Exhibition lamp and exhibition method

Abstract

The invention relates to the technical field of exhibition lamps, in particular to an exhibition lamp and an exhibition method, and the method comprises the following steps: inputting preset exhibit database information, extracting exhibit numbers, material types, dominant tone ranges and size information, carrying out point-by-point scanning on exhibit surfaces, collecting reflection spectrum data, converting the reflection spectrum data into CIELAB values, and integrating the extracted information and the collected data. And establishing an exhibit basic information set. The comprehensive exhibit basic information set is established by combining the preset database information and the real-time scanning and acquisition of the surface reflection spectrum or the CIELAB value of the exhibit, so that the subsequent illumination design can be carried out based on the unique optical characteristics of each exhibit, the accuracy and pertinence of personalized illumination are improved, and the material details and color levels can be deeply revealed. Secondly, processing the optical data of the exhibit by using a preset weight set associated with a specific display target, and generating an ideal display illumination parameter including spectral distribution and a brightness value;

Description

Technical Field

[0001] The present invention relates to the technical field of exhibition lamps, and in particular to an exhibition lamp and a display method. Background Art

[0002] The field of exhibition lighting technology involves the use of artificial light sources to illuminate exhibits in museums, art galleries, and commercial display spaces to optimize visual presentation and ensure the protection of the exhibits. Key issues in this field include precisely controlling the light source's spectral power distribution, color temperature, color rendering, light intensity, and beam angle to accurately reproduce the inherent colors and textures of exhibits, or to create a specific artistic atmosphere based on curatorial requirements.

[0003] Existing exhibition lighting display technology has several shortcomings in practical applications. Although current technology focuses on the control of light source parameters, such as spectrum, color temperature, color rendering and light intensity, in actual implementation, it often lacks consideration and utilization of the individual optical characteristics of each exhibit. Lighting design often relies on general standards or designer experience to select and set light sources. It is difficult to provide a truly optimized spectral lighting solution for specific exhibits, such as materials with special fluorescent effects, metals with complex reflective properties, or paintings with subtle color gradients. This results in some key material details or subtle color differences of the exhibits not being fully displayed, affecting the complete communication of the exhibit information. For example, for a bronze artifact, general high-color rendering lighting may be able to roughly restore its color, but may not be able to highlight its unique metallic luster and rust texture layers. Therefore, improvement is needed. Summary of the Invention

[0004] The purpose of the present invention is to solve the shortcomings of the prior art and to propose an exhibition lamp and a display method.

[0005] To achieve the above-mentioned object, the present invention adopts the following technical solution: a display method, comprising the following steps: inputting information from a preset exhibit database, extracting exhibit number, material type, main color range, and size information, scanning the exhibit surface point by point, collecting reflectance spectrum data, converting the data into CIELAB values, integrating the extracted information with the collected data, and establishing a basic exhibit information set; Based on the material type and main color range in the basic information set of the exhibit, a preset weight set is selected. The preset weight set corresponds to the texture detail expression, color perception restoration, or artistic style target. The preset weight set is applied to the exhibit reflectance spectrum data or CIELAB value to determine the target spectral distribution composed of peak wavelength, bandwidth, and relative intensity. The target brightness value is calculated based on the exhibit size to generate ideal display lighting parameters; Activate ambient light sensors at target locations around exhibits to capture incident light, analyze ambient light intensity data, and perform spectrophotometric measurements on the ambient light spectrum, recording the energy values ​​of each band or calculating CIEXYZ tristimulus values ​​to obtain ambient light chromaticity coordinates. Combine intensity with spectrum or chromaticity information to obtain real-time ambient light parameters. The target spectral distribution and target brightness values ​​in the ideal display lighting parameters are called, and the real-time ambient light parameters are introduced to simulate the apparent color and brightness of the exhibits under mixed lighting. The simulation results are compared with the target set by the ideal display lighting parameters, the deviation value is quantified, and the required adjustment of the light source spectral distribution offset and the light source brightness increase or decrease is reversely calculated to generate the lighting compensation amount.

[0006] Preferably, the method further comprises: Integrate the target spectrum of ideal display lighting parameters, target brightness, spectral offset of lighting compensation, and brightness increase or decrease to generate a corrected target spectrum and brightness. Based on the spectral characteristics of each RGB, Amber, Cyan, and WhiteLED channel, decompose the corrected target spectrum into each channel, calculate the required luminous flux ratio of each channel, convert it into the corresponding PWM duty cycle value, and establish the light source drive instruction; The PWM duty cycle value of each channel in the light source driving instruction is sent to the exhibition light control unit through the communication interface, modulating the driving current, controlling the luminous intensity of each channel of RGB, Amber, Cyan and WhiteLED in the multi-channel LED group, and mixing to form the specified spectrum and brightness output light.

[0007] Preferably, the steps for obtaining the basic exhibit information set are: Input the preset exhibit database information, locate the corresponding exhibit entry through the record identifier, sequentially read the exhibit number, material type field, main color range record and dimension value, organize the read information into a structured form, filter out null values ​​or invalid entries, and form a structured exhibit description; Based on the three-dimensional model or position coordinates of the exhibit in the structured exhibit description, a spectral sensor scanning path is planned to cover the visible surface of the exhibit, and the sensor is driven to move along the path and collect the raw data stream of the reflectance spectrum point by point, or the CIELAB three-dimensional coordinate values ​​of the predetermined key color area are calculated to obtain the surface optical measurement value; The structured exhibit description information and the surface optical measurement values ​​are integrated, data association is performed based on the exhibit number, unit unification and coordinate system conversion are performed, abnormal measurement points are filtered out, and the data is stored in a designated data structure to establish a basic exhibit information set.

[0008] Preferably, the steps for obtaining the ideal display lighting parameters are: Based on the material type text and main color range values ​​in the exhibit basic information set, matching the preset rule library, retrieving the texture enhancement, color fidelity or target artistic style parameter set associated with the display target, selecting the corresponding multidimensional weight vector, and obtaining the target effect weight; Applying the target effect weight, performing weighted averaging on the reflectance spectrum data or CIELAB values ​​of each point in the basic information set of the exhibit, searching for spectral morphology parameters that satisfy the maximum value of the weighted objective function through iterative optimization, and determining the target spectral distribution of peak wavelength, full width at half maximum, and energy ratio of each band; Combined with the exhibit surface area or characteristic dimensions recorded in the exhibit basic information set and the target spectral distribution, the average brightness lumen value required for the exhibit surface is calculated according to the preset illumination standard, and the spectral morphological parameters and the average brightness lumen value are combined to generate the ideal display lighting parameters.

[0009] Preferably, the steps of acquiring the real-time ambient light parameters are: Activate the ambient light sensor at one or more preset monitoring points around the exhibit, adjust the sensor's optical axis to a specific direction to capture the main ambient incident light, perform photoelectric conversion and amplify the signal, and read the ambient light intensity lux value corresponding to the calibration curve to obtain the ambient illumination reading; Using a sensor that is synchronized or serial with the ambient illuminance reading, the built-in spectroscopic element, such as a grating or filter wheel, is activated to disperse the incident ambient light by wavelength, measure and record a sequence of energy intensity values ​​within a preset wavelength interval, or integrate and calculate the CIEXYZ tristimulus values ​​and then convert them into chromaticity coordinates to form ambient spectral chromaticity data; Combine the ambient illuminance reading value with the spectral energy sequence or chromaticity coordinates in the ambient spectrum and chromaticity data, add timestamp information, check whether the data is within the valid range, and package it into a data frame containing intensity, spectrum or chromaticity information to obtain real-time ambient light parameters.

[0010] Preferably, the steps for obtaining the illumination compensation amount are: The target spectral energy sequence and target brightness value in the ideal display lighting parameters are called, and the ambient spectral energy sequence and ambient illuminance value in the real-time ambient light parameters are introduced. According to the color mixing model, the corresponding light energy is superimposed wavelength by wavelength, and the spectral energy distribution and integrated brightness of the light reflected from the exhibit surface under the mixed light are calculated to obtain the mixed light simulation value. Comparing the spectral energy distribution, integrated brightness, and calculated chromaticity coordinates of the mixed illumination simulation value with the corresponding target values ​​in the ideal display illumination parameters, calculating the color coordinate difference value, and calculating the brightness percentage difference, quantifying the degree of visual perception deviation between the two, and obtaining a perception effect deviation amount; Based on the value in the perceived effect deviation and the percentage of brightness difference, the compensatory adjustment required for the light source to offset the deviation is reversely calculated, the numerical sequence of the energy of each spectral band that needs to be increased or decreased and the lumen difference that needs to be adjusted for the overall brightness are determined, and the lighting compensation amount is established.

