CN-121978574-A - Defect detection method and system for LED flexible lamp strip

CN121978574ACN 121978574 ACN121978574 ACN 121978574ACN-121978574-A

Abstract

The invention relates to the technical field of LED lamp strip test, solves the problem that the multi-dimensional defect detection of an LED flexible lamp strip cannot be realized under a complex working condition in the prior art, and provides a defect detection method and a defect detection system of the LED flexible lamp strip, wherein the method comprises the steps of obtaining preset identification information of the LED flexible lamp strip to be detected; the method comprises the steps of obtaining power-on initial electrical parameters according to power supply safety parameters corresponding to preset identification information, driving and detecting an LED flexible lamp strip when the power-on initial electrical parameters meet preset stable conditions to obtain driving protocol parameters of a target driving integrated circuit, performing multi-dimensional performance test on the LED flexible lamp strip according to preset performance test conditions corresponding to the driving protocol parameters to obtain performance test results, and inputting the performance test results into a pre-trained multi-dimensional defect detection model to obtain defect detection results. The invention can realize the defect detection of the LED flexible lamp strip under the multi-type driving and complex working conditions.

Inventors

Yang Fangrui
ZHANG WENTING
LI YONGHUAI
LU HONG

Assignees

深圳市优一像电子有限公司

Dates

Publication Date: 20260505
Application Date: 20251229

Claims (10)

