A LED light source incoming inspection method and system based on adaptive compensation

Abstract

The application provides an LED light source incoming material detection method and system based on adaptive compensation, which comprises the following steps: obtaining the light signal of the target LED light source through a spectrum acquisition device; performing light splitting and photoelectric conversion processing on the light signal to obtain corresponding spectral electrical signal data; extracting multiple spectral characteristic parameters by using a spectral analysis algorithm based on the spectral electrical signal data, and constructing spectral feature data; determining the current detection state based on the spectral feature data and environmental state parameters; determining the corresponding compensation parameters based on the current detection state, correcting the spectral data based on the compensation parameters to obtain compensated spectral data, and recalculating the spectral feature data based on the compensated spectral data; determining the detection result based on the compensated spectral data, and outputting the detection result. The application can reduce system error and environmental influence, and improve the accuracy and stability of LED light source incoming material detection.

Description

Technical Field

[0001] This application relates to the field of spectral detection, and in particular to a method and system for inspecting incoming LED light sources based on adaptive compensation. Background Technology

[0002] Existing LED light source inspection systems still have certain technical shortcomings in practical applications, making it difficult to simultaneously meet the requirements of incoming material inspection for inspection accuracy, inspection efficiency, and multi-parameter analysis. Specific problems are as follows:

[0003] The detection results are easily affected by ambient light. During the optical signal acquisition process, external ambient light will be superimposed on the target spectral signal, causing deviation in the spectral data and thus affecting the accuracy of the detection results.

[0004] The lack of a comprehensive analysis mechanism for environmental conditions and reference spectra during data processing makes it difficult to effectively correct the collected spectral data, resulting in poor stability of the detection results under different detection environments.

[0005] In the process of multi-parameter detection, the detection system relies on multiple detection modules or multiple measurements, and lacks the ability to conduct comprehensive analysis based on unified spectral data, resulting in low detection efficiency.

[0006] There is a lack of efficient linkage mechanism between spectral data processing and result output, and there is a delay in data analysis and result generation, which makes it difficult to meet the real-time requirements of incoming material inspection.

[0007] Existing testing systems have limited adaptability to LED light sources of different specifications and lack a unified data processing and correction mechanism during the testing process, resulting in poor consistency of test results under different size or power conditions.

[0008] Therefore, there is an urgent need for an incoming LED light source inspection method and system based on adaptive compensation. Summary of the Invention

[0009] This application provides an LED light source incoming material inspection method and system based on adaptive compensation to solve the problems of the prior art.

[0010] This application provides a method for inspecting incoming LED light sources based on adaptive compensation, including:

[0011] Spectral acquisition: acquiring the light signal of the target LED light source through a spectral acquisition device;

[0012] Spectroscopic and photoelectric conversion processing: The optical signal is subjected to spectral and photoelectric conversion processing to obtain the corresponding spectral electrical signal data;

[0013] Data analysis involves using spectral analysis algorithms based on the spectral electrical signal data to extract various spectral characteristic parameters and construct spectral feature data.

[0014] The detection status is determined based on spectral feature data and environmental state parameters.

[0015] Adaptive compensation involves determining corresponding compensation parameters based on the current detection state, correcting the spectral data based on the compensation parameters to obtain compensated spectral data, and recalculating spectral feature data based on the compensated spectral data.

[0016] The results are output, and the detection results are determined based on the compensated spectral data.

[0017] In one possible design, the current detection state is determined based on the difference features between the spectral feature data and the reference spectral data.

[0018] In one possible design, determining the current detection state includes:

[0019] The difference features are compared with a preset difference threshold to obtain the difference comparison result;

[0020] The environmental state parameters are compared with a preset environmental range to obtain the environmental state comparison result.

[0021] The current detection status is determined based on the difference comparison results and the environmental status comparison results.

[0022] In one possible design, the reference spectral data is standard spectral data acquired and updated via a standard light source interface.

[0023] In one possible design, the environmental state parameters include ambient temperature, which is acquired by a temperature sensor.

[0024] In one possible design, the compensation parameters are determined based on a preset mapping relationship between a compensation strategy and the detection state;

[0025] For different detection states, corresponding compensation strategies are preset. Each compensation strategy includes compensation parameters for correcting spectral data. After determining the current detection state, a compensation strategy corresponding to the current detection state is selected from the preset compensation strategies, and the corresponding compensation parameters are extracted.