[0011] Preferably, the steps of obtaining the light source driving instruction are: Integrating the target spectral energy sequence and target brightness value of the ideal display lighting parameters with the spectral energy increase and decrease sequence and the brightness adjustment lumen difference in the lighting compensation amount to obtain a new target spectral energy sequence and new target brightness value after compensation adjustment, and generating a corrected lighting target set; Based on the standard spectral energy distribution curves of RGB, Amber, Cyan, and White LED channels stored in the database, a constrained least squares method is performed on the new target spectral energy sequence in the modified illumination target set to obtain the luminous flux numerical ratio required to drive each LED channel to emit light to synthesize the target spectrum, thereby generating a channel luminous flux ratio; According to the ratio of the luminous flux of each channel in the channel luminous flux ratio, combined with the new target brightness value in the corrected illumination target set and the light efficiency parameters of each LED, the required input power of each channel is calculated, and then converted into the corresponding PWM pulse width modulation duty cycle percentage value according to the LED driver characteristic curve to establish the light source driving instruction.

[0012] Preferably, the steps of obtaining the output light with the specified spectrum and brightness are: The PWM duty cycle percentage values ​​of each channel in the light source driving instruction are encoded into a data frame sequence including a target address, instruction code, data payload, and checksum according to a preset communication protocol of the exhibition light control unit, thereby obtaining a control instruction packet to be sent; the control instruction packet to be sent is sent to the exhibition light control unit with the target ID via a wired DMX512 and DALI or wireless Zigbee and Bluetooth communication interface, and the control unit is waited for to return a response signal confirming receipt or execution status, and the validity of the response signal is verified to obtain a driving current modulation basis; Based on the driving current modulation basis successfully received and analyzed, the exhibition light control unit generates a pulse signal with a corresponding duty cycle through an internal PWM generator, drives the constant current source to adjust the current flowing to the RGB, Amber, Cyan and White LEDs, controls the light output intensity of each channel, and mixes to form output light with a specified spectral form and brightness level.

[0013] The present invention provides an exhibition lamp, comprising a mounting base, a bracket fixedly mounted on the surface of the mounting base, a lamp cup fixedly mounted on the top of the bracket, a lens fixedly mounted on the top of the lamp cup, and a light bar and a pattern fixedly mounted on the bottom surface of the mounting base.

[0014] Compared with the prior art, the advantages and positive effects of the present invention are: The present invention combines preset database information with real-time scanning and collection of the reflectance spectrum or CIELAB value of the exhibit surface to establish a comprehensive basic information set for the exhibits, so that subsequent lighting design can be based on the unique optical characteristics of each exhibit, improving the accuracy and pertinence of personalized lighting, and helping to deeply reveal material details and color levels. Secondly, the optical data of the exhibits is processed using a preset weight set associated with a specific display target to generate ideal display lighting parameters containing spectral distribution and brightness values. This method goes beyond traditional color temperature and color rendering index adjustments, and can actively shape the light environment according to curatorial intentions, achieving specific visual effects on exhibits, such as texture enhancement or optimized expression of a specific artistic style. Furthermore, by real-time monitoring of the intensity and spectral or chromatic characteristics of the ambient light in the exhibition area, dynamic ambient light parameters are obtained, providing a quantitative basis for dealing with ambient light interference. By introducing mixed lighting simulation and deviation quantification steps, the system calculates the appearance of exhibits under the combined effects of ideal lighting and real-time ambient light, and compares it with the desired target. This allows for reverse engineering to accurately calculate the spectrum and brightness compensation, thereby proactively offsetting the interference caused by ambient light variations on the audience's visual perception and ensuring the stability and consistency of the exhibits' visual presentation under varying ambient lighting conditions. Finally, the ideal lighting parameters are combined with the calculated compensation to generate a corrected lighting target. This is then decomposed based on the spectral characteristics of each multi-channel LED channel, and PWM drive instructions are calculated to directly control the desired spectrum and brightness of the lamp's mixed output, ensuring that the optimization and compensation calculation results can be physically implemented with high precision. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a schematic diagram of the steps of the present invention; Figure 2 Schematic diagram of the exhibition light in the present invention.

[0016] Reference numerals: 1. Mounting base; 2. Bracket; 3. Lamp cup; 4. Lens; 5. Light strip; 6. Pattern. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0018] See also Figure 1 The present invention provides a technical solution, a display method, comprising the following steps: Input the preset exhibit database information, extract the exhibit number, material type, main color range and size information, scan the exhibit surface point by point, collect reflectance spectrum data, convert it into CIELAB values, integrate the extracted information with the collected data, and establish the basic exhibit information set; Based on the material type and main color range in the exhibit basic information set, a preset weight set is selected. The preset weight set corresponds to the texture detail expression, color perception restoration, or artistic style target. The preset weight set is applied to the exhibit reflectance spectrum data or CIELAB values ​​to determine the target spectral distribution composed of peak wavelength, bandwidth, and relative intensity. The target brightness value is calculated based on the exhibit size to generate the ideal display lighting parameters; Activate ambient light sensors at target locations around exhibits to capture incident light, analyze ambient light intensity data, and perform spectrophotometric measurements on the ambient light spectrum, recording the energy values ​​of each band or calculating CIEXYZ tristimulus values ​​to obtain ambient light chromaticity coordinates. Combine intensity with spectrum or chromaticity information to obtain real-time ambient light parameters. Call the target spectral distribution and target brightness values ​​in the ideal display lighting parameters, and introduce real-time ambient light parameters to simulate the apparent color and brightness of the exhibits under mixed lighting. Compare the simulation results with the target set by the ideal display lighting parameters, quantify the deviation value, reversely calculate the required adjustment of the light source spectral distribution offset and the light source brightness increase or decrease, and generate the lighting compensation amount; The target spectrum of the ideal display lighting parameters, the target brightness, the spectral offset of the lighting compensation amount, and the brightness increase or decrease are integrated to generate the corrected target spectrum and brightness. Based on the spectral characteristics of each RGB, Amber, Cyan and WhiteLED channel, the corrected target spectrum is decomposed into each channel, and the required luminous flux ratio of each channel is calculated and converted into the corresponding PWM duty cycle value to establish the light source driving instruction; The PWM duty cycle value of each channel in the light source driving instruction is sent to the exhibition light control unit through the communication interface, modulating the driving current, controlling the luminous intensity of each channel of RGB, Amber, Cyan and WhiteLED in the multi-channel LED group, and mixing to form the specified spectrum and brightness output light.

[0019] The steps to obtain the basic information set of exhibits are as follows: Input the preset exhibit database information, locate the corresponding exhibit entry through the record identifier, sequentially read the exhibit number, material type field, main color range record and dimension value, organize the read information into a structured form, filter out null values ​​or invalid entries, and form a structured exhibit description; Based on the 3D model or location coordinates of the exhibit in the structured exhibit description, the spectral sensor scanning path is planned to cover the visible surface of the exhibit. The sensor is driven along the path and collects the raw data stream of the reflectance spectrum point by point, or the CIELAB 3D coordinate values ​​of the predetermined key color area are calculated to obtain the surface optical measurement value. Integrate structured exhibit description information and surface optical measurement values, associate data based on exhibit number, perform unit unification and coordinate system conversion, filter out abnormal measurement points and store them in the specified data structure to establish the basic information set of the exhibits.

