Integrated electronic product accessory parameter test system based on computer automatic analysis

Abstract

The invention relates to the technical field of parameter testing, in particular to an integrated electronic product accessory parameter testing system based on computer automatic analysis, and the system can realize the following steps through the mutual cooperation of a plurality of modules: obtaining a target infrared image corresponding to an integrated electronic product to be detected, target accessory areas representing different target accessories are extracted; the target accessory areas are clustered; determining an initial radiation anomaly index corresponding to each target accessory area, and screening out an abnormal candidate accessory area; determining a self heat source abnormal index and other heat source influence indexes corresponding to each abnormal candidate accessory area; a real abnormal accessory area is screened out; and performing parameter testing on the accessories represented by each real abnormal accessory area. According to the method, the accessories which are represented by the real abnormal accessory area and run abnormally are screened out, and the normal accessories which do not need to be subjected to parameter testing are excluded, so that the efficiency of performing parameter testing on the integrated electronic product accessories is improved.

Description

Technical Field

[0001] The invention relates to the technical field of parameter testing, and in particular to an integrated electronic product accessory parameter testing system based on computer automatic analysis. Background Art

[0002] With the rapid development of science and technology, integrated electronic products are increasingly used in daily life, for example, they can be used in smart phones and home appliances. Therefore, it is very important to perform parameter testing on accessories in integrated electronic products. Among them, accessories in integrated electronic products often heat up at the center during operation, for example, resistors and capacitors often heat up at the center during operation. At present, the method commonly used to perform parameter testing on accessories is: to perform parameter testing on accessories manually.

[0003] However, when performing parameter tests on components in integrated electronic products manually, the following technical problems often occur: When performing parameter testing on accessories in integrated electronic products manually, since each parameter of each accessory in the integrated electronic product often needs to be tested manually, the efficiency of the parameter testing is often poor. Summary of the invention

[0004] In order to solve the technical problem of low efficiency in parameter testing of integrated electronic product accessories, the present invention proposes an integrated electronic product accessory parameter testing system based on computer automatic analysis.

[0005] In a first aspect, the present invention provides an integrated electronic product accessory parameter testing system based on computer automatic analysis, the system comprising: An image acquisition and extraction module is used to acquire a target infrared image corresponding to the integrated electronic product to be inspected, and to extract target accessory areas representing different target accessories from the target infrared image; A region clustering module is used to cluster all target accessory regions according to the major axis distances and minor axis distances corresponding to all target accessory regions to obtain target clusters; A screening module is used to determine the initial radiation anomaly index corresponding to each target accessory region according to the difference in grayscale distribution change between each target accessory region and other target accessory regions in the target cluster to which it belongs, and screen out abnormal candidate accessory regions from all target accessory regions based on all initial radiation anomaly indicators; The self-heat source abnormality index determination module is used to determine the self-heat source abnormality index corresponding to each abnormal candidate accessory area according to the grayscale disorder degree corresponding to each abnormal candidate accessory area and the grayscale difference between the centroid of each abnormal candidate accessory area and the edge pixel points of the corresponding preset windows of different sizes; Other heat source impact index determination module, used to determine other heat source impact index corresponding to each abnormal candidate accessory area according to the distance and high temperature difference between each abnormal candidate accessory area and other abnormal candidate accessory areas; A region screening module is used to screen out real abnormal accessory regions from all abnormal candidate accessory regions according to their own heat source abnormality indicators and other heat source influence indicators corresponding to all abnormal candidate accessory regions; The parameter testing module is used to perform parameter testing on the accessories represented by each real abnormal accessory area.

[0006] In combination with the first aspect above, in a possible implementation manner, extracting target accessory regions representing different target accessories from the target infrared image includes: Acquire a target RGB image corresponding to the integrated electronic product to be detected; Filtering reference accessory regions representing different target accessories from the target RGB image; According to the correspondence between the target RGB image and the target infrared image, an accessory region corresponding to each reference accessory region is screened out from the target infrared image as a target accessory region.

[0007] In combination with the first aspect, in a possible implementation manner, clustering all target accessory regions according to the major axis distances and minor axis distances corresponding to all target accessory regions to obtain a target cluster includes: The distance between every two edge pixels on each target accessory area is determined as a reference distance, and a reference distance set corresponding to each target accessory area is obtained; Determine the maximum value in the reference distance set corresponding to each target accessory area as the major axis distance corresponding to each target accessory area; Determine the minimum value in the reference distance set corresponding to each target accessory area as the short axis distance corresponding to each target accessory area; The major axis distance and the minor axis distance corresponding to each target accessory area are used to form a binary vector corresponding to each target accessory area; The target accessory areas whose Euclidean distance between corresponding binary vectors is less than a preset distance threshold are divided into the same cluster, and each obtained cluster is determined as a target cluster.

