A detection method, device and electronic device for an LED driving power supply

Abstract

The present application provides a detection method, device and electronic device for an LED driving power supply, relating to the technical field of detection. In this method, 3D scan data for the LED driving power supply is obtained; according to the 3D scan data, a first position corresponding to a first component and a second position corresponding to a second component are determined, the LED driving power supply includes a plurality of components, and the first component and the second component are any two components among the plurality of components; based on the first position and the second position, a thermal interaction influence between the first component and the second component is determined; if it is determined that the thermal interaction influence is within a preset influence range, it is determined that the LED driving power supply is qualified, and the preset influence range is pre-correspondingly set according to the first component and the second component; if it is determined that the thermal interaction influence is not within the preset influence range, it is determined that the LED driving power supply is unqualified. Implementing the technical solution provided by the present application facilitates improving the detection accuracy of the LED driving power supply.

Description

Technical Field

[0001] The present application relates to the technical field of detection technology, and particularly relates to a detection method, device and electronic device for an LED driving power supply. Background Art

[0002] Under the background of the rapid development of LED lighting technology, as the core component of an LED lighting system, the performance and quality of an LED driving power supply directly affect the stability and reliability of the entire lighting system. However, in the process of the ex-factory quality inspection of traditional LED driving power supplies, there are often significant technical limitations and deficiencies.

[0003] Traditionally, the quality inspection of LED driving power supplies mainly relies on manual inspection and simple performance tests. Although manual inspection is intuitive, it is easily affected by human factors, resulting in subjectivity and inconsistency of the inspection results. At the same time, it is difficult for manual inspection to comprehensively cover all potential defects and problems, especially for complex circuit structures and minor component failures, which are often difficult to accurately identify. Therefore, the accuracy of the above traditional detection for LED driving power supplies is relatively low.

[0004] Therefore, there is an urgent need for a detection method, device and electronic device for an LED driving power supply. Summary of the Invention

[0005] The present application provides a detection method, device and electronic device for an LED driving power supply, which is convenient for improving the detection accuracy of the LED driving power supply.

[0006] In the first aspect of the present application, a detection method for an LED driving power supply is provided. The method includes: obtaining 3D scan data for the LED driving power supply; determining a first position corresponding to a first component and a second position corresponding to a second component according to the 3D scan data, where the LED driving power supply includes a plurality of components, and the first component and the second component are any two components among the plurality of components; determining a thermal interaction influence between the first component and the second component based on the first position and the second position; if it is determined that the thermal interaction influence is within a preset influence range, determining that the LED driving power supply is qualified, where the preset influence range is pre-correspondingly set according to the first component and the second component; if it is determined that the thermal interaction influence is not within the preset influence range, determining that the LED driving power supply is unqualified.

[0007] By adopting the above technical solution, by obtaining the 3D scan data of the LED driver power supply, this method can capture the precise positions and shapes of each component inside the power supply with unprecedented accuracy. This high precision not only facilitates subsequent analysis but also ensures the accuracy of the detection results. Compared with traditional manual inspection, this method realizes the automation of the detection process. Automation not only improves the detection efficiency, reduces the time and cost of manual operation, but also reduces the risk of human error. By automatically analyzing the 3D scan data through software algorithms, the positional relationship between components can be quickly determined, and then the influence of thermal interaction can be evaluated. This method not only focuses on the basic functions of the LED driver power supply but also deeply analyzes the influence of thermal interaction between components. This comprehensiveness and in-depthness help to discover potential heat dissipation problems or design defects that may be difficult to detect in simple performance tests. By evaluating the influence of thermal interaction, the performance and stability of the power supply in actual use can be judged more accurately. The setting of the preset influence range makes this method have a certain degree of flexibility and adaptability. Different component combinations may have different thermal interaction characteristics. By presetting the corresponding influence range, customized detection can be carried out for different types and specifications of LED driver power supplies. This flexibility helps to meet the detection requirements in different application scenarios. By comprehensively considering the component positions and the influence of thermal interaction, this method can more accurately judge the quality of the LED driver power supply. When the influence of thermal interaction is within the preset range, it indicates that the power supply design is reasonable and the heat dissipation is good, thus improving the reliability and service life of the power supply. On the contrary, when the influence of thermal interaction exceeds the preset range, it prompts the designer or manufacturer to improve or optimize the power supply. Therefore, it is convenient to improve the detection accuracy of the LED driver power supply.

[0008] Optionally, the determining the first position corresponding to the first component and the second position corresponding to the second component according to the 3D scan data specifically includes: determining an LED driver power supply model according to the 3D scan data; performing feature extraction on the LED driver power supply model to obtain shape features, size features, and color features corresponding to each of the multiple components; comparing the shape features, the size features, and the color features with a preset feature group through image comparison to obtain a target feature group, where one preset feature group corresponds to one component and one component corresponds to one position; and determining the first position corresponding to the first component and the second position corresponding to the second component based on the target feature group.

[0009] By adopting the above technical solution, an LED driver power supply model can be constructed through 3D scan data, and the internal structure and component layout of the power supply can be accurately restored. Subsequently, the feature extraction process, including shape features, size features, and color features, further refines the recognition accuracy of the components. This multi-dimensional feature extraction method makes the recognition of components more accurate, thereby improving the accuracy of determining the positions of components. The entire process is highly automated. From model construction to feature extraction, then to image comparison and position determination, it all relies on computer algorithms and software tools. This automated processing method not only improves work efficiency but also reduces the possibility of human intervention and errors. At the same time, the intelligent feature comparison and recognition technology enables the system to automatically match the preset feature groups and quickly locate the target components, further enhancing the intelligent level of detection. The setting of the preset feature groups makes this method have a certain degree of adaptability and flexibility. Different LED driver power supplies may contain different types of components. By pre-defining multiple feature groups, various detection requirements can be flexibly addressed. At the same time, when encountering new components or design changes, only the preset feature groups need to be updated, without the need for large-scale adjustment of the entire detection process. By comprehensively considering multiple features such as the shape, size, and color of the components, this method can more comprehensively identify the components and accurately determine their positions. This comprehensive recognition method helps to reduce the situations of misjudgment and missed judgment, improving the reliability of detection. At the same time, the image comparison technology based on multiple features also further enhances the accuracy and stability of recognition.

[0010] Optionally, determining the LED driver power supply model according to the 3D scan data specifically includes: obtaining the point cloud data of the LED driver power supply according to the 3D scan data, where the point cloud data includes bare board point cloud data and component point cloud data; performing a separation process on the bare board point cloud data to obtain first point cloud data; constructing the individual point cloud data in the first point cloud data into patches and performing a smoothing process on the patches to obtain second point cloud data; removing the bare board point cloud data in the second point cloud data that is not connected to the component point cloud data to obtain third point cloud data; performing a smoothing process on the bare board point cloud data in the third point cloud data to obtain fourth point cloud data; and constructing the LED driver power supply model according to the fourth point cloud data and the component point cloud data.