[0026] In one possible design, the compensation parameters include at least one of a gain coefficient for correcting spectral data, a zero-point offset, or a compensation amount based on ambient temperature.

[0027] In one possible design, the spectral acquisition device includes an integrating sphere and an optical fiber probe;

[0028] The integrating sphere is used to homogenize the light signal emitted by the target LED light source;

[0029] The fiber optic probe is positioned at the light outlet of the integrating sphere to receive the optical signal processed by the integrating sphere and transmit the optical signal to the beam splitting and photoelectric conversion processing unit.

[0030] This application also provides an LED light source incoming material inspection system based on adaptive compensation, including:

[0031] The spectrum acquisition module acquires the light signal of the target LED light source through a spectrum acquisition device.

[0032] The spectral splitting and photoelectric conversion processing module performs spectral splitting and photoelectric conversion processing on the optical signal to obtain the corresponding spectral electrical signal data.

[0033] The data analysis module uses spectral analysis algorithms to extract various spectral characteristic parameters based on the spectral electrical signal data, and constructs spectral feature data.

[0034] The detection status determination module determines the current detection status based on spectral feature data and environmental status parameters.

[0035] The adaptive compensation module determines the corresponding compensation parameters based on the current detection state, and performs correction processing on the spectral data based on the compensation parameters to obtain compensated spectral data, and recalculates the spectral feature data based on the compensated spectral data.

[0036] The result output module determines the detection result based on the compensated spectral data and outputs the detection result.

[0037] Compared with the prior art, this application has the following beneficial effects:

[0038] This application provides an LED light source incoming material inspection method and system based on adaptive compensation. The method performs difference analysis and detection status determination on spectral data, and corrects the spectral data based on compensation parameters to achieve dynamic correction of spectral feature data, thereby improving the accuracy and stability of the detection results and reducing the impact of environmental factors on the detection results.

[0039] Furthermore, this application constructs differential features by introducing reference spectral data and determines the detection state by combining environmental state parameters. At the same time, it generates compensation parameters based on a compensation strategy to adaptively correct the spectral data, thereby achieving consistency of detection results under different detection conditions and improving the reliability and adaptability of multi-parameter detection. Attached Figure Description

[0040] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0041] Figure 1 This is a schematic flowchart illustrating an LED light source incoming material inspection method based on adaptive compensation according to an example embodiment of this application;

[0042] Figure 2 This is a schematic diagram of the structure of an integrating sphere according to an example embodiment of this application;

[0043] Figure 3 This is a schematic diagram of the structure of a CCD detector according to an example embodiment of this application;

[0044] Figure 4 This is a schematic diagram of the structure of an LED light source incoming material inspection system based on adaptive compensation, according to an example embodiment of this application.

[0045] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0046] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0047] This embodiment proposes an LED light source incoming material detection method and system based on adaptive compensation, which is applicable to the incoming material quality detection of LED light sources in various optical water quality analysis equipment. Specifically, it includes the detection of infrared LED light sources for turbidity, the detection of visible light LED light sources for residual chlorine in DPD colorimetric method, and the detection of incoming materials for dissolved oxygen detection using fluorescence method. It can also be extended to other water quality analysis equipment such as COD detection, ammonia nitrogen detection, and heavy metal detection, as well as LED light source incoming material detection scenarios in fields such as industrial process analysis, environmental monitoring, and laboratory optical detection.

[0048] This application constructs difference features based on spectral feature data and reference spectral data, and determines the detection state by combining environmental state parameters. Based on this, corresponding compensation parameters are generated according to the detection state, and the spectral data is corrected based on the compensation parameters to obtain compensated spectral data. The spectral feature data is then recalculated based on the compensated spectral data, thereby forming an adaptive compensation processing chain of "difference feature construction - detection state determination - compensation parameter generation - spectral data correction - feature reconstruction" to achieve dynamic correction of spectral detection results.