[0008] In combination with the first aspect above, in a possible implementation, determining the initial radiation anomaly index corresponding to each target accessory area according to the difference in grayscale distribution change between each target accessory area and other target accessory areas in the target cluster to which it belongs includes: The variance of the grayscale values ​​corresponding to all the pixels in each target accessory area is determined as the grayscale disorder degree corresponding to each target accessory area; The mean of the grayscale values ​​corresponding to all the pixels in each target accessory area is determined as the grayscale representative factor corresponding to each target accessory area; According to the grayscale disorder degree and grayscale representative factor corresponding to each target accessory area, the grayscale distribution characteristic value corresponding to each target accessory area is determined, wherein the grayscale disorder degree is positively correlated with the grayscale distribution characteristic value, and the grayscale representative factor is negatively correlated with the grayscale distribution characteristic value; According to the difference between the grayscale distribution characteristic value corresponding to each target accessory area and the grayscale distribution characteristic values ​​corresponding to other target accessory areas in the target cluster to which it belongs, the initial radiation anomaly index corresponding to each target accessory area is determined.

[0009] In combination with the first aspect above, in a possible implementation, determining the initial radiation anomaly index corresponding to each target accessory area according to the difference between the grayscale distribution characteristic value corresponding to each target accessory area and the grayscale distribution characteristic values ​​corresponding to other target accessory areas in the target cluster to which it belongs includes: The average of the grayscale values ​​corresponding to all the pixels in the preset rectangular window corresponding to each pixel in each target accessory area is determined as the overall grayscale factor corresponding to each pixel in each target accessory area; The maximum value among the overall grayscale factors corresponding to all pixels in each target accessory area is determined as the overall representative grayscale index corresponding to each target accessory area; The initial radiation anomaly index corresponding to each target accessory area is determined based on the absolute value of the difference between the grayscale distribution eigenvalue corresponding to each target accessory area and the grayscale distribution eigenvalues ​​corresponding to other target accessory areas in the target cluster to which it belongs, and the difference between the overall representative grayscale index corresponding to each target accessory area and the overall representative grayscale index corresponding to other target accessory areas in the target cluster to which it belongs.

[0010] In combination with the first aspect above, in a possible implementation, the formula corresponding to the initial radiation anomaly index corresponding to the target accessory area is: ;in, It is The target cluster The initial radiation anomaly index corresponding to the target accessory area; is the serial number of the target cluster; and It is The serial numbers of different target accessory regions in a target cluster; is the normalization function; It is The number of target accessory regions in a target cluster; It is the absolute value function; It is The target cluster The grayscale confusion degree corresponding to the target accessory area; It is The target cluster The grayscale confusion degree corresponding to the target accessory area; It is The target cluster The grayscale representative factor corresponding to the target accessory area; It is The target cluster The grayscale representative factor corresponding to the target accessory area; It is The target cluster Grayscale distribution eigenvalues ​​corresponding to the target accessory area; It is The target cluster Grayscale distribution eigenvalues ​​corresponding to the target accessory area; It is The target cluster The overall representative grayscale index corresponding to the target accessory area; It is The target cluster The overall representative grayscale index corresponding to the target accessory area.

[0011] In combination with the first aspect above, in a possible implementation, the step of screening out abnormal candidate accessory areas from all target accessory areas based on all initial radiation abnormality indicators includes: If the initial radiation anomaly index corresponding to the target accessory area is greater than a preset initial anomaly threshold, the target accessory area is determined as an abnormal candidate accessory area.

[0012] In combination with the first aspect above, in a possible implementation, the formula corresponding to the abnormal heat source abnormality index corresponding to the abnormal candidate accessory area is: ;in, It is The abnormal heat source abnormality index corresponding to each abnormal candidate accessory area; is the sequence number of the abnormal candidate accessory area; It is The grayscale disorder degree corresponding to the abnormal candidate accessory area is equal to The variance of the grayscale values ​​corresponding to all pixels in the abnormal candidate accessory area; is the number of preset windows of different sizes; is the serial number of the preset windows of different sizes; is a natural exponential function; It is The centroid of the abnormal candidate accessory region and the The maximum value of the Euclidean distances between edge pixels of preset windows of different sizes; is the normalization function; It is The gray value corresponding to the centroid of the abnormal candidate accessory area; It is The centroid of the abnormal candidate accessory region corresponds to the The mean grayscale value corresponding to all edge pixels of preset windows of different sizes.

