation coefficient lookup table. The pedestrian density value of each spatial unit is converted into the corresponding light attenuation coefficient in real time through parallel table lookup operation. The converted attenuation coefficient matrix is ​​processed by a three-dimensional morphological dilation algorithm to simulate the soft boundary effect of human shadows. Finally, a dynamic light attenuation field with the same resolution as the original light influence domain model is generated.

[0020] The dynamic light attenuation field and the light influence domain model are subjected to voxel-by-voxel scalar multiplication. The effective light intensity after shading is calculated by the physical optics model. The specific calculation formula is: effective light intensity = original light intensity × (1 - shadow attenuation coefficient) × atmospheric transmittance, where the shadow attenuation coefficient is provided by the dynamic light attenuation field and the atmospheric transmittance is corrected in real time according to the spatial relative humidity parameter.

[0021] The above physical simulation process is repeated for each time slice. The calculated effective light intensity distribution is stored in time sequence as a four-dimensional tensor structure to obtain the dynamic occlusion model. The first three dimensions of the four-dimensional tensor structure correspond to spatial coordinates, and the fourth dimension corresponds to the time series. S1025. Using the time-series data of the light sensitivity distribution matrix as input, the Sobel edge detection operator is used to perform convolution operations on the light sensitivity distribution matrix at each time slice, calculating the partial derivatives of each spatial point in the X, Y, and Z directions to obtain the spatial gradient tensor describing the drastic change in spatial sensitivity; simultaneously, along the time dimension, backward difference calculation is performed on the light sensitivity values ​​of the same spatial coordinate point at different time slices to obtain the rate of change of light sensitivity at that point over time, and a time volatility scalar field is output; the spatial gradient tensor and the time volatility scalar together constitute the digitized light sensitivity level fluctuation information.

[0022] S103. Based on the light sensitivity level fluctuation information, the boundary constraints corresponding to each exhibition theme, the location of each lighting device, and the real-time effective working range, the three-dimensional model of the exhibition is divided into meshes using a mesh algorithm to obtain a sequence of exhibition illuminance control areas. The real-time effective working range is the area where the lighting device meets the target light parameters for the corresponding time period at its rated power. Specifically, based on the rated power and light distribution curve data of the lighting device, and the target light parameter control interval set for the corresponding partition in the current time period, the spatial boundary where the illuminance of the lamp reaches the preset target illuminance threshold is calculated in the three-dimensional scene using ray tracing and illuminance distribution simulation algorithms. The intersection operation of this boundary surface with the surface of the three-dimensional model of the exhibition is performed to calculate the effective illumination area on the illuminated surface, obtaining the real-time effective working range value of the lighting device under the current operating conditions. In this embodiment, the real-time effective working range is inversely proportional to the required target illuminance. It should be further explained that the specific steps for meshing the displayed 3D model using a meshing algorithm in this embodiment include: Using the spatial gradient data and time-varying volatility data from the light sensitivity level fluctuation information as basic inputs, the comprehensive sensitivity weight value of each spatial point is calculated. Specifically, the spatial gradient magnitude is multiplied by a preset spatial sensitivity coefficient, and the time volatility is multiplied by a preset time sensitivity coefficient. The two products are then added together to obtain the final comprehensive sensitivity weight value. The spatial sensitivity coefficient and the time sensitivity coefficient are determined through expert experience and historical data analysis. Simultaneously, by combining the spatial functional zoning information in the boundary constraints, the grid density coefficients corresponding to each functional zone are obtained by querying the preset grid density configuration table; By fusing spatial sensitivity weights with grid density coefficients, a multi-constraint weight field is generated that simultaneously reflects the fluctuation characteristics of light sensitivity levels and the requirements of functional zoning. This embodiment integrates two core dimensions: light-sensitive protection constraints and functional zoning management constraints. Light-sensitive protection constraints, derived from spatial gradient and temporal volatility data, are used to identify and prioritize the protection of areas with high light damage risk. Functional zoning management constraints define differentiated grid division precision based on the display needs and operational standards of each functional area (such as key display cases and transition corridors). By quantifying and fusing these two types of constraints, the generated multi-constraint weight field provides a scientific basis for subsequent adaptive grid subdivision, ensuring that the final illuminance control areas achieve both precise cultural relic protection and meet diverse exhibition functional requirements.

[0023] Using a multi-constraint weight field and a preset subdivision threshold as input parameters, a cube bounding box covering the entire exhibition space is initialized as the starting node. A recursive subdivision algorithm is used to traverse the octree structure. When the difference in weight values ​​within a node exceeds a set threshold, the cube node is uniformly divided into eight child nodes. At the same time, the spatial relationship between the node and the effective working range boundary of the lighting equipment is detected, and local refinement is performed in the illumination boundary area according to the preset minimum grid size requirement.

[0024] For each terminal grid cell obtained after subdividing the octree, its spatial geometric center coordinates are first calculated. Based on these coordinates, all lighting devices that may affect the cell are identified using a spatial proximity search algorithm, and a preliminary device association list is established. Subsequently, the light contribution intensity of each lighting device in the list to the grid cell is accurately calculated based on the optical propagation model, and the maximum light contribution value is identified. Finally, the maximum light contribution value is compared with the minimum illuminance threshold preset by the system. If it is consistently lower than the threshold, the grid cell is officially marked as a non-illuminated area and excluded from subsequent illuminance control optimization calculations. After completing the division and labeling of all terminal grid units, a region growing algorithm is used to intelligently merge the grid units by combining the spatial adjacency relationship of the terminal grid units, the similarity of the light physical characteristics between units, and the consistency of the exhibition functional zones to which they belong. Specifically, the region growing algorithm starts from the seed unit and finds and merges adjacent units in its spatial neighborhood that simultaneously meet the requirements of light characteristic differences within the tolerance range and belong to the same functional zone. For each illuminance control area formed after merging, a complete set of control parameters is generated. This set of parameters precisely defines the spatial geometric boundary of the area, the set of associated lighting equipment, the average light sensitivity level in the area, and the unified basic lighting requirement index. S104. Based on the semantic information of the exhibition theme of each exhibition illuminance control area, extract the light sensitivity level and protection requirement text information of the exhibits corresponding to each exhibition illuminance control area; wherein the protection requirement text information corresponds to the light parameter constraint range of the exhibits, which is set by those skilled in the art based on the current storage status of the exhibits and in combination with professional technology. S105. Based on the light sensitivity level and protection requirement text information of the current exhibit, combined with a preset light parameter mapping table, a set of basic target light parameter intervals corresponding to the current exhibition illuminance control area is set. The set of basic target light parameter intervals includes a basic interval of target illuminance parameters, a basic interval of target color temperature parameters, a basic interval of target color rendering index parameters, and an illuminance-color temperature coupling mapping function established based on the Krutov effect matching principle. It should be further explained that the process of constructing the light parameter mapping table in this embodiment includes: collecting light sensitivity data of exhibit materials from international lighting standards (such as CIE or ICOM), combining it with the light damage threshold measured in the laboratory, using statistical regression analysis or machine learning algorithms to map the light sensitivity level and protection requirement text information to the parameter intervals of target illuminance, color temperature, and color rendering index, and establishing the illuminance-color temperature coupling mapping relationship based on the Krutov effect model through function fitting method, and finally generating a structured light parameter lookup table.