[0011] By adopting the above technical solution, first, the 3D scan data is subdivided into bare board point cloud data and component point cloud data. This refined classification provides a basis for subsequent processing. Through the gradual processing of the bare board point cloud data, including separation, patch construction, smoothing, and removal of unconnected parts, the high precision and accuracy of the final model are ensured. This refined data processing method helps to improve the realism and detail performance of the model. The whole process is highly automated, reducing the need for manual intervention. From the acquisition of point cloud data to the construction of the final model, it is all automatically completed by computer algorithms and software tools. This not only improves work efficiency but also reduces the risk of human errors. Automated processing makes it more efficient and reliable when dealing with large amounts of data. Through multiple smoothing processes and removal of unnecessary point cloud data, the noise and interference factors in the model are effectively reduced. The smoothing process makes the surface of the model smoother and more in line with the appearance characteristics of the actual object. At the same time, removing the bare board point cloud data that is not connected to the component point cloud data ensures the accurate position of the components in the model, which is consistent with the actual situation. The constructed LED driver power supply model is an important basis for subsequent work such as thermal interaction influence analysis, performance evaluation, and design optimization. An accurate model can provide more reliable data support, helping to understand the performance and stability of the power supply more deeply. At the same time, the component position information in the model is also one of the key factors for thermal interaction analysis.

[0012] Optionally, determining the thermal interaction influence between the first component and the second component based on the first position and the second position specifically includes: determining the heat conduction path between the first component and the second component according to the first position and the second position; determining a first thermal resistance, a second thermal resistance, and a third thermal resistance according to the heat conduction path, where the first thermal resistance is the thermal resistance between the first component and the circuit board of the LED driver power supply, the second thermal resistance is the thermal resistance between the second component and the circuit board of the LED driver power supply, and the third thermal resistance is the thermal resistance between the circuit board of the LED driver power supply and the environment where the LED driver power supply is located; determining the thermal interaction influence based on the first thermal resistance, the second thermal resistance, and the third thermal resistance.

[0013] By adopting the above technical solution, by determining the heat conduction paths between components and calculating the relevant thermal resistances accordingly (including the first thermal resistance, the second thermal resistance, and the third thermal resistance), this method provides a scientific and accurate way to evaluate the thermal interaction influence between components. This evaluation method based on physical principles is more reliable than simply relying on experience or intuitive judgment and can more accurately reflect the thermal interaction situation of components in actual operation. This method not only considers the direct heat conduction between components but also the thermal resistances between them and the circuit board and the environment. This comprehensive consideration makes the evaluation result closer to the actual situation and can more accurately reflect the thermal interaction characteristics of components in a complex working environment. By calculating the thermal resistances and determining the thermal interaction influence based on these values, this method has a certain predictability. In the product design stage, this method can be used to predict the influence of different component layouts on thermal interaction, thereby optimizing the design scheme and improving the thermal performance and reliability of the product. Understanding the thermal interaction influence between components helps engineers to carry out targeted optimizations in the design stage. This method not only helps to improve the overall performance of the product but also can reduce the failure rate and maintenance cost caused by overheating. During the production process, by quickly evaluating the thermal interaction influence between components, potential thermal problems can be detected in a timely manner and adjusted. This helps to reduce the rework and repair work caused by thermal problems, improve production efficiency, and product quality.

[0014] Optionally, determining the thermal interaction influence based on the first thermal resistance, the second thermal resistance, and the third thermal resistance specifically includes: obtaining the first power consumption corresponding to the first component and obtaining the second power consumption corresponding to the second component; receiving the ambient temperature of the environment where the LED driver power supply is located sent by the ambient temperature sensor; calculating the temperature of the first component based on the first power consumption, the first thermal resistance, and the ambient temperature; calculating the temperature of the second component based on the second power consumption, the second thermal resistance, and the ambient temperature; and calculating the thermal interaction influence according to the temperature of the first component and the temperature of the second component.

[0015] By adopting the above technical solution, by comprehensively considering the three key factors of the power consumption, thermal resistance, and ambient temperature of the components, this method can more accurately calculate the actual operating temperature of the components. This accuracy is crucial for evaluating the thermal interaction influence between components because temperature is one of the key factors affecting heat conduction and thermal radiation. This method is based on the basic principles of thermodynamics and relates physical quantities such as the power consumption, thermal resistance, and ambient temperature of the components through a mathematical model, thereby calculating the temperature of the components. This scientific method is more reliable than simply relying on experience or intuitive judgment and can more accurately reflect the thermal state of the components during actual operation. During the calculation process, not only the power consumption and thermal resistance of the components themselves are considered, but also the influence of the ambient temperature is taken into account. This comprehensive consideration makes the evaluation result closer to the actual situation and can more accurately reflect the thermal interaction characteristics of the components in a complex working environment. Since this method can receive the data of the ambient temperature sensor in real time, it can dynamically calculate the temperature and thermal interaction influence of the components.

[0016] Optionally, determining the heat conduction path between the first component and the second component according to the first position and the second position specifically includes: obtaining the first material property corresponding to the first component and obtaining the second material property corresponding to the second component; if it is determined that the LED drive power supply includes a heat sink, obtaining the heat dissipation path; constructing a thermal network model of the LED drive power supply according to the first position, the second position, the first material property, the second material property, and the heat dissipation path; and determining the heat conduction path between the first component and the second component according to the thermal network model.

[0017] By adopting the above technical solution, by considering the material properties of the components, this method can more accurately simulate the heat conduction process between the components. Different materials have different thermal conductivities, which directly affect the heat transfer speed and efficiency. Therefore, taking the material properties into consideration can make the determination of the heat conduction path more accurate. In addition to the position and material properties of the components, this method also considers the influence of the heat dissipation path. In an LED drive power supply, the heat sink is a key heat dissipation component, and its design and layout have an important impact on the overall thermal performance. By obtaining the heat dissipation path and incorporating it into the construction of the thermal network model, the heat conduction and heat dissipation conditions inside the power supply can be comprehensively reflected, which helps to better understand the thermal interaction phenomenon and conduct thermal management design.

[0018] Optionally, the method further includes: obtaining the standard layout data of the LED drive power supply; marking the heat dissipation abnormal components included in the unqualified LED drive power supply in the LED drive power supply model according to the standard layout data to obtain a model to be displayed; and displaying the model to be displayed through an AR device.

[0019] By adopting the above technical solutions, by obtaining the standard layout data, it is possible to quickly identify which components in the unqualified LED driver power supply have abnormal heat dissipation. This comparison method based on standard data greatly improves the efficiency of fault troubleshooting and reduces the time and workload of manual inspection. Compared with troubleshooting based solely on experience or intuition, using the standard layout data as a reference can more accurately locate the problematic components. The standard layout data usually contains information such as the exact positions, models, and specifications of the components, providing a reliable basis for fault troubleshooting. Marking the components with abnormal heat dissipation in the LED driver power supply model to obtain the model to be displayed and displaying it through an AR device is very intuitive. AR technology can superimpose virtual information onto the real world, enabling users to intuitively see the positions and states of the problematic components and perform fault troubleshooting without disassembling or opening the device.