1. A method for detecting defects of an LED flexible light strip, the method comprising: Acquiring preset identification information of an LED flexible lamp strip to be detected; according to the power supply safety parameters corresponding to the preset identification information, carrying out controlled power-on the LED flexible lamp strip to obtain power-on initial electric parameters; When the power-on initial electrical parameter meets a preset stable condition, driving and detecting the LED flexible lamp strip to obtain a driving protocol parameter of a target driving integrated circuit; According to preset performance test conditions corresponding to the driving protocol parameters, performing multi-dimensional performance test on the LED flexible lamp strip to obtain a performance test result; inputting the performance test result into a pre-trained multi-dimensional defect detection model to obtain a defect detection result.
2. The method for detecting defects of an LED flexible light strip according to claim 1, wherein said performing controlled power-up on the LED flexible light strip according to the power supply security parameter corresponding to the preset identification information, and obtaining the power-up initial electrical parameter comprises: according to the preset identification information, determining rated power supply voltage and rated working current corresponding to the preset identification information, and obtaining power supply reference parameters; configuring the output voltage of the power supply and the current threshold value of the current limiting circuit according to the power supply reference parameter to obtain a power supply control parameter; according to the power supply control parameters, controlling a power supply to gradually load voltage to the LED flexible lamp strip, and executing a controlled power-on process; in the controlled power-on process, starting current and voltages at two ends of the LED flexible lamp strip are used as power-on electrical measurement data; and calculating a starting current peak value and an end-to-end voltage drop according to the power-on electrical measurement data to obtain the power-on initial electrical parameter.
3. The method for detecting defects of an LED flexible light strip according to claim 1, wherein when the power-on initial electrical parameter satisfies a preset stable condition, performing driving detection on the LED flexible light strip, and obtaining a driving protocol parameter of a target driving integrated circuit includes: when the power-on initial electrical parameter meets a preset stable condition, determining a candidate driving integrated circuit corresponding to the preset identification information according to the preset identification information; Loading trial driving signals to the LED flexible lamp strips one by one according to the driving signal template set corresponding to the candidate driving integrated circuit, and acquiring optical response data and electrical response data of the LED flexible lamp strips in the trial driving process to obtain a trial response data set; comparing the response consistency of different driving signal templates in the driving signal template set according to the heuristic response data set, and determining a target driving signal template matched with the LED flexible lamp strip; And extracting the protocol type, the time sequence parameter, the level parameter and the data format parameter according to the target driving signal template to obtain the driving protocol parameter.
4. The method for detecting defects of an LED flexible light strip according to claim 3, wherein when the power-on initial electrical parameter satisfies a preset stable condition, obtaining a driving signal template set corresponding to a preset candidate driving integrated circuit according to the preset identification information comprises: calculating the starting current change rate and the end-to-end voltage fluctuation rate according to the power-on initial electrical parameters to obtain a stability judgment index; Comparing the stability judgment index with a preset stability threshold, and if the stability judgment index is smaller than the stability threshold, enabling the power-on initial electric parameter to meet the preset stability condition; When the initial power-on electrical parameter meets a preset stable condition, analyzing the product model, the power supply gear and the interface level of the LED flexible lamp strip according to the preset identification information to obtain a candidate driving integrated circuit set; and acquiring a driving signal template corresponding to each candidate driving integrated circuit in the candidate driving integrated circuit set as the driving signal template set according to a preset driving signal template library.
5. The method for detecting defects of an LED flexible light strip according to claim 3, wherein said performing a multi-dimensional performance test on said LED flexible light strip according to a preset performance test condition corresponding to said driving protocol parameter, obtaining a performance test result comprises: analyzing the protocol type, the time sequence parameter and the level parameter, and determining the driving mode of the LED flexible lamp strip; Determining a candidate driving integrated circuit model set according to the driving mode and preset identification information; According to the driving mode and the candidate driving integrated circuit model set, retrieving performance test conditions from a preset performance test condition library to obtain an initial performance test condition set; According to the time sequence parameters and the level parameters, checking and screening the initial performance test condition set to obtain the preset performance test conditions; And carrying out multidimensional performance test on the LED flexible lamp strip according to the preset performance test conditions to obtain a performance test result.
6. The method for detecting defects of an LED flexible light strip according to claim 5, wherein said performing a multi-dimensional performance test on said LED flexible light strip according to said preset performance test conditions, obtaining a performance test result comprises: configuring output parameters for driving control according to the preset performance test conditions to obtain driving configuration parameters; Calling performance test conditions corresponding to different drive integrated circuit models according to the drive configuration parameters to generate an initial performance test sequence covering the drive characteristics of multiple types; according to the initial performance test sequence, driving signals are sequentially loaded on the LED flexible lamp strip to form tests with different power levels, and performance execution results are obtained; acquiring a multidimensional performance response data set of the LED flexible lamp strip under different driving integrated circuit types and different performances according to the performance execution result; and comparing and analyzing response characteristics of different driving integrated circuit models according to the multidimensional performance response data set, and classifying detection results of different performance working conditions to obtain the performance test result.
7. The method for detecting defects of an LED flexible light strip according to claim 6, wherein said obtaining a multidimensional performance response data set of said LED flexible light strip under different driving integrated circuit models and different performance conditions according to said performance execution result comprises: marking the running time of the LED flexible lamp strip under different driving integrated circuit types and different performance working conditions according to the performance execution result to obtain working condition index information; Acquiring electrical operation data, optical operation data, thermal operation data and mechanical response data of the LED flexible lamp strip under various working conditions according to the working condition index information; and performing time alignment and space calibration on the electrical operation data, the optical operation data, the thermal operation data and the mechanical response data to obtain the multi-dimensional performance response data set.
8. The method for detecting defects of an LED flexible light strip according to any one of claims 1 to 7, wherein inputting the performance test results into a pre-trained multi-dimensional defect detection model to obtain defect detection results comprises: Analyzing the electrical parameters, the optical parameters and the mechanical parameters of different driving integrated circuit models according to the performance test result to obtain target detection data sets corresponding to various models; according to each target detection data set, carrying out statistical calculation on current fluctuation, voltage drop drift and power consumption change to obtain an electrical anomaly index; According to each target detection data set, carrying out statistical calculation on brightness attenuation, chromaticity shift and stroboscopic amplitude to obtain an optical anomaly index; According to each target detection data set, analyzing the temperature rise gradient, the hot spot position and the bending response to obtain a mechanical abnormality index; inputting the electrical abnormality index, the optical abnormality index and the mechanical abnormality index into the multi-dimensional defect detection model to obtain a corresponding initial defect detection result; and classifying and summarizing the defect types under different driving integrated circuit models and different performance working conditions according to the initial defect detection result to obtain the defect detection result.
9. The method for detecting defects of an LED flexible light strip according to claim 8, wherein said analyzing the temperature rise gradient, the hot spot position and the bending response according to each of said target detection data sets, to obtain the mechanical abnormality index comprises: extracting and aligning temperature distribution data at different sampling moments according to each target detection data set to obtain a temperature distribution sequence; According to the temperature distribution sequence, calculating the temperature change rate of each region to obtain a temperature rise gradient index; Positioning and tracking local extreme points in the temperature distribution according to the temperature distribution sequence to obtain a hot spot position index; According to each target detection data set, carrying out correlation calculation on bending curvature, bending cycle times, corresponding current change rate and brightness change rate to obtain bending response indexes; And carrying out comprehensive comparison and association analysis on the detection result according to the temperature rise gradient index, the hot spot position index and the bending response index to obtain the mechanical abnormality index.
10. A defect detection system for a flexible LED strip, comprising at least one processor, at least one memory, and computer program instructions stored in the memory, which when executed by the processor, implement the method of any of claims 1-9.