[0025] The construction process of the illuminance-color temperature coupling mapping function in this embodiment includes: First, determining the upper and lower limits of the basic illuminance range and the upper and lower limits of the basic color temperature range of the current control area; Based on the visual perception characteristics of the human eye under the Krutov effect, establishing a coupling mapping function between the illuminance parameter and the color temperature parameter; The input variables of this function include the upper and lower limits of the target illuminance range and the upper and lower limits of the target color temperature range of the current display area; The output variable of the mapping function is the target color temperature value corresponding to the input illuminance value. The process of constructing the mapping function includes: first, determining the minimum and maximum values ​​of the illuminance range, as well as the minimum and maximum values ​​of the color temperature range; when the input illuminance value approaches the minimum value of the illuminance range, the output color temperature value simultaneously approaches the minimum value of the color temperature range; when the input illuminance value approaches the maximum value of the illuminance range, the output color temperature value simultaneously approaches the maximum value of the color temperature range. Between the minimum and maximum values ​​of the illuminance range, a piecewise nonlinear function is used to realize the conversion relationship between illuminance and color temperature; a smaller color temperature change slope is set in the lower range of the illuminance range; and a larger color temperature change slope is set in the upper range of the illuminance range. The transformation slope of the piecewise nonlinear function is controlled by a preset visual atmosphere adjustment factor, which is set according to different exhibition theme types. Finally, the target color temperature value that matches the input illuminance value is output through the mapping function, thus completing the parameter coupling of illuminance and color temperature.

[0026] S106. Based on the light sensitivity level of each exhibit, the change curves of light parameter variations and exhibit damage degree are obtained through the controlled variable method, including: luminous flux-illuminance-exhibit damage degree change curve, spectral power distribution-color temperature-exhibit damage degree change curve, and spectral power distribution-color rendering index-exhibit damage degree change curve; the luminous flux-illuminance-exhibit damage degree change curve is used to quantify the functional relationship between the total light radiation energy per unit time and the photochemical damage rate of the exhibit material; the spectral power distribution-color temperature-exhibit damage degree change curve is used to analyze the differentiated damage caused to specific materials by the differences in blue light band radiation intensity of different color temperature light sources, establishing a constraint at the spectral energy distribution level for setting a protective color temperature upper limit; the spectral power distribution-color rendering index-exhibit damage degree change curve is used to... To assess the high-energy band radiation risks associated with broadening or equalizing the spectrum in pursuit of high color rendering, and to provide an optimization target for determining the lowest damaging spectral composition while meeting color reproduction requirements, the luminous flux-illuminance-exhibit damage variation curves, spectral power distribution-color temperature-exhibit damage variation curves, and spectral power distribution-color rendering index-exhibit damage variation curves in this embodiment were obtained experimentally by those skilled in the art using the controlled variable method. Here, the spectral power distribution-color rendering index-exhibit damage variation curve represents the color rendering index-exhibit damage variation curve; the spectral power distribution represents the variable that directly adjusts the color rendering index, not the variable in the curve. The same applies to the luminous flux-illuminance-exhibit damage variation curves and the spectral power distribution-color temperature-exhibit damage variation curves. The curve construction in this embodiment is based on the following principles, specifically: Luminous flux, as the total light energy radiated by the light source, has a spatial distribution density that determines the illuminance value received per unit area of ​​the illuminated object; the two constitute a physical relationship between total amount and distribution density. Spectral power distribution determines the color characteristics of the light source through the energy ratio of different wavelengths of light. When the proportion of short-wavelength blue-violet light increases, the color temperature value increases, resulting in a cool tone; when the proportion of long-wavelength red light increases, the color temperature value decreases, resulting in a warm tone. Color temperature is essentially a quantitative representation of the color characteristics of spectral power distribution. The color rendering index depends on the continuity and integrity of the spectral power distribution. A continuous spectrum can provide full-band support for the color reflection of objects, thereby achieving high-fidelity color reproduction. Spectral gaps will lead to color distortion. The color rendering index is a quantitative evaluation of the color reproduction capability of the spectral power distribution.

[0027] S107. Based on the evaluation algorithm combining the change curve of light parameter change and the degree of damage to exhibits, the light-sensitive damage rate and the corresponding damage change direction of the exhibits in each exhibition illuminance control area are obtained. S108. Simultaneously, based on the semantic and value information of the exhibits corresponding to the exhibition illuminance control area, combined with the expert evaluation system, the importance of the exhibits in the exhibition illuminance control area is obtained. S109. Based on the light-sensitive damage rate and the importance of the exhibits in each exhibition illuminance control area, determine the length of the light parameter buffer zone; it should be further explained that the process of determining the length of the light parameter buffer zone in this embodiment includes: The photosensitive damage rate is combined with the importance of the exhibit using principal component analysis to calculate the comprehensive buffer coefficient. The comprehensive buffer coefficient is then multiplied by a predefined baseline buffer length, and the product is the final optical parameter buffer length. Simultaneously, based on the corresponding damage change direction, the buffer starting point corresponding to each basic target optical parameter interval is determined. For example, taking the basic interval of target illuminance parameters, when the slope of the luminous flux-illuminance-exhibition damage degree change curve is positive, an increase in illuminance will increase the rate of damage to the exhibit. In this case, taking the upper limit of the basic interval of target illuminance parameters as the starting point and the length of the illuminance parameter buffer interval as the radius, extending negatively towards the midpoint of the basic interval of target illuminance parameters, as shown below, yields the target illuminance parameter interval. Figure 2 As shown in 2a, where a , b These are the lower and upper limits of the interval, respectively. c Let A be the midpoint of the interval, and let A be the length of the light parameter buffer zone corresponding to the basic interval of the target illuminance parameters. When the slope of the curve representing the change in luminous flux, illuminance, and exhibit damage is negative, it indicates that increasing illuminance will reduce the rate of exhibit damage. In this case, starting from the lower limit of the target illuminance parameter baseline interval and using the length of the luminous parameter buffer zone as the radius, extend positively towards the midpoint of the target illuminance parameter baseline interval to obtain the target illuminance parameter interval; for example... Figure 2 As shown in 2b, where a , b These are the lower and upper limits of the interval, respectively. c Let B be the midpoint of the interval, and let B be the length of the light parameter buffer zone corresponding to the basic interval of the target illuminance parameter. S110. Based on the basic target optical parameter range, buffer length, and buffer start point, obtain the target optical parameter control range set.