[0013] In combination with the first aspect above, in a possible implementation, the formula corresponding to other heat source influence indicators corresponding to the abnormal candidate accessory area is: ;in, It is Other heat source impact indicators corresponding to the abnormal candidate accessory areas; and is the serial number of different abnormal candidate accessory areas; is the number of abnormal candidate accessory regions; is a natural exponential function; It is The high temperature points in the abnormal candidate parts area are The Euclidean distance between the high temperature points in the abnormal candidate accessory area; the high temperature point in the abnormal candidate accessory area is the pixel point with the largest overall grayscale factor in the abnormal candidate accessory area; is the normalization function; It is The overall representative grayscale index corresponding to the abnormal candidate accessory area is used to represent the Local high temperature conditions in the abnormal candidate accessory area; It is The overall representative grayscale index corresponding to the abnormal candidate accessory area is used to represent the The local high temperature situation of the abnormal candidate accessory area.

[0014] In combination with the first aspect, in a possible implementation, screening out the real abnormal accessory region from all abnormal candidate accessory regions according to the self-heat source abnormality index and other heat source influence indexes corresponding to all abnormal candidate accessory regions includes: According to the own heat source abnormality index and other heat source influence indexes corresponding to each abnormal candidate accessory area, the target abnormality index corresponding to each abnormal candidate accessory area is determined, wherein the own heat source abnormality index is positively correlated with the target abnormality index, and the other heat source influence index is negatively correlated with the target abnormality index; If the target abnormality index corresponding to the abnormal candidate accessory area is greater than the preset target abnormality threshold, the abnormal candidate accessory area is determined to be a real abnormal accessory area.

[0015] In a second aspect, the present invention provides an integrated electronic product accessory parameter testing method based on computer automatic analysis implemented by an integrated electronic product accessory parameter testing system based on computer automatic analysis, the method comprising: Acquire a target infrared image corresponding to the integrated electronic product to be inspected, and extract target accessory areas representing different target accessories from the target infrared image; According to the major axis distance and minor axis distance corresponding to all target accessory regions, all target accessory regions are clustered to obtain the target cluster; According to the difference in grayscale distribution changes between each target accessory region and other target accessory regions in the target cluster to which it belongs, the initial radiation anomaly index corresponding to each target accessory region is determined, and based on all the initial radiation anomaly indexes, abnormal candidate accessory regions are screened out from all target accessory regions; According to the grayscale disorder degree corresponding to each abnormal candidate accessory area and the grayscale difference between the centroid of each abnormal candidate accessory area and the edge pixel points of the corresponding preset windows of different sizes, the self-heat source abnormality index corresponding to each abnormal candidate accessory area is determined; Determine other heat source impact indicators corresponding to each abnormal candidate accessory area according to the distance and high temperature difference between each abnormal candidate accessory area and other abnormal candidate accessory areas; According to the corresponding self-heat source abnormality indexes and other heat source influence indexes of all abnormal candidate accessory areas, the real abnormal accessory areas are screened out from all abnormal candidate accessory areas; Parametric tests are performed on the accessories represented by each real abnormal accessory region.

[0016] In a third aspect, a server is provided, comprising a memory and a processor. The memory is used to store executable program code, and the processor is used to call and run the executable program code from the memory, so that the device executes the above-mentioned integrated electronic product accessory parameter testing method based on computer automatic analysis.

[0017] In a fourth aspect, a computer program product is provided, which includes: a computer program code, which, when executed on a computer, enables the computer to execute the above-mentioned integrated electronic product accessory parameter testing method based on computer automatic analysis.

[0018] In a fifth aspect, a computer-readable storage medium is provided, which stores a computer program code. When the computer program code runs on a computer, the computer executes the above-mentioned integrated electronic product accessory parameter testing method based on computer automatic analysis.

[0019] The present invention has the following beneficial effects: The integrated electronic product accessory parameter testing system based on computer automatic analysis of the present invention screens out accessories with abnormal operation represented by the real abnormal accessory area, excludes normal accessories that do not need to be parameter tested, and solves the technical problem of low efficiency in parameter testing of integrated electronic product accessories, thereby improving the efficiency of parameter testing of integrated electronic product accessories. Compared with manual parameter testing of accessories in integrated electronic products, the present invention comprehensively considers multiple indicators related to abnormal operation of accessories in the process of parameter testing of accessories in integrated electronic products, such as initial radiation abnormality indicators, self-heat source abnormality indicators and other heat source influence indicators, thereby screening out abnormal accessories that need to be parameter tested represented by the real abnormal accessory area, reducing the time waste caused by parameter testing of normal accessories to a certain extent, thereby improving the efficiency of parameter testing of integrated electronic product accessories. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0021] Figure 1 It is a structural schematic diagram of an integrated electronic product accessory parameter testing system based on computer automatic analysis of the present invention; Figure 2 It is a flow chart of the integrated electronic product accessory parameter testing method based on computer automatic analysis of the present invention; Figure 3 The figure is a schematic diagram of the structure of a computer device of the present invention. DETAILED DESCRIPTION

[0022] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation methods, structures, features and effects of the technical solutions proposed by the present invention are described in detail below in conjunction with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0023] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0024] refer to Figure 1 , shows a schematic diagram of the structure of an integrated electronic product accessory parameter testing system based on computer automatic analysis according to the present invention. The integrated electronic product accessory parameter testing system based on computer automatic analysis includes: The image acquisition and extraction module 101 is used to acquire a target infrared image corresponding to the integrated electronic product to be inspected, and extract target accessory regions representing different target accessories from the target infrared image.