[0049] Figure 1 This is a schematic flowchart illustrating an adaptive compensation-based LED light source incoming material inspection method according to an example embodiment of this application. Figure 1 As shown, the LED light source incoming material inspection method based on adaptive compensation includes:

[0050] Step S101: Spectral acquisition. The light signal of the target LED light source is acquired through a spectral acquisition device.

[0051] In this step, the spectral acquisition device includes an integrating sphere and an optical fiber probe;

[0052] The integrating sphere, as the core of optical signal collection, is used to homogenize the optical signal emitted by the target LED light source and eliminate the influence of the light source's non-uniformity on the detection results.

[0053] The fiber optic probe is positioned at the light outlet of the integrating sphere to receive the optical signal processed by the integrating sphere and transmit the optical signal to the beam splitting and photoelectric conversion processing unit.

[0054] In one embodiment, the aperture size of the light inlet is adjusted by an aperture adjuster to accommodate target LED light sources of different sizes. The target LED light source is then placed at the light inlet. The light emitted by the target LED light source enters the integrating sphere and undergoes multiple diffuse reflections to form a uniform light intensity distribution, thereby eliminating the influence of uneven light emission and forming a stable optical signal. The optical signal is output from the integrating sphere's exit port and transmitted to the beam splitting and photoelectric conversion processing unit via a fiber optic probe.

[0055] The spectral acquisition device also includes an ambient light shield, which is used to physically isolate external ambient light, reduce the interference of ambient light on optical signal acquisition from the source, and improve measurement accuracy.

[0056] It should be noted that the integrating sphere structure used in this application is as follows: Figure 2As shown, this integrating sphere measures luminous flux based on the integrating sphere spectrophotometry method. The integrating sphere is a spherical cavity with its inner wall coated with a uniform white diffuse reflective layer of barium sulfate or magnesium oxide (optionally, a high-performance Spectraflect diffuse reflective coating). The target LED light source is placed inside the cavity, and a diffuse screen is used to prevent the target LED light source from directly shining on the detector. After the light radiation emitted by the target LED light source is reflected multiple times by the wall of the integrating sphere, the illuminance of the sphere wall is uniformly distributed. The detector measures the illuminance proportional to the luminous flux, and a temperature sensor monitors the internal temperature in real time and performs compensation processing. By comparing with a standard lamp, the luminous flux of the target LED light source (unit: lumen lm) is calculated, and the luminous flux is converted into a light signal characterizing the light emission characteristics of the target LED light source.

[0057] Step S102: Spectroscopy and photoelectric conversion processing. The optical signal is subjected to spectral splitting and photoelectric conversion processing to obtain the corresponding spectral electrical signal data.

[0058] In this step, after receiving the optical signal transmitted by the fiber optic probe, the optical signal is split by a grating beam splitting unit, decomposing it into multiple spectral components within the wavelength range of 350 nm to 1000 nm. The optical signal corresponding to each wavelength is converted into a weak electrical signal by a linear CCD detector. This weak electrical signal is then amplified by a signal amplification circuit to obtain the corresponding spectral electrical signal data. The spectral electrical signal data is used to characterize the intensity information of optical signals at different wavelengths and can be represented as a voltage signal, current signal, or corresponding digital signal.

[0059] In one embodiment, the grating beam splitting unit employs a reflective diffraction grating with an optical glass substrate on which fine grooves are periodically etched. The groove spacing matches the wavelength range of the light to be measured, which is 350 nm to 1000 nm. The grating surface is coated with a high-reflectivity aluminum film (reflectivity ≥ 90%) to ensure beam splitting efficiency and accuracy. The detection band can be adjusted according to detection requirements to adapt to different types of LED light sources.

[0060] CCD Detector: Employs an industrial-grade high-sensitivity linear CCD detector with ≥2048 pixels and an exposure time range of 40 µs to 5 s, which can be adaptively adjusted according to the type of light source to be tested. Compared with the fixed integration time method, it can further improve the detection accuracy of weak light signals. At the same time, it works with a high-speed data acquisition circuit to scan the pixel voltage to meet the needs of rapid detection.