[0020] Specifically, input the preset exhibit database information, perform a search operation in the database (such as the Exhibits table in the SQL database) through the provided record identifier (for example, a unique string such as "Artifact_Bronze_Statue_003"), accurately locate the entry or record row representing a specific exhibit, and read the data fields from the row in a predetermined order, including the exhibit number (such as "BZ003"), the material type field (read the text value, such as "Bronze"), the main color range record (read the value or range, such as CIELAB The format of L value is between 30 and 50, a value is between 5 and 15, and b value is between 15 and 25) and size values ​​(read length, width, and height values, such as "0.5, 0.3, 1.2", in meters). The original information read from the database is mapped according to the predefined key-value pair format and converted into a standardized data structure, such as a JSON object {"id":"BZ003","material":"bronze","color_range":{"L_min":30,"L_max":50,"a_min": ":5, "a_max":15, "b_min":15, "b_max":25}, "dimensions":{"length":0.5, "width":0.3, "height":1.2}}, then perform validity check and filtering on the structured data to check whether there are empty values, for example, the material type field cannot be empty, check whether the dimension values ​​are all positive numbers, if the length, width or height is less than or equal to zero, then the entry is considered invalid, at the same time, according to the preset material type list (the list is pre-set based on the materials supported by the system), First define, for example, including "oil painting", "watercolor", "bronze", "ceramics", "textiles", etc.) Check whether the read material type field value is in the list. If the material type is "unknown" or not in the list, the entry is judged to be invalid. For the main color range record, check whether its value is within the reasonable range of the corresponding color space (such as CIELAB's L is 0-100, a and b are between -128 and 127). If it exceeds, it is judged to be invalid. All entries judged to be invalid will be discarded and will not be included in subsequent processing. All valid entries that have passed the verification are collected to form a structured exhibit description.

[0021] Based on the exhibit 3D model file (e.g., a reference to the "BZ003_model.stl" file) contained in the structured exhibit description obtained in the previous step or the precise position coordinates of the exhibit in the exhibition hall (e.g., X=10.5m, Y=5.2m, Z=1.5m, and the corresponding rotation angle), the scanning path planning is started. If a 3D model is provided, a coverage algorithm based on the model surface is used. For example, a uniform grid is virtually generated on the model surface. The grid density is set according to the material type and size. For example, for a bronze material with rich details, the target sampling density is set to 100 square meters. 20 points per square centimeter, while for exhibits with smooth surfaces, 5 points per square centimeter are set. A sensor movement trajectory sequence (a series of spatial coordinate points) that can traverse these grid points and avoid the model's own occlusion area is calculated. If the position coordinates and size are provided, a bounding box is estimated based on the size information, and a raster scanning path covering the main visible surface of the bounding box facing the audience is planned (for example, starting from the upper left corner, moving horizontally, then moving down one step, and moving horizontally in the opposite direction until the entire estimated surface is covered). The working distance and field of view of the sensor must be considered when planning the path to ensure that the sensor is accurate. To ensure the integrity of the scan, the planned path coordinate sequence is then converted into a specific motion control instruction (e.g., an instruction code that complies with a specific robot or motion platform protocol) and sent to the drive mechanism of the spectral sensor (e.g., a six-axis robotic arm or an XYZ three-axis platform) through a control interface, so that it moves according to the planned path. At each sampling point specified in the path planning, the spectral sensor is triggered to perform a measurement and collect the original spectral data stream of the reflected light at that point. The data stream contains a series of wavelengths and their corresponding light intensity values ​​(e.g., from 380nm to 780nm, an intensity value is recorded every 5nm), or As an alternative, if the structured exhibit description specifies specific predetermined key color areas (for example, the description clearly states "Buddha statue face" or "inscription area", which are pre-marked in the model or coordinates by cultural relics experts according to their importance), the sensor only moves to representative points within these specified areas (such as the center of the area or the point with the most prominent color), and calculates the CIELAB three-dimensional coordinate values ​​at these points, that is, by collecting spectral data, and then using the standard observer function and the spectral power distribution data of the preset light source (such as CIE standard light source D65), according to CIE1976L * a * b * The color space definition formula is used to calculate the L of the point * 、a * and b * Values ​​are stored together with the corresponding spatial coordinates of all collected spectral data streams or calculated CIELAB coordinate values ​​to obtain surface optical measurement values.

[0022] The structured exhibit description information obtained in the previous step (including exhibit number, material, color tone, size, etc.) is integrated with the surface optical measurement values ​​obtained in the same step (including the spatial coordinates of each sampling point and the corresponding spectral data or CIELAB values). Based on the exhibit number associated with each surface optical measurement value when it is recorded, the measurement data is accurately attributed to the corresponding structured exhibit description information, realizing a one-to-many association between the description information and the optical measurement values ​​based on the exhibit number. Then, unit unification and coordinate system conversion processing are performed to check and ensure that all spatial coordinates (from path planning and sensor positioning) use a unified unit, for example, converting all millimeters or centimeters to meters. At the same time, the pre-calibrated coordinate system conversion parameters (usually a 4x4 homogeneous transformation matrix, which is obtained by placing a calibration plate at a known position on the exhibit and scanning it with the sensor to describe the rotation and translation relationship between the sensor coordinate system and the global coordinate system of the exhibit or exhibition hall) are applied to convert the spatial coordinates associated with all surface optical measurements from the sensor's own coordinate system to a unified coordinate system centered on the exhibit or the global exhibition hall coordinate system. The conversion formula is P global =M transform ×P sensor , where P global is the transformed coordinate, P sensor is the original sensor coordinate, M transform is the transformation matrix obtained by calibration. Subsequently, the transformed optical measurement data is screened for abnormal points, and statistical methods are used to identify and eliminate unreliable data points that may be caused by measurement noise, surface defects or ambient light interference. For example, all L * The value (or the light intensity value of a specific wavelength) is calculated, and its quartiles Q1 (25th percentile) and Q3 (75th percentile) are calculated. The interquartile range IQR = Q3-Q1 is calculated, and a judgment threshold coefficient k is set. The setting of the coefficient k refers to the empirical value. For most application scenarios, k = 1.5 is usually selected to balance the detection sensitivity and the false positive rate. According to this setting, L * The measurement points with values ​​less than Q1-1.5×IQR or greater than Q3+1.5×IQR are marked as abnormal points. * Value and b * The same operation is performed for the values ​​(or other key parameters in the spectral data). For example, if an exhibit L *For example, if Q1 = 35 and Q3 = 45, then IQR = 10. The outlier threshold is less than 35 - 1.5 × 10 = 20 or greater than 45 + 1.5 × 10 = 60. All measurement point data marked as outliers will be removed from the dataset. Finally, the valid data after integration, association, unit unification, coordinate conversion, and outlier screening will be stored in a predefined data structure suitable for subsequent query and analysis, such as a database table or memory object containing exhibit metadata and a list of corresponding valid measurement points (each point containing coordinates and optical data). This will establish a complete basic information set for the exhibit.

[0023] The steps to obtain the ideal display lighting parameters are: Based on the material type text and main color range values ​​in the exhibit basic information set, the preset rule library is matched to retrieve the texture enhancement, color fidelity or target artistic style parameter set associated with the display target, and the corresponding multidimensional weight vector is selected to obtain the target effect weight; Apply the target effect weights to perform a weighted average of the reflectance spectrum data or CIELAB values ​​at each point in the exhibit's basic information set. Through iterative optimization, find the spectral morphology parameters that meet the maximum value of the weighted objective function and determine the target spectral distribution of peak wavelength, full width at half maximum, and energy ratio of each band. Combined with the exhibit surface area or characteristic dimensions recorded in the exhibit basic information set and the target spectral distribution, the average brightness lumen value required for the exhibit surface is calculated according to the preset illumination standard. The spectral morphological parameters and the average brightness lumen value are combined to generate the ideal display lighting parameters.

