Detection method and device of LED driving power supply and electronic equipment

Abstract

The invention provides a detection method and device of an LED driving power supply and electronic equipment, and relates to the technical field of detection. The method comprises the following steps: acquiring 3D scanning data for an LED driving power supply; according to the 3D scanning data, a first position corresponding to the first component and a second position corresponding to the second component are determined, the LED driving power supply comprises a plurality of components, and the first component and the second component are any two components in the plurality of components; determining 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, it is determined that the LED driving power supply is qualified, and the preset influence range is correspondingly set in advance according to the first component and the second component; and 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. By implementing the technical scheme provided by the invention, the detection accuracy of the LED driving power supply can be improved.

Description

Technical Field

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

[0002] In the context of the rapid development of LED lighting technology, the performance and quality of LED driver power supply, as the core component of LED lighting system, directly affect the stability and reliability of the entire lighting system. However, in the traditional factory quality inspection process of LED driver power supply, there are often significant technical limitations and deficiencies.

[0003] Traditionally, quality inspection of LED driver 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 in the test results. At the same time, manual inspection is difficult to fully cover all potential defects and problems, especially for complex circuit structures and minor component failures, which are often difficult to accurately identify. Therefore, the above traditional detection accuracy of LED driver power supplies is low.

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

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

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

[0007] By adopting the above technical solution, by obtaining 3D scanning data of the LED driver power supply, the method can capture the precise position and shape of each component inside the power supply with unprecedented accuracy. This high accuracy not only helps the subsequent analysis, but also ensures the accuracy of the test 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. Through the automatic analysis of 3D scanning data by software algorithms, the positional relationship between components can be quickly determined, and then the thermal interaction influence can be evaluated. This method not only focuses on the basic functions of the LED driver power supply, but also deeply analyzes the thermal interaction influence between components. This comprehensiveness and depth helps to discover potential heat dissipation problems or design defects that may be difficult to detect in simple performance tests. By evaluating the thermal interaction influence, the performance and stability of the power supply in actual use can be more accurately judged. The setting of the preset influence range makes this method flexible and adaptable. Different combinations of components may have different thermal interaction characteristics. By pre-setting the corresponding influence range, customized detection can be performed for LED driver power supplies of different types and specifications. This flexibility helps to meet the detection needs in different application scenarios. By comprehensively considering the position of components and the influence of thermal interaction, this method can more accurately judge the quality of 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, thereby 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 easy to improve the detection accuracy of LED driver power supply.

[0008] Optionally, determining a first position corresponding to a first component and a second position corresponding to a second component according to the 3D scanning data specifically includes: determining an LED driver power supply model according to the 3D scanning data; performing feature extraction on the LED driver power supply model to obtain shape features, size features and color features corresponding to a plurality of the components; performing image comparison on the shape features, the size features and the color features 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; and determining a first position corresponding to the first component and a second position corresponding to the second component based on the target feature group.

[0009] By adopting the above technical solution, the LED driver power supply model is constructed through 3D scanning data, which can accurately restore the internal structure and component layout of the power supply. The subsequent feature extraction process, including shape features, size features and color features, further refines the recognition accuracy of components. This multi-dimensional feature extraction method makes the identification of components more accurate, thereby improving the accuracy of determining the location of components. The entire process is highly automated, from model construction to feature extraction, to image comparison and position determination, all relying 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 group and quickly locate the target component, further improving the intelligent level of detection. The setting of the preset feature group makes this method adaptable and flexible. Different LED driver power supplies may contain different types of components. By pre-defining multiple feature groups, various detection requirements can be flexibly responded to. At the same time, when encountering new components or design changes, only the preset feature group needs to be updated, without large-scale adjustments to the entire detection process. By comprehensively considering multiple features of components, such as shape, size, and color, this method can more comprehensively identify components and accurately determine their locations. This comprehensive recognition method helps reduce misjudgments and missed judgments and improves the reliability of detection. At the same time, 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 scanning data specifically includes: obtaining point cloud data of the LED driver power supply according to the 3D scanning data, the point cloud data including bare board point cloud data and component point cloud data; separating 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 facet, and smoothing the facet 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; smoothing 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 scanning data is subdivided into bare board point cloud data and component point cloud data. This refined classification provides a basis for subsequent processing. By gradually processing the bare board point cloud data, including separation, surface 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 entire 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 completed automatically through computer algorithms and software tools. This not only improves work efficiency, but also reduces the risk of human error. Automated processing makes it more efficient and reliable when processing large amounts of data. By smoothing multiple times and removing unnecessary point cloud data, the noise and interference factors in the model are effectively reduced. Smoothing 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 that the position of the components in the model is accurate and consistent with the actual situation. The constructed LED driver power supply model is an important basis for subsequent thermal interaction influence analysis, performance evaluation, and design optimization. An accurate model can provide more reliable data support and help to gain a deeper understanding of the performance and stability of the power supply. At the same time, the component location information in the model is also one of the key factors in 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 a 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, the first thermal resistance being the thermal resistance between the first component and the circuit board of the LED driver power supply, the second thermal resistance being the thermal resistance between the second component and the circuit board of the LED driver power supply, and the third thermal resistance being 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.