[0020] In the second aspect of the present application, a detection device for an LED driver power supply is provided. The detection device includes an acquisition module and a processing module. Among them, the acquisition module is used to acquire 3D scan data for the LED driver power supply; the processing module is used to determine the first position corresponding to the first component and the second position corresponding to the second component according to the 3D scan data. The LED driver power supply includes a plurality of components, and the first component and the second component are any two components among the plurality of components; the processing module is further used to determine the thermal interaction influence between the first component and the second component based on the first position and the second position; the processing module is further used to determine that the LED driver power supply is qualified if it is determined that the thermal interaction influence is within a preset influence range, and the preset influence range is pre-correspondingly set according to the first component and the second component; the processing module is further used to determine that the LED driver power supply is unqualified if it is determined that the thermal interaction influence is not within the preset influence range.

[0021] In the third aspect of the present application, an electronic device is provided. The electronic device includes a processor, a memory, a user interface, and a network interface. The memory is used to store instructions, and both the user interface and the network interface are used to communicate with other devices. The processor is used to execute the instructions stored in the memory so that the electronic device executes the method described above.

[0022] In the fourth aspect of the present application, a computer-readable storage medium is provided. The computer-readable storage medium stores instructions that, when executed, execute the method described above.

[0023] In summary, one or more technical solutions provided in the present application have at least the following technical effects or advantages:

[0024] By obtaining the 3D scan data of the LED driver power supply, this method can capture the precise positions and shapes of various components inside the power supply with unprecedented accuracy. This high precision not only facilitates subsequent analysis but also ensures the accuracy of the detection results. Compared with traditional manual inspection, this method realizes the automation of the detection process. Automation not only improves the detection efficiency, reduces the time and cost of manual operation, but also reduces the risk of human errors. By automatically analyzing the 3D scan data through software algorithms, the positional relationships between components can be quickly determined, and then the influence of thermal interaction can be evaluated. This method not only focuses on the basic functions of the LED driver power supply but also deeply analyzes the influence of thermal interaction between components. This comprehensiveness and in-depthness help to discover potential heat dissipation problems or design defects that may be difficult to detect in simple performance tests. By evaluating the influence of thermal interaction, the performance and stability of the power supply in actual use can be judged more accurately. The setting of the preset influence range makes this method have a certain degree of flexibility and adaptability. Different component combinations may have different thermal interaction characteristics. By presetting the corresponding influence range, customized detection can be carried out for different types and specifications of LED driver power supplies. This flexibility helps to meet the detection requirements in different application scenarios. By comprehensively considering the component positions and the influence of thermal interaction, this method can more accurately judge the quality of the LED driver power supply. When the influence of thermal interaction is within the preset range, it indicates that the power supply is reasonably designed and has good heat dissipation, thus improving the reliability and service life of the power supply. On the contrary, when the influence of thermal interaction exceeds the preset range, it prompts the designer or manufacturer to improve or optimize the power supply. Therefore, it is convenient to improve the detection accuracy of the LED driver power supply. Description of the Drawings

[0025] Figure 1 It is a schematic flowchart of a method for detecting an LED driver power supply provided by an embodiment of the present application.

[0026] Figure 2 It is another schematic flowchart of a method for detecting an LED driver power supply provided by an embodiment of the present application.

[0027] Figure 3 It is a schematic diagram of the modules of a detection device for an LED driver power supply provided by an embodiment of the present application.

[0028] Figure 4 It is a schematic structural diagram of an electronic device provided by an embodiment of the present application.

[0029] Description of the reference numerals: 31, acquisition module; 32, processing module; 41, processor; 42, communication bus; 43, user interface; 44, network interface; 45, memory. Detailed Embodiments

[0030] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of this specification. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all the embodiments.

[0031] In the description of the embodiments of this application, words such as "for example" or "for illustration" are used to give examples, illustrations or explanations. Any embodiment or design solution described as "for example" or "for illustration" in the embodiments of this application should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Rather, the use of words such as "for example" or "for illustration" is intended to present the relevant concepts in a specific manner.

[0032] In the description of the embodiments of this application, the term "plurality" means two or more. For example, a plurality of systems means two or more systems, and a plurality of screen terminals means two or more screen terminals. In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly indicating the technical features indicated. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. The terms "include", "comprise", "have" and their variants all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0033] In the context of the ever-changing era of LED lighting technology, as the lifeblood of the system, the performance and quality assurance of LED driver power supplies are directly related to the stable operation and reliability of the entire lighting system. However, reviewing the factory quality inspection process of traditional LED driver power supplies, it is not difficult to find the significant technical bottlenecks and deficiencies therein.

[0034] Traditional detection means mainly rely on manual inspection and basic performance testing. Although this method is intuitive and convenient, it is inevitably limited by the subjective fluctuations of human judgment, resulting in significant differences and uncertainties in detection results. More critically, manual detection is difficult to deeply explore the subtle structures of products and potential defects in complex circuits. Especially when faced with subtle faults of micro-components, its recognition accuracy and comprehensiveness are significantly insufficient. These factors jointly restrict the comprehensive and accurate control of the quality of LED driver power supplies by traditional detection modes, leading to limitations in the overall detection accuracy.

[0035] To solve the above technical problems, this application provides a detection method for LED driver power supplies, referring to Figure 1 , Figure 1Schematic flowchart of a detection method for an LED driver power supply provided by an embodiment of the present application. This detection method is applied to a server and includes steps S110 to S150 as follows:

[0036] S110. Obtain 3D scan data for the LED driver power supply.

[0037] Specifically, a server is a high-performance computer device used for storing, processing, and transmitting data or applications. In the embodiment of the present application, the server is used as the central point for data processing and storage, responsible for receiving, processing, and storing data from external devices or systems. The 3D scan data for the LED driver power supply refers to data containing information such as the three-dimensional shape, dimensions, and structure of the LED driver power supply obtained using 3D scan technology. 3D scan technology is a non-contact measurement method that can quickly and accurately obtain the three-dimensional model of an object. Among them, the 3D scan data for the LED driver power supply does not include its outer shell but includes detailed information such as its internal layout, component positions, and heat dissipation structure.

[0038] For example, assume an LED lighting manufacturer needs to perform precise three-dimensional modeling and performance analysis on its newly designed LED driver power supply. To achieve this goal, they may adopt the following steps during factory inspection: First, the manufacturer will place the LED driver power supply in an environment suitable for 3D scanning, ensuring there are no obstructions and the scanning area is well-lit. At the same time, they may use marker points or specific patterns to assist the scanning process and improve scanning accuracy. Next, the manufacturer will use a high-precision 3D scanner to scan the LED driver power supply. The scanner will emit laser or light onto the object's surface and capture the reflected light to calculate the three-dimensional coordinates of the object. This process may require scanning from multiple angles to ensure a complete and accurate three-dimensional model is obtained. After the scanning is completed, the 3D scanner will transmit the obtained 3D scan data to the server. This can be achieved through a wired connection (such as USB, Ethernet) or a wireless connection (such as Wi-Fi, Bluetooth). The server will receive and store this data for subsequent processing and analysis.

[0039] S120. Determine the first position corresponding to the first component and the second position corresponding to the second component according to the 3D scan data. The LED driver power supply includes multiple components, and the first component and the second component are any two components among the multiple components.

[0040] Specifically, as mentioned before, this is data on the three-dimensional shape, size, structure, etc. of the LED driver power supply obtained through 3D scanning technology. This data contains the precise position and shape information of all components inside the LED driver power supply. By processing and analyzing the 3D scan data, the server can identify the specific positions of each component inside the LED driver power supply. This involves computer vision technologies such as image recognition, feature extraction, and matching. The server will store and represent this position information in coordinates or other forms. In this passage, the "first component" and the "second component" refer to any two specific components in the LED driver power supply. These two components can be any type of component, such as capacitors, resistors, transistors, etc. Based on determining the positions of all components, the server specifically focuses on and determines the specific positions of these two components.

[0041] For example, suppose there is an LED driver power supply that contains multiple components, such as capacitor C1, resistor R2, transistor Q3, etc. The manufacturer wants to know the specific positions of two of these components, such as capacitor C1 and resistor R2, inside the LED driver power supply. The manufacturer first uses a 3D scanner to scan the LED driver power supply to obtain its complete three-dimensional model data. This data contains the internal layout of the LED driver power supply and the precise position and shape of all components. After the scan is completed, the 3D scanner transmits the scan data to the server. The server starts processing this data to prepare for identifying the positions of the components. The server uses computer vision and image processing technologies to process and analyze the scan data. By identifying the features of the components (such as shape, size, pin layout, etc.), the server can determine the specific position of each component inside the LED driver power supply. Based on identifying the positions of all components, the server specifically focuses on the positions of capacitor C1 and resistor R2. They may be identified according to the component model number, label, or other unique identifiers. Finally, the server determines that capacitor C1 is located in the upper left corner of the LED driver power supply, while resistor R2 is located on its right side near the middle.

[0042] In a possible implementation manner, determining the first position corresponding to the first component and the second position corresponding to the second component according to the 3D scan data specifically includes: determining the LED driver power supply model according to the 3D scan data; extracting features from the LED driver power supply model to obtain the shape features, size features, and color features corresponding to each of the multiple components; performing image comparison on the shape features, size features, and color features with a preset feature group to obtain a target feature group, where one preset feature group corresponds to one component and one component corresponds to one position; and determining the first position corresponding to the first component and the second position corresponding to the second component based on the target feature group.

[0043] Specifically, a three-dimensional model of the LED driver power supply is constructed based on the 3D scan data. This model accurately reflects the internal structure of the LED driver power supply and the layout of the components. After obtaining the three-dimensional model of the LED driver power supply, the next step is to extract the features of each component in the model. These features include the shape, size, and color of the components, etc., which play a crucial role in the subsequent image comparison process. The shape feature describes the geometric form of the component, such as circular, square, rectangular, etc. The size feature describes the dimensions of the component, such as diameter, length, width, etc. The color feature describes the color information of the component. Although color information may not be directly obtained for some types of 3D scans (such as laser-based scans), it can be obtained in some optical-based scans or estimated through subsequent processing. The extracted features need to be compared with a preset feature group. The preset feature group is predefined, with each group corresponding to a component and containing the feature information such as the shape, size, and color of the component. Through comparison, the preset feature group that matches the features of the components in the scan data can be found, thereby determining the type of the component. Once the type of the component (i.e., the matching target feature group is found), its specific position can be determined based on its position in the LED driver power supply model. This position information is represented in coordinates or other forms.

[0044] For example, suppose there is an LED driver power supply that contains components such as capacitor C1, resistor R2, and transistor Q3. The goal is to determine the positions of capacitor C1 (the first component) and resistor R2 (the second component) in the LED driver power supply. Use a 3D scanner to scan the LED driver power supply to obtain its three-dimensional scan data. Then, use this data to construct a three-dimensional model of the LED driver power supply on the server. Extract the features of each component in the model. For example, extract the shape (cylindrical), size (diameter and height), and color (gray or blue, depending on the actual situation) of capacitor C1. Similarly, extract the corresponding features for resistor R2 and other components. Compare the extracted features with the preset feature group. The preset feature group contains the feature information of all possible components such as capacitor C1 and resistor R2. Through comparison, the preset feature groups that match the features of capacitor C1 and resistor R2 can be found. Once the types of capacitor C1 and resistor R2 are determined, their respective positions can be found in the three-dimensional model of the LED driver power supply. For example, it may be found that capacitor C1 is located in the upper left corner of the model, while resistor R2 is located below and near the middle.

[0045] In a possible implementation manner, based on the 3D scan data, an LED drive power supply model is determined, which specifically includes: obtaining the point cloud data of the LED drive power supply according to the 3D scan data, where the point cloud data includes bare board point cloud data and component point cloud data; performing separation processing on the bare board point cloud data to obtain first point cloud data; constructing the point cloud data in the first point cloud data into patches and performing smoothing processing on the patches to obtain second point cloud data; removing the bare board point cloud data in the second point cloud data that is not connected to the component point cloud data to obtain third point cloud data; performing smoothing processing on the bare board point cloud data in the third point cloud data to obtain fourth point cloud data; and constructing an LED drive power supply model based on the fourth point cloud data and the component point cloud data.

[0046] Specifically, after the 3D scan is completed, the point cloud data of the LED drive power supply will be obtained. The point cloud data is composed of a large number of points in space, and these points record the shape and position information of the object surface. In this scenario, the point cloud data is subdivided into bare board point cloud data and component point cloud data. The bare board point cloud data represents the surface information of the substrate (or called the bare board) of the LED drive power supply, while the component point cloud data represents the surface information of each component installed on the substrate. Since the bare board point cloud data and the component point cloud data may be mixed together during scanning, separation processing is required. The purpose of this step is to separate the bare board point cloud data from the total point cloud data for subsequent separate processing. The separated bare board point cloud data is composed of discrete points. To construct a three-dimensional model of the bare board, these points need to be connected into patches. This process involves algorithms such as triangulation. After constructing the patches, smoothing processing is also required to eliminate surface unevenness caused by scanning noise or errors, making the model smoother and more realistic. In the smoothed bare board point cloud data, there may still be some isolated points or small areas that are not connected to the component point cloud data. These areas may be caused by scanning noise or errors, so they need to be removed to ensure the accuracy of the final model. After removing the unconnected bare board point cloud data, further smoothing processing may be required for the remaining bare board point cloud data to further improve the quality of the model surface. Finally, the processed bare board point cloud data (i.e., the fourth point cloud data) is combined with the component point cloud data, and a complete LED drive power supply model is constructed through tools such as 3D modeling software. This model will include the shape and structure of the bare board and the position and form of each component installed on it.

[0047] S130. Based on the first position and the second position, determine the thermal interaction influence between the first component and the second component.

[0048] Specifically, the server has determined the specific positions of the first component and the second component in the LED driver power supply by processing 3D scan data. These position information are represented in coordinates or other forms, reflecting the precise positions of the components in three-dimensional space. In an electronic device, components generate heat during operation. If two components are close to each other in space, the heat generated by one component may affect the temperature of the other component through ways such as air convection, thermal radiation, or heat conduction. In the embodiment of the present application, this mutual influence is referred to as the thermal interaction influence. After determining the positions of the components, the server will evaluate the thermal interaction influence between them based on this position information and the thermal characteristics of the components (such as heat generation, thermal resistance, etc.). This involves techniques such as thermal simulation, thermal analysis, or thermal calculation. Through these techniques, the temperature distribution of the components under normal operating conditions and their thermal interaction can be predicted. Among them, understanding the thermal interaction influence between components is of great significance for the design, optimization, and fault prevention of electronic devices. It can help engineers predict and avoid problems caused by thermal interaction, such as overheating of components, performance degradation, or shortened lifespan.

[0049] In a possible implementation manner, based on the first position and the second position, to determine the thermal interaction influence between the first component and the second component, specifically includes: according to the first position and the second position, determine the heat conduction path between the first component and the second component; according to the heat conduction path, determine the first thermal resistance, the second thermal resistance, and the third thermal resistance. The first thermal resistance is the thermal resistance between the first component and the circuit board of the LED driver power supply, the second thermal resistance is the thermal resistance between the second component and the circuit board of the LED driver power supply, and the third thermal resistance is the thermal resistance between the circuit board of the LED driver power supply and the environment where the LED driver power supply is located; based on the first thermal resistance, the second thermal resistance, and the third thermal resistance, determine the thermal interaction influence.

[0050] Specifically, first, according to the specific positions of the first component and the second component in the LED driver power supply, determine the heat conduction paths between them and between them and the circuit board. The heat conduction path refers to the path through which heat is transferred from one component to another component or the circuit board and then further transferred to the environment. These paths may include air convection, thermal radiation, and the heat conduction of the circuit board material itself. After determining the heat conduction paths, the next step is to calculate the thermal resistances associated with these paths. Thermal resistance is a key parameter in the heat transfer process, which represents the ease of heat transfer. In this scenario, three main thermal resistances are involved: The first thermal resistance: the thermal resistance between the first component and the circuit board of the LED driver power supply. This thermal resistance reflects the ease of heat generated by the first component being transferred to the circuit board by a certain means (such as heat conduction, thermal radiation). The second thermal resistance: the thermal resistance between the second component and the circuit board of the LED driver power supply. Similar to the first thermal resistance, this thermal resistance reflects the heat transfer situation between the second component and the circuit board. The third thermal resistance: the thermal resistance between the circuit board of the LED driver power supply and the surrounding environment. This thermal resistance indicates how the heat on the circuit board is transferred to the surrounding environment (such as air). After obtaining the first thermal resistance, the second thermal resistance, and the third thermal resistance, the thermal interaction influence between the first component and the second component can be calculated based on these thermal resistances. This process involves complex thermal calculations or simulations to evaluate the impact of the heat generated by one component on the temperature of another component.

[0051] In a possible implementation manner, based on the first thermal resistance, the second thermal resistance, and the third thermal resistance, determine the thermal interaction influence, which specifically includes: obtaining the first power consumption corresponding to the first component and obtaining the second power consumption corresponding to the second component; receiving the ambient temperature sent by the ambient temperature sensor for the environment where the LED driver power supply is located; calculating the temperature of the first component based on the first power consumption, the first thermal resistance, and the ambient temperature; calculating the temperature of the second component based on the second power consumption, the second thermal resistance, and the ambient temperature; and calculating the thermal interaction influence according to the temperature of the first component and the temperature of the second component.

[0052] Specifically, first, it is necessary to obtain the power consumption of the first component (such as a high-power LED) and the second component (such as a temperature-sensitive diode). Power consumption refers to the electrical energy consumed by a component during operation, which directly determines the heat generated by the component. These power consumption values can be obtained from the component's data sheet or through actual measurement. Next, it is necessary to receive the ambient temperature sent by the ambient temperature sensor for the environment where the LED driver power supply is located. Ambient temperature is one of the starting or ending points of heat transfer and is crucial for evaluating the component temperature and the thermal interaction influence between them. Based on the power consumption, thermal resistance, and ambient temperature of the components, thermal formulas can be used to calculate the temperature of the components. Specifically, for each component, its temperature can be regarded as a function of power consumption, thermal resistance, and ambient temperature. By solving this thermal equation, the temperature of the component under the working state can be obtained. After obtaining the temperatures of the two components, the thermal interaction influence between them can be evaluated. The thermal interaction influence can be regarded as the degree of influence of the temperature change of one component on the temperature of another component, measuring the degree of mutual influence between the two components due to heat conduction. A higher thermal interaction influence indicates a more significant thermal interaction between the components, which may cause the component temperature to deviate from its designed operating temperature range, thereby affecting the performance and lifespan of the LED driver power supply. It can be quantified by comparing the temperature differences of the two components with and without thermal interaction. The specific calculation formula is as follows:

[0053] ;

[0054] where, T 1 ＇ and T 2 ＇ are the temperatures of the first component and the second component when operating under mutual thermal influence respectively; T 1 and T 2 are the temperatures of the first component and the second component when operating independently (i.e., without considering mutual thermal influence) respectively. T avg is the average temperature of the two components when operating independently, that is, (T 1 +T 2 ) / 2, which is used for normalizing the calculation of the thermal interaction influence.

[0055] Next, use the power consumption P 1 of the first component, the first thermal resistance R th1 and the ambient temperature T amb , and calculate the temperature of the first component through the formula T 1 =T amb +P 1 ×R th1 . Similarly, use the power consumption P 2 of the second component and the second thermal resistance R th2Calculate the temperature T of the second component 2 。

[0056] For example, assume there are two components in two LED driver power supplies. The first component is a high-power switching transistor, and the second component is a temperature-sensitive capacitor. When working independently, the temperature T of the switching transistor 1 = 80 °C, and the temperature T of the capacitor 2 = 60 °C. When they work simultaneously, due to thermal interaction, the temperature of the switching transistor rises to T 1 ＇ = 85 °C, and the temperature of the capacitor rises to T 2 ＇ = 65 °C due to the thermal radiation of the switching transistor. At this time, T avg = (80 + 60) / 2 = 70 °C, and the thermal interaction influence T is approximately equal to 0.071. This value represents the percentage of the temperature change caused by thermal interaction between the two components relative to their average temperature, providing a basis for designers to evaluate the rationality of thermal design.

[0057] In addition, if the importance or thermal sensitivity of the two components in the system is different, the weighted sum of their temperature rises can be considered. The choice of weights depends on the specific application scenario and design requirements, which will not be elaborated here.

[0058] In a possible implementation manner, according to the first position and the second position, determine the heat conduction path between the first component and the second component, specifically including: obtaining the first material property corresponding to the first component, and obtaining the second material property corresponding to the second component; if it is determined that the LED driver power supply includes a heat sink, obtain the heat dissipation path; according to the first position and the second position, combining the first material property, the second material property, and the heat dissipation path, construct a thermal network model of the LED driver power supply; according to the thermal network model, determine the heat conduction path between the first component and the second component.

[0059] Specifically, each component (such as capacitors, inductors, semiconductor devices, etc.) has its specific material properties, which directly affect its heat conduction and thermal resistance performance. For example, metals have good heat conductivity, while some plastics or ceramics are relatively poor. In this step, it is necessary to obtain the material properties of the first component (such as a power transistor) and the second component (such as a capacitor near a heat sink), such as thermal conductivity, specific heat capacity, etc. The heat sink is a key component for heat dissipation in the LED driver power supply. It helps the components dissipate heat by increasing the surface area and / or using highly efficient heat conduction materials. If the driver power supply includes a heat sink, it is necessary to further obtain the structure, position of the heat sink and its connection method with the components in order to analyze the heat conduction path subsequently. The thermal network model is a mathematical model that simulates the heat flow in a system. It takes into account the positions of the components, their material properties, and their thermal connections (such as heat conduction paths) with each other. In this step, according to the first position and the second position of the components, combined with their material properties and (if any) heat dissipation paths, a thermal network model of the entire LED driver power supply is constructed using thermal network analysis software or algorithms. By analyzing the constructed thermal network model, the heat flow between the components and through the heat dissipation path can be calculated. Especially for the first component and the second component, the heat conduction path between them can be clarified, including direct heat conduction (such as through the PCB board) and indirect heat conduction (such as through the heat sink).

[0060] For example, suppose there is an LED driver power supply that includes a high-power MOSFET (the first component) located in the center of the PCB board and an aluminum electrolytic capacitor (the second component) near the heat sink. Obtain material properties: The MOSFET is mainly made of silicon and has good heat conductivity; the aluminum electrolytic capacitor contains electrolyte and an aluminum shell, and its heat conductivity is relatively low. This driver power supply includes an aluminum heat sink located on one side of the PCB board and is in contact with the heat source (such as the MOSFET) on the PCB board through a thermal pad. Taking the MOSFET, capacitor, PCB board, and heat sink as nodes, according to their actual connections (such as the MOSFET is connected to the heat sink through the PCB board, and the capacitor is indirectly connected to the MOSFET or other components through the copper foil on the PCB board) and their respective material properties, a thermal network model is constructed. Through the analysis of the thermal network model, it can be determined that the heat generated by the MOSFET is mainly conducted to the heat sink through the PCB board, and at the same time, a part of the heat is also conducted to the capacitor through the copper foil on the PCB board. In this way, the heat conduction path between the MOSFET and the capacitor is clarified.

[0061] S140. If it is determined that the thermal interaction influence is within the preset influence range, then it is determined that the LED driver power supply is qualified, and the preset influence range is set in advance according to the first component and the second component.

[0062] S150. If it is determined that the thermal interaction influence is not within the preset influence range, it is determined that the LED driver power supply is unqualified.

[0063] Specifically, the preset influence range is set in advance through thermal simulation experiments according to the design requirements of the LED driver power supply, the characteristics of the components, and the overall performance objectives of the system. It defines an acceptable range of thermal interaction influence, that is, the thermal interaction influence within this range is considered normal and will not have an adverse impact on the system performance. This range is preset for specific component pairs (such as the first component and the second component) because different component pairs may have different thermal interaction characteristics. After obtaining the actual thermal interaction influence through measurement or calculation, it is compared with the preset influence range. If the thermal interaction influence is within the preset range, it indicates that the LED driver power supply meets the design requirements in terms of thermal interaction and is therefore determined to be qualified. If the thermal interaction influence exceeds the preset range, it indicates that there are problems with the LED driver power supply in terms of thermal interaction, which may lead to a decrease in system performance or component damage, and is therefore determined to be unqualified. Therefore, when performing factory quality inspection on the LED driver power supply, this method is convenient for improving the detection accuracy of the LED driver power supply.

[0064] In a possible implementation manner, referring to Figure 2 , Figure 2 FIG. is another flowchart of a method for detecting an LED driver power supply provided by an embodiment of the present application. It includes steps S210 to S230, and the above steps are as follows: S210. Obtain the standard layout data of the LED driver power supply; S220. According to the standard layout data, mark the heat dissipation abnormal components included in the unqualified LED driver power supply in the LED driver power supply model to obtain a model to be displayed; S230. Display the model to be displayed through an AR device.

[0065] Specifically, the standard layout data refers to a standardized component layout information that the LED driver power supply follows during the design and manufacturing processes. This layout is determined based on factors such as optimal thermal management, electrical performance, and manufacturing efficiency. The server obtains this standard layout data in a certain way (such as from a database, design file, or data packet provided by the manufacturer). The server compares the actual layout or test data of the unqualified LED driver power supply with the standard layout data. Through this comparison, the server can identify which components have positions, models, or connection methods that do not conform to the standard layout, especially those components that may cause abnormal heat dissipation. These components with abnormal heat dissipation may be due to improper positions, mismatched models, or blocked heat dissipation paths. Once the components with abnormal heat dissipation are identified, the server marks these components in the virtual model of the LED driver power supply. The marking may include highlighting, adding annotations, or changing colors, etc., so that users can intuitively see which components have problems. The server sends the model to be displayed to an AR device (such as AR glasses, tablets, or smartphones, etc.). The AR device combines the virtual model to be displayed with the real-world environment using its own display and tracking technologies, presenting a mixed reality effect. Users can view through the AR device which components in the LED driver power supply model have abnormal heat dissipation and can observe and analyze from multiple angles and distances, facilitating later rework and remanufacturing.

[0066] This application also provides a detection device for an LED driver power supply. Referring to Figure 3 , Figure 3 is a schematic diagram of the modules of a detection device for an LED1 driver power supply provided by an embodiment of this application. The detection device is a server, including an acquisition module 31 and a processing module 32. Among them, the acquisition module 31 acquires 3D scan data for the LED driver power supply; the processing module 32 determines a first position corresponding to a first component and a second position corresponding to a second component according to the 3D scan data. The LED driver power supply includes multiple components, and the first component and the second component are any two components among the multiple components; the processing module 32 determines the thermal interaction influence between the first component and the second component based on the first position and the second position; if the processing module 32 determines that the thermal interaction influence is within a preset influence range, it determines that the LED driver power supply is qualified, and the preset influence range is pre-correspondingly set according to the first component and the second component; if the processing module 32 determines that the thermal interaction influence is not within the preset influence range, it determines that the LED driver power supply is unqualified.

[0067] In a possible implementation, the processing module 32 determines a first position corresponding to a first component and a second position corresponding to a second component according to the 3D scan data. Specifically, the processing module 32 determines an LED driver power supply model according to the 3D scan data; the processing module 32 extracts features from the LED driver power supply model to obtain shape features, size features, and color features corresponding to each of the multiple components; the processing module 32 performs image comparison on the shape features, size features, and color features with a preset feature group to obtain a target feature group, where one preset feature group corresponds to one component, and one component corresponds to one position; the processing module 32 determines the first position corresponding to the first component and the second position corresponding to the second component based on the target feature group.

[0068] In a possible implementation, the processing module 32 determines an LED driver power supply model according to the 3D scan data. Specifically, the processing module 32 obtains point cloud data of the LED driver power supply according to the 3D scan data, and the point cloud data includes bare board point cloud data and component point cloud data; the processing module 32 performs separation processing on the bare board point cloud data to obtain first point cloud data; the processing module 32 constructs the first point cloud data into patches and smooths the patches to obtain second point cloud data; the processing module 32 removes the bare board point cloud data that is not connected to the component point cloud data in the second point cloud data to obtain third point cloud data; the processing module 32 smooths the bare board point cloud data in the third point cloud data to obtain fourth point cloud data; the processing module 32 constructs an LED driver power supply model according to the fourth point cloud data and the component point cloud data.

[0069] In a possible implementation, the processing module 32 determines the thermal interaction influence between the first component and the second component based on the first position and the second position. Specifically, the processing module 32 determines a heat conduction path between the first component and the second component according to the first position and the second position; the processing module 32 determines a first thermal resistance, a second thermal resistance, and a third thermal resistance according to the heat conduction path, where the first thermal resistance is the thermal resistance between the first component and the circuit board of the LED driver power supply, the second thermal resistance is the thermal resistance between the second component and the circuit board of the LED driver power supply, and the third thermal resistance is the thermal resistance between the circuit board of the LED driver power supply and the environment where the LED driver power supply is located; the processing module 32 determines the thermal interaction influence based on the first thermal resistance, the second thermal resistance, and the third thermal resistance.

[0070] In a possible implementation manner, the processing module 32 determines the thermal interaction influence based on the first thermal resistance, the second thermal resistance, and the third thermal resistance. Specifically, it includes: the acquisition module 31 acquires the first power consumption corresponding to the first component and the second power consumption corresponding to the second component; the acquisition module 31 receives the ambient temperature of the environment where the LED driver power supply is located sent by the ambient temperature sensor; the processing module 32 calculates the temperature of the first component based on the first power consumption, the first thermal resistance, and the ambient temperature; the processing module 32 calculates the temperature of the second component based on the second power consumption, the second thermal resistance, and the ambient temperature; the processing module 32 calculates the thermal interaction influence according to the temperature of the first component and the temperature of the second component.

[0071] In a possible implementation manner, the processing module 32 determines the heat conduction path between the first component and the second component according to the first position and the second position. Specifically, it includes: the acquisition module 31 acquires the first material property corresponding to the first component and the second material property corresponding to the second component; if the processing module 32 determines that the LED driver power supply includes a radiator, it acquires the heat dissipation path; the processing module 32 constructs a thermal network model of the LED driver power supply according to the first position and the second position, in combination with the first material property, the second material property, and the heat dissipation path; the processing module 32 determines the heat conduction path between the first component and the second component according to the thermal network model.

[0072] In a possible implementation manner, the acquisition module 31 acquires the standard layout data of the LED driver power supply; the processing module 32 marks the heat dissipation abnormal components included in the unqualified LED driver power supply in the LED driver power supply model according to the standard layout data to obtain a model to be displayed; the processing module 32 displays the model to be displayed through an AR device.

[0073] It should be noted that: when the device provided in the above embodiment realizes its functions, only the above-mentioned division of each functional module is used for illustration. In actual applications, the above functions can be allocated to different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0074] This application also provides an electronic device. Refer to Figure 4 , Figure 4 which is a schematic structural diagram of an electronic device provided in an embodiment of this application. The electronic device may include: at least one processor 41, at least one network interface 44, a user interface 43, a memory 45, and at least one communication bus 42.

[0075] Among them, the communication bus 42 is used to realize the connection and communication between these components.

[0076] Among them, the user interface 43 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 43 may also include a standard wired interface and a wireless interface.

[0077] Among them, the network interface 44 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface).

[0078] Among them, the processor 41 may include one or more processing cores. The processor 41 uses various interfaces and circuits to connect various parts within the entire server. By running or executing instructions, programs, code sets, or instruction sets stored in the memory 45, and by calling the data stored in the memory 45, it executes various functions of the server and processes data. Optionally, the processor 41 may be implemented in at least one of the hardware forms of digital signal processing (DSP), field-programmable gate array (FPGA), and programmable logic array (PLA). The processor 41 may integrate a combination of one or several of a central processing unit (CPU), a graphics processing unit (GPU), and a modem, etc. Among them, the CPU mainly processes the operating system, user interface, application programs, etc.; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communication. It can be understood that the above-mentioned modem may not be integrated into the processor 41 and may be implemented separately by a single chip.

[0079] Among them, the memory 45 may include a Random Access Memory (RAM), or may also include a Read-Only Memory. Optionally, the memory 45 includes a non-transitory computer-readable storage medium. The memory 45 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 45 may include a program storage area and a data storage area. Among them, the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned method embodiments, etc.; the data storage area may store data involved in the above-mentioned method embodiments. Optionally, the memory 45 may also be at least one storage device located far from the aforementioned processor 41. As Figure 4 shown, in the memory 45 as a computer storage medium, there may be included an operating system, a network communication module, a user interface module, and an application program for a method of detecting an LED driving power supply.

[0080] In Figure 4 the electronic device shown, the user interface 43 is mainly used to provide an input interface for the user to obtain user input data; and the processor 41 can be used to call the application program for a method of detecting an LED driving power supply stored in the memory 45. When executed by one or more processors, the electronic device is caused to execute the method as described in one or more of the above embodiments.

[0081] It should be noted that for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that this application is not limited by the described action sequence, because according to this application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0082] This application also provides a computer-readable storage medium, and the computer-readable storage medium stores instructions. When executed by one or more processors, the electronic device is caused to execute the method as described in one or more of the above embodiments.

[0083] In the above embodiments, the descriptions of the various embodiments have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0084] In several embodiments provided in the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection between each other can be through some service interfaces. The indirect coupling or communication connection of the device or unit can be in electrical or other forms.

[0085] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0086] In addition, in each embodiment of the present application, each functional unit can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0087] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to enable a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the methods in each embodiment of the present application. The aforementioned memory includes: various media such as USB flash drives, mobile hard disks, magnetic disks or optical discs that can store program codes.

[0088] The above are only exemplary embodiments of the present disclosure and should not be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made in accordance with the teachings of the present disclosure still fall within the scope covered by the present disclosure. After considering the specification and the disclosure of the practical truth, those skilled in the art will easily think of other implementation schemes of the present disclosure. The present application aims to cover any variations, uses or adaptive changes of the present disclosure, and these variations, uses or adaptive changes follow the general principles of the present disclosure and include the common general knowledge or conventional technical means in the technical field not recorded in the present disclosure. The specification and the embodiments are only regarded as exemplary, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A method for detecting an LED driving power supply, characterized in that: The method comprises: Get 3D scan data for LED driver power supply; Determine, according to the 3D scanning data, a first position corresponding to a first component and a second position corresponding to a second component, wherein the LED driving power supply includes a plurality of components, and the first component and the second component are any two components among the plurality of components; Determining a thermal interaction influence between the first component and the second component based on the first position and the second position; If it is determined that the thermal interaction influence is within a preset influence range, then the LED driving power supply is determined to be qualified, and the preset influence range is pre-set according to the first component and the second component; If it is determined that the thermal interaction influence is not within the preset influence range, then the LED driving power supply is determined to be unqualified; The determining, based on the first position and the second position, the thermal interaction influence between the first component and the second component specifically includes: Determining a heat conduction path between the first component and the second component according to the first position and the second position; According to the heat conduction path, a first thermal resistance, a second thermal resistance and a third thermal resistance are determined, wherein the first thermal resistance is the thermal resistance between the first component and the circuit board of the LED driver power supply, the second thermal resistance is the thermal resistance between the second component and the circuit board of the LED driver power supply, and the third thermal resistance is the thermal resistance between the circuit board of the LED driver power supply and the environment in which the LED driver power supply is located; determining the thermal interaction influence based on the first thermal resistance, the second thermal resistance, and the third thermal resistance; The determining the thermal interaction influence based on the first thermal resistance, the second thermal resistance and the third thermal resistance specifically includes: Obtaining a first power consumption corresponding to the first component, and obtaining a second power consumption corresponding to the second component; Receiving an ambient temperature of an environment in which the LED driving power supply is located, sent by an ambient temperature sensor; Calculating a first component temperature based on the first power consumption, the first thermal resistance, and the ambient temperature; Calculating a second component temperature based on the second power consumption, the second thermal resistance and the ambient temperature; Calculating the thermal interaction influence according to the first component temperature and the second component temperature; The thermal interaction influence is specifically calculated using the following formula: ； Among them, T is the thermal interaction influence, T1 ＇ and T2 ＇ are the temperatures of the first component and the second component when they work under mutual thermal influence; T1 and T2 are the temperatures of the first component and the second component when they work independently, that is, without considering mutual thermal influence; T avg is the average temperature of the first component and the second component when they work independently, that is, (T1+T2) / 2, which is used to calculate the normalized thermal interaction influence; Using the first power consumption P1 and the first thermal resistance R of the first component th1 and ambient temperature T amb , through the formula T1=T amb +P1×R th1 The temperature of the first component is calculated; similarly, the second power consumption P2 and the second thermal resistance R of the second component are used. th2 Calculate the second component temperature T2.

2. The detection method of LED driving power supply according to claim 1, characterized in that: Determining a first position corresponding to the first component and a second position corresponding to the second component according to the 3D scanning data specifically includes: Determine an LED driving power supply model according to the 3D scanning data; Extracting features of the LED driving power supply model to obtain shape features, size features, and color features corresponding to the components; Performing image comparison on the shape feature, the size feature and the color feature with a preset feature group to obtain a target feature group, wherein one preset feature group corresponds to one component, and one component corresponds to one position; Based on the target feature group, a first position corresponding to the first component and a second position corresponding to the second component are determined.

3. The detection method of LED driving power supply according to claim 2, characterized in that: Determining the LED driving power supply model according to the 3D scanning data specifically includes: According to the 3D scanning data, point cloud data of the LED driving power supply is obtained, wherein the point cloud data includes bare board point cloud data and component point cloud data; Separating and processing the bare board point cloud data to obtain first point cloud data; Constructing each point cloud data in the first point cloud data into a surface patch, and performing smoothing processing on the surface patch to obtain second point cloud data; removing bare board point cloud data that is not connected to the component point cloud data from the second point cloud data to obtain third point cloud data; Smoothing the bare plate point cloud data in the third point cloud data to obtain fourth point cloud data; The LED driving power supply model is constructed based on the fourth point cloud data and the component point cloud data.

4. The method for detecting an LED driving power supply according to claim 1, characterized in that: The determining, according to the first position and the second position, a heat conduction path between the first component and the second component specifically includes: Acquire a first material property corresponding to the first component, and acquire a second material property corresponding to the second component; If it is determined that the LED driving power supply includes a heat sink, obtaining a heat dissipation path; According to the first position and the second position, in combination with the first material property, the second material property and the heat dissipation path, a thermal network model of the LED driving power supply is constructed; A heat conduction path between the first component and the second component is determined according to the thermal network model.

5. The method for detecting an LED driving power supply according to claim 2, characterized in that: The method further comprises: Acquiring standard layout data of the LED driving power supply; According to the standard layout data, abnormal heat dissipation components contained in the unqualified LED driver power supply are marked in the LED driver power supply model to obtain a model to be displayed; The model to be displayed is displayed through an AR device.

6. A detection device for LED driving power supply, characterized in that: The detection device executes the method according to any one of claims 1 to 5, and comprises an acquisition module (31) and a processing module (32), wherein: The acquisition module (31) is used to acquire 3D scanning data for the LED driving power supply; The processing module (32) is used to determine a first position corresponding to a first component and a second position corresponding to a second component according to the 3D scanning data, wherein the LED driving power supply includes a plurality of components, and the first component and the second component are any two components among the plurality of components; The processing module (32) is further used to determine the thermal interaction influence between the first component and the second component based on the first position and the second position; The processing module (32) is further configured to determine that the LED driving power supply is qualified if it is determined that the thermal interaction influence is within a preset influence range, wherein the preset influence range is pre-set correspondingly according to the first component and the second component; The processing module (32) is further configured to determine that the LED driving power supply is unqualified if it is determined that the thermal interaction influence is not within the preset influence range.

7. An electronic device, characterized in that: The electronic device comprises a processor (41), a memory (45), a user interface (43) and a network interface (44), wherein the memory (45) is used to store instructions, the user interface (43) and the network interface (44) are both used to communicate with other devices, and the processor (41) is used to execute the instructions stored in the memory (45) so that the electronic device executes the method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 5 is performed.

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