[0024] Specifically, based on the material type text (e.g., "silk") and the main color range value (e.g., CIELAB value L is 60-80, a is -5 to 5, and b* is 10 to 20, indicating a light yellow tone) provided by the basic information set of the exhibit, the system will query a preset rule base, which is jointly established by lighting experts and cultural relics protection experts and contains a series of conditional rules for determining appropriate lighting strategy parameters based on the exhibit attributes and preset display goals (the goal can be selected by the user through the interface, such as "maximum color restoration", "highlighting the gold wire texture" or "simulating the original candlelight effect"). The query process first matches the material type and the main color range. For example, there is a rule in the rule library: "IF material = 'silk' AND main color = 'light yellow' AND display target = 'maximum color reproduction'", then the system will retrieve the color fidelity parameter set associated with this rule. This parameter set contains the spectral characteristic tendencies required to achieve the target (for example, requiring the spectral coverage of the light source to be as wide and smooth as possible, the color rendering index CRIRa target value to be greater than 95, the special color rendering index of a specific color sample such as R9 to be greater than 90, etc.), and specifies a corresponding multi-dimensional weight vector, which is used to balance different optimization targets in subsequent steps. For example, for the "maximum color reproduction" target, its weight vector is defined as w = [w fidelity ,w texture ,w style ], where each component represents the importance of color fidelity, texture expression, and artistic style conformity. Based on expert settings or historical optimization results, this vector is assigned a value of [0.8, 0.1, 0.1], indicating that color fidelity accounts for 80% of the importance, and texture and style each account for 10%. The basis for setting this weight value is: for colorful silk, accurately restoring its inherent color is the primary task (therefore w fidelity =0.8), while taking texture (w texture =0.1) and overall style (w style =0.1), these weight values ​​are stored in the rule base and associated with specific rule entries and parameter sets. The multidimensional weight vector [0.8, 0.1, 0.1] selected and extracted is the target effect weight.

[0025] Apply the target effect weights (e.g. [0.8, 0.1, 0.1]) obtained in the previous step to the reflectance spectrum data (R i (λ)) or CIELAB value for processing. The core is to construct and optimize a weighted objective function F(S light ), which is designed to evaluate the spectrum S of the candidate lighting source light (λ) The comprehensive performance under the current weight, the function form is, for example, F(S light )=w fidelity ×Mfidelity (S light )+w texture ×M texture (S light )+w style ×M style (S light ), where each component of w is the target effect weight value, M fidelity Is a measure of color fidelity, which can be calculated using the average color rendering index CRIRa or a more comprehensive standard such as TM-30-18 Rf value. light (λ) is the difference between the color of the exhibit's average reflectance spectrum under illumination and the color under the standard light source; M texture It is a measure of texture performance, which is quantified by analyzing the slight differences in brightness or chromaticity between points on the surface of the exhibit under simulated lighting (for example, calculating the local standard deviation or entropy of the simulated image); M style It is a measure of artistic style conformity, which is measured by calculating the average color temperature and color coordinates under simulated lighting and the degree of closeness to the target style (such as "candlelight effect" requires low color temperature and yellowish coordinates). The calculation of these metrics is based on the physical model, that is, the simulated lighting S light (λ) irradiates each point on the surface of the exhibit (with reflection spectrum R i (λ)) after the reflected light spectrum S reflected,i (λ)=S light (λ)×R i (λ), and then further calculate the chromaticity value or image features, and then use an iterative optimization algorithm, such as the gradient-based conjugate gradient method or the gradient-free particle swarm optimization algorithm, to find the weighted objective function F(S light ) reaches the maximum value of the optimal light source spectral morphological parameters. The optimization process adjusts the parameters that describe the shape of the light source spectrum, such as modeling it as a linear combination coefficient of multiple (for example, 6, corresponding to RGB, Amber, Cyan, WhiteLED) benchmark LED spectra, or directly optimizing the relative energy value of the spectrum in several (for example, one per 10nm) band intervals. The stopping condition of the optimization iteration is set to the increment of the objective function value is less than a preset small positive number (for example, 10 -4 ) or reaches the preset maximum number of iterations (e.g. 500 times), after the optimization is completed, the optimal light source spectral energy distribution S is obtained. optimal(λ), and finally, analyze this optimal spectrum and extract its key morphological features: calculate the wavelength with the highest energy as the peak wavelength (for example, 590nm), calculate the wavelength width where the spectral intensity drops to half of the peak as the full width at half maximum (FWHM, for example, 80nm), and integrate the spectrum according to the agreed bands (such as blue 400-495nm, green 495-570nm, yellow 570-590nm, and red 590-780nm). Calculate the proportion of the energy of each band to the total energy (for example, 15% for blue, 35% for green, 20% for yellow, and 30% for red). These parameters together constitute the target spectral distribution.

[0026] Combined with the exhibit surface area (e.g., the exact value obtained by consulting the records is 1.5 square meters) or characteristic dimensions (e.g., if the recorded dimensions are 2.0 meters in width and 0.75 meters in height, the estimated surface area is 2.0×0.75=1.5 square meters) recorded in the exhibit basic information set, and the target spectral distribution (including peak wavelength, full width at half maximum, and energy ratio of each band) determined in the previous step, the final required light illuminance is calculated based on a detailed preset illumination standard. This preset illumination standard is a lookup table or rule set developed based on international museum lighting specifications (e.g., CIE157:2004 or subsequent updated versions) and combined with specific exhibition hall requirements. It divides exhibits into different light sensitivity levels based on the material type text in the exhibit basic information set (for example, Level 1: extremely sensitive, such as silk and watercolor; Level 2: sensitive, such as oil painting and wood; Level 3: insensitive, such as metal, stoneware and ceramics), and sets a recommended annual exposure and the corresponding maximum illumination value for each level. For example, for "silk" (material type text), it is divided into Level 1 (extremely sensitive), and the corresponding preset illumination standard stipulates that the maximum allowable illumination is 50 lux. This 50 lux is the basis for calculation. Then, using this illumination standard value (E=50lux) and the exhibit surface area (A=1.5m 2 ), calculate the total average brightness lumen value (Φ) required for the exhibit surface. The calculation method is average brightness lumen value Φ=E×A. Substituting the value into Φ=50lux×1.5m 2 =75 lumens. This 75 lumens value represents the total luminous flux that needs to be projected onto the surface of the exhibit to meet the preset illumination standard. Finally, the spectral morphology parameters of the target spectral distribution obtained previously (such as peak wavelength 590nm, FWHM 80nm, and energy ratio of each band) are combined with the calculated average brightness lumen value (75 lumens) to form a complete set of parameters that describe the ideal lighting conditions and generate the ideal display lighting parameters.

[0027] The steps to obtain real-time ambient light parameters are: Activate the ambient light sensor at one or more preset monitoring points around the exhibit, adjust the sensor's optical axis to a specific direction to capture the main ambient incident light, perform photoelectric conversion and amplify the signal, and read the ambient light intensity lux value corresponding to the calibration curve to obtain the ambient illumination reading; Using a sensor that is synchronized or serial with the ambient illuminance reading, the built-in spectroscopic element, such as a grating or filter wheel, is activated to disperse the incident ambient light by wavelength, measure and record a sequence of energy intensity values ​​within a preset wavelength interval, or integrate and calculate the CIEXYZ tristimulus values ​​and then convert them into chromaticity coordinates to form ambient spectral chromaticity data; Combine the ambient illuminance reading value with the spectral energy sequence or chromaticity coordinates in the ambient spectrum and chromaticity data, add timestamp information, check whether the data is within the valid range, and package it into a data frame containing intensity, spectrum or chromaticity information to obtain real-time ambient light parameters.

[0028] Specifically, one or more monitoring points pre-set and installed around the exhibit (for example, one is installed at the top left front of the display case and one is installed at the bottom right rear, and these locations are selected based on the analysis of the main ambient light incident path) activate the ambient light sensor (for example, by sending a specific I2C or wireless command to start the sensor). If the sensor is equipped with an angle adjustment mechanism, its optical axis direction is adjusted according to a preset strategy. For example, it is pointed at the main ambient light source (such as a window or ceiling light panel, whose direction angle is pre-stored in the system configuration) to capture direct or main indirect light, or pointed at a diffuse reflective surface (such as a ceiling) to measure the overall ambient diffuse light level. After the photodiode inside the sensor receives the incident light, photoelectric conversion occurs. A weak current signal is generated, which is then converted into a voltage signal by an internal transimpedance amplifier and linearly amplified by a multi-stage operational amplifier to ensure that the signal amplitude is suitable for subsequent processing. The amplified analog voltage signal is sent to the analog-to-digital converter (ADC) for digitization to obtain a raw digital reading. The system then searches for the sensor's unique calibration curve data stored in the sensor's non-volatile memory or in the system configuration file. This calibration curve is established during production calibration or on-site calibration by comparing the sensor reading with the reading of a standard illuminance meter under different known illuminances. It is usually expressed as a function or lookup table that maps the ADC raw reading to a lux value, for example, a second-order polynomial function lux = a × (reading) 2 +b×reading+c, where coefficients a, b, and c are the specific calibration constants of this sensor (for example, a=0.0001, b=0.5, c=5). Substitute the current ADC reading into this function to calculate the calibrated ambient light intensity lux value and obtain the ambient illumination reading.