[0028] This process establishes a quantitative relationship curve between changes in optical parameters and the degree of damage to exhibits, enabling precise calculation of the rate and direction of light-sensitive damage. The method first obtains curves showing changes in luminous flux, illuminance, and exhibit damage degree, as well as curves showing changes in spectral power distribution, color temperature, and exhibit damage degree, using a controlled variable method, thus constructing a complete light damage assessment system. Based on this, and combined with expert evaluation of the exhibits' cultural value and historical significance, a complete evaluation system for exhibit importance is formed. Based on the two key indicators of light-sensitive damage rate and exhibit importance, the system calculates a comprehensive buffer coefficient using a preset weighting function, thereby determining the specific length of the buffer zone for each optical parameter. The innovation of this process lies in intelligently determining the buffer starting point based on the direction of damage change: when increasing parameters would exacerbate damage, a protective buffer zone is established outside the upper limit of the basic interval; when increasing parameters could reduce the risk of damage, a safety guarantee zone is constructed outside the lower limit of the basic interval. This directional buffering mechanism forms a multi-layered protection system. It provides stringent protection for high-value, highly sensitive exhibits by increasing the buffer zone length to achieve stricter tolerance for light parameter control; simultaneously, it maintains flexibility in regulating ordinary exhibits, appropriately relaxing the control range to optimize the viewing experience. Compared to traditional static threshold methods, this technical solution establishes a dynamic correlation between light damage mechanisms and control parameters, achieving a fundamental shift from passive protection to proactive prevention. This method not only ensures that light parameters are always maintained within an absolutely safe range, but more importantly, it enables differentiated protection strategies based on the characteristics of different types of exhibits. Through this refined control approach, it effectively extends the lifespan of exhibits, improves the quality of the viewing experience, and maintains the system's energy efficiency.

[0029] It should be further explained that the process of generating the optical parameter control index of the partition in this embodiment includes: S301. Based on the photosensitive damage rate and the importance of exhibits, a priority factor for control indicators is constructed. In this embodiment, the priority factor is used to dynamically adjust the decision weight allocation of three control objectives: exhibit protection, visitor experience, and energy efficiency. Specifically, it includes: normalizing the photosensitive damage rate and multiplying it by a preset damage weight coefficient; simultaneously, multiplying the exhibit importance level by a preset importance weight coefficient; and adding the two product results to generate the priority factor. The system presets a high-priority threshold and a low-priority threshold to divide the system into three control intervals. When the priority factor is above the high threshold, the decision weight of the exhibit protection indicator is increased; when it is below the low threshold, the decision weight of the visitor experience and energy efficiency indicators is increased. This dynamic weight allocation mechanism achieves a differentiated control strategy. The damage weight coefficient and importance weight coefficient in this embodiment are obtained by analyzing the contribution of the photosensitive damage rate and the exhibit importance level to the corresponding exhibit protection requirements using principal component analysis. S302. Collect exhibit suitability indicators, viewing experience indicators, energy-saving indicators, illuminance, chromaticity, color rendering index, luminous flux deviation, spectral power distribution deviation, and corresponding exhibition time periods for each exhibition illuminance control area, and construct a hierarchical target mapping function. In this embodiment, the exhibit suitability indicator evaluates the cultural relic protection effect by quantifying the degree of conformity between real-time light parameters and exhibit safety thresholds. Its core basis is whether the illuminance is within the safe range, whether the color temperature exceeds the protection upper limit, and whether the color rendering index meets the spectral quality requirements. The viewing experience indicator comprehensively considers factors such as illuminance uniformity, color temperature comfort, and color reproduction to evaluate the degree to which the light environment meets the visual comfort and viewing effect of the audience. The energy-saving efficiency indicator reflects the energy utilization efficiency of the system under the premise of meeting the protection and experience requirements by comparing the ratio of actual energy consumption to theoretical baseline energy consumption.

[0030] In this embodiment, the hierarchical target mapping function includes a full-time hierarchical adaptability mapping function, a time-segmented hierarchical exhibition experience mapping function, and a time-segmented hierarchical energy-saving mapping function; the exhibition time includes working hours and rest periods; it should be further noted that the hierarchical target mapping function in this embodiment is constructed by combining a first-level target variable layer (exhibits' overall evaluation score, exhibit adaptability index, exhibition experience index, and energy-saving index), a second-level target light parameter variable layer (illuminance, chromaticity, and color rendering index), and a third-level light parameter control index variable layer (light flux deviation and spectral power distribution deviation) with a gradient boosting regression tree; it should be further noted that the overall exhibition evaluation score in this embodiment is obtained by combining exhibit adaptability index, exhibition experience index, and energy-saving index with a comprehensive fuzzy evaluation algorithm; It should be further explained that the construction and training process of the hierarchical target mapping function in this embodiment includes: S3021. Using the exhibit suitability index as the dependent variable and illuminance, chromaticity, and color rendering index as independent variables, the gradient boosting regression tree algorithm is used to obtain the first factor weights of illuminance, chromaticity, and color rendering index on the exhibit suitability index. The first factor weights are then mapped to the target variable layer and the target light parameter variable layer in the all-time-time hierarchical suitability mapping function as the first inversion mapping weight sequence. S3022. Obtain the second factor weights of light flux deviation and spectral power distribution deviation for luminance, chrominance and color rendering index, respectively, and map the second factor weights between the target light parameter variable layer and the light parameter control index variable layer in the full-time hierarchical adaptation mapping function as the second inversion mapping weight sequence. S3023. Based on the above process of obtaining the first inversion mapping weight sequence and the second inversion mapping weight sequence corresponding to the all-time-time layered adaptation degree mapping function, obtain the third inversion mapping weight sequence, the fourth inversion mapping weight sequence, the fifth inversion mapping weight sequence, and the sixth inversion mapping weight sequence corresponding to the time-time layered exhibition experience mapping function and the time-time layered energy-saving mapping function, respectively. S3024. Map the first inversion mapping weight sequence with the second inversion mapping weight sequence, the third inversion mapping weight sequence with the fourth inversion mapping weight sequence, and the fifth inversion mapping weight sequence with the sixth inversion mapping weight sequence to the corresponding variables in the hierarchical target mapping function to obtain the constructed hierarchical target mapping function; further, in this embodiment, the total score of the exhibition evaluation is used as the root node of the gradient boosting regression tree, and the first-level leaf nodes are constructed using the exhibit suitability index, the viewing experience index, and the energy-saving index; illuminance, chromaticity, and color rendering index are the second-level leaf nodes; luminous flux and spectral power distribution are the third-level leaf nodes, using the first inversion mapping weight sequence, The second, third, fourth, fifth, and sixth inversion mapping weight sequences are the branch connections between the aforementioned leaf nodes. The membership relationship between the exhibit suitability index, visitor experience index, energy-saving index, and the total exhibition evaluation score calculated by the comprehensive fuzzy evaluation algorithm is used as the branch connection between the first-level leaf nodes and the root node; a hierarchical gradient boosting regression tree is constructed. Furthermore, based on the aforementioned hierarchical gradient boosting regression tree, this training process uses a forward step-by-step algorithm to construct the gradient boosting regression tree, gradually stacking base learners starting from the initial constant root node, and continuously optimizing the model by fitting negative gradients. During training, gradient descent is simultaneously used to iteratively optimize the six inversion mapping weight sequences, calculating gradients based on the loss function and adjusting weight values ​​through backpropagation. Finally, a validation set is used to evaluate model performance, optimizing model performance by adjusting hyperparameters such as tree depth and learning rate, while simultaneously verifying whether the node connection relationships conform to optical physics laws and exhibition protection requirements, ensuring that the model possesses both predictive accuracy and physical rationality. S3025. Based on the environmental parameters collected in real time for each exhibition illuminance control area, combined with the hierarchical target mapping function and the exhibition period, a simulation algorithm is used to conduct simulation training by combining exhibit suitability index, visitor experience index, energy saving index, and the total exhibition evaluation score and corresponding thresholds to obtain the trained hierarchical target mapping function.