[0025] Among them, the integrated electronic product to be tested may be an integrated electronic product for which accessory parameter testing is to be performed. An integrated electronic product may be an electronic device that integrates multiple electronic components and systems into a compact module or product. The electronic components in an integrated electronic product are also called accessories in an integrated electronic product. These products are usually characterized by smaller size, lower power consumption, higher integration and higher efficiency. Integrated electronic products are widely used in consumer electronics, communication equipment, automotive electronics, industrial control and other fields. The target infrared image may be an infrared image of the integrated electronic product to be tested. The electronic components on the surface of the integrated electronic product to be tested may be arranged in a single row. The target accessory may be an electronic component that exhibits central heating during operation. For example, the target accessory may be, but is not limited to, a resistor and a capacitor. The target accessory area may be an area where the target accessory is mapped to the target infrared image.

[0026] As an example, this step may include the following steps: The first step is to obtain the target infrared image and target RGB image corresponding to the above-mentioned integrated electronic product to be detected.

[0027] The target RGB image may be an RGB (Red Green Blue, color system) image of the surface of the integrated electronic product to be inspected. The target infrared image and the target RGB image may have the same size, and the same position therein may represent the same accessory.

[0028] For example, a camera can be used to collect a surface RGB image of the integrated electronic product to be inspected before operation as a target RGB image, and an infrared thermal imager can be used to collect an infrared image of the integrated electronic product to be inspected at the current moment during operation as a target infrared image, wherein the camera and the infrared thermal imager can be placed at the same position when performing image acquisition, and the camera and the infrared thermal imager can have the same shooting angle. The current moment can be the current time when the integrated electronic product to be inspected is in operation.

[0029] In the second step, reference accessory regions representing different target accessories are screened out from the target RGB image.

[0030] The reference accessory region may be a region where the target accessory is mapped to the target RGB image.

[0031] For example, the region representing each target accessory can be screened out from the target RGB image through threshold segmentation or neural network recognition technology as the reference accessory region.

[0032] In the third step, according to the correspondence between the target RGB image and the target infrared image, an accessory region corresponding to each reference accessory region is screened out from the target infrared image as a target accessory region.

[0033] For example, an area having the same position as the reference accessory area may be screened out from the target infrared image as the target accessory area.

[0034] Optionally, regions representing different target accessories may be directly extracted from the target infrared image through threshold segmentation or neural network recognition technology as target accessory regions.

[0035] It should be noted that when electronic products are running, part of the electrical energy will be scattered as heat radiation due to the current passing through the resistor. This may cause the edges of the areas representing the accessories of the electronic products in the infrared image to be blurred and the boundaries to be unclear. At this time, directly extracting the accessory areas representing different accessories from the infrared image may lead to inaccurate edge division of the accessory areas. Therefore, the accessory area is indirectly extracted through the RGB image, thereby improving the accuracy of identifying the target accessory area.

[0036] The region clustering module 102 is used to cluster all target accessory regions according to the major axis distances and minor axis distances corresponding to all target accessory regions to obtain target clusters.

[0037] As an example, this step may include the following steps: In the first step, the distance between every two edge pixels on each target accessory area is determined as a reference distance, and a reference distance set corresponding to each target accessory area is obtained.

[0038] The reference distance set corresponding to the target accessory region may include: the distances between all edge pixels on the target accessory region.

[0039] In the second step, the maximum value in the reference distance set corresponding to each target accessory area is determined as the major axis distance corresponding to each target accessory area.

[0040] In the third step, the minimum value in the reference distance set corresponding to each target accessory area is determined as the short axis distance corresponding to each target accessory area.

[0041] In the fourth step, the major axis distance and the minor axis distance corresponding to each target accessory area are used to form a binary vector corresponding to each target accessory area.

[0042] The major axis distance and the minor axis distance may be elements in a binary vector, and the major axis distance may be the first element in the binary vector, and the minor axis distance may be the second element in the binary vector.

[0043] In the fifth step, the target accessory areas whose Euclidean distance between corresponding binary vectors is less than a preset distance threshold are divided into the same cluster, and each obtained cluster is determined as the target cluster.

[0044] The binary vectors corresponding to the target accessory regions in the target cluster are relatively similar. The preset distance threshