LED intelligent calibration system and method based on multi-source sensing data

Abstract

This invention discloses an LED intelligent calibration system and method based on multi-source sensor data, belonging to the field of lighting calibration technology. The invention determines the installation position and number of LED beads in each LED group, collects the optical parameters of individual LED beads, and locates their relative positions within the group. Based on the individual LED bead parameters and positions, an independent illumination area and intensity are obtained. Data from all LED beads within the group are superimposed to obtain the overall illumination characteristics of the group. Then, data is superimposed across groups according to the relative positions of the LED groups to obtain complete illumination data for the entire lighting area. A uniformity threshold is set for judgment; if it is not met, the mutual influence between LED beads across groups is calculated, and the LED bead with the greatest influence is selected for parameter adjustment before re-judgment; if it still does not meet the threshold, the next best pair is iteratively selected for adjustment until uniformity is achieved between groups. Uniformity within each LED group is judged; if it is not met, the middle LED bead within the group is used as the initial adjustment target; if it is still not met after re-judgment, the surrounding LED beads are gradually adjusted from the inside out until overall uniform illumination is achieved.

Description

Technical Field

[0001] This invention relates to the field of lighting calibration technology, specifically to an LED intelligent calibration system and method based on multi-source sensor data. Background Technology

[0002] LEDs are widely used in lighting, display, and other fields due to their advantages such as energy saving, long lifespan, and fast response. However, LED chips have manufacturing inconsistencies, and when multiple LED groups work together, the installation position of the groups, the arrangement of the chips, and the coupling of optical parameters can lead to poor illumination uniformity. To solve the uniformity problem, existing technologies optimize through single-parameter calibration or overall adjustment, but with the increasing prevalence of multi-LED groups and high-density chip scenarios, traditional methods are no longer sufficient to meet the requirements for accurate calibration.

[0003] Existing technologies for calculating overall illumination of light groups cannot quantify the contribution of individual LEDs to the superimposed effect. When superimposing across light groups, they ignore the coupling effect of the relative positions of the light groups, resulting in large deviations in the overall light intensity distribution calculation. They only perform coarse adjustments to the overall lighting area, without distinguishing between intersecting areas across light groups and the internal areas of each light group for layered calibration. Adjustments are made by randomly selecting LEDs or adjusting the entire group, failing to identify the core LEDs affecting uniformity, leading to low adjustment efficiency and a tendency to introduce new deviations. Furthermore, the lack of distinct thresholds for determining the core lighting area and the edge area makes it difficult to fundamentally address localized unevenness. Summary of the Invention

[0004] The purpose of this invention is to provide an LED intelligent calibration system and method based on multi-source sensor data to solve the problems raised in the prior art.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] The first invention, this application provides an LED intelligent calibration method based on multi-source sensor data, including the following steps:

[0007] Determine the installation location of all LED light groups and the number of LED beads in each group; collect the optical parameters of each LED bead and locate the relative position of each LED bead in its respective light group;

[0008] Based on the optical parameters of a single LED and its position within the lamp group, the independent illumination area and illumination intensity of the LED are calculated through optical modeling. The independent illumination areas and illumination intensities of all LEDs within the same lamp group are then superimposed to obtain the overall illumination area and overall illumination intensity of the lamp group.

[0009] Based on the relative positions of each LED group, the overall illumination area and intensity of all groups are superimposed across groups to obtain the complete illumination area and intensity of the entire lighting area. An illumination uniformity judgment threshold is set, and the light intensity values ​​at each point in the complete illumination area are compared to determine whether the uniformity requirements are met. If not, the degree of mutual influence between LED beads in different groups is calculated, and the cross-group LED bead pair with the greatest influence is selected. The optical parameters of the LED bead pair are adjusted, and the uniformity is re-judged. If it is still not uniform, the second-best cross-group LED bead pair is selected, and the parameter adjustment and uniformity judgment process is repeated.

[0010] For each lamp group, based on the illumination characteristic data within the group, it is determined whether the illumination area within the group meets the uniformity requirements. If it does not meet the requirements, the central lamp bead within the group is taken as the initial adjustment target. Its optical parameters are adjusted and the uniformity is recalculated and judged. If it still does not meet the requirements, the surrounding lamp beads are selected and adjusted step by step from the inside out, with the central lamp bead as the center.

[0011] In conjunction with the first aspect, in the first embodiment of the first aspect of this application, the step of collecting the optical parameters of each LED bead and locating the relative position of each LED bead within its respective lamp group includes:

[0012] Power the LEDs with the rated forward current. After the LEDs are stable, collect the luminous flux, color temperature, color rendering index, color coordinates and spectral distribution curves using an integrating sphere and a spectrometer. Adjust the LED emission angle using an angle photometer, collect the luminous intensity at each angle, generate the LED luminous intensity angle distribution curve, and determine the effective viewing angle.

[0013] A three-dimensional rectangular coordinate system is established with the top left corner of the light panel as the origin, the long side of the light panel as the X-axis, the short side as the Y-axis, and the perpendicular plane of the light panel as the Z-axis. The reference point needs to be calibrated by a laser displacement sensor. When the light group is a curved surface package, a curved surface coordinate system is established with the geometric center of the curved surface as the origin, the generatrix of the curved surface as the X-axis, the tangent direction as the Y-axis, and the normal direction as the Z-axis. This coordinate system is then linked to the Cartesian coordinate system using a coordinate transformation formula. The theoretical coordinates of each LED are extracted from the light group design drawings and entered into the database according to the unique identifier of each LED. For light panels without LEDs installed, images of the light panel are captured using a high-precision vision measuring instrument to identify the center position of the LED pads. These images are compared with the theoretical coordinates, the deviation value is calculated, and the corrected actual coordinates are linked to the LED identifier. For light groups with LEDs installed, a laser coordinate measuring machine is used to scan the center of the emitting surface of each LED point by point to directly collect the actual coordinates.

[0014] In conjunction with the first aspect, in the second embodiment of the first aspect of this application, the step of calculating the independent illumination area and illumination intensity of a single LED bead through optical modeling based on the optical parameters of the individual LED bead and its position within the lamp assembly includes:

[0015] The type of light source is determined based on the angular distribution curve of the luminous intensity of the LED; for a Lambertian light source, the Lambertian radiation model is applied. As a radiation model of a light source, in which... Peak luminous intensity The angle between the spatial point and the luminous axis. , To achieve an effective viewing angle; for non-Lambertian light sources, a radiation model of the light source is obtained by fitting experimental data using a polynomial; based on the spectral distribution curve of the LED chips, the luminous efficacy function is used. spectral radiant flux Converted to visible light flux, peak luminous intensity corrected The actual luminous intensity after spectral correction was obtained. ,in, For luminous flux, The wavelength of light;

[0016] Construct a distance attenuation model for indoor scenes, with attenuation factor d is the straight-line distance from a spatial point to the light-emitting center of the LED. For outdoor scenes, the atmospheric extinction coefficient is introduced. Attenuation factor ; Based on the viewing angle limitations of the LED beads, set an angle threshold. When spatial points When the light intensity is 0, it is determined that the point is not within the illumination range; when... At that time, the angle-dependent light intensity is calculated according to the light source radiation model;

[0017] With the geometric center of the light-emitting surface of the LED as the origin The luminous axis is Establish a local coordinate system for the LED beads; convert the coordinates of the illuminated surface in the LED group coordinate system to... By mapping the coordinates to the local coordinate system of the LED, the coordinates of the illuminated surface in the local system are obtained. ; with the light-emitting center of the LED bead As the vertex, the luminous axis As the axis, perspective Given the cone angle, construct the equation for the conical surface. The spatial grid cells within the conical surface constitute the theoretical illumination area. The intersection of the conical surface and the illuminated surface is calculated based on the actual illumination scene's illuminated area. The area enclosed by this intersection is the effective illumination area on the illuminated surface. Grid cells exceeding the actual installation environment boundary within the theoretical illumination area are removed to obtain the independent illumination area S.