[0031] S303. When the priority factor of the control indicator is greater than the preset threshold of the priority factor of the control indicator and the current exhibition period is a working period, the full-time hierarchical adaptation mapping function is set as the first constraint main control function for the entire exhibition period, and the time-segmented hierarchical viewing experience mapping function is set as the second constraint control auxiliary function for the working period. When the current exhibition period is a rest period, the time-segmented hierarchical energy-saving mapping function is set as the second constraint control auxiliary function. In this embodiment, the all-time hierarchical adaptation mapping function serves as the primary constraint control function, ensuring that the core requirement of cultural relic protection is prioritized at all times. During working hours, the exhibition experience mapping function is set as the secondary constraint function, reflecting the synergistic optimization of visitor experience and exhibit protection during public opening hours. During off-peak hours, the energy-saving mapping function is elevated to the secondary constraint function, rationally utilizing non-open time to reduce energy consumption while ensuring exhibit safety. This dynamic priority allocation mechanism achieves an adaptive balance between the three major objectives of cultural relic protection, exhibition experience, and energy management through intelligent matching of time period characteristics and protection needs.

[0032] S304. Using the first constraint main control function and the second constraint auxiliary control function of the working period as the objective function, and combining the target light parameter control interval set as the constraint search interval, the optimization search algorithm first searches for the first target light parameter control interval set that maximizes the first constraint main control function and minimizes the exhibit damage rate. When the search is completed, the second target light parameter control interval set that maximizes the second constraint auxiliary function during the working period is searched within the first target light parameter control interval set. This second target light parameter control interval set is then used as the first local target light parameter control interval set for the working period of the current exhibition illumination control area. In this embodiment, the optimization search algorithm uses a non-dominated sorting genetic algorithm with an elitist strategy to solve multi-objective optimization problems. It should be further explained that the specific implementation process of the non-dominated sorting genetic algorithm with an elitist strategy in this embodiment includes: Using the primary control function of the working period and the exhibit damage rate function as dual optimization objectives, and the target light parameter control interval set as constraints, a non-dominated sorting genetic algorithm with an elitist strategy is employed to solve the problem. Specifically: Within the constraints defined by the target light parameter control interval set, an initial population of a certain number of individuals is randomly initialized, where each individual consists of three decision variables: a specific illuminance value, a specific color temperature value, and a specific color rendering index value. Two objective function values ​​are simultaneously calculated for each individual in the population: the first constraint master control function value and the exhibit damage rate value. Based on the distribution of all individuals' values ​​on the two objective functions, a non-dominated sorting operation is performed to divide them into different levels of non-dominated layers, and the crowding distance index of individuals is calculated within each non-dominated layer. A tournament selection operator based on crowding comparison is used to select a specified number of superior individuals from the current population. The selected superior individuals are subjected to simulated binary crossover and polynomial mutation operations in sequence. The crossover operation controls the generation of offspring individuals through the crossover distribution index, and the mutation operation introduces random perturbation through the mutation distribution index. The original population and the newly generated offspring population are merged to form a temporary population. The non-dominated sorting and crowding calculation are re-executed on the temporary population. According to the elite retention strategy, a specified number of optimal individuals are selected from the temporary population to form a new generation population. The above selection, crossover, mutation and elite retention operations are repeated until the preset maximum number of generations is reached. Finally, the optimal solution set at the Pareto front in all non-dominated layers is output as the first target light parameter control interval set.

[0033] All non-dominated solutions in the first target optical parameter control interval set are used as the initial feasible region for the sequential quadratic programming algorithm. Within this feasible region, a specific solution that maximizes the second constraint control auxiliary function during the working period is selected as the optimization starting point. A quadratic approximation model of the objective function is constructed at the current iteration point. This model contains accurate first-order gradient information and an approximate Hessian matrix. Simultaneously, the constraints are linearized to form a quadratic programming subproblem with equality and inequality constraints. The effective set method is used to solve this quadratic programming subproblem, obtaining the feasible descent direction at the current iteration point. A one-dimensional exact search is performed along the descent direction based on the Armijo line search criterion, and the optimal step size satisfying the sufficient descent condition is determined using a backtracking method. The current iteration point position is updated using this optimal step size, and the objective function value and gradient information at the new position are recalculated. The complete process of constructing the quadratic approximation model, solving for the feasible descent direction, and updating the iteration point is repeated until the Euclidean norm of the objective function gradient vector is less than the preset convergence tolerance. At this point, the final iteration point output is the optimal first local target optical parameter control interval set for the working period. S305. Using the first constraint main control function and the second constraint auxiliary control function of the rest period as the objective function, and combining the target light parameter control interval set as the constraint search interval, by optimizing the search algorithm, first search the first target light parameter control interval set that maximizes the first constraint main control function and minimizes the exhibit damage rate. When the search is completed, search the second target light parameter control interval set that minimizes the second constraint auxiliary function during the rest period, and use it as the second local target light parameter control interval set of the current exhibition illumination control area during the rest period. S306. Based on the first or second local target light parameter control interval set of the current exhibition illuminance control area and the all-time hierarchical adaptation degree mapping function, the light parameter control index of the current exhibition illuminance control area during the working period is obtained by inversion. S3061. Based on the initial light parameter control index and the simulation control algorithm, the illumination parameters of the lighting equipment are adjusted. At the same time, the adjusted exhibit adaptability index, viewing experience index, and energy saving index are collected and combined with the corresponding preset index thresholds to obtain the exhibit adaptability index deviation value, viewing experience index deviation value, and energy saving index deviation value. S3062. Using the exhibit adaptability index deviation value, the exhibition experience index deviation value, and the energy saving index deviation value, perform local target light parameter control interval set optimization search and iterative adjustment of lighting equipment illumination parameters along the all-time-time layered adaptability mapping function until the preset index threshold is met, and obtain the light parameter control index of the generated partition that meets the conditions.

[0034] S307. When the priority factor of the control index is less than or equal to the preset threshold of the priority factor of the control index, the exhibits in the current exhibition illumination control area are determined to be ordinary exhibits, and the corresponding processing logic is used for processing, specifically: S3071. Set the time-segmented and layered exhibition experience mapping function as the first optimization objective function for working hours, and set the time-segmented and layered energy-saving mapping function as the second optimization objective function for working hours. Also, set the all-time layered adaptability mapping function as a basic constraint condition that must be met. S3072. Using the first and second optimization objective functions for the working period, combined with the target optical parameter control interval set as the constraint search space, a multi-objective optimization algorithm is used to solve the problem: First, all optical parameter solutions that maximize the first optimization objective function or reach a preset excellent threshold are searched within the target optical parameter control interval set, forming a first candidate solution set; then, a second candidate solution set that maximizes the second optimization objective function or reaches a preset excellent threshold is searched within the first candidate solution set; finally, the solution with the best comprehensive evaluation value is selected from the second candidate solution set as the local target optical parameter control interval set for the working period. S3073. For the rest period, set the time-segmented layered energy-saving mapping function as the first optimization objective function, and use the full-time layered adaptation mapping function as the basic constraint condition; directly search within the target light parameter control interval set to find the optimal solution that maximizes the first optimization objective function and whose full-time layered adaptation mapping function value is not lower than its preset safety threshold, and use it as the local target light parameter control interval set for the rest period. S3074. Based on the obtained local target light parameter control interval set for each time period, forward calculation is performed through the all-time-period hierarchical adaptation mapping function, the time-period hierarchical viewing experience mapping function, and the time-period hierarchical energy-saving mapping function. The corresponding light parameter control index variables are output by constructing the light flux and spectral power distribution corresponding to the exhibit adaptability index, viewing experience index, and energy-saving efficiency index.

[0035] It should be further explained that the specific steps for obtaining the light parameter control index of the current exhibition illuminance control area in this embodiment include: S3075. Input the illuminance value, color temperature value, and color rendering index value of the local target light parameter control interval of the current exhibition illuminance control area into the all-time layered adaptability mapping function. Calculate the quantitative value of the exhibit adaptability index through the first inversion mapping weight sequence stored in the mapping function. The specific execution process is as follows: multiply each light parameter value by the corresponding first inversion mapping weight, sum all the product results, add a preset bias term, and finally output the normalized exhibit adaptability index value through the S-shaped activation function.

[0036] S3076. Based on the illuminance, color temperature, and color rendering index values ​​concentrated in the local target light parameter control interval, and combined with the second inversion mapping weight sequence stored in the all-time hierarchical adaptation mapping function, the luminous flux deviation and spectral power distribution deviation are calculated by inversion. The specific execution process is as follows: a set of linear inversion equations is established with light parameters as input and control deviation as output, and the optimal luminous flux deviation and spectral power distribution deviation values ​​corresponding to the actual light parameter values ​​are obtained by solving the least squares method.

[0037] S3077. Input the local target light parameter control interval set into the corresponding time-segmented hierarchical exhibition experience mapping function and time-segmented hierarchical energy-saving mapping function. Calculate the exhibition experience index value during working hours and the energy-saving index value during off-hours through the third inversion mapping weight sequence and the fifth inversion mapping weight sequence, respectively. The specific execution process is as follows: automatically select the corresponding mapping function according to the current exhibition period, substitute the light parameter value into the corresponding weight calculation formula, and output the index value after linear combination and activation function processing.

[0038] S3078. The exhibit suitability index, visitor experience index, energy saving index, luminous flux deviation and spectral power distribution deviation obtained by inversion calculation are standardized and combined to form a complete set of optical parameter control indexes. The specific execution process is as follows: the values ​​of each index are normalized so that they fall into the value range of zero to one, and finally the processed index values ​​are encapsulated into a standard data structure for output.

[0039] This embodiment achieves intelligent and precise control of the exhibition lighting environment by establishing a complete light sensitivity level assessment system. First, a light sensitivity level assessment model is constructed based on the exhibit type, material, and cultural value. A light influence domain model is established using 3D spatial modeling and ray tracing technology. Through dynamic crowd density simulation and light sensitivity level fluctuation analysis, multi-dimensional lighting environment assessment data is generated. An innovative hierarchical objective mapping function architecture is adopted. The total exhibition evaluation score, exhibit suitability index, visitor experience index, and energy-saving index constitute the objective variable layer; illuminance, color temperature, and color rendering index constitute the light parameter variable layer; and luminous flux deviation and spectral power distribution deviation constitute the control index variable layer. A gradient boosting regression tree is used to establish a quantitative mapping relationship between each level. The system dynamically adjusts the control strategy according to the priority factors of the control indicators, prioritizing the protection of important exhibits and optimizing the visitor experience and energy efficiency for ordinary exhibits. In terms of optimization algorithms, a non-dominated sorting genetic algorithm with an elitist strategy is used for multi-objective optimization, combined with a sequential quadratic programming algorithm for precise search to ensure the acquisition of a Pareto optimal solution. By establishing an illuminance-color temperature coupling mapping function, visual comfort optimization based on the Krutov effect is achieved. Finally, through inversion calculations, the target light parameter control interval set is transformed into executable light parameter control indices, generating specific illuminance adjustment commands, color temperature adjustment commands, spectral quality control commands, operating mode switching commands, and regional collaborative control commands. This multi-layered and comprehensive technical solution effectively resolves the contradiction between cultural relic protection and viewing experience and energy consumption management in traditional exhibition lighting. It achieves multi-objective optimization by improving the viewing experience and reducing energy consumption while ensuring the safety of exhibits, providing a complete intelligent solution for exhibition lighting environment management.

[0040] Example 2 Please see Figure 3 Another embodiment of the present invention provides: an exhibition space light environment parameter optimization and control system based on illuminance perception, comprising: a data acquisition module, a target parameter determination module, a decision module, an instruction generation module, and an execution module; The data acquisition module is used to acquire exhibition theme information and environmental parameter information of the exhibition space. The exhibition theme information includes at least exhibition theme semantic information and the importance of exhibits. The target parameter determination module determines a set of target light parameter control intervals for each exhibition theme based on the exhibition theme information. The set of target light parameter control intervals includes at least a target illuminance control interval, a target color temperature control interval, and a target color rendering index control interval. The decision-making module generates light parameter control indicators for each exhibition theme based on the target light parameter control interval set for each theme and the environmental parameters, exhibit importance, and exhibition time period for each theme area. The light parameter control indicators include luminous flux deviation and spectral power distribution deviation. The environmental parameters include at least natural illuminance and spatial pedestrian density. The instruction generation module is used to input the light parameter control indicators of the partitions into a preset adaptive control algorithm to generate optimized control instructions for the lighting equipment in each area of ​​the exhibition space. The execution module is used to execute the optimization and control instructions to drive the lighting equipment so that the light environment parameters of the exhibition space meet the target light parameter control range set.

[0041] It should be further explained that the generation of optimized control instructions for the lighting equipment in each area of ​​the exhibition space in this embodiment includes: Generate lighting equipment illuminance control instructions, specifically: Real-time illuminance monitoring values ​​for each zone are collected through a distributed illuminance sensor network, and preset target illuminance parameters and exhibit suitability index data are obtained simultaneously. The validity of the collected illuminance data is verified, including data range checks and outlier filtering, to ensure the accuracy and reliability of the input parameters.

[0042] The decision-making process is based on the exhibition period markers: during working hours, the optimal illuminance range is determined according to the exhibition experience index, and during off-peak hours, the minimum illuminance threshold is calculated according to the exhibit suitability index. The decision-making process takes into account the exhibit protection level and energy consumption control requirements, and uses a weighted algorithm to obtain the final target illuminance value.

[0043] The determined target illuminance value is compiled into control command parameters that the device can recognize, including the luminaire device address code, dimming level value, fading time parameter, and execution priority identifier; the parameter compilation follows the standard lighting control protocol format requirements to ensure the integrity and executability of the command.

[0044] Control signals are transmitted via a digital addressable lighting interface protocol or an analog dimming interface; the digital protocol uses Manchester encoding for data encapsulation and transmission, while the analog signal is output using a voltage linear regulation method; the transmission process includes a data verification mechanism to ensure the accuracy and stability of signal transmission.

[0045] The luminaire driver receives and parses control commands, and precisely controls the luminous intensity of the light source by adjusting the output current value or changing the pulse width modulation duty cycle. The adjustment process adopts a closed-loop control algorithm, which monitors the output parameters in real time and performs dynamic compensation to ensure the accuracy and stability of illuminance control.

[0046] Continuously monitor the actual illuminance value after adjustment and compare it with the target illuminance value in real time; establish a deviation early warning mechanism, automatically initiating the readjustment process when the deviation exceeds the allowable range; simultaneously record the adjustment process data to form a complete closed-loop control and quality traceability system. Generate color temperature adjustment instructions for lighting equipment, specifically: The system continuously collects real-time color temperature monitoring values ​​for each zone using color temperature sensors. It also acquires visual comfort scores and color fidelity index data from the exhibition experience indicators, and reads the theoretically optimal color temperature recommendation value calculated by the illuminance-color temperature coupling mapping function based on the current illuminance.

[0047] During working hours, the target color temperature value is determined based on the Krutov effect calculation model. This calculation process comprehensively considers the reference color temperature, the current illuminance value, and the color temperature adjustment coefficient. During off-peak hours, a fixed energy-saving color temperature setting value is used. Finally, the final target color temperature is determined by combining the calculated value and the viewing experience index through a weighted average method.

[0048] The duty cycle ratio of the cool white channel and the warm white channel is calculated based on the color temperature and PWM conversion model. This model establishes the correspondence between the color temperature value and the duty cycle of the two channels. The specific duty cycle parameters are determined by interpolation calculation to ensure that the output color temperature accurately matches the target value.

[0049] The calculated PWM duty cycle parameters are converted into specific drive current values, and dimming commands containing device address, channel selection, and duty cycle parameters are sent to the luminaires through the standard lighting control protocol to synchronously adjust the drive status of cool white and warm white LED channels.

[0050] Set the allowable range for color temperature fluctuation. When the color temperature fluctuation exceeds the threshold, the proportional-integral-derivative (PID) adjustment algorithm is activated. The duty cycle correction amount is determined by calculating the current error, cumulative error, and error change rate to maintain the stability of the output color temperature.

[0051] Record the deviation data between the actual output color temperature and the target color temperature, store key parameters such as timestamps, target color temperature, actual color temperature, duty cycle parameters and viewing experience indicators during the control process, and generate a performance report that includes color temperature compliance rate, control response time and energy consumption data.

[0052] The specific process for generating spectral control commands for lighting equipment is as follows: The system collects real-time color rendering index (CRI) monitoring values, spectral power distribution curve data, and exhibit suitability index parameters for each zone. The CRI monitoring values ​​include real-time measurement data of the general CRI Ra and the special CRI R9. The spectral power distribution curve includes detailed power distribution in the 380nm-780nm band. The exhibit suitability index includes a score on the degree to which the current light environment meets the protection requirements of the exhibits.

[0053] Based on the collected data, the appropriate spectral mode is determined. When the color rendering index is lower than the preset protection threshold or the spectral power distribution deviation exceeds the allowable range, the full-spectrum mode is activated. When it is detected that a specific exhibit material needs to enhance a certain band of spectrum, the specific band enhancement mode is activated. When the exhibit's compatibility index shows a high protection requirement, the safe spectral mode that filters ultraviolet and short-wave blue light is adopted.

[0054] Calculate the LED driving parameters based on the selected spectral mode. In full-spectrum mode, adjust the driving current ratio of each color LED chip to achieve continuous spectral output. In specific band enhancement mode, increase the driving current of the target band LED and reduce the output of the interference band. In safe spectral mode, limit the ultraviolet LED current and adjust the driving parameters of the blue light chip.

[0055] The spectral calibration procedure is executed, and the output spectrum is monitored in real time by the built-in spectrometer. It is compared with the target spectral curve and the driving current of each LED channel is dynamically fine-tuned to ensure that the deviation between the actual output spectral power distribution and the theoretical calculation value is controlled within ±5%.

[0056] Verify the quality of the output spectrum, confirm that the color rendering index meets the preset threshold requirements, that the spectral power distribution curve meets the exhibit protection specifications, that the exhibit compatibility index is maintained at a qualified level, and feed the verification results back to the control system to form a closed-loop management.

[0057] When the spectral quality fails to meet the standard, the backup plan is automatically activated, abnormal spectral data and handling measures are recorded, and a spectral quality report is generated for subsequent analysis and system optimization.

[0058] The process of generating a lighting equipment operation mode switching command is as follows: The system collects real-time data on exhibition time slots, energy efficiency indicators, lighting equipment operating status parameters, and current energy consumption for each zone. The exhibition time slots include precise time definitions for weekday opening hours, holiday opening hours, and closing hours. The energy efficiency indicators include the ratio of real-time power to baseline power. The equipment operating status includes the operating temperature of the lamps, operating time, and fault code information.

[0059] Based on the collected data, the system determines the current operating mode to be executed. When the system time is during the working period and the energy efficiency index is better than the preset threshold, the full power operation mode is activated. When the system time enters the rest period or the energy efficiency index is lower than the preset threshold, the system automatically switches to the energy-saving operation mode. When the equipment operating status data is abnormal, the safety protection mode is activated.

[0060] Specific parameter configurations are generated for each operating mode. In full-power operating mode, the illuminance value is set to the optimal value for viewing, the color temperature is set to the upper limit of the comfortable range, and the color rendering index is kept at the highest level. In energy-saving operating mode, the illuminance value is set to the safety maintenance value, the color temperature is adjusted to the energy-saving spectral ratio, and the color rendering index is kept at the basic requirements. In safety protection mode, abnormal equipment is shut down and the lighting parameters of adjacent areas are adjusted for compensation.

[0061] In energy-saving operation mode, the standby power of the lamps is dynamically adjusted based on real-time monitored energy consumption data. When the ambient illuminance is sufficient, the artificial lighting power is appropriately reduced, and when the equipment temperature rises, the power output is automatically reduced. Through power feedback closed-loop control, the energy consumption is always maintained in the optimal range.

[0062] When switching operating modes, a gradual adjustment algorithm is used. The illuminance parameter smoothly transitions between target values ​​according to a preset gradual curve, and the color temperature parameter achieves natural switching through step-by-step adjustment, avoiding the impact of sudden changes in illuminance parameters on exhibits and the viewing environment.

[0063] Continuously monitor actual energy consumption data, equipment status parameters, and light environment quality indicators under various operating modes; record the time point and execution effect of mode switching; establish an operating mode performance evaluation database to provide data support for subsequent mode optimization. Generate regional lighting coordinated control instructions; the specific implementation process is as follows: Establish boundary buffer zones by identifying the boundary areas between adjacent exhibition areas. Within the buffer zone, systematically deploy a network of monitoring points to synchronously collect real-time illuminance values, color temperature values, spectral power distribution data, and color coordinate parameters of each monitoring point. At the same time, mark the locations of key visual observation points that allow viewers to simultaneously observe adjacent areas from their field of vision.

[0064] Illuminance gradient values ​​are calculated based on the collected boundary area data, which reflect the degree of illuminance change per unit distance; color temperature difference between adjacent areas is calculated; color coordinate offset is calculated to assess color differences; and spectral continuity index is calculated to analyze the correlation of spectral power distribution.

[0065] The system automatically generates control strategies based on the calculated difference index. When the illuminance gradient exceeds the standard, the illuminance smoothing algorithm is activated to establish a transition zone. When the color temperature difference is too large, the color temperature fusion algorithm is activated. When the color coordinate offset exceeds the standard, the spectral power distribution is adjusted. When the spectral continuity is insufficient, the LED channel ratio is optimized to improve spectral connection.

[0066] The lighting equipment in the boundary area is grouped into a collaborative control group. The illuminance transition curve is uniformly set for the equipment in the group to achieve a smooth transition. The color temperature mixing ratio is dynamically adjusted according to the position weight, and synchronous dimming commands are sent to ensure that all equipment responds in a consistent manner.

[0067] Verification monitoring points are set up in the boundary area to continuously evaluate the control effect. When the monitoring indicators exceed the predetermined threshold, the transition curve parameters are automatically adjusted. At the same time, equipment status and energy consumption data are recorded for continuous optimization of the control strategy.

[0068] Establish a comprehensive anomaly handling process. When equipment failure occurs, compensation is made by adjusting the parameters of adjacent devices. When communication is interrupted, local cache parameters are enabled to maintain operation. When data is abnormal, backup sensors or predictive control modes are activated to ensure system reliability.

[0069] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments under the guidance of the present invention without departing from the spirit and scope of the claims. All of these variations are within the protection scope of the present invention.

Claims

1. A method for optimizing and controlling the light environment parameters of an exhibition space based on illuminance perception, characterized in that, include: Obtain exhibition theme information and environmental parameter information of the exhibition space, wherein the exhibition theme information includes at least semantic information of the exhibition theme and the importance of the exhibits; Based on the exhibition theme information, a target light parameter control interval set is determined for each exhibition theme. The target light parameter control interval set includes at least a target illuminance control interval, a target color temperature control interval, and a target color rendering index control interval. Based on the target light parameter control interval set for each exhibition theme, the environmental parameters of each theme area, the importance of exhibits, and the exhibition period, light parameter control indicators for each area are generated; the light parameter control indicators include luminous flux deviation and spectral power distribution deviation; the environmental parameters include at least natural illuminance and spatial pedestrian density. The light parameter control index of the partition is input into a preset adaptive control algorithm to generate optimized control instructions for the lighting equipment in each area of ​​the exhibition space; The optimized control command is executed to drive the lighting equipment so that the light environment parameters of the exhibition space meet the target light parameter control range set.

2. The method for optimizing and controlling the light environment parameters of an exhibition space based on illuminance perception as described in claim 1, characterized in that, The process of determining the target light parameter control interval set for each exhibition theme includes: By acquiring information on the exhibition themes within the exhibition space, the boundary constraints corresponding to each exhibition theme, and the location and maximum effective working range of each lighting device, and combining this with modeling algorithms, a three-dimensional model of the exhibition is obtained. Based on the exhibition theme information, extract the light sensitivity level information of the exhibits under the corresponding exhibition theme and the light sensitivity level fluctuation information at different locations; Based on the light sensitivity level fluctuation information, the boundary constraints corresponding to each exhibition theme, the location of each lighting device, and the real-time effective working range, the three-dimensional model of the exhibition is divided into grids using a grid algorithm to obtain the exhibition illuminance control area sequence; wherein the real-time effective working range is the area size of the region where the lighting device meets the target light parameters for the corresponding time period under rated power.

3. The method for optimizing and controlling the light environment parameters of an exhibition space based on illuminance perception as described in claim 2, characterized in that, The process of determining the target light parameter control interval set for each exhibition theme also includes: Based on the semantic information of the exhibition theme of each exhibition illuminance control area, extract the text information of the light sensitivity level and protection requirements of the exhibits corresponding to each exhibition illuminance control area; Based on the light sensitivity level and protection requirements of the current exhibits, combined with a preset light parameter mapping table, a set of basic target light parameter intervals is set for the current exhibition illuminance control area. The set of basic target light parameter intervals includes a basic interval for target illuminance parameters, a basic interval for target color temperature parameters, a basic interval for target color rendering index parameters, and an illuminance-color temperature coupling mapping function established based on the Krutov effect matching principle. Based on the light sensitivity level of each exhibit, the curves of change in light parameters and the degree of damage to the exhibit are obtained by controlling the variable method. These curves include: luminous flux-illuminance-exhibit damage rate change curve, spectral power distribution-color temperature-exhibit damage rate change curve, and spectral power distribution-color rendering index-exhibit damage rate change curve.

4. The method for optimizing and controlling the light environment parameters of an exhibition space based on illuminance perception as described in claim 3, characterized in that, The process of obtaining the target light parameter control interval set for each exhibition theme also includes: Based on the change curve of each light parameter change and the degree of damage to the exhibit, the photosensitive damage rate and the corresponding damage change direction of the exhibit corresponding to each exhibition illuminance control area are obtained. Simultaneously, based on the semantic and value information of the exhibits corresponding to the exhibition illumination control area, combined with the expert evaluation system, the importance of the exhibits in the exhibition illumination control area is obtained; Based on the light-sensitive damage rate and the importance of the exhibits in each exhibition illumination control area, the length of the light parameter buffer zone is determined; at the same time, based on the corresponding damage change direction, the buffer start point corresponding to each basic target light parameter interval is determined. Based on the basic target optical parameter range, buffer length, and buffer start point, the target optical parameter control range set is obtained.

5. The method for optimizing and controlling the light environment parameters of an exhibition space based on illuminance perception as described in claim 4, characterized in that, The process of generating the optical parameter control index for the partition includes: Based on the rate of photosensitive damage and the importance of the exhibits, a priority factor for control indicators is constructed. Collect exhibit suitability indicators, visitor experience indicators, energy saving indicators, illuminance, colorimetry, color rendering index, luminous flux deviation, spectral power distribution deviation, and corresponding exhibition time periods for each exhibition illuminance control area, and construct a hierarchical target mapping function. The hierarchical target mapping function includes a full-time hierarchical suitability mapping function, a time-segmented hierarchical visitor experience mapping function, and a time-segmented hierarchical energy saving mapping function. The exhibition time periods include working hours and rest periods. When the priority factor of the control indicator is greater than the preset threshold of the priority factor of the control indicator and the current exhibition period is a working period, the full-time hierarchical adaptation mapping function is set as the first constraint main control function for the entire exhibition period, and the time-segmented hierarchical viewing experience mapping function is set as the second constraint auxiliary function for the working period. When the current exhibition period is a rest period, the time-segmented hierarchical energy-saving mapping function is set as the second constraint auxiliary function.

6. The method for optimizing and controlling the light environment parameters of an exhibition space based on illuminance perception as described in claim 5, characterized in that, The process of generating the optical parameter control index for the partition also includes: Using the first constraint main control function and the second constraint auxiliary control function of the working period as the objective function, and combining the target light parameter control interval set as the constraint search interval, the search algorithm is optimized to first search the target light parameter control interval set that maximizes the first constraint main control function and minimizes the exhibit damage rate. When the search is completed, the second target light parameter control interval set that maximizes the second constraint auxiliary function during the working period is searched in the first target light parameter control interval set, which is used as the first local target light parameter control interval set of the current exhibition illumination control area during the working period. Using the first constraint main control function and the second constraint auxiliary control function of the rest period as the objective function, and combining the target light parameter control interval set as the constraint search interval, the search algorithm is optimized to first search the first target light parameter control interval set that maximizes the first constraint main control function and minimizes the exhibit damage rate. When the search is completed, the second target light parameter control interval set that minimizes the second constraint auxiliary function during the rest period is searched in the first target light parameter control interval set, which is used as the second local target light parameter control interval set of the current exhibition illumination control area during the rest period. Based on the first or second local target light parameter control interval set of the current exhibition illuminance control area, combined with the all-time hierarchical adaptation degree mapping function, the light parameter control index of the current exhibition illuminance control area during the working period is obtained by inversion.

7. The method for optimizing and controlling the light environment parameters of an exhibition space based on illuminance perception as described in claim 6, characterized in that, The hierarchical target mapping function is constructed by combining a gradient boosting regression tree with the following components: the total exhibition evaluation score, exhibit suitability index, visitor experience index, and energy-saving index; a second-level target light parameter variable layer constructed with illuminance, chromaticity, and color rendering index; and a third-level light parameter control index variable layer constructed with luminous flux deviation and spectral power distribution deviation. The total exhibition evaluation score is obtained by combining the exhibit suitability index, visitor experience index, and energy-saving index with a comprehensive fuzzy evaluation algorithm. The construction and training process of the hierarchical target mapping function includes: Using exhibit suitability index as dependent variable and illuminance, chromaticity, and color rendering index as independent variables, the gradient boosting regression tree algorithm is used to obtain the first factor weights of illuminance, chromaticity, and color rendering index on exhibit suitability index. The first factor weights are then mapped to the target variable layer and the target light parameter variable layer in the all-time hierarchical suitability mapping function as the first inversion mapping weight sequence. The luminous flux deviation and spectral power distribution deviation are obtained as second factor weights for luminance, chromaticity, and color rendering index, respectively. These second factor weights are then mapped between the target optical parameter variable layer and the optical parameter control index variable layer in the full-time hierarchical adaptation mapping function, serving as the second inversion mapping weight sequence.

8. The method for optimizing and controlling the light environment parameters of an exhibition space based on illuminance perception as described in claim 7, characterized in that, The construction and training process of the hierarchical target mapping function also includes: Based on the above process of obtaining the first and second inversion mapping weight sequences corresponding to the all-time-time layered adaptation mapping function, the third, fourth, fifth, and sixth inversion mapping weight sequences corresponding to the time-time layered exhibition experience mapping function and the time-time layered energy-saving mapping function are obtained respectively. Map the first inversion mapping weight sequence with the second inversion mapping weight sequence, the third inversion mapping weight sequence with the fourth inversion mapping weight sequence, and the fifth inversion mapping weight sequence with the sixth inversion mapping weight sequence to the corresponding variables in the hierarchical objective mapping function to obtain the constructed hierarchical objective mapping function; Based on the environmental parameters collected in real time for each exhibition illumination control area, combined with the hierarchical target mapping function and the exhibition period, a simulation algorithm is used to conduct simulation training by combining exhibit suitability index, visitor experience index, energy saving index, and the total exhibition evaluation score and corresponding thresholds to obtain the trained hierarchical target mapping function.

9. A system for optimizing and controlling the light environment parameters of an exhibition space based on illuminance perception, which is implemented based on the method for optimizing and controlling the light environment parameters of an exhibition space based on illuminance perception as described in any one of claims 1-8, characterized in that, include: Data acquisition module, target parameter determination module, decision-making module; The data acquisition module is used to acquire exhibition theme information and environmental parameter information of the exhibition space. The exhibition theme information includes at least exhibition theme semantic information and the importance of exhibits. The target parameter determination module determines a set of target light parameter control intervals for each exhibition theme based on the exhibition theme information. The set of target light parameter control intervals includes at least a target illuminance control interval, a target color temperature control interval, and a target color rendering index control interval. The decision module generates light parameter control indicators for each exhibition theme based on the target light parameter control interval set for each exhibition theme and the environmental parameters, exhibit importance, and exhibition time period for each theme area. The light parameter control indicators include luminous flux deviation and spectral power distribution deviation. The environmental parameters include at least natural illuminance and spatial pedestrian density.

10. The exhibition space light environment parameter optimization and control system based on illuminance perception as described in claim 9, characterized in that, It also includes an instruction generation module and an execution module; The instruction generation module is used to input the light parameter control index of the partition into a preset adaptive control algorithm to generate optimized control instructions for the lighting equipment in each area of ​​the exhibition space. The execution module is used to execute the optimization and control instructions to drive the lighting equipment so that the light environment parameters of the exhibition space meet the target light parameter control range set.

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