[0029] An ambient light sensor or its spectrum measurement module is started synchronously with the acquisition of ambient illuminance readings (if the sensor is integrated) or serially thereafter (if it is an independent device or mode switching), and its built-in spectroscopic mechanism is started. If a micro grating is used as a spectroscopic element, the incident ambient light is diffracted by the grating after passing through the slit and projected onto a linear array image sensor (such as a CCD or CMOS array) according to wavelength dispersion. Each pixel on the array corresponds to a narrow wavelength range. By reading the signal intensity of all pixels, the energy distribution in the entire spectral range is obtained. If filter wheel technology is used, the stepper motor rotates the filter wheel so that a series of narrow-band interference filters with different center wavelengths (for example, covering 380nm to 780nm, with a center wavelength every 10nm) are placed in the optical path in sequence. In front of a single photodetector in the sensor, each time a filter is switched, the intensity of light passing through the filter is measured. After completing a round of rotation, a series of light intensity data at discrete wavelength points are obtained. Regardless of the method, the measured raw signal needs to be corrected according to the calibration data stored in the sensor (including the spectral response efficiency and wavelength accuracy of each pixel or filter). Finally, a sequence of energy intensity values ​​is recorded, which represents the relative or absolute spectral power distribution of the ambient light at a preset wavelength interval (for example, an intensity value is recorded every 5nm). (For example, the format is [[wavelength 1, intensity 1], [wavelength 2, intensity 2], ..., [wavelength n, intensity n]]). Alternatively, the system can also choose to perform an integral calculation based on the measured spectral energy distribution data S ambient (λ) and the color matching functions of the International Commission on Illumination (CIE) 1931 standard colorimetric observers The CIEXYZ tristimulus values ​​are calculated by the following integral: Among them, S ambient (λ) is the measured spectral power distribution of ambient light, is the color matching function, k is a normalization constant (usually 683 lm / W), the integration range covers the visible light wavelength, and then according to the calculated X, Y, Z values, further conversion is obtained to obtain the CIE1931 chromaticity coordinates (x, y). The calculation formula is x = X / (X+Y+Z) and y = Y / (X+Y+Z), and finally the environmental spectral chromaticity data containing the spectral energy sequence or CIEXYZ and chromaticity coordinates are formed.

[0030] Combine the environmental illuminance reading value obtained in the first step (e.g., 150 lux) with the environmental spectral chromaticity data formed in the second step (e.g., containing a detailed spectral energy sequence [[380, 0.02], [385, 0.03],..., [780, 0.05]] or the calculated chromaticity coordinates x = 0.45, y = 0.41). At the same time, obtain the current system date and time and format it into an accurate timestamp (e.g., accurate to milliseconds, such as "2025-04-30T17:54:35.580+08:00"), and add this timestamp information to the combined data. Then, perform a validity check on the combined data, compare the values therein with the valid range defined in the sensor specification or system configuration. For example, check whether the environmental illuminance reading is within the normal working range of the sensor (e.g., 0.1 lux to 8000 lux). If the reading is 150 lux, it is within this range and is determined to be valid; check whether the intensity values of each wavelength in the spectral data are lower than the saturation threshold of the sensor (e.g., the relative intensity does not exceed 1.0); or check whether the calculated chromaticity coordinates x and y fall within the valid region defined by the CIE1931 chromaticity diagram (e.g., it is required that x > 0 and y > 0 and x + y < 1, and according to the fact that the actual light source usually does not cover the entire horseshoe region, a narrower empirical range may also be set, such as 0.1 < x < 0.7 and 0.1 < y < 0.7). These valid ranges (0.1 - 8000 lux, x = [0.1, 0.7], y = [0.1, 0.7]) are preset based on the physical limitations of the used sensor and the statistical understanding of the typical exhibition hall ambient light conditions. If any data exceeds the preset valid range, the data point or the entire data set may be marked as invalid or suspicious. Finally, integrate and encapsulate the data containing the valid (or marked) environmental illuminance reading, spectral energy sequence or chromaticity coordinates, and timestamp information into a data frame in a standard format, such as a JSON object {"timestamp": "...", "sensor_id": "EnvSensor01", "illuminance_lux": 150, "spectrum_data": [[...]], "status": "valid"} or a structure containing chromaticity_x: 0.45, chromaticity_y: 0.41 fields to obtain the real-time ambient light parameters.

[0031] The steps for obtaining the light compensation amount are as follows: The target spectral energy sequence and target brightness value in the ideal display lighting parameters are called, and the ambient spectral energy sequence and ambient illuminance value in the real-time ambient light parameters are introduced. Based on the color mixing model, the corresponding light energy is superimposed wavelength by wavelength, and the spectral energy distribution and integrated brightness of the light reflected from the exhibit surface under mixed light illumination are calculated to obtain the mixed light simulation value. Compare the spectral energy distribution, integrated brightness, and calculated chromaticity coordinates of the mixed illumination simulation values ​​with the corresponding target values ​​in the ideal display illumination parameters, calculate the color coordinate difference value, and calculate the brightness percentage difference, quantify the degree of visual perception deviation between the two, and obtain the perception effect deviation amount; Based on the value in the perceived effect deviation and the percentage of brightness difference, the compensatory adjustment required to offset the deviation is reversely calculated, the numerical sequence of the energy of each spectral band that needs to be increased or decreased and the lumen difference that needs to be adjusted for the overall brightness are determined, and the lighting compensation amount is established.

[0032] Specifically, the previously determined ideal display illumination parameters are called and the target spectral energy sequence (expressed as the relative energy value at each wavelength, such as S target (λ)) and the target brightness value (e.g. L target =75 lumens), and at the same time introduce the latest real-time ambient light parameters to extract the ambient spectral energy sequence (S ambient (λ)) and the corresponding ambient illumination value (E ambient , for example, 25 lux is used to understand the ambient light intensity but is not directly used for spectrum superposition). According to the basic physical principle of color mixing, that is, the energy of light is linearly superimposed according to wavelength, first the output spectrum S of the currently set (or last compensated) light source is source (λ)(its shape is based on S target (λ) but the overall intensity may have been adjusted) and the ambient light spectrum S reaching the exhibit surface ambient_at_exhibit (λ) (Here, for example, its spectral shape is consistent with the S measured by the sensor ambient (λ) is the same, but its intensity may be adjusted according to the geometric relationship between the sensor position and the exhibit position, or simply use S directly for uniform intensity. ambient (λ)) adds the energy at each wavelength point to obtain the total incident spectrum S irradiated on the surface of the exhibit total_incident (λ)=S source (λ)+S ambient_at_exhibit (λ), and then, using the average surface spectral reflectance data R of the exhibit stored in the exhibit basic information set avg (λ) (obtained by averaging the reflectance spectrum data of multiple measurement points on the exhibit surface) and calculating the spectral energy distribution of the light reflected from the exhibit surface under mixed lighting conditions. The calculation formula is S reflected (λ)=S total_incident (λ)×Ravg (λ), then, based on the calculated reflection spectrum S reflected (λ), by integrating it with the CIE standard observer visual function V(λ), the integrated brightness of the exhibit presented to the observer under mixed illumination is calculated (corresponding to the CIEY stimulus value, or converted into equivalent lumen value). The calculation result S reflected (λ) and L simulated Together they form the mixed lighting simulation value.

[0033] Compare the mixed illumination simulation value obtained in the previous step (including the simulated reflected spectral energy distribution S reflected (λ) and the simulated integrated brightness L simulated ) and the target value corresponding to the ideal display illumination parameter as a benchmark, specifically, first from the simulated reflection spectrum S reflected (λ) Calculate its corresponding chromaticity coordinates (such as CIE1931 (x, y) coordinates or the more commonly used CIELAB coordinates ), similarly, from the target spectral energy sequence S in the ideal display illumination parameters target (λ) and the average reflectivity R of the exhibit avg (λ) is multiplied to obtain the ideal reflection spectrum S reflected_ideal (λ), and calculate the ideal chromaticity coordinates Then, the color coordinate difference between the simulated color coordinate and the ideal color coordinate is calculated using the industry standard CIEDE2000 (ΔE 00 ) color difference formula, which can better match the human eye's perception of color differences: At the same time, the simulated integrated brightness L is calculated simulated Compared with the target brightness value L set in the ideal display lighting parameters target The percentage difference in brightness between the two is calculated as follows: ΔL%=((L simulated -L target ) / L target )×100%. For example, if the simulated brightness is 80 lumens and the target brightness is 75 lumens, the brightness difference is +6.67%. These two quantitative indicators, namely the color coordinate difference value ΔE 00 The percentage difference in brightness ΔL% and the degree of perceived deviation between the visual effect under the current mixed lighting conditions and the ideal target are jointly quantified to obtain the perceived effect deviation.

[0034] Based on the perceptual effect deviation obtained in the previous step, that is, the color coordinate difference value ΔE 00The reverse calculation process is performed based on the brightness difference percentage ΔL%, to determine what compensatory adjustment is needed to the light source (i.e., the adjustable multi-channel LED lamp) to offset this deviation. For the brightness deviation, a proportional control strategy is used to calculate the lumen difference ΔΦ that the overall brightness needs to be adjusted. source , the calculation formula is ΔΦ source =-γ×(ΔL% / 100)×L target , where γ is a control gain coefficient whose value (e.g. set to 0.7) is determined by experimental debugging, aiming to make the system converge to the target brightness stably and quickly, avoiding overshoot or oscillation. For example, if ΔL% = +6.67%, L target =75 lumens, and γ = 0.7, then the brightness needs to be adjusted by ΔΦ source =-0.7×(6.67 / 100)×75≈-3.5 lumens, indicating that the light source output needs to be reduced by about 3.5 lumens; for color deviation ΔE 00 , it is necessary to determine the specific numerical sequence of energy increases and decreases in each spectral band. For example, a sensitivity model is established to describe the relationship between the intensity change of each light source channel (such as RGB, Amber, Cyan, WhiteLED) and the final perceived color (CIELAB value) (this can be achieved by calculating the Jacobian matrix J, where the elements of J represent the effect of changing the intensity of a certain LED channel on the color L * ,a * ,b * value), and then according to the current color deviation vector Solve the linear equations JΔI=-ΔC to infer the amount of adjustment required for each LED channel intensity ΔI=[ΔI R ,ΔI G ,...,ΔI W ], where ΔI is usually expressed as a percentage change in the original intensity (e.g., R channel increases by 2%, G channel decreases by 1%, etc.). This sequence indicates how to adjust the spectral shape to approach the target color. The calculated channel intensity adjustment sequence ΔI and the overall brightness adjustment lumen difference ΔΦ are used to calculate the spectral shape. source Combined together, a lighting compensation amount is established.

[0035] The steps to obtain the light source driving instruction are: Integrate the target spectral energy sequence and target brightness value of the ideal display lighting parameters with the spectral energy increase and decrease sequence and brightness adjustment lumen difference in the lighting compensation amount to obtain the new target spectral energy sequence and new target brightness value after compensation adjustment, and generate a corrected lighting target set; Based on the standard spectral energy distribution curves for RGB, Amber, Cyan, and White LED channels stored in the database, a constrained least squares method is performed on the new target spectral energy sequence in the corrected illumination target set to obtain the luminous flux ratio required to drive each LED channel to emit light to synthesize the target spectrum, thereby generating the channel luminous flux ratio. According to the luminous flux ratio of each channel in the channel luminous flux ratio, combined with the new target brightness value in the corrected illumination target set and the light efficiency parameters of each LED, the required input power of each channel is calculated, and then converted into the corresponding PWM pulse width modulation duty cycle percentage value according to the LED driver characteristic curve to establish the light source driving instruction.

[0036] Specifically, the ideal display illumination parameters (including the target spectral energy sequence S target (λ) and target brightness value L target ) and the illumination compensation calculated in the previous step (including the spectral energy increase and decrease sequence, with each channel adjusting the percentage ΔI i Indicates the difference between the brightness adjustment lumen value ΔΦ source ), first, by adjusting the brightness by the lumen difference ΔΦ source The brightness setting value L applied to the current light source current_source (i.e. the brightness value issued by the last instruction or the initial target brightness value), calculate the new target brightness value L after compensation adjustment new_target =L current_source +ΔΦ source And make sure that the value does not exceed the minimum (usually 0) and maximum allowable output lumens range of the light source hardware. For example, if the current brightness is 78 lumens and the compensation amount is -3.5 lumens, the new target brightness is 74.5 lumens. At the same time, according to the spectral energy increase and decrease sequence ΔI i (For example, R+2%, G-1%, B+3%, A0%, C-1%, W+1%), adjust the current light source spectrum S source (λ) the relative intensity of each LED channel (assuming the current relative intensity of each channel is I current,i ), calculate the new relative intensity I new,i =I current,i ×(1+ΔI i / 100), and ensure that all I new,i is a non-negative value, and these new relative intensities I new,i Compared with the standard spectrum P of each channel i (λ) The synthesized spectrum is the new target spectrum energy sequence S after compensation adjustment new_target (λ)=∑ i I new,i P i (λ)(This is an implicit definition. The actual operation is to determine I new,i), the calculated compensation adjusted new target spectral energy sequence (by I new,i Definition) and the new target brightness value L new_target Combine to generate a corrected lighting target set.

[0037] According to the standard spectral energy distribution curve P of each LED channel stored in the system database for the currently used multi-channel LED lamp (for example, including six channels of RGB, Amber, Cyan and White), i (λ) (these curves are provided by the luminaire manufacturer or obtained through precise laboratory measurements, representing the spectral shape of each channel under unit driving power or unit luminous flux, and stored as wavelength-relative intensity data pairs), and the new target spectral energy sequence S in the corrected illumination target set generated in the previous step new_target (λ)(by the target relative channel strength I new,i Define, or directly use the optimized target spectrum), perform constrained least squares operation, the goal of which is to find a set of driving coefficients c i ≥0 (corresponding to each LED channel i), so that the standard spectrum of each channel P is weighted by these coefficients i (λ) The synthesized spectrum S synth (λ)=∑ i c i P i (λ) and the new target spectral energy sequence S new_target The difference between (λ) is the smallest, that is, solving the optimization problem: The optimization problem is subject to the constraint c i ≥0, because the LED channel cannot emit negative energy, the non-negative least squares (NNLS) algorithm solver provided in the numerical calculation library (such as the implementation of the interior point method) is used to obtain the optimal coefficient value c R ,c G ,c B ,c A ,c C ,c W , these coefficient values ​​c i Physically, the luminous flux (or a quantity proportional to it) that each channel needs to contribute when synthesizing the target spectrum is normalized to calculate the luminous flux proportion c' of each channel. i =c i / ∑ j c j , obtain the luminous flux value ratio required to drive each LED channel to emit light, and generate the channel luminous flux ratio.

[0038] According to the channel luminous flux ratio generated in the previous step (that is, the normalized luminous flux ratio value c' of each channel i , for example, R: 0.24, G: 0.12, B: 0.05, A: 0.07, C: 0.02, W: 0.50), combined with the new target brightness value L determined by the corrected illumination target set new_target (e.g. 74.5 lumens), and call the light effect parameter η of each LED channel of the lamp stored in the database i (i.e., luminous flux per watt of electrical power, in lm / W, for example, η R =80,η G =150,η B =50,η A =100,η C =70,η W =120lm / W), first calculate the absolute luminous flux value Φ that each channel needs to emit i =c′ i ×L new_target (For example, the red channel needs to emit 0.24×74.5≈17.88 lumens), and then use the light effect parameter η i Calculate the required luminous flux Φ required to drive each channel i Input power to be consumed i =Φ i / η i (For example, the red channel requires an input power of 17.88 / 80≈0.2235 watts). Next, based on the characteristic curve of the LED driver connected to each channel (this curve describes the relationship between the duty cycle of the input PWM signal and the driver's output current or output power, usually provided by the driver manufacturer or obtained through experimental calibration and stored as a lookup table or function), the calculated input power required for each channel is converted to i (Or first convert it into the corresponding driving current I according to the VI characteristic curve of the LED i ) is reversely converted into the corresponding PWM pulse width modulation duty cycle percentage value D i For example, if the inverse function of the red channel driver characteristic curve is D R =f -1 (Power R ), then substitute the calculated Power R Get the required duty cycle D R (e.g. 45.5%), perform this conversion on all channels and get a set of PWM duty cycle values ​​(e.g. D R =45.5%,D G =20.1%,D B =15.0%,D A =22.8%,DC =10.5%,D W =60.2%), ensuring that these values ​​are within the valid range of 0% to 100%, and establishing the light source driving instructions.

[0039] The steps to obtain the specified spectrum and brightness output light are: The PWM duty cycle percentage values ​​of each channel in the light source drive instruction are encoded into a data frame sequence containing the target address, instruction code, data payload, and checksum according to the preset communication protocol of the exhibition light control unit, thereby obtaining a control instruction packet to be sent. The control instruction packet to be sent is sent to the exhibition light control unit with the target ID via the wired DMX512 and DALI or wireless Zigbee and Bluetooth communication interface, and the control unit is waited for to return a response signal confirming the receipt or execution status. The validity of the response signal is verified to obtain the driving current modulation basis. Based on the successfully received and analyzed driving current modulation basis, the exhibition lighting control unit generates a pulse signal with a corresponding duty cycle through the internal PWM generator, drives the constant current source to adjust the current flowing to the RGB, Amber, Cyan and WhiteLEDs, controls the light output intensity of each channel, and mixes them to form the output light with the specified spectral form and brightness level.

[0040] Specifically, the PWM duty cycle percentage values ​​of each channel (e.g., R=45.5%, G=20.1%, B=15.0%, A=22.8%, C=10.5%, W=60.2%) contained in the light source drive instruction established in the previous step are encoded according to the preset communication protocol supported by the target exhibition light control unit. The selected protocol (e.g., DMX512) is determined by the system configuration, which is based on the type of lamps and control network installed on site. According to the requirements of the DMX512 protocol, the PWM duty cycle percentage D of each channel is first converted to 45.5%. i (0 to 100) is linearly mapped to the 8-bit data value of DMX512 (0 to 255), and the calculation formula is DMX value i = round (D i / 100×255) to obtain the DMX value corresponding to each channel (for example, R=116, G=51, B=38, A=58, C=27, W=154). Next, the target address of the luminaire is determined, that is, the starting channel number set on the DMX link (for example, 101). The calculated DMX values ​​for each channel are then organized into a data payload in sequence (R channel corresponds to address 101, G corresponds to 102, and so on to W corresponds to 106). For the DMX512 protocol, there is usually no specific instruction code field. The channel value itself represents the instruction, and the application layer data frame checksum is usually not mandatory. Finally, the byte sequence containing the DMX start code (0x00) and all channel data values ​​starting from channel 1 and including the target channel (at least up to 106) is organized according to DMX512 timing requirements (including BREAK and MAB signals) to form one or more DMX data frame sequences, thereby obtaining the control instruction packet to be sent.

[0041] Through the communication interface specified by the system configuration (in this case, the wired DMX512 interface, connected to the corresponding RS-485 physical layer transceiver), the control instruction packet to be sent (DMX512 data frame sequence) obtained in the previous step is sent to the connected network bus. The target of this instruction packet is the exhibition light control unit with the starting address (target ID) of 101 on the network. For standard DMX512 communication, it is designed as a one-way broadcast. The sending end usually does not receive the response signal from the receiving end. Therefore, after the sending operation is completed, the system assumes that the instruction has been sent, and does not execute the steps of waiting for the response and verifying the validity of the response. [(If a protocol that supports two-way communication is used, such as DALI or a wireless protocol based on Zigbee / Bluetooth, the sending end will start a The timer (sets a preset timeout period based on the protocol specification and network conditions, such as 200 milliseconds for DALI and 500 milliseconds for wireless protocols) waits for the target control unit to return a response signal confirming the receipt or execution status. After receiving the response, it will check whether its source address matches, whether the status code indicates success (such as DALI's ACK response), and whether the possible checksum is correct. Only after passing these checks can the command be considered successfully received and confirmed). However, in the current DMX512 scenario, successfully handing over the data frame sequence to the physical layer sending interface and the interface reporting the sending completion (no hardware sending error) is considered to have obtained the basis for driving current modulation (from the sender's perspective it is "sent", and the receiver is based on the received data), and thus obtain the basis for driving current modulation.

[0042] The exhibition light control unit (whose DMX starting address is set to 101) located inside the target lamp, while continuously monitoring the DMX bus data stream, successfully receives and parses the data frame according to the DMX512 protocol rules (identifies its own address 101 and extracts the data values ​​116, 51, 38, 58, 27, 154 of channels 101 to 106), and uses these received DMX values ​​as the basis for effective drive current modulation. The microcontroller (MCU) inside the control unit first reversely converts these DMX values ​​(in the range of 0-255) into the corresponding PWM duty cycle percentage value (in the range of 0-100%), for example, using formula D i =(DMX value i / 255)×100% to obtain the target duty cycle of each channel (RGBACW) (R=45.5%, G=20.1%, etc.). Subsequently, the MCU generates a duty cycle D for each LED channel independently through its internal integrated multi-channel PWM generator hardware. i and a pulse width modulated (PWM) square wave signal with a predetermined frequency (e.g., 2000 Hz, which is selected by design to ensure that there is no flicker and the driver can respond effectively). These PWM signals are respectively sent to the control input terminals of the constant current source drive circuits of the corresponding channels. The constant current source drive circuits (e.g., using a switch-mode buck or buck-boost topology) adjust the magnitude of their output DC current according to the duty cycle of the input PWM signal, so that the drive current I flowing to the corresponding RGB, Amber, Cyan, and White LED modules (or lamp arrays) is out,i and duty cycle D i The six independently controlled channels are spatially and angularly mixed in the optical system of the luminaire (such as a lens array, mixing cavity or diffuser) to form a uniform output light with a specified spectral shape (determined by the intensity ratio of each channel) and a specified brightness level (determined by the overall current level).

[0043] See also Figure 2 The present invention provides an exhibition lamp, including a mounting base 1, a bracket 2 is fixedly installed on the surface of the mounting base 1, a lamp cup 3 is fixedly installed on the top of the bracket 2, a lens 4 is fixedly installed on the top of the lamp cup 3, and a light strip 5 and a pattern 6 are fixedly installed on the bottom surface of the mounting base 1.

[0044] The external external switch can be used to control the light cup 3, the light strip 5, and the light cup 3 and the light strip 5 to light up at the same time, so that the user can choose the appropriate lighting effect according to different needs. At the same time, the brightness of the light cup 3 and the light strip 5 can be controlled by adjusting the switch to adjust the brightness required by the user; and when switching to the display function, each light cup 3 will light up in a cycle to show the user different light effects and brightness; the user can change to different patterns 6 to achieve the effect of stage lighting.

[0045] The above are merely preferred embodiments of the present invention and do not limit the present invention in any other form. Any technician familiar with the profession may use the technical content disclosed above to change or modify it into an equivalent embodiment with equivalent changes and apply it to other fields. However, any simple modification, equivalent change and modification made to the above embodiment based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall still fall within the scope of protection of the technical solution of the present invention.

Claims

1. A display method, characterized in that: The following steps are involved: Input the preset exhibit database information, extract the exhibit number, material type, main color range and size information, scan the exhibit surface point by point, collect reflectance spectrum data, convert it into CIELAB values, integrate the extracted information with the collected data, and establish the basic exhibit information set; Based on the material type and main color range in the basic information set of the exhibit, a preset weight set is selected. The preset weight set corresponds to the texture detail expression, color perception restoration, or artistic style target. The preset weight set is applied to the exhibit reflectance spectrum data or CIELAB value to determine the target spectral distribution composed of peak wavelength, bandwidth, and relative intensity. The target brightness value is calculated based on the exhibit size to generate ideal display lighting parameters; Activate ambient light sensors at target locations around exhibits to capture incident light, analyze ambient light intensity data, and perform spectrophotometric measurements on the ambient light spectrum, recording the energy values ​​of each band or calculating CIEXYZ tristimulus values ​​to obtain ambient light chromaticity coordinates. Combine intensity with spectrum or chromaticity information to obtain real-time ambient light parameters. The target spectral distribution and target brightness values ​​in the ideal display lighting parameters are called, and the real-time ambient light parameters are introduced to simulate the apparent color and brightness of the exhibits under mixed lighting. The simulation results are compared with the target set by the ideal display lighting parameters, the deviation value is quantified, and the required adjustment of the light source spectral distribution offset and the light source brightness increase or decrease is reversely calculated to generate the lighting compensation amount.

2. The display method according to claim 1, characterized in that: The method further comprises: Integrate the target spectrum of ideal display lighting parameters, target brightness, spectral offset of lighting compensation, and brightness increase or decrease to generate a corrected target spectrum and brightness. Based on the spectral characteristics of each RGB, Amber, Cyan, and WhiteLED channel, decompose the corrected target spectrum into each channel, calculate the required luminous flux ratio of each channel, convert it into the corresponding PWM duty cycle value, and establish the light source drive instruction; The PWM duty cycle value of each channel in the light source driving instruction is sent to the exhibition light control unit through the communication interface, modulating the driving current, controlling the luminous intensity of each channel of RGB, Amber, Cyan and WhiteLED in the multi-channel LED group, and mixing to form the specified spectrum and brightness output light.

3. The display method according to claim 1, characterized in that: The steps for obtaining the basic exhibit information set are as follows: Input the preset exhibit database information, locate the corresponding exhibit entry through the record identifier, sequentially read the exhibit number, material type field, main color range record and dimension value, organize the read information into a structured form, filter out null values ​​or invalid entries, and form a structured exhibit description; Based on the three-dimensional model or position coordinates of the exhibit in the structured exhibit description, a spectral sensor scanning path is planned to cover the visible surface of the exhibit, and the sensor is driven to move along the path and collect the raw data stream of the reflectance spectrum point by point, or the CIELAB three-dimensional coordinate values ​​of the predetermined key color area are calculated to obtain the surface optical measurement value; The structured exhibit description information and the surface optical measurement values ​​are integrated, data association is performed based on the exhibit number, unit unification and coordinate system conversion are performed, abnormal measurement points are filtered out, and the data is stored in a designated data structure to establish a basic exhibit information set.

4. The display method according to claim 1, characterized in that: The steps for obtaining the ideal display lighting parameters are: Based on the material type text and main color range values ​​in the exhibit basic information set, matching the preset rule library, retrieving the texture enhancement, color fidelity or target artistic style parameter set associated with the display target, selecting the corresponding multidimensional weight vector, and obtaining the target effect weight; Applying the target effect weight, performing weighted averaging on the reflectance spectrum data or CIELAB values ​​of each point in the basic information set of the exhibit, searching for spectral morphology parameters that satisfy the maximum value of the weighted objective function through iterative optimization, and determining the target spectral distribution of peak wavelength, full width at half maximum, and energy ratio of each band; Combined with the exhibit surface area or characteristic dimensions recorded in the exhibit basic information set and the target spectral distribution, the average brightness lumen value required for the exhibit surface is calculated according to the preset illumination standard, and the spectral morphological parameters and the average brightness lumen value are combined to generate the ideal display lighting parameters.

5. The display method according to claim 1, characterized in that: The steps for obtaining the real-time ambient light parameters are as follows: Activate the ambient light sensor at one or more preset monitoring points around the exhibit, adjust the sensor's optical axis to a specific direction to capture the main ambient incident light, perform photoelectric conversion and amplify the signal, and read the ambient light intensity lux value corresponding to the calibration curve to obtain the ambient illumination reading; Using a sensor that is synchronized or serial with the ambient illuminance reading, the built-in spectroscopic element, such as a grating or filter wheel, is activated to disperse the incident ambient light by wavelength, measure and record a sequence of energy intensity values ​​within a preset wavelength interval, or integrate and calculate the CIEXYZ tristimulus values ​​and then convert them into chromaticity coordinates to form ambient spectral chromaticity data; Combine the ambient illuminance reading value with the spectral energy sequence or chromaticity coordinates in the ambient spectrum and chromaticity data, add timestamp information, check whether the data is within the valid range, and package it into a data frame containing intensity, spectrum or chromaticity information to obtain real-time ambient light parameters.

6. The display method according to claim 1, characterized in that: The steps for obtaining the illumination compensation amount are as follows: The target spectral energy sequence and target brightness value in the ideal display lighting parameters are called, and the ambient spectral energy sequence and ambient illuminance value in the real-time ambient light parameters are introduced. According to the color mixing model, the corresponding light energy is superimposed wavelength by wavelength, and the spectral energy distribution and integrated brightness of the light reflected from the exhibit surface under the mixed light are calculated to obtain the mixed light simulation value. Comparing the spectral energy distribution, integrated brightness, and calculated chromaticity coordinates of the mixed illumination simulation value with the corresponding target values ​​in the ideal display illumination parameters, calculating the color coordinate difference value, and calculating the brightness percentage difference, quantifying the degree of visual perception deviation between the two, and obtaining a perception effect deviation amount; Based on the value in the perceived effect deviation and the percentage of brightness difference, the compensatory adjustment required for the light source to offset the deviation is reversely calculated, the numerical sequence of the energy of each spectral band that needs to be increased or decreased and the lumen difference that needs to be adjusted for the overall brightness are determined, and the lighting compensation amount is established.

7. The display method according to claim 2, characterized in that: The steps for obtaining the light source driving instruction are: Integrating the target spectral energy sequence and target brightness value of the ideal display lighting parameters with the spectral energy increase and decrease sequence and the brightness adjustment lumen difference in the lighting compensation amount to obtain a new target spectral energy sequence and new target brightness value after compensation adjustment, and generating a corrected lighting target set; Based on the standard spectral energy distribution curves of RGB, Amber, Cyan, and White LED channels stored in the database, a constrained least squares method is performed on the new target spectral energy sequence in the modified illumination target set to obtain the luminous flux numerical ratio required to drive each LED channel to emit light to synthesize the target spectrum, thereby generating a channel luminous flux ratio; According to the ratio of the luminous flux of each channel in the channel luminous flux ratio, combined with the new target brightness value in the corrected illumination target set and the light efficiency parameters of each LED, the required input power of each channel is calculated, and then converted into the corresponding PWM pulse width modulation duty cycle percentage value according to the LED driver characteristic curve to establish the light source driving instruction.

8. The display method according to claim 2, characterized in that: The steps for obtaining the output light with the specified spectrum and brightness are: The PWM duty cycle percentage values ​​of each channel in the light source driving instruction are encoded into a data frame sequence including a target address, instruction code, data payload and checksum according to the preset communication protocol of the exhibition light control unit to obtain a control instruction packet to be sent; Through the wired DMX512 and DALI or wireless Zigbee and Bluetooth communication interface, the control instruction packet to be sent is sent to the exhibition light control unit of the target ID, and the control unit is waited for to return a response signal confirming the reception or execution status, and the validity of the response signal is verified to obtain the driving current modulation basis; Based on the driving current modulation basis successfully received and analyzed, the exhibition light control unit generates a pulse signal with a corresponding duty cycle through an internal PWM generator, drives the constant current source to adjust the current flowing to the RGB, Amber, Cyan and White LEDs, controls the light output intensity of each channel, and mixes to form output light with a specified spectral form and brightness level.

9. The exhibition lamp according to any one of claims 1 to 8, characterized in that: The invention comprises a mounting seat (1), a bracket (2) is fixedly mounted on the surface of the mounting seat (1), a lamp cup (3) is fixedly mounted on the top of the bracket (2), a lens (4) is fixedly mounted on the top of the lamp cup (3), and a light strip (5) and a pattern (6) are fixedly mounted on the bottom surface of the mounting seat (1).

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