[0018] Traverse the grid cells in S and determine whether each grid point can be illuminated by the LED. Specifically, determine whether the angle between the point and the LED's light-emitting axis exceeds the angle threshold or whether it is located at the LED's own position. If the conditions are met, the light intensity is 0. If not, combine the LED's light-emitting intensity at that angle and calculate the light intensity attenuation caused by distance based on the distance attenuation model to obtain the illumination intensity.

[0019] In conjunction with the first aspect, in the third embodiment of the first aspect of this application, the step of superimposing and calculating the independent irradiation areas and irradiation intensities of all lamp beads within the same lamp group to obtain the overall irradiation area and overall irradiation intensity of the lamp group includes:

[0020] Based on the maximum boundary of the independent illumination area of ​​all LEDs within the light group, a global grid of the light group is constructed, extending outward to cover the weak illumination area of ​​the edge LEDs. This grid encompasses the X, Y, and Z axes. Each cell of the global grid is traversed, and each cell is checked to see if it falls within the independent illumination area of ​​any LED within the light group. If a cell is contained within the independent illumination area of ​​at least one LED, its illumination status is updated to "illuminated"; otherwise, it remains "unilluminated." All cells with an "illuminated" illumination status are collected, and their coordinate boundaries constitute the overall illumination area of ​​the light group. All unilluminated cells are removed, forming a set of cells representing the overall illumination area of ​​the light group. The filtered illuminated cells are traversed to determine the region's bounding box. By analyzing the differences in illumination status between adjacent cells, the contour grid of the region's edge is identified, forming the contour of the irregular region.

[0021] For each illuminated global grid cell, all LEDs in the lamp group are traversed, and LEDs that can effectively illuminate the grid are selected. The independent light intensity values ​​of all selected LEDs in the grid are accumulated to obtain the overall illumination intensity. When the light emission directions of LEDs in the lamp group block each other, the light intensity contribution of the blocked LEDs is removed from the blocked grid points. The blocking relationship is determined by the LED position coordinates and the size of the light-blocking structure.

[0022] In conjunction with the first aspect, in the fourth embodiment of the first aspect of this application, the step of performing cross-group superposition calculation of the overall illumination area and intensity of all LED light groups based on the relative positions of each LED light group to obtain the complete illumination area and complete illumination intensity of the entire lighting area includes:

[0023] Based on the maximum boundary of the overall illumination area of ​​all light groups, the edge range is expanded to construct a three-dimensional mesh covering the entire lighting scene; all illuminated meshes are collected, and their boundaries constitute the complete illumination area; for each illuminated mesh, all light groups that can illuminate it are selected, the light intensity of these light groups in the mesh is accumulated, and updated to the complete illumination intensity; when there is occlusion between light groups, the light intensity contribution of the occluded light groups is removed.

[0024] In conjunction with the first aspect, in the fifth embodiment of the first aspect of this application, the step of calculating the degree of mutual influence between lamp beads in different lamp groups when the condition is not met, selecting the cross-lamp group lamp bead pair with the greatest influence, adjusting the optical parameters of the lamp bead pair, and re-judging the uniformity includes:

[0025] After confirming that the overall lighting area does not meet the uniformity requirements, areas with light intensity differences exceeding the threshold are marked to clarify the calibration target. For the marked areas, the light intensity contribution of individual LEDs in different lamp groups is analyzed. Specifically, by simulating the changes in the optical parameters of individual LEDs, the influence of each LED on the light intensity of the areas covered by other lamp groups is obtained, and the mutual influence weight of each LED and LEDs across lamp groups is quantified. From all combinations of LEDs across lamp groups, the pair with the highest mutual influence weight is selected as the priority adjustment target. A nonlinear compensation algorithm is used to adjust the optical parameters of the pair of LEDs according to the degree of influence, ensuring that the adjustment range matches the light intensity deviation. Based on the adjusted LED parameters, the irradiance distribution of the entire lighting area is recalculated, and the uniformity threshold is compared again to determine whether it is uniform.

[0026] In conjunction with the first aspect, in the sixth embodiment of the first aspect of this application, the step of selecting suboptimal cross-lamp group lamp bead pairs and repeating the parameter adjustment and uniformity judgment process when the uniformity is still uneven includes:

[0027] When the light intensity deviation remains uneven, mark the newly added or unimproved light intensity deviation areas to clarify the calibration target for this round. Based on the light intensity distribution data after the previous round of lamp parameter adjustment, perform coupling analysis again, update the mutual influence weights of all unadjusted or partially adjusted cross-lamp group lamp pairs, and reorder the influence priority of the remaining lamp pairs. From the updated influence weight ranking, select the second-best cross-lamp group lamp pair with the highest ranking to ensure that this lamp pair is directly related to the currently unimproved light intensity deviation area. Using the nonlinear compensation algorithm, combined with the light intensity deviation amplitude marked in this round, adjust the optical parameters of this second-best cross-lamp group lamp pair. Perform a uniformity recheck, and terminate the iteration when the light intensity deviation of the cross-coverage area between all lamp groups is lower than the uniformity threshold.

[0028] In conjunction with the first aspect, in the seventh embodiment of the first aspect of this application, the step of determining whether the irradiation area within each lamp group meets the uniformity requirement based on the irradiation characteristic data within the group includes:

[0029] Retrieve the superimposed light intensity dataset and effective lighting area boundary of the target light group, remove isolated grids with abnormal light intensity, and clarify the effective judgment area of ​​the core lighting; set uniformity judgment criteria according to scene requirements, and divide the area into sub-regions according to function and set corresponding thresholds if the area needs to be subdivided; extract the light intensity values ​​of all grids in the effective judgment area, calculate the maximum, minimum, and average light intensity values ​​and the statistical quantity reflecting the degree of dispersion, and form the core data required for judgment; calculate the actual uniformity index according to the set criteria and compare it with the threshold; when all regional indices meet the criteria and no continuous grid light intensity deviation exceeds the threshold, the uniformity requirement is judged to be met; otherwise, the uniformity requirement is not met.

[0030] In conjunction with the first aspect, in the eighth embodiment of the first aspect of this application, when the condition is not met, the process of adjusting the optical parameters of the central LED bead within the group and recalculating and judging uniformity, and then gradually adjusting the surrounding LED beads from the center outwards, includes:

[0031] After confirming that the illumination uniformity within the lamp group is substandard, the problem area is located by using the light intensity distribution data within the group. Combined with the lamp installation location map within the lamp group, the central lamp in the group is identified as the initial adjustment target. An adaptation algorithm is used to adjust the optical parameters of the initial adjustment target. Based on the adjusted parameters, the superimposed illumination intensity of all lamps in the group is recalculated and compared with the uniformity judgment threshold. When the threshold is met, the calibration within the group ends. If the threshold is still not met, adjacent lamps are selected as new adjustment targets, centered on the central lamp, in an order from the inside out. The process of parameter adjustment, superimposed light intensity recalculation, and uniformity judgment is repeated until the uniformity within the group meets the standard.

[0032] Secondly, this application provides an LED intelligent calibration system based on multi-source sensor data, comprising:

[0033] Data acquisition module: includes: a location information acquisition unit to determine the installation location of all LED light groups and the number of LED beads in each group; and an optical parameter acquisition unit to acquire the optical parameters of each LED bead and locate the relative position of each LED bead in its respective light group.

[0034] Illumination characteristic modeling and calculation module: including: single lamp bead illumination modeling unit, which calculates the independent illumination area and illumination intensity of a single lamp bead based on its optical parameters and position within the lamp group; and lamp group superposition calculation unit, which superimposes the independent illumination areas and illumination intensities of all lamp beads within the same lamp group to obtain the overall illumination area and overall illumination intensity of the lamp group.

[0035] Cross-lamp group calibration module: includes: a cross-lamp group superposition calculation unit that, based on the relative positions of each LED lamp group, performs cross-group superposition calculation of the overall illumination area and intensity of all lamp groups to obtain the complete illumination area and complete illumination intensity of the entire lighting area; a cross-lamp group uniformity judgment unit that sets the illumination uniformity judgment threshold, compares the light intensity values ​​of each point in the complete illumination area, and judges whether the uniformity requirements are met; when the requirements are not met, the cross-lamp group calibration unit calculates the degree of mutual influence between the lamp beads in different lamp groups, selects the cross-lamp group lamp bead pair with the greatest influence, adjusts the optical parameters of the lamp bead pair, and re-judges the uniformity; when it is still not uniform, it selects the second-best cross-lamp group lamp bead pair and repeats the parameter adjustment and uniformity judgment process;

[0036] Intra-group calibration module: includes: Intra-group uniformity determination unit, for each lamp group, based on intra-group illumination characteristic data, determines whether the intra-group illumination area meets the uniformity requirements; When the requirements are not met, the intra-group calibration unit takes the central lamp in the group as the initial adjustment object, adjusts its optical parameters and recalculates and judges the uniformity. When it still does not meet the requirements, it selects the surrounding lamps from the inside out and adjusts them step by step, with the central lamp as the center.

[0037] Compared with the prior art, the beneficial effects of the present invention are:

[0038] 1. This invention employs a three-level calculation method: independent modeling of individual LED beads, superposition within LED groups, and superposition across LED groups. This method quantifies the contribution of individual LED beads and LED groups to the overall illumination layer by layer, eliminating the superposition error of traditional overall calculation.

[0039] 2. This invention performs hierarchical calibration across lamp groups and within groups. When crossing lamp groups, high-impact lamp pairs are selected through coupling analysis for precise adjustment. Within a group, iterates from the inside out starting with the middle lamp, avoiding blind adjustment and forming a closed loop of calculation, judgment, and iteration to fundamentally solve local unevenness.

[0040] 3. The present invention refines the uniformity thresholds of the core and edge regions, taking into account the needs of different scenarios. After calibration, both the overall and local uniformity meet the standards, while reducing adjustment energy consumption and LED attenuation loss. Attached Figure Description

[0041] Figure 1 This is a schematic diagram of the steps of an LED intelligent calibration method based on multi-source sensor data according to the present invention;

[0042] Figure 2 This is a system structure diagram of an LED intelligent calibration system based on multi-source sensor data according to the present invention. Detailed Implementation

[0043] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0044] Example: Figures 1-2 As shown, the present invention provides a technical solution:

[0045] like Figure 1 As shown, this application provides an LED intelligent calibration method based on multi-source sensor data, including the following steps:

[0046] Step S100: Determine the installation location of all LED light groups and the number of LED beads in each group; collect the optical parameters of each LED bead and locate the relative position of each LED bead in its respective light group;

[0047] Specifically, the lamp beads are powered by their rated forward current. After the lamp beads have stabilized, the luminous flux, color temperature, color rendering index, color coordinates, and spectral distribution curve are collected using an integrating sphere and a spectrometer. The luminous angle of the lamp beads is adjusted using an angle photometer, and the luminous intensity is collected at each angle to generate the luminous intensity angle distribution curve of the lamp beads and determine the effective viewing angle.

[0048] A three-dimensional rectangular coordinate system is established with the top left corner of the light panel as the origin, the long side of the light panel as the X-axis, the short side as the Y-axis, and the perpendicular plane of the light panel as the Z-axis. The reference point needs to be calibrated by a laser displacement sensor. When the light group is a curved surface package, a curved surface coordinate system is established with the geometric center of the curved surface as the origin, the generatrix of the curved surface as the X-axis, the tangent direction as the Y-axis, and the normal direction as the Z-axis. This coordinate system is then linked to the Cartesian coordinate system using a coordinate transformation formula. The theoretical coordinates of each LED are extracted from the light group design drawings and entered into the database according to the unique identifier of each LED. For light panels without LEDs installed, images of the light panel are captured using a high-precision vision measuring instrument to identify the center position of the LED pads. These images are compared with the theoretical coordinates, the deviation value is calculated, and the corrected actual coordinates are linked to the LED identifier. For light groups with LEDs installed, a laser coordinate measuring machine is used to scan the center of the emitting surface of each LED point by point to directly collect the actual coordinates.

[0049] In one specific embodiment, two LED light groups (identified as G01 and G02) are set up, each containing 10 SMD2835 LED beads, with a rated forward current of 20mA and a package size of 2.8×3.5mm; G01 is a 300×100mm flat light board, and G02 is an arc-shaped light board with a radius of curvature of 500mm (unfolded size 300×100mm). The data acquisition equipment includes a HAAS-2000 integrating sphere with an accuracy of ±2%, an AvaSpec-ULS2048 spectrometer with a wavelength range of 380-780nm, a GM-1000 angle photometer with an angle step size of 5°, a laser displacement sensor with an accuracy of ±0.001mm, and an LK-G80 laser coordinate measuring machine with an accuracy of ±0.01mm.

[0050] After stabilizing at 20mA for 30 seconds, data was collected. G01-B01 had a luminous flux of 12.5 lm, a color temperature of 5000K, a color rendering index of 82, an effective viewing angle of 120°, and a peak luminous intensity of 3.8 cd; G01-B05 had a luminous flux of 12.3 lm, a color temperature of 5050K, a color rendering index of 81, an effective viewing angle of 120°, and a peak luminous intensity of 3.7 cd; G02-B06 had a luminous flux of 12.4 lm, a color temperature of 4950K, a color rendering index of 83, an effective viewing angle of 118°, and a peak luminous intensity of 3.9 cd. In the angular distribution test, G01-B01 had a luminous intensity of 3.8 cd at 0° (direction facing) and decreased to 1.9 cd at 60° (viewing angle boundary), consistent with the Lambertian distribution characteristics.

[0051] G01 uses its top-left corner as the origin (0,0,0), with the long side as the X-axis, the short side as the Y-axis, and the vertical light panel as the Z-axis, calibrated by a laser displacement sensor. G02 uses the geometric center of the curved surface as the origin (0,0,0), with the generatrix as the X-axis, the tangent as the Y-axis, and the normal as the Z-axis, and is associated with the Cartesian coordinate system through coordinate transformation. When G01 is not assembled, the theoretical coordinates of B01 are (50,50,0), and the visual measurement shows that the center deviation of the solder pads is ΔX=+0.01mm and ΔY=-0.008mm, with actual coordinates of (50.01,49.992,0). When G02 is assembled, the laser scan shows the center of the emitting surface of B06, with actual coordinates of (100.02,50.01,0.5).

[0052] Step S200: Based on the optical parameters of a single LED and its position within the lamp group, calculate the independent illumination area and illumination intensity of the LED through optical modeling; superimpose the independent illumination areas and illumination intensities of all LEDs within the same lamp group to obtain the overall illumination area and overall illumination intensity of the lamp group.

[0053] Specifically, the type of light source is determined based on the angular distribution curve of the luminous intensity of the LED beads; for a Lambertian light source, the Lambertian radiation model is applied. As a radiation model of a light source, in which... Peak luminous intensity The angle between the spatial point and the luminous axis. , To achieve an effective viewing angle; for non-Lambertian light sources, a radiation model of the light source is obtained by fitting experimental data using a polynomial; based on the spectral distribution curve of the LED chips, the luminous efficacy function is used. spectral radiant flux Converted to visible light flux, peak luminous intensity corrected The actual luminous intensity after spectral correction was obtained. ,in, For luminous flux, The wavelength of light;

[0054] Construct a distance attenuation model for indoor scenes, with attenuation factor d is the straight-line distance from a spatial point to the light-emitting center of the LED. For outdoor scenes, the atmospheric extinction coefficient is introduced. Attenuation factor ; Based on the viewing angle limitations of the LED beads, set an angle threshold. When spatial points When the light intensity is 0, it is determined that the point is not within the illumination range; when... At that time, the angle-dependent light intensity is calculated according to the light source radiation model;

[0055] With the geometric center of the light-emitting surface of the LED as the origin The luminous axis is Establish a local coordinate system for the LED beads; convert the coordinates of the illuminated surface in the LED group coordinate system to... By mapping the coordinates to the local coordinate system of the LED, the coordinates of the illuminated surface in the local system are obtained. ; with the light-emitting center of the LED bead As the vertex, the luminous axis As the axis, perspective Given the cone angle, construct the equation for the conical surface. The spatial grid cells within the conical surface constitute the theoretical illumination area. The intersection of the conical surface and the illuminated surface is calculated based on the actual illumination scene's illuminated area. The area enclosed by this intersection is the effective illumination area on the illuminated surface. Grid cells exceeding the actual installation environment boundary within the theoretical illumination area are removed to obtain the independent illumination area S.

[0056] Traverse the grid cells in S and determine whether each grid point can be illuminated by the LED. Specifically, determine whether the angle between the point and the LED's light-emitting axis exceeds the angle threshold or whether it is located at the LED's own position. If the conditions are met, the light intensity is 0. If not, combine the LED's light-emitting intensity at that angle and calculate the light intensity attenuation caused by distance based on the distance attenuation model to obtain the illumination intensity.

[0057] Furthermore, based on the maximum boundary of the independent illumination area of ​​all LED beads within the lamp group, the system expands outward to cover the weak illumination area of ​​edge LED beads, constructing a global grid for the lamp group encompassing the X, Y, and Z axes. Each cell of the global grid is traversed, and each cell is checked to see if it falls within the independent illumination area of ​​any LED bead within the lamp group. If a cell is contained within the independent illumination area of ​​at least one LED bead, its illumination status is updated to illuminated; otherwise, it remains unilluminated. All cells with an illuminated status are collected, and their coordinate boundaries constitute the overall illumination area of ​​the lamp group. All unilluminated cells are removed, forming a set of grids representing the overall illumination area of ​​the lamp group. The filtered illuminated grids are traversed to determine the region's bounding box. The contour grids of the region's edges are identified through the differences in illumination status between adjacent cells, forming the contour of the irregular region.

[0058] For each illuminated global grid cell, all LEDs in the lamp group are traversed, and LEDs that can effectively illuminate the grid are selected. The independent light intensity values ​​of all selected LEDs in the grid are accumulated to obtain the overall illumination intensity. When the light emission directions of LEDs in the lamp group block each other, the light intensity contribution of the blocked LEDs is removed from the blocked grid points. The blocking relationship is determined by the LED position coordinates and the size of the light-blocking structure.

[0059] In one specific embodiment, lamp group G01 (300×100mm flat light panel, containing 10 SMD2835 LEDs) was selected as the modeling object. An indoor office lighting scene was set, with the illuminated surface being a horizontal ground 2.5m above the light panel (ambient temperature 25℃, no significant airflow interference). Based on the data collected by S100, it was determined that all LEDs in G01 are Lambertian light sources with a peak luminous intensity range of 3.7-3.9cd and an effective viewing angle of 120°. An indoor scene distance attenuation model (without atmospheric extinction coefficient correction) was adopted, and the global grid of the lamp group was divided into 1cm steps. The grid range covered the X-axis 0-3.5m, Y-axis 0-1.2m, and Z-axis 2.3-2.7m (including the illuminated surface and 20cm space above and below), ensuring complete capture of the LED illumination range. Based on the spectral distribution curve of the LED beads (380-780nm, peak wavelength 450nm), after correction by the optical performance function, the actual luminous intensity I'0 of G01-B01 is 3.75cd, that of G01-B05 is 3.68cd, and that of G01-B10 (edge ​​LED beads) is 3.82cd.

[0060] Taking G01-B01 (actual coordinates 50.01, 49.992, 0) as an example, a local coordinate system is established (the center of the luminous surface is the origin, and the Z1 axis is perpendicular to the lamp panel and pointing downwards). After mapping the coordinates of the illuminated surface to the local system, Z1 = 2.5m. A conical surface is constructed according to a 120° perspective. The theoretical illumination area forms a circular outline on the illuminated surface. After removing the actual environmental boundaries (the office wall limits X ≤ 3.2m and Y ≤ 1.0m), the independent illumination area S is a circle with a diameter of 1.44m (the center coordinates correspond to X = 0 and Y = 0 in the local system, and X = 50.01cm, Y = 49.992cm, and Z = 2.5m in the global system). In the light intensity calculation, the light intensity at a distance of 2.5m from the center of the illuminated surface (directly facing the light-emitting axis of the LED) with an angle of 0° is 3.75cd × cos0° ÷ (2.5m)² = 0.6cd. At a point 0.72m from the center (viewpoint boundary) with an angle of 60°, the light intensity is 3.75cd × cos60° ÷ (2.5m)² = 0.15cd. Points beyond 1.44m with an angle exceeding 60° have a light intensity of 0. Similarly, the independent illumination area of ​​edge LEDs G01-B10 (actual coordinates 290.03, 50.02, 0) on the illuminated surface is a circle with a diameter of 1.44m. The center corresponds to a global coordinate of X = 290.03cm and Y = 50.02cm, and the edge overlaps with the G01-B01 illumination area by approximately 0.3m.

[0061] Based on the maximum boundary of the independent illumination area of ​​all LED beads (X0.1m-3.4m, Y0.05m-1.15m), the area is expanded outward by 10% (covering the weak illumination area of ​​the edge LED beads), finally determining the global grid range of the light group as X0-3.5m, Y0-1.2m, and Z2.3-2.7m. Traversing the global grid cells, it is determined that the "illuminated" grid must be contained within the independent area of ​​at least one LED bead. The final selected overall illumination area presents an irregular rectangle of 3.2m × 0.95m on the illuminated surface—X-axis boundary 0.2m-3.4m (excluding invalid grids outside the wall surface), Y-axis boundary 0.08m-1.03m. The edge contour of the area exhibits the characteristics of arc-shaped ends in the X direction and a gentle edge in the Y direction due to the arrangement of LED beads. There are no unilluminated grids in the core overlapping area (X0.5-3.0m, Y0.2-1.0m), and the continuity is good.

[0062] The light intensity was accumulated point by point on the "illuminated" grid of the illuminated surface. The core overlapping area (X1.5m, Y0.5m) was simultaneously illuminated by five LEDs: G01-B03, B04, B05, B06, and B07. The independent light intensities of a single LED at this point were 0.22cd, 0.25cd, 0.23cd, 0.24cd, and 0.21cd, respectively, and the total light intensity after superposition was 1.15cd. The average light intensity of the core area was 0.92cd, with a maximum value of 1.18cd (X1.8m, Y0.6m, 6 LEDs superimposed) and a minimum value of 0.75cd (X0.8m, Y0.3m, 3 LEDs superimposed). The edge area (X3.2m, Y0.5m) is illuminated only by two LEDs, G01-B09 and B10, with a superimposed light intensity of 0.32 cd. The average light intensity in the edge area is 0.28 cd, with a minimum of 0.21 cd (X3.4m, Y1.0m, illuminated only by B10). The spacing between the LEDs within the lamp assembly is 25mm, with no obvious light-blocking structure. Only a small amount of grid along the edge of the lamp panel (X3.3m, Y0.1m) is slightly obscured by the lamp panel frame. After removing the light intensity contribution from the obscured LED (B10), the light intensity at this point is corrected from 0.23 cd to 0.21 cd, which conforms to the actual illumination pattern.

[0063] The calculated illumination intensity of a single LED bead perfectly matches the Lambertian radiation model and the distance attenuation law. For example, the light intensity of G01-B05 at the center of the illuminated surface is 0.59 cd, which deviates from the theoretical calculation value by ≤2%. After the LED groups are superimposed, the coefficient of variation of light intensity in the core area is 0.12, and that in the edge area is 0.18. There is no obvious change in light intensity (the maximum difference between adjacent grids is 0.08 cd), which verifies the accuracy of the superposition calculation and provides reliable data support for subsequent uniformity determination.

[0064] Step S300: Based on the relative positions of each LED group, perform cross-group superposition calculation on the overall illumination area and intensity of all groups to obtain the complete illumination area and complete illumination intensity of the entire lighting area; set an illumination uniformity judgment threshold, compare the light intensity values ​​of each point in the complete illumination area, and determine whether the uniformity requirements are met; if not, calculate the degree of mutual influence between LED beads in different groups, select the cross-group LED bead pair with the greatest influence, adjust the optical parameters of the LED bead pair, and re-judge the uniformity; if still not uniform, select the second-best cross-group LED bead pair, and repeat the parameter adjustment and uniformity judgment process;

[0065] Specifically, based on the maximum boundary of the overall illumination area of ​​all light groups, the edge range is expanded to construct a three-dimensional grid covering the entire lighting scene; all illuminated grids are collected, and their boundaries constitute the complete illumination area; for each illuminated grid, all light groups that can illuminate it are selected, the light intensity of these light groups in the grid is accumulated, and updated to the complete illumination intensity; when there is occlusion between light groups, the light intensity contribution of the occluded light groups is removed.

[0066] Furthermore, after confirming that the overall lighting area did not meet the uniformity requirements, areas with light intensity differences exceeding the threshold were marked to clarify the calibration target. For the marked areas, the light intensity contribution of individual LEDs in different lamp groups was analyzed. Specifically, by simulating the changes in the optical parameters of individual LEDs, the influence of each LED on the light intensity of the areas covered by other lamp groups was obtained, and the mutual influence weight of each LED and LEDs across lamp groups was quantified. From all combinations of LEDs across lamp groups, the pair with the highest mutual influence weight was selected as the priority adjustment target. A nonlinear compensation algorithm was used to adjust the optical parameters of the pair of LEDs according to the degree of influence, ensuring that the adjustment range matched the light intensity deviation. Based on the adjusted LED parameters, the irradiance distribution of the entire lighting area was recalculated, and the uniformity threshold was compared again to determine whether it was uniform.

[0067] Furthermore, when the light intensity deviation remains uneven, newly added or unimproved light intensity deviation areas are marked to clarify the calibration target for this round. Based on the light intensity distribution data after the previous round of lamp parameter adjustment, a new coupling analysis is performed to update the mutual influence weights of all unadjusted or partially adjusted cross-lamp group lamp pairs, and the influence priority of the remaining lamp pairs is reordered. From the updated influence weight ranking, the second-best cross-lamp group lamp pair with the highest ranking is selected to ensure that this lamp pair is directly related to the currently unimproved light intensity deviation area. Using the nonlinear compensation algorithm, combined with the light intensity deviation amplitude marked in this round, the optical parameters of this second-best cross-lamp group lamp pair are adjusted. A uniformity re-check is performed, and the iteration is terminated when the light intensity deviation of the cross-coverage area between all lamp groups is lower than the uniformity threshold.

[0068] In one specific embodiment, lamp groups G01 (flat light panel, 300×100mm) and G02 (curved light panel, radius of curvature 500mm) are used. The two light groups are installed parallel to each other on the same horizontal ceiling, with a center-to-center distance of 1.8m and an installation height of 2.8m. The illuminated surface remains the horizontal ground 2.5m above the ceiling (i.e., 0.3m above the illuminated surface). The indoor lighting scene has no obvious obstructions, the atmospheric extinction coefficient is negligible, and the global three-dimensional mesh is divided at 1cm steps, covering the X-axis (0-5m), Y-axis (0-1.5m), and Z-axis (0.1-0.5m) (including the illuminated surface and a 20cm vertical space), ensuring complete capture of the area where the two light groups intersect. Uniformity criteria are set as follows: indoor office lighting intensity variation coefficient ≤ 0.15, maximum to minimum luminous intensity ratio ≤ 1.5:1.

[0069] Mapping the overall illumination data of G01 and G02 to the same global coordinate system, the complete illumination area presents an irregular rectangle of 4.8m×1.4m on the illuminated surface, with X-axis boundaries of 0.3m-5.1m and Y-axis boundaries of 0.12m-1.52m. The overlapping coverage area of ​​the two light groups is concentrated at 2.2m-3.0m on the X-axis and 0.2m-1.3m on the Y-axis (approximately 0.64㎡). The initial light intensity distribution after superposition shows that the average light intensity in the core area of ​​the intersection is 1.32 cd, the maximum value is 1.85 cd (X2.6m, Y0.7m, 6 LEDs from both groups are illuminating the same area), and the minimum value is 0.98 cd (X4.5m, Y1.4m, only the edge LEDs of G02 are illuminating the same area). The overall coefficient of variation is 0.21, and the ratio of maximum to minimum light intensity is 1.89:1, both of which exceed the set threshold. Therefore, the initial uniformity is not up to standard. The intersection area X2.5m-2.7m and Y0.6m-0.8m are marked as bright spots (light intensity exceeding 1.6 cd), and the edge area X4.2m-4.8m and Y1.2m-1.4m are marked as dark areas (light intensity below 1.1 cd).

[0070] For the marked bright spots and dark areas, a cross-lamp group coupling analysis was conducted—simulating the change of ±5% in the luminous intensity of a single lamp bead to monitor its impact on the light intensity of the intersection and edge areas. The results showed that G01-B06 (actual coordinates 180.02, 50.03, 0, peak luminous intensity 3.88 cd) and G02-B05 (actual coordinates 100.02, 50.01, 0.5, peak luminous intensity 3.92 cd) had the highest mutual influence weight (0.86). Both are located directly above the intersection of the two lamp groups, contributing 42% to the light intensity of the bright spot area. A nonlinear compensation algorithm was used to fine-tune the actual luminous intensity of G01-B06 from 3.88 cd to 3.65 cd (attenuation of 6%), and G02-B05 from 3.92 cd to 3.70 cd (attenuation of 5.6%), with the adjustment range precisely matching the light intensity deviation of the bright spot area (0.25 cd). After recalculating the cross-group superimposed light intensity, the peak brightness of the bright spot in the cross region decreased to 1.52 cd, the average light intensity in the core region was 1.28 cd, the overall coefficient of variation decreased to 0.17, and the maximum-to-minimum light intensity ratio was 1.63:1. Although this was a significant improvement over the initial state, it still did not fully meet the threshold requirements and further iterative calibration was needed.

[0071] Based on the light intensity distribution data after the first adjustment, the influence weight of the LED beads across the lamp group was updated. G01-B06 and G02-B05, which had been adjusted, were removed. Among the remaining LED bead pairs, G01-B07 (actual coordinates 210.04, 50.02, 0, peak luminous intensity 3.85cd) and G02-B04 (actual coordinates 70.01, 50.03, 0.5, peak luminous intensity 3.89cd) had the highest influence weight (0.78). They also corresponded to the secondary bright spots in the cross area X2.4m-2.8m and Y0.5m-0.9m and the dark area in the edge area X4.3m-4.7m. Using the nonlinear compensation algorithm, the actual luminous intensity of G01-B07 was fine-tuned from 3.85 cd to 3.72 cd (a 3.4% decrease). Simultaneously, for the edge dark areas, the actual luminous intensity of G02-B09 (edge ​​LEDs, peak luminous intensity 3.81 cd) was fine-tuned from 3.81 cd to 3.95 cd (a 3.7% increase), balancing the light intensity in the dark areas. After recalculation, the average luminous intensity in the core area of ​​the fully illuminated region was 1.25 cd, the maximum was 1.48 cd, and the minimum was 1.05 cd. The luminous intensity deviation in the intersection area was all below 0.12 cd, the overall coefficient of variation decreased to 0.13, and the maximum-to-minimum luminous intensity ratio was 1.41:1, all meeting the set uniformity threshold. The marked bright spots and dark areas were completely eliminated, and the luminous intensity transition in the area where the two LED groups overlapped was smooth, terminating the cross-LED group iterative calibration.

[0072] Ten feature points (including three points in the cross-core area, four points in the single-lamp group coverage area, and three points in the edge area) were randomly selected within the complete illumination area for light intensity verification. The deviation between the measured and calculated values ​​was ≤±3%. Among them, the light intensity at X2.6m and Y0.7m in the cross-core area was 1.45cd, and the light intensity at X4.5m and Y1.3m in the edge area was 1.08cd, which met the uniformity requirements. The entire calibration process only adjusted the optical parameters of four lamps, and the adjustment range was controlled within ±6%, which did not exceed the rated operating range of the lamps, ensuring the stability and energy efficiency of the lighting system.

[0073] Step S400: For each lamp group, based on the illumination characteristic data within the group, determine whether the illumination area within the group meets the uniformity requirements; if not, take the central lamp bead within the group as the initial adjustment object, adjust its optical parameters, recalculate and judge the uniformity; if it still does not meet the standard, select the surrounding lamp beads from the inside out and adjust them step by step, with the central lamp bead as the center.

[0074] Specifically, the system retrieves the superimposed light intensity dataset and effective lighting area boundaries of the target light group, removes isolated grids with abnormal light intensity, and clarifies the effective judgment area of ​​the core lighting. It sets uniformity judgment criteria based on scene requirements, dividing the area into sub-regions according to function and setting corresponding thresholds if necessary. It extracts the light intensity values ​​of all grids within the effective judgment area, calculates the maximum, minimum, and average light intensity values, as well as statistics reflecting the degree of dispersion, forming the core data required for judgment. It calculates the actual uniformity index according to the set criteria and compares it with the threshold. When all regional indices meet the criteria and no continuous grid light intensity deviation exceeds the threshold, the uniformity requirement is satisfied; otherwise, it is not satisfied.

[0075] Furthermore, after confirming that the illumination uniformity within the lamp group is substandard, the problem area is located by using the light intensity distribution data within the group. Combined with the lamp installation position map within the lamp group, the central lamp in the group is identified as the initial adjustment target. An adaptation algorithm is used to adjust the optical parameters of the initial adjustment target. Based on the adjusted parameters, the superimposed illumination intensity of all lamps in the group is recalculated and compared with the uniformity judgment threshold. When the threshold is met, the calibration within the group ends. If the threshold is still not met, adjacent lamps are selected as new adjustment targets, centered on the central lamp, in an order from the inside out. The process of parameter adjustment, superimposed light intensity recalculation, and uniformity judgment is repeated until the uniformity within the group is met.

[0076] In one specific embodiment, lamp group G02 (curved light panel, radius of curvature 500mm, containing 10 LEDs) is selected. Following the indoor office lighting scenario, the uniformity judgment criteria within the group are set as follows: the coefficient of variation of the core lighting area (Y-axis 0.2-1.0m) ≤ 0.15, and the maximum to minimum light intensity ratio ≤ 1.5:1; the effective judgment area excludes grids with edge light intensity lower than 10% of the average light intensity, focusing on the core area (X-axis 0.5-3.0m, Y-axis 0.1-1.1m), with a grid step size of 1cm. The superimposed light intensity data within group G02 is retrieved; the core area light intensity ranges from 0.68-1.25cd, with an average light intensity of 0.92cd.

[0077] The luminous intensity statistics of the core area were calculated. The maximum value was 1.25 cd (X1.5m, Y0.6m, directly below the central LED), and the minimum value was 0.68 cd (X2.8m, Y0.9m, the area covered by edge LEDs). The coefficient of variation was 0.18, and the maximum-to-minimum luminous intensity ratio was 1.84:1, all exceeding the threshold, indicating that the uniformity within the group was not up to standard. The problem area was located by using the luminous intensity distribution map: the central area (X1.2-1.8m, Y0.4-0.8m) was a bright spot (luminous intensity ≥ 1.1 cd), and the edge area (X2.5-3.0m, Y0.8-1.0m) was a dark area (luminous intensity ≤ 0.75 cd). Combined with the LED position map, the central LEDs G02-B05 (actual coordinates 100.02, 50.01, 0.5, peak luminous intensity 3.92 cd) were determined to be the initial adjustment targets.

[0078] The optical parameters of G02-B05 were fine-tuned using an adaptive algorithm, reducing its actual luminous intensity from 3.92 cd to 3.70 cd (a decrease of 5.6%), and the superimposed luminous intensity within the group was recalculated. After adjustment, the average luminous intensity in the core area was 0.89 cd, the maximum was 1.12 cd, and the minimum was 0.72 cd, with the coefficient of variation decreasing to 0.16. The ratio of maximum to minimum luminous intensity was 1.56:1, which is close to the threshold but still not up to standard, requiring further iterative adjustment.

[0079] Centered on G02-B05, adjacent LEDs G02-B04 (X0.7m, Y0.5m) and G02-B06 (X2.3m, Y0.6m) were selected as new adjustment targets, arranged from the inside out. The luminous intensity of G02-B04 was fine-tuned from 3.89cd to 3.75cd (attenuation of 3.6%), and that of G02-B06 was fine-tuned from 3.85cd to 3.78cd (attenuation of 1.8%), balancing the light intensity of the central bright spot and the edge dark area. After recalculation, the core area light intensity ranged from 0.75 to 1.10cd, with an average light intensity of 0.90cd, a coefficient of variation of 0.13, and a maximum-to-minimum light intensity ratio of 1.47:1, all meeting the judgment criteria. The uniformity within the group was satisfactory, and the adjustment was terminated.

[0080] like Figure 2 As shown, this application provides an LED intelligent calibration system based on multi-source sensor data, comprising:

[0081] Data acquisition module: includes: a location information acquisition unit to determine the installation location of all LED light groups and the number of LED beads in each group; and an optical parameter acquisition unit to acquire the optical parameters of each LED bead and locate the relative position of each LED bead in its respective light group.

[0082] Illumination characteristic modeling and calculation module: including: single lamp bead illumination modeling unit, which calculates the independent illumination area and illumination intensity of a single lamp bead based on its optical parameters and position within the lamp group; and lamp group superposition calculation unit, which superimposes the independent illumination areas and illumination intensities of all lamp beads within the same lamp group to obtain the overall illumination area and overall illumination intensity of the lamp group.

[0083] Cross-lamp group calibration module: includes: a cross-lamp group superposition calculation unit that, based on the relative positions of each LED lamp group, performs cross-group superposition calculation of the overall illumination area and intensity of all lamp groups to obtain the complete illumination area and complete illumination intensity of the entire lighting area; a cross-lamp group uniformity judgment unit that sets the illumination uniformity judgment threshold, compares the light intensity values ​​of each point in the complete illumination area, and judges whether the uniformity requirements are met; when the requirements are not met, the cross-lamp group calibration unit calculates the degree of mutual influence between the lamp beads in different lamp groups, selects the cross-lamp group lamp bead pair with the greatest influence, adjusts the optical parameters of the lamp bead pair, and re-judges the uniformity; when it is still not uniform, it selects the second-best cross-lamp group lamp bead pair and repeats the parameter adjustment and uniformity judgment process;

[0084] Intra-group calibration module: includes: Intra-group uniformity determination unit, for each lamp group, based on intra-group illumination characteristic data, determines whether the intra-group illumination area meets the uniformity requirements; When the requirements are not met, the intra-group calibration unit takes the central lamp in the group as the initial adjustment object, adjusts its optical parameters and recalculates and judges the uniformity. When it still does not meet the requirements, it selects the surrounding lamps from the inside out and adjusts them step by step, with the central lamp as the center.

[0085] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A smart LED calibration method based on multi-source sensor data, characterized in that, Includes the following steps: Determine the installation location of all LED light groups and the number of LED beads in each group; Collect the optical parameters of each LED bead and locate the relative position of each LED bead in its respective lamp group; Based on the optical parameters of a single LED and its position within the lamp assembly, the independent illumination area and illumination intensity of the LED are calculated through optical modeling. The individual illumination areas and illumination intensities of all lamp beads within the same lamp group are superimposed and calculated to obtain the overall illumination area and overall illumination intensity of the lamp group. Based on the relative positions of each LED group, the overall illumination area and intensity of all groups are superimposed across groups to obtain the complete illumination area and intensity of the entire lighting area. An illumination uniformity judgment threshold is set, and the light intensity values ​​at each point in the complete illumination area are compared to determine whether the uniformity requirements are met. If not, the degree of mutual influence between LED beads in different groups is calculated, and the cross-group LED bead pair with the greatest influence is selected. The optical parameters of the LED bead pair are adjusted, and the uniformity is re-judged. If it is still not uniform, the second-best cross-group LED bead pair is selected, and the parameter adjustment and uniformity judgment process is repeated. For each lamp group, based on the illumination characteristic data within the group, it is determined whether the illumination area within the group meets the uniformity requirements. If it does not meet the requirements, the central lamp bead within the group is taken as the initial adjustment target. Its optical parameters are adjusted and the uniformity is recalculated and judged. If it still does not meet the requirements, the surrounding lamp beads are selected and adjusted step by step from the inside out, with the central lamp bead as the center.

2. The LED intelligent calibration method based on multi-source sensor data according to claim 1, characterized in that, The process of collecting the optical parameters of each LED bead and locating the relative position of each LED bead within its respective lamp group includes: Power the LEDs with the rated forward current. After the LEDs are stable, collect the luminous flux, color temperature, color rendering index, color coordinates and spectral distribution curves using an integrating sphere and a spectrometer. Adjust the LED emission angle using an angle photometer, collect the luminous intensity at each angle, generate the LED luminous intensity angle distribution curve, and determine the effective viewing angle. A three-dimensional rectangular coordinate system is established with the top left corner of the light panel as the origin, the long side of the light panel as the X-axis, the short side as the Y-axis, and the perpendicular plane of the light panel as the Z-axis. The reference point needs to be calibrated by a laser displacement sensor. When the light group is a curved surface package, a curved surface coordinate system is established with the geometric center of the curved surface as the origin, the generatrix of the curved surface as the X-axis, the tangent direction as the Y-axis, and the normal direction as the Z-axis. This coordinate system is then linked to the Cartesian coordinate system using a coordinate transformation formula. The theoretical coordinates of each LED are extracted from the light group design drawings and entered into the database according to the unique identifier of each LED. For light panels without LEDs installed, images of the light panel are captured using a high-precision vision measuring instrument to identify the center position of the LED pads. These images are compared with the theoretical coordinates, the deviation value is calculated, and the corrected actual coordinates are linked to the LED identifier. For light groups with LEDs installed, a laser coordinate measuring machine is used to scan the center of the emitting surface of each LED point by point to directly collect the actual coordinates.

3. The LED intelligent calibration method based on multi-source sensor data according to claim 2, characterized in that, The calculation of the independent illumination area and illumination intensity of a single LED bead based on its optical parameters and position within the lamp assembly, through optical modeling, includes: The type of light source is determined based on the angular distribution curve of the luminous intensity of the LED; for a Lambertian light source, the Lambertian radiation model is applied. As a radiation model of a light source, in which... Peak luminous intensity The angle between the spatial point and the luminous axis. , To achieve an effective viewing angle; for non-Lambertian light sources, a radiation model of the light source is obtained by fitting experimental data using a polynomial; based on the spectral distribution curve of the LED chips, the luminous efficacy function is used. spectral radiant flux Converted to visible light flux, peak luminous intensity corrected The actual luminous intensity after spectral correction was obtained. ,in, For luminous flux, The wavelength of light; Construct a distance attenuation model for indoor scenes, with attenuation factor d is the straight-line distance from a spatial point to the light-emitting center of the LED. For outdoor scenes, the atmospheric extinction coefficient is introduced. Attenuation factor ; Based on the viewing angle limitations of the LED beads, set an angle threshold. When spatial points When the light intensity is 0, it is determined that the point is not within the illumination range; when... At that time, the angle-dependent light intensity is calculated according to the light source radiation model; With the geometric center of the light-emitting surface of the LED as the origin The light-emitting axis is Establish a local coordinate system for the LED beads; convert the coordinates of the illuminated surface in the LED group coordinate system to... By mapping the coordinates to the local coordinate system of the LED, the coordinates of the illuminated surface in the local system are obtained. ; with the light-emitting center of the LED bead As the vertex, the luminous axis As the axis, perspective Construct the equation of the conical surface for the cone angle. The spatial grid cells within the conical surface constitute the theoretical illumination area. The intersection of the conical surface and the illuminated surface is calculated based on the actual illumination scene's illuminated area. The area enclosed by this intersection is the effective illumination area on the illuminated surface. Grid cells exceeding the actual installation environment boundary within the theoretical illumination area are removed to obtain the independent illumination area S. Traverse the grid cells in S and determine whether each grid point can be illuminated by the LED. Specifically, determine whether the angle between the point and the LED's light-emitting axis exceeds the angle threshold or whether it is located at the LED's own position. If the conditions are met, the light intensity is 0. If not, combine the LED's light-emitting intensity at that angle and calculate the light intensity attenuation caused by distance based on the distance attenuation model to obtain the illumination intensity.

4. The LED intelligent calibration method based on multi-source sensor data according to claim 1, characterized in that, The calculation of the individual illumination areas and illumination intensities of all lamps within the same lamp group, superimposed to obtain the overall illumination area and overall illumination intensity of the lamp group, includes: Based on the maximum boundary of the independent illumination area of ​​all LEDs within the light group, a global grid of the light group is constructed, extending outward to cover the weak illumination area of ​​the edge LEDs. This grid encompasses the X, Y, and Z axes. Each cell of the global grid is traversed, and each cell is checked to see if it falls within the independent illumination area of ​​any LED within the light group. If a cell is contained within the independent illumination area of ​​at least one LED, its illumination status is updated to "illuminated"; otherwise, it remains "unilluminated." All cells with an "illuminated" illumination status are collected, and their coordinate boundaries constitute the overall illumination area of ​​the light group. All unilluminated cells are removed, forming a set of cells representing the overall illumination area of ​​the light group. The filtered illuminated cells are traversed to determine the region's bounding box. By analyzing the differences in illumination status between adjacent cells, the contour grid of the region's edge is identified, forming the contour of the irregular region. For each illuminated global grid cell, all LEDs in the lamp group are traversed, and LEDs that can effectively illuminate the grid are selected. The independent light intensity values ​​of all selected LEDs in the grid are accumulated to obtain the overall illumination intensity. When the light emission directions of LEDs in the lamp group block each other, the light intensity contribution of the blocked LEDs is removed from the blocked grid points. The blocking relationship is determined by the LED position coordinates and the size of the light-blocking structure.

5. The LED intelligent calibration method based on multi-source sensor data according to claim 1, characterized in that, Based on the relative positions of each LED light group, the overall illumination area and intensity of all light groups are calculated by superimposing the data across groups to obtain the complete illumination area and complete illumination intensity of the entire lighting area, including: Based on the maximum boundary of the overall illumination area of ​​all light groups, the edge range is expanded to construct a three-dimensional mesh covering the entire lighting scene; all illuminated meshes are collected, and their boundaries constitute the complete illumination area; for each illuminated mesh, all light groups that can illuminate it are selected, the light intensity of these light groups in the mesh is accumulated, and updated to the complete illumination intensity; when there is occlusion between light groups, the light intensity contribution of the occluded light groups is removed.

6. The LED intelligent calibration method based on multi-source sensor data according to claim 1, characterized in that, When the condition is not met, the degree of mutual influence between LED beads in different lamp groups is calculated, the cross-lamp group LED bead pair with the greatest influence is selected, the optical parameters of the LED bead pair are adjusted, and the uniformity is reassessed, including: After confirming that the overall lighting area does not meet the uniformity requirements, areas with light intensity differences exceeding the threshold are marked to clarify the calibration target. For the marked areas, the light intensity contribution of individual LEDs in different lamp groups is analyzed. Specifically, by simulating the changes in the optical parameters of individual LEDs, the influence of each LED on the light intensity of the areas covered by other lamp groups is obtained, and the mutual influence weight of each LED and LEDs across lamp groups is quantified. From all combinations of LEDs across lamp groups, the pair with the highest mutual influence weight is selected as the priority adjustment target. A nonlinear compensation algorithm is used to adjust the optical parameters of the pair of LEDs according to the degree of influence, ensuring that the adjustment range matches the light intensity deviation. Based on the adjusted LED parameters, the irradiance distribution of the entire lighting area is recalculated, and the uniformity threshold is compared again to determine whether it is uniform.

7. The LED intelligent calibration method based on multi-source sensor data according to claim 1, characterized in that, When the distribution is still uneven, the process of selecting the second-best cross-lamp group LED bead pairs and repeating the parameter adjustment and uniformity judgment process includes: When the light intensity deviation remains uneven, mark the newly added or unimproved light intensity deviation areas to clarify the calibration target for this round. Based on the light intensity distribution data after the previous round of lamp parameter adjustment, perform coupling analysis again, update the mutual influence weights of all unadjusted or partially adjusted cross-lamp group lamp pairs, and reorder the influence priority of the remaining lamp pairs. From the updated influence weight ranking, select the second-best cross-lamp group lamp pair with the highest ranking to ensure that this lamp pair is directly related to the currently unimproved light intensity deviation area. Using the nonlinear compensation algorithm, combined with the light intensity deviation amplitude marked in this round, adjust the optical parameters of this second-best cross-lamp group lamp pair. Perform a uniformity recheck, and terminate the iteration when the light intensity deviation of the cross-coverage area between all lamp groups is lower than the uniformity threshold.

8. The LED intelligent calibration method based on multi-source sensor data according to claim 1, characterized in that, For each lamp group, based on the group's illumination characteristic data, determining whether the illumination area within the group meets the uniformity requirements includes: Retrieve the superimposed light intensity dataset and effective lighting area boundary of the target light group, remove isolated grids with abnormal light intensity, and clarify the effective judgment area of ​​the core lighting; set uniformity judgment criteria according to scene requirements, and divide the area into sub-regions according to function and set corresponding thresholds if the area needs to be subdivided; extract the light intensity values ​​of all grids in the effective judgment area, calculate the maximum, minimum, and average light intensity values ​​and the statistical quantity reflecting the degree of dispersion, and form the core data required for judgment; calculate the actual uniformity index according to the set criteria and compare it with the threshold; when all regional indices meet the criteria and no continuous grid light intensity deviation exceeds the threshold, the uniformity requirement is judged to be met; otherwise, the uniformity requirement is not met.

9. The LED intelligent calibration method based on multi-source sensor data according to claim 1, characterized in that, When the condition is not met, the central LED in the group is used as the initial adjustment target. Its optical parameters are adjusted, and the uniformity is recalculated and judged. If the condition is still not met, the surrounding LEDs are selected and adjusted step by step from the center outwards, including: After confirming that the illumination uniformity within the lamp group is substandard, the problem area is located by using the light intensity distribution data within the group. Combined with the lamp installation position map within the lamp group, the central lamp in the group is identified as the initial adjustment target. The optical parameters of the initial adjustment target are adjusted, and the superimposed illumination intensity of all lamps in the group is recalculated based on the adjusted parameters. The result is compared with the uniformity judgment threshold. When the threshold is met, the calibration within the group ends. If the threshold is still not met, adjacent lamps are selected as new adjustment targets, centered on the central lamp, in an order from the inside out. The process of parameter adjustment, superimposed light intensity recalculation, and uniformity judgment is repeated until the uniformity within the group meets the standard.

10. An LED intelligent calibration system based on multi-source sensor data, using the LED intelligent calibration method based on multi-source sensor data according to any one of claims 1-9, characterized in that, include: Data acquisition module: includes: a location information acquisition unit to determine the installation location of all LED light groups and the number of LED beads in each group; and an optical parameter acquisition unit to acquire the optical parameters of each LED bead and locate the relative position of each LED bead in its respective light group. Illumination characteristic modeling and calculation module: including: single lamp bead illumination modeling unit, which calculates the independent illumination area and illumination intensity of a single lamp bead based on its optical parameters and position within the lamp group; and lamp group superposition calculation unit, which superimposes the independent illumination areas and illumination intensities of all lamp beads within the same lamp group to obtain the overall illumination area and overall illumination intensity of the lamp group. Cross-lamp group calibration module: includes: a cross-lamp group superposition calculation unit that, based on the relative positions of each LED lamp group, performs cross-group superposition calculation of the overall illumination area and intensity of all lamp groups to obtain the complete illumination area and complete illumination intensity of the entire lighting area; a cross-lamp group uniformity judgment unit that sets the illumination uniformity judgment threshold, compares the light intensity values ​​of each point in the complete illumination area, and judges whether the uniformity requirements are met; when the requirements are not met, the cross-lamp group calibration unit calculates the degree of mutual influence between the lamp beads in different lamp groups, selects the cross-lamp group lamp bead pair with the greatest influence, adjusts the optical parameters of the lamp bead pair, and re-judges the uniformity; when it is still not uniform, it selects the second-best cross-lamp group lamp bead pair and repeats the parameter adjustment and uniformity judgment process; Intra-group calibration module: includes: Intra-group uniformity determination unit, for each lamp group, based on intra-group illumination characteristic data, determines whether the intra-group illumination area meets the uniformity requirements; When the requirements are not met, the intra-group calibration unit takes the central lamp in the group as the initial adjustment object, adjusts its optical parameters and recalculates and judges the uniformity. When it still does not meet the requirements, it selects the surrounding lamps from the inside out and adjusts them step by step, with the central lamp as the center.

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