[0013] By adopting the above technical solution, by determining the heat conduction path between components and calculating the relevant thermal resistance values ​​(including the first thermal resistance, the second thermal resistance and the third thermal resistance) based on it, 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 relying solely on experience or intuitive judgment, and can more accurately reflect the thermal interaction of components in actual work. This method not only considers the direct heat conduction between components, but also considers the thermal resistance between them and the circuit board and the environment. This comprehensive consideration makes the evaluation results 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 resistance values ​​and determining the thermal interaction influence based on these values, this method has a certain degree of predictability. In the product design stage, this method can be used to predict the impact 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 make targeted optimizations in the design stage. This method not only helps to improve the overall performance of the product, but also reduces the failure rate and maintenance costs caused by overheating. During the production process, by quickly evaluating the thermal interaction between components, potential thermal problems can be discovered and adjusted in a timely manner. This helps reduce rework and repair work caused by thermal problems and improves 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 a first power consumption corresponding to the first component, and obtaining a second power consumption corresponding to the second component; receiving an ambient temperature for the environment in which the LED driver 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; and calculating the thermal interaction influence based on the first component temperature and the second component temperature.

[0015] By adopting the above technical solution, the method can more accurately calculate the actual operating temperature of the components by comprehensively considering the three key factors of the power consumption, thermal resistance and ambient temperature of the components. This accuracy is crucial for evaluating the thermal interaction between components, because temperature is one of the key factors affecting heat conduction and heat radiation. Based on the basic principles of thermodynamics, this method connects physical quantities such as the power consumption, thermal resistance and ambient temperature of the components through a mathematical model to calculate the temperature of the components. This scientific method is more reliable than relying solely on experience or intuitive judgment, and can more accurately reflect the thermal state of the components in actual work. In 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. This comprehensive consideration makes the evaluation results 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 data from the ambient temperature sensor in real time, the temperature and thermal interaction influence of the components can be dynamically calculated.

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

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

[0018] Optionally, the method also includes: obtaining standard layout data of the LED driver power supply; marking abnormal heat dissipation components contained in an 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; and displaying the model to be displayed through an AR device.

[0019] By adopting the above technical solution, by obtaining 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 troubleshooting and reduces the time and workload of manual inspection. Compared with troubleshooting based on experience or intuition alone, using standard layout data as a reference can more accurately locate problematic components. Standard layout data usually contains information such as the precise location, model, and specifications of components, providing a reliable basis for troubleshooting. It is very intuitive to mark components with abnormal heat dissipation in the LED driver power supply model, obtain the model to be displayed, and display it through AR devices. AR technology can superimpose virtual information on the real world, allowing users to intuitively see the location and status of problematic components, and troubleshoot without disassembling or opening the device.