Description

Defect detection method and system for LED flexible lamp strip Technical Field The invention relates to the technical field of LED lamp strip testing, in particular to a defect detection method and system for an LED flexible lamp strip. Background The LED flexible lamp strip has the characteristics of being bendable, windable, flexible to install, uniform in light emission and the like, and is widely applied to the fields of architectural decoration, stage lighting, display screens, automobile interior trim and the like. However, the flexible lamp strip is prone to uneven brightness, color shift, stroboscopic anomalies and even partial lamp bead failure due to differences in driving integrated circuits, insufficient process consistency or device performance caused by long-time operation during production and use. Therefore, systematic defect detection is performed on the LED flexible lamp strip, which is not only a necessary link for guaranteeing product quality and reliability, but also an important means for improving user experience and reducing after-sales maintenance cost. The existing LED lamp strip defect detection technology mainly comprises a static electric performance test and an optical detection method. For example, the working current and voltage of the lamp strip are sampled to judge whether the circuit is abnormal or not, or the optical sensor is used for detecting the brightness and chromaticity parameters to judge whether the problems of dark spots, color drift and uneven light emission exist or not. Part of the schemes also introduce high temperature performance tests to evaluate the reliability of the lamp strip under long-term high load operating conditions. These detection methods can find significant failure problems to some extent, but still have significant limitations. However, the existing defect detection technology generally has the following problems that firstly, most methods are designed only for a single type of driving circuit, self-adaptive identification and matching of different driving integrated circuits are lacked, and the detection requirements of compatibility of multiple types cannot be covered, secondly, the traditional test mainly uses a single working condition, and the potential defects of a lamp strip in complex working scenes such as multiple power levels, different color combinations, different refreshing frequencies and the like are difficult to truly reflect, thirdly, the existing detection technology generally cannot acquire electrical, optical, thermal and mechanical response data at the same time for the special bending and winding use scenes of the flexible lamp strip, so that the failure risk caused by mechanical stress is difficult to effectively evaluate. The prior Chinese patent CN118351422A discloses a training method and device of an LED lamp strip defect detection model, a computer-readable storage medium and the LED lamp strip defect detection method, wherein the training method comprises the steps of selecting a typical positive sample from an LED lamp strip training set only containing the positive sample through K-means++ clustering to construct a memory pool, generating a pseudo-abnormal sample expansion training set by using Berlin noise and texture data, combining a pre-trained resnet feature extraction network, a multi-scale feature fusion network and a spatial attention mechanism, training to obtain a detection model capable of outputting a defect prediction graph of an image to be detected, so that the robustness of the model is improved, and the model is convenient to migrate and use among different image datasets. According to the technical scheme, the luminous image collected by the camera is always used as the only input, the detection dimension is mainly concentrated on the brightness distribution and the luminous appearance, and the multi-dimensional characteristic defects such as electrical, optical, thermal and mechanical stress and the like of the flexible lamp strip under complex working conditions such as different driving currents, different PWM dimming modes, bending tensile states, thermal drift generated by long-term lighting, voltage drop and the like are not modeled and monitored, and the fusion with data such as online electrical property test, temperature sensing and strain monitoring is not involved, so that the comprehensive performance failure risk of the flexible lamp strip in a real application scene is difficult to reflect in time. Therefore, how to realize multi-dimensional defect detection of the LED flexible light strip under a complex working condition is a technical problem to be solved urgently. Disclosure of Invention In view of the above, the embodiment of the invention provides a method and a system for detecting defects of an LED flexible light strip, which are used for solving the problem that the multi-dimensional defect detection of the LED flexible light strip can not be realized under a complex w