[0061] The structure of the linear CCD detector is as follows: Figure 3As shown, the exposure time range of this linear CCD detector is 40 µs to 5 s, and it can be adaptively adjusted according to the type of light source. After the optical signal is transmitted through the fiber optic probe, it is collimated by a collimating lens, and the optical signal is split by a grating beam splitting unit. The collecting lens focuses the decomposed wavelength optical signals onto the focal plane. The linear CCD detector is used to receive the optical signals corresponding to each wavelength. The pixels of the linear CCD detector are arranged linearly, and different pixel positions correspond to different wavelength spectral components. The voltage signal output by each pixel represents the intensity of the corresponding wavelength optical signal. The high-speed data acquisition circuit scans and acquires the voltage signals output by each pixel of the linear CCD detector to obtain the spectral electrical signal data of the target LED light source.

[0062] Signal amplification circuit: A low-noise operational amplifier is used to amplify the weak electrical signal after CCD conversion by 100 to 1000 times in an adjustable manner to improve signal recognition and reduce data processing errors. The signal-to-noise ratio of the amplified electrical signal is ≥40dB.

[0063] Step S103: Data analysis. Based on the spectral electrical signal data, a spectral analysis algorithm is used to extract various spectral characteristic parameters and construct spectral feature data.

[0064] In this step, the spectral analysis algorithm is used to perform high-speed calculations on the spectral electrical signal data to obtain various spectral characteristic parameters of the target LED light source, including color temperature, color rendering index, illuminance, spectral distribution, peak wavelength, and half-width. It also supports the calculation of CIE 1931 x / y color coordinates, u'v' color coordinates, CRI R1-R15 color rendering index, and TM-30-18 fidelity / color gamut data.

[0065] In one implementation, upon receiving the spectral electrical signal data, a high-speed 16-bit A / D converter converts the spectral electrical signal data into a digital signal. The embedded processor then runs a spectral analysis algorithm to perform high-speed calculations on the digital signal, obtaining various spectral characteristic parameters of the target LED light source, including color temperature, color rendering index, illuminance, spectral distribution, peak wavelength, and half-width.

[0066] In one implementation, the spectral electrical signal data is processed based on a pre-established wavelength calibration relationship and photometric response relationship to obtain spectral data.

[0067] The spectral data is a set of spectral data after wavelength calibration and photometric response correction, including multiple wavelength sampling points and corresponding light intensity or spectral power values, used to characterize the spectral distribution of the target LED light source at each wavelength.

[0068] Among them, the wavelength calibration relationship is used to determine the correspondence between pixel position and wavelength; the photometric response relationship is used to correct the light intensity response at different wavelengths to improve the accuracy of spectral analysis.

[0069] After obtaining multiple spectral characteristic parameters, each spectral characteristic parameter is combined according to a preset data structure to construct spectral feature data. The spectral feature data is used to uniformly characterize the spectral characteristics of the target LED light source and serves as input for subsequent detection status determination.

[0070] Step S104: Determine the detection status. Based on spectral feature data and environmental state parameters, determine the current detection status.

[0071] In this step, determining the current detection state includes:

[0072] The difference features are compared with a preset difference threshold to obtain the difference comparison result;

[0073] The environmental state parameters are compared with a preset environmental range to obtain the environmental state comparison result.

[0074] The current detection status is determined based on the difference comparison results and the environmental status comparison results.

[0075] The current detection state is determined based on the differences between the spectral feature data and the reference spectral data. These differences include spectral intensity differences, peak position shifts, or spectral shape similarities. The reference spectral data is standard spectral data acquired and updated via a standard light source interface.

[0076] In one implementation, after obtaining the spectral feature data, the spectral feature data is compared with reference spectral data to obtain difference features. These difference features include differences in spectral intensity, peak position shifts, or spectral shape similarity. The reference spectral data is standard spectral data acquired and updated through a standard light source interface and stored in memory.

[0077] In addition, environmental state parameters are acquired, including ambient temperature, which is obtained by a temperature sensor.

[0078] After obtaining the difference features and environmental state parameters, the difference features are compared with preset difference thresholds to obtain difference comparison results; and the environmental state parameters are compared with preset environmental ranges to obtain environmental state comparison results. Based on the difference comparison results and environmental state comparison results, the current detection state is classified, specifically including:

[0079] When the difference feature is less than the preset difference threshold and the environmental state parameter is within the preset environmental range, the current detection state is determined to be normal.