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

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

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

[0023] In summary, one or more technical solutions provided in this application have at least the following technical effects or advantages: By acquiring 3D scan data of the LED driver, this method can capture the precise position and shape of each component inside the power supply with unprecedented accuracy. This high accuracy not only helps with subsequent analysis, but also ensures the accuracy of the test results. Compared with traditional manual inspection, this method realizes the automation of the detection process. Automation not only improves detection efficiency, reduces the time and cost of manual operation, but also reduces the risk of human error. Through the automatic analysis of 3D scan data by software algorithms, the positional relationship between components can be quickly determined, and then the thermal interaction influence can be evaluated. This method not only focuses on the basic functions of the LED driver, but also deeply analyzes the thermal interaction influence between components. This comprehensiveness and depth helps to discover potential heat dissipation problems or design defects that may be difficult to detect in simple performance tests. By evaluating the thermal interaction influence, the performance and stability of the power supply in actual use can be more accurately judged. The setting of the preset influence range makes this method flexible and adaptable. Different combinations of components may have different thermal interaction characteristics. By pre-setting the corresponding influence range, customized detection can be performed for LED drivers of different types and specifications. This flexibility helps to meet the detection needs in different application scenarios. By comprehensively considering the position of components and the influence of thermal interaction, this method can more accurately judge the quality of 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, thereby 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 easy to improve the detection accuracy of LED driver power supply. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A schematic flow chart of a method for detecting an LED driving power supply provided in an embodiment of the present application.

[0025] Figure 2 Another schematic flow chart of a method for detecting an LED driving power supply provided in an embodiment of the present application.

[0026] Figure 3 A module schematic diagram of a detection device for an LED driving power supply provided in an embodiment of the present application.

[0027] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0028] Explanation of the reference numerals: 31, acquisition module; 32, processing module; 41, processor; 42, communication bus; 43, user interface; 44, network interface; 45, memory. DETAILED DESCRIPTION

[0029] In order to enable technicians in this field 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 drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0030] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.

[0031] In the description of the embodiments of the present application, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0032] In the era of rapid development of LED lighting technology, the performance and quality assurance of LED driver power supply, as the lifeblood of the system, are directly related to the stable operation and reliability of the entire lighting system. However, looking back at the factory quality inspection process of traditional LED driver power supply, it is not difficult to find significant technical bottlenecks and deficiencies.

[0033] Traditional detection methods 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 between detection results. More importantly, manual detection is difficult to deeply explore the potential defects in the subtle structure and complex circuits of the product, especially when facing subtle faults of miniature 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 supply by traditional detection mode, resulting in limitations in the overall detection accuracy.

[0034] In order to solve the above technical problems, the present application provides a detection method for LED driving power supply, referring to Figure 1 , Figure 1A flow chart of a method for detecting an LED driving power supply provided in an embodiment of the present application. The detection method is applied to a server and includes steps S110 to S150, which are as follows: S110, obtaining 3D scanning data for the LED driving power supply.

[0035] Specifically, a server is a high-performance computer device for storing, processing, and transmitting data or applications. In an embodiment of the present application, the server is used as a central point for data processing and storage, and is responsible for receiving, processing, and storing data from external devices or systems. The 3D scanning data for the LED driver power supply refers to data on the three-dimensional shape, size, structure, and other information of the LED driver power supply obtained using 3D scanning technology. 3D scanning technology is a non-contact measurement method that can quickly and accurately obtain a three-dimensional model of an object. Among them, the 3D scanning data for the LED driver power supply does not include its outer shell, but includes detailed information such as its internal layout, component location, and heat dissipation structure.

[0036] For example, suppose an LED luminaire manufacturer needs to perform accurate 3D modeling and performance analysis of its newly designed LED driver. To achieve this goal, they may take the following steps during factory inspection: First, the manufacturer will place the LED driver in an environment suitable for 3D scanning, ensuring that there are no obstructions and the scanning area is well lit. At the same time, they may use markers 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. The scanner will emit lasers or light onto the surface of the object and capture the reflected light to calculate the 3D coordinates of the object. This process may require scanning from multiple angles to ensure that a complete and accurate 3D model is obtained. After the scan is completed, the 3D scanner will transmit the acquired 3D scan data to a 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.

[0037] S120. Determine, based on the 3D scanning data, a first position corresponding to the first component and a second position corresponding to the 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.