[0080] When the difference feature is greater than or equal to the preset difference threshold and the environmental state parameter is within the preset environmental range, the current detection state is determined to be a deviation state.

[0081] When the difference feature is greater than or equal to the preset difference threshold and the environmental state parameter exceeds the preset environmental range, the current detection state is determined to be an abnormal state.

[0082] The preset difference threshold is a threshold determined based on the equipment calibration process or statistical analysis of historical test data, and is used to characterize the allowable range of spectral characteristics deviating from the reference spectrum.

[0083] The preset environmental range is the range of ambient temperature values ​​determined based on the environmental requirements of the spectral measurement process or the experimental test results. It is used to characterize the range of environmental conditions under which the current measurement process is in normal working condition.

[0084] Step S105: Adaptive compensation. Based on the current detection state, determine the corresponding compensation parameters, and perform correction processing on the spectral data based on the compensation parameters to obtain compensated spectral data. Recalculate the spectral feature data based on the compensated spectral data.

[0085] In this step, the spectral data is the wavelength-calibrated and photometric response-corrected spectral data obtained in step S103.

[0086] After obtaining the current detection state, compensation parameters are determined based on the mapping relationship between the preset compensation strategy and the detection state. Specifically, corresponding compensation strategies are preset for different detection states, and each compensation strategy includes compensation parameters for correcting spectral data. After determining the current detection state, a compensation strategy corresponding to the current detection state is selected from the preset compensation strategies, and the corresponding compensation parameters are extracted to complete the determination of the compensation parameters.

[0087] The compensation parameters include at least one of a gain coefficient for correcting spectral data, a zero-point offset, or a compensation amount based on ambient temperature.

[0088] The correction process involves applying compensation parameters to the spectral data, where:

[0089] Gain adjustment or offset correction is performed on the light intensity values ​​in the spectral data based on compensation parameters;

[0090] Alternatively, the spectral data can be compensated and corrected based on the compensation amount of ambient temperature to reduce the impact of temperature drift and system response error on the detection results, thus obtaining compensated spectral data.

[0091] It should be noted that the preset compensation strategy is based on the factory calibration results of the spectral acquisition device, the statistical analysis results of historical detection data, or the experimental calibration data, and establishes a mapping relationship between the detection status and the compensation parameters in order to achieve targeted compensation for different error sources.

[0092] It should be further explained that, since the compensation process corrects the light intensity values ​​in the spectral data, the spectral feature data calculated based on the spectral data before compensation may have deviations. Therefore, it is necessary to recalculate the spectral feature data based on the spectral data after compensation in order to improve the accuracy and stability of spectral feature extraction, thereby improving the reliability of subsequent spectral analysis or detection results.

[0093] Step S106: Output the results. Determine the detection results based on the compensated spectral data and output the detection results.

[0094] In this step, spectral features are calculated based on the compensated spectral data, and the corresponding detection results are determined according to these features. The detection results include spectral feature parameters or corresponding detection index results calculated based on the compensated spectral data. By determining the results using the compensated spectral data, the impact of system response errors and environmental factors on the detection results can be effectively reduced, thereby improving the accuracy and stability of the detection results.

[0095] This embodiment constructs difference features based on spectral feature data and reference spectral data, and determines the detection state by combining environmental state parameters. It further generates compensation parameters and corrects the spectral feature data, thereby achieving dynamic compensation for the spectral detection results. Through this processing method, the accuracy and stability of the spectral detection results can be improved, ensuring consistency of the detection results under different environmental conditions.

[0096] Figure 4 This is a schematic diagram of the structure of an LED light source incoming material inspection system based on adaptive compensation, according to an example embodiment of this application. Figure 4 As shown, the LED light source incoming material inspection system 400 based on adaptive compensation provided in this embodiment includes: a spectrum acquisition module 410, a spectral and photoelectric conversion processing module 420, a data analysis module 430, a detection status determination module 440, an adaptive compensation module 450, and a result output module 460.

[0097] The spectrum acquisition module 410 acquires the light signal of the target LED light source through the spectrum acquisition device;

[0098] The spectral splitting and photoelectric conversion processing module 420 performs spectral splitting and photoelectric conversion processing on the optical signal to obtain the corresponding spectral electrical signal data.