[0038] Specifically, as mentioned above, this is data about the three-dimensional shape, size, structure and other information of the LED driver power supply obtained through 3D scanning technology. These data contain the precise position and shape information of all components inside the LED driver power supply. By processing and analyzing the 3D scanning 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, "first component" and "second component" refer to any two specific components in the LED driver power supply. These two components can be any type of components, such as capacitors, resistors, transistors, etc. On the basis of determining the positions of all components, the server pays special attention to and determines the specific positions of these two components.

[0039] For example, suppose there is an LED driver that contains multiple components, such as capacitor C1, resistor R2, transistor Q3, etc. The manufacturer wants to know the specific locations of two of the components, such as capacitor C1 and resistor R2, inside the LED driver. The manufacturer first uses a 3D scanner to scan the LED driver to obtain its complete three-dimensional model data. This data contains the internal layout of the LED driver and the precise location and shape of all components. After the scan is completed, the 3D scanner transmits the scan data to the server. The server begins to process the data and prepares to identify the location of the components. The server uses computer vision and image processing technology to process and analyze the scan data. By identifying the characteristics of the components (such as shape, size, pin layout, etc.), the server can determine the specific location of each component inside the LED driver. Based on the identification of all component locations, the server pays special attention to the locations of capacitor C1 and resistor R2. They may be identified based on the component model, label or other unique identifier. Finally, the server determines that capacitor C1 is located in the upper left corner of the LED driver, while resistor R2 is located near the middle of its right side.

[0040] In a possible implementation, a first position corresponding to a first component and a second position corresponding to a second component are determined based on 3D scanning data, specifically including: determining an LED driver power supply model based on the 3D scanning data; performing feature extraction on the LED driver power supply model to obtain shape features, size features, and color features corresponding to 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, wherein one preset feature group corresponds to one component, and one component corresponds to one position; based on the target feature group, determining a first position corresponding to the first component and a second position corresponding to the second component.

[0041] Specifically, a three-dimensional model of the LED driver is constructed based on the 3D scanning data. This model accurately reflects the internal structure of the LED driver and the layout of the components. After obtaining the three-dimensional model of the LED driver, the next step is to extract features from each component in the model. These features include the shape, size, and color of the components, which play a key role in the subsequent image comparison process. Shape features describe the geometric form of components, such as round, square, rectangular, etc. Size features describe the size of components, such as diameter, length, width, etc. Color features describe the color information of components. Although color information may not be directly obtained for some types of 3D scanning (such as laser-based scanning), it can be obtained in some optical-based scanning or estimated through subsequent processing. The extracted features need to be compared with the preset feature group. The preset feature group is defined in advance, and each group corresponds to a component, which contains the feature information of the component such as shape, size, and color. Through comparison, the preset feature group that matches the component features in the scan data can be found to determine the type of the component. Once the type of component is determined (i.e., a matching target feature group is found), its specific location can be determined based on the location of the component in the LED driver power supply model. This location information is expressed in coordinates or other forms.

[0042] For example, suppose there is an LED driver that contains components such as capacitor C1, resistor R2, and transistor Q3. The goal is to determine the location of capacitor C1 (first component) and resistor R2 (second component) in the LED driver. Use a 3D scanner to scan the LED driver and obtain its three-dimensional scan data. Then, use this data to build a three-dimensional model of the LED driver on the server. Perform feature extraction on each component in the model. For example, the shape (cylindrical), size (diameter and height), and color (gray or blue, depending on the actual situation) of capacitor C1 are extracted. Similarly, corresponding features are extracted for resistor R2 and other components. The extracted features are compared with a preset feature group. The preset feature group contains feature information of all possible components such as capacitor C1 and resistor R2. Through comparison, a preset feature group that matches the features of capacitor C1 and resistor R2 can be found. Once the types of capacitor C1 and resistor R2 are determined, their respective locations can be found in the three-dimensional model of the LED driver. For example, you might find capacitor C1 in the upper left corner of the model, while resistor R2 is below it near the middle.

[0043] In a possible implementation, determining an LED driver power supply model based on 3D scanning data specifically includes: obtaining point cloud data of the LED driver power supply based on the 3D scanning data, the point cloud data including 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 facet, and smoothing the facet to obtain second point cloud data; removing 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; smoothing the bare board point cloud data in the third point cloud data to obtain fourth point cloud data; and constructing an LED driver power supply model based on the fourth point cloud data and the component point cloud data.

[0044] Specifically, after the 3D scan is completed, the point cloud data of the LED driver will be obtained. Point cloud data is composed of a large number of points in space, which record the shape and position information of the surface of the object. In this scenario, the point cloud data is subdivided into bare board point cloud data and component point cloud data. Bare board point cloud data represents the surface information of the substrate (or bare board) of the LED driver, while component point cloud data represents the surface information of each component installed on the substrate. Since bare board point cloud data and component point cloud data may be mixed together during scanning, they need to be separated. 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. In order 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 the patch is constructed, smoothing is also required to eliminate the surface unevenness caused by scanning noise or errors, making the model smoother and more realistic. The bare board point cloud data after smoothing may still contain some isolated points or small areas that are not connected to the component point cloud data. These areas may be caused by noise or errors during scanning, so they need to be removed to ensure the accuracy of the final model. After removing the unconnected bare board point cloud data, the remaining bare board point cloud data may need to be further smoothed 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 driver power 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.

[0045] S130: Determine a thermal interaction influence between the first component and the second component based on the first position and the second position.

[0046] Specifically, the server has determined the specific positions of the first component and the second component in the LED driver power supply by processing the 3D scanning data. These position information are expressed in coordinates or other forms, reflecting the precise positions of the components in three-dimensional space. In electronic devices, components generate heat when working. If two components are close in space, the heat generated by one component may affect the temperature of the other component through air convection, thermal radiation or heat conduction. In the embodiment of the present application, this mutual influence is referred to as thermal interaction influence. After determining the position of the components, the server will evaluate the thermal interaction influence between them based on these position information and the thermal characteristics of the components (such as heat generation, thermal resistance, etc.). This involves technologies such as thermal simulation, thermal analysis or thermal calculation, through which the temperature distribution of components under normal working conditions and the thermal interaction between them 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 equipment. It can help engineers predict and avoid problems caused by thermal interaction, such as overheating of components, performance degradation or shortened life.

[0047] In a possible implementation, based on the first position and the second position, determining 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; determining a first thermal resistance, a second thermal resistance and a third thermal resistance according to the heat conduction path, the first thermal resistance being the thermal resistance between the first component and the circuit board of the LED driver power supply, the second thermal resistance being the thermal resistance between the second component and the circuit board of the LED driver power supply, and the third thermal resistance being 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.

[0048] Specifically, first, according to the specific positions of the first component and the second component in the LED driver, the heat conduction paths between them and between them and the circuit board are determined. The heat conduction path refers to the path through which heat is transferred from one component to another component or circuit board, and then further to the environment. These paths may include air convection, thermal radiation, and thermal conduction of the circuit board material itself. After determining the heat conduction path, the thermal resistance associated with these paths needs to be calculated. Thermal resistance is a key parameter in the heat transfer process, which indicates the ease of heat transfer. In this scenario, three main thermal resistances are involved: First thermal resistance: thermal resistance between the first component and the circuit board of the LED driver. This thermal resistance reflects the ease of heat generated by the first component to be transferred to the circuit board in some way (such as heat conduction, thermal radiation). Second thermal resistance: thermal resistance between the second component and the circuit board of the LED driver. Similar to the first thermal resistance, this thermal resistance reflects the heat transfer between the second component and the circuit board. Third thermal resistance: thermal resistance between the circuit board of the LED driver and the 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 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 effect of heat generated by one component on the temperature of another component.

[0049] In a possible implementation, based on the first thermal resistance, the second thermal resistance and the third thermal resistance, the thermal interaction influence is determined, specifically including: 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 for the environment in which the LED driver power supply is located, which is sent by an ambient temperature sensor; calculating the first component temperature based on the first power consumption, the first thermal resistance and the ambient temperature; calculating the second component temperature based on the second power consumption, the second thermal resistance and the ambient temperature; and calculating the thermal interaction influence based on the first component temperature and the second component temperature.

[0050] 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 when it is working, which directly determines the heat generated by the component. These power consumption values ​​can be obtained from the data sheet of the component or actual measurement. Next, it is necessary to receive the ambient temperature of the environment in which the LED driver power supply is located, which is sent by the ambient temperature sensor. The ambient temperature is one of the starting points or end points of heat transfer, and is crucial for evaluating the temperature of the components and the thermal interaction between them. Based on the power consumption, thermal resistance and ambient temperature of the components, the temperature of the components can be calculated using a thermal formula. 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 in the working state can be obtained. After obtaining the temperatures of the two components, the thermal interaction between them can be evaluated. The thermal interaction effect can be regarded as the degree of influence of the temperature change of one component on the temperature of another component, which measures the degree of mutual influence between the two components due to heat conduction. A higher thermal interaction influence means that the thermal interaction between components is more significant, which may cause the component temperature to deviate from its designed operating temperature range, thereby affecting the performance and life of the LED driver. This can be quantified by comparing the temperature difference between two components with and without thermal interaction, using the following calculation formula: ; Among them, T1 ＇ and T2 ＇ 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 (i.e., without considering mutual thermal influence). avg It is the average temperature of two components when they work independently, that is, (T1+T2) / 2, which is used to calculate the normalized thermal interaction effect.

[0051] Next, use the power consumption P1 of the first component and the first thermal resistance R 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 power consumption P2 and the second thermal resistance R of the second component are used. th2 Calculate the temperature T2 of the second component.

[0052] For example, suppose there are two components in the LED driver power supply. The first component is a high-power switch tube, and the second component is a temperature-sensitive capacitor. When working independently, the switch tube temperature T1 = 80°C and the capacitor temperature T2 = 60°C. When they work at the same time, due to thermal interaction, the switch tube temperature rises to T1.＇ =85℃, and the capacitor temperature rises to T2 due to the heat radiation of the switch tube ＇ =65℃. At this time, T avg =(80+60) / 2=70℃, then 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 two components relative to their average temperature, providing designers with a basis for evaluating the rationality of thermal design.

[0053] In addition, if two components have different importance or thermal sensitivity in the system, you can consider taking a weighted sum of their temperature rises. The choice of weight depends on the specific application scenario and design requirements, which will not be elaborated here.

[0054] In a possible implementation, determining a heat conduction path between a first component and a second component according to a first position and a second position specifically includes: obtaining a first material property corresponding to the first component, and obtaining a second material property corresponding to the second component; if it is determined that the LED driver power supply includes a heat sink, obtaining the heat dissipation path; constructing a thermal network model of the LED driver power supply according to the first position and the second position, combining 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.

[0055] Specifically, each component (such as capacitors, inductors, semiconductor devices, etc.) has its own specific material properties, which directly affect its thermal conductivity and thermal resistance performance. For example, metals have good thermal 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 used for heat dissipation in the LED driver power supply. It helps the components to dissipate heat by increasing the surface area and / or using efficient heat conduction materials. If the driver power supply includes a heat sink, it is necessary to further obtain the structure, position and connection method between the heat sink and the components in order to analyze the heat conduction path later. The thermal network model is a mathematical model that simulates the flow of heat in the system, which takes into account the position of the components, the material properties and the thermal connection between them (such as the heat conduction path). In this step, according to the first and second positions of the components, combined with their material properties and (if any) heat dissipation paths, the 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 flow of heat between components and through the heat dissipation path can be calculated. In particular, for the first component and the second component, the heat conduction path between them can be clearly identified, including direct heat conduction (such as through the PCB board) and indirect heat conduction (such as through the heat sink).

[0056] For example, suppose there is an LED driver that contains a high-power MOSFET (first component) located in the center of the PCB and an aluminum electrolytic capacitor (second component) near the heat sink. Get material properties: MOSFET is mainly made of silicon and has good thermal conductivity; aluminum electrolytic capacitors contain electrolyte and aluminum casing and have relatively low thermal conductivity. This driver contains an aluminum heat sink located on one side of the PCB and in contact with the heat source (such as MOSFET) on the PCB through a thermal pad. Take the MOSFET, capacitor, PCB and heat sink as nodes, and build a thermal network model based on their actual connections (such as MOSFET connected to the heat sink through the PCB, and capacitor indirectly connected to MOSFET or other components through copper foil on the PCB) and their respective material properties. 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, and some heat is also conducted to the capacitor through the copper foil on the PCB. In this way, we have clarified the heat conduction path between the MOSFET and the capacitor.

[0057] S140: If it is determined that the thermal interaction influence is within a preset influence range, the LED driving power supply is determined to be qualified. The preset influence range is pre-set according to the first component and the second component.

[0058] S150: 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.

[0059] Specifically, the preset influence range is set in advance through thermal simulation experiments based on the design requirements of the LED driver power supply, the characteristics of the components, and the overall performance goals 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 effect on the system performance. This range is preset for a specific pair of components (such as the first component and the second component), because different pairs of components may have different thermal interaction characteristics. After the actual thermal interaction influence is obtained by measurement or calculation, it is compared with the preset influence range. If the thermal interaction influence is within the preset range, it means 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 means that the LED driver power supply has problems in terms of thermal interaction, which may cause system performance degradation 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 used to facilitate improving the detection accuracy of the LED driver power supply.

[0060] In one possible implementation, refer to Figure 2 , Figure 2Another flow chart of a method for detecting an LED driver power supply provided in an embodiment of the present application. The method includes steps S210 to S230, wherein the steps are as follows: S210, obtaining standard layout data of the LED driver power supply; S220, marking abnormal heat dissipation components contained in an unqualified LED driver power supply in an LED driver power supply model according to the standard layout data to obtain a model to be displayed; S230, displaying the model to be displayed through an AR device.

[0061] Specifically, standard layout data refers to a standardized component layout information followed by the LED driver during the design and manufacturing process. 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 some way (such as from a database, design file, or data package provided by the manufacturer). The server compares the actual layout or test data of the unqualified LED driver with the standard layout data. Through comparison, the server can identify which components are inconsistent with the standard layout in terms of location, model, or connection method, especially those components that may cause abnormal heat dissipation. These abnormal heat dissipation components may be caused by improper location, mismatched models, or blocked heat dissipation paths. Once the abnormal heat dissipation components are identified, the server will mark these components in the virtual model of the LED driver. The marking may include highlighting, adding annotations, or changing colors, 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). The AR device uses its own display and tracking technology to combine the virtual model to be displayed with the environment in the real world to present a mixed reality effect. Users can use AR devices to check which components in the LED driver power supply model have abnormal heat dissipation, and observe and analyze them from multiple angles and distances, making it easier to rework and remake them later.

[0062] The present application also provides a detection device for an LED driving power supply, referring to Figure 3 , Figure 3A module schematic diagram of a detection device for an LED1 driver power supply provided in an embodiment of the present application. The detection device is a server, comprising an acquisition module 31 and a processing module 32, wherein the acquisition module 31 acquires 3D scanning 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 scanning data, the LED driver power supply comprises a plurality of components, the first component and the second component are any two components among the plurality of 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, the LED driver 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 the processing module 32 determines that the thermal interaction influence is not within the preset influence range, the LED driver power supply is determined to be unqualified.

[0063] 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 based on 3D scanning data, specifically including: the processing module 32 determines an LED driver power supply model based on the 3D scanning data; the processing module 32 performs feature extraction on the LED driver power supply model to obtain shape features, size features and color features corresponding to 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.

[0064] In a possible implementation, the processing module 32 determines the LED driver power supply model based on the 3D scanning data, specifically including: the processing module 32 obtains the point cloud data of the LED driver power supply based on the 3D scanning data, and the point cloud data includes bare board point cloud data and component point cloud data; the processing module 32 separates the bare board point cloud data to obtain first point cloud data; the processing module 32 constructs each point cloud data in the first point cloud data into a facet, and smoothes the facet 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 smoothes the bare board point cloud data in the third point cloud data to obtain fourth point cloud data; the processing module 32 constructs the LED driver power supply model based on the fourth point cloud data and the component point cloud data.

[0065] 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 including: 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; the processing module 32 determines the first thermal resistance, the second thermal resistance and the third thermal resistance according to the heat conduction path, 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; the processing module 32 determines the thermal interaction influence based on the first thermal resistance, the second thermal resistance and the third thermal resistance.

[0066] In a possible implementation, 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 including: the acquisition module 31 acquires the first power consumption corresponding to the first component, and acquires the second power consumption corresponding to the second component; the acquisition module 31 receives the ambient temperature of the environment in which the LED driver power supply is located sent by the ambient temperature sensor; the processing module 32 calculates the first component temperature based on the first power consumption, the first thermal resistance and the ambient temperature; the processing module 32 calculates the second component temperature based on the second power consumption, the second thermal resistance and the ambient temperature; the processing module 32 calculates the thermal interaction influence based on the first component temperature and the second component temperature.

[0067] In a possible implementation, 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 including: the acquisition module 31 acquires the first material property corresponding to the first component, and acquires the second material property corresponding to the second component; if the processing module 32 determines that the LED driver power supply includes a heat sink, the processing module 32 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, combined 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.

[0068] In a possible implementation, the acquisition module 31 acquires standard layout data of the LED driver power supply; the processing module 32 marks the abnormal heat dissipation components contained in the unqualified LED driver power supply in the LED driver power supply model according to the standard layout data to obtain the model to be displayed; the processing module 32 displays the model to be displayed through the AR device.

[0069] It should be noted that: when the device provided in the above embodiment realizes its function, only the division of the above functional modules is used as an example. In actual application, the above functions can be assigned to different functional modules as needed, 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.

[0070] The present application also provides an electronic device, referring to Figure 4 , Figure 4 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 .

[0071] The communication bus 42 is used to realize the connection and communication between these components.

[0072] 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.

[0073] The network interface 44 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0074] Among them, the processor 41 may include one or more processing cores. The processor 41 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 45, and calling data stored in the memory 45. Optionally, the processor 41 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 41 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 41, and it can be implemented separately through a chip.

[0075] Among them, the memory 45 may include a random access memory (RAM) or a read-only memory (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, wherein 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, etc. The memory 45 may also be optionally at least one storage device located away from the aforementioned processor 41. As Figure 4 As shown, the memory 45 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an application program of a method for detecting a LED driving power supply.

[0076] exist Figure 4 In the electronic device shown, the user interface 43 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 41 can be used to call an application program for storing a detection method for an LED driving power supply in the memory 45. When executed by one or more processors, the electronic device executes one or more methods such as the above-mentioned embodiments.

[0077] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the order of the actions described, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0078] The present application also provides a computer-readable storage medium, which stores instructions. When executed by one or more processors, the electronic device executes one or more of the methods described in the above embodiments.

[0079] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0080] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of units, which is only a logical function division. There may be other division methods in actual implementation, such as 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 mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0081] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0082] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0083] 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 this understanding, the technical solution of the present application, 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, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0084] The above is only an exemplary embodiment of the present disclosure, and the scope of the present disclosure cannot be limited thereto. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and the truth of practice, it will be easy for those skilled in the art to think of other embodiments of the present disclosure. This application is intended to cover any modification, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field that are not recorded in the present disclosure. The description and examples are regarded as exemplary only, 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 it is determined that the LED driving power supply is unqualified.

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, 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; The thermal interaction influence is determined based on the first thermal resistance, the second thermal resistance, and the third thermal resistance.

5. The method for detecting an LED driving power supply according to claim 4, characterized in that: 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; The thermal interaction influence is calculated according to the first component temperature and the second component temperature.

6. The method for detecting an LED driving power supply according to claim 4, 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.

7. 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.

8. A detection device for LED driving power supply, characterized in that: The detection device 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, the LED driving power supply comprising a plurality of components, the first component and the second component being 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.

9. 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 7.

10. 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 7 is performed.

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