[0099] Data analysis module 430 uses a spectral analysis algorithm based on the spectral electrical signal data to extract various spectral characteristic parameters and construct spectral feature data;

[0100] The detection status determination module 440 determines the current detection status based on spectral feature data and environmental status parameters.

[0101] The adaptive compensation module 450 determines the corresponding compensation parameters based on the current detection state, and performs correction processing on the spectral data based on the compensation parameters to obtain compensated spectral data, and recalculates the spectral feature data based on the compensated spectral data.

[0102] The result output module 460 determines the detection result based on the compensated spectral data and outputs the detection result.

[0103] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the foregoing claims.

[0104] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope.

Claims

1. A method for inspecting incoming LED light sources based on adaptive compensation, characterized in that, include: Spectral acquisition: acquiring the light signal of the target LED light source through a spectral acquisition device; Spectroscopic and photoelectric conversion processing: The optical signal is subjected to spectral and photoelectric conversion processing to obtain the corresponding spectral electrical signal data; Data analysis involves using spectral analysis algorithms based on the spectral electrical signal data to extract various spectral characteristic parameters and construct spectral feature data. The detection status is determined based on spectral feature data and environmental state parameters. Adaptive compensation involves determining corresponding compensation parameters based on the current detection state, correcting the spectral data based on the compensation parameters to obtain compensated spectral data, and recalculating spectral feature data based on the compensated spectral data. The results are output, and the detection results are determined based on the compensated spectral data.

2. The LED light source incoming material inspection method based on adaptive compensation according to claim 1, characterized in that, The current detection status is determined based on the difference between the spectral feature data and the reference spectral data.

3. The LED light source incoming material inspection method based on adaptive compensation according to claim 2, characterized in that, The determination of the current detection status includes: The difference features are compared with a preset difference threshold to obtain the difference comparison result; The environmental state parameters are compared with a preset environmental range to obtain the environmental state comparison result. The current detection status is determined based on the difference comparison results and the environmental status comparison results.

4. The LED light source incoming material inspection method based on adaptive compensation according to claim 2, characterized in that, The reference spectral data is standard spectral data acquired and updated through a standard light source interface.

5. The LED light source incoming material inspection method based on adaptive compensation according to claim 1, characterized in that, The environmental status parameters include the ambient temperature, which is acquired by a temperature sensor.

6. The LED light source incoming material inspection method based on adaptive compensation according to claim 1, characterized in that, The compensation parameters are determined based on the mapping relationship between a preset compensation strategy and the detection state; For different detection states, corresponding compensation strategies are preset. Each compensation strategy includes compensation parameters for correcting spectral data. After determining the current detection state, a compensation strategy corresponding to the current detection state is selected from the preset compensation strategies, and the corresponding compensation parameters are extracted.

7. The LED light source incoming material inspection method based on adaptive compensation according to claim 1, characterized in that, The compensation parameters include at least one of a gain coefficient for correcting spectral data, a zero-point offset, or a compensation amount based on ambient temperature.

8. The LED light source incoming material inspection method based on adaptive compensation according to claim 1, characterized in that, The spectral acquisition device includes an integrating sphere and an optical fiber probe; The integrating sphere is used to homogenize the light signal emitted by the target LED light source; The fiber optic probe is positioned at the light outlet of the integrating sphere to receive the optical signal processed by the integrating sphere and transmit the optical signal to the beam splitting and photoelectric conversion processing unit.

9. An LED light source incoming material inspection system based on adaptive compensation, characterized in that, include: The spectrum acquisition module acquires the light signal of the target LED light source through a spectrum acquisition device. The spectral splitting and photoelectric conversion processing module performs spectral splitting and photoelectric conversion processing on the optical signal to obtain the corresponding spectral electrical signal data. The data analysis module uses spectral analysis algorithms to extract various spectral characteristic parameters based on the spectral electrical signal data, and constructs spectral feature data. The detection status determination module determines the current detection status based on spectral feature data and environmental status parameters. The adaptive compensation module determines the corresponding compensation parameters based on the current detection state, and performs correction processing on the spectral data based on the compensation parameters to obtain compensated spectral data, and recalculates the spectral feature data based on the compensated spectral data. The result output module determines the detection result based on the compensated spectral data and outputs the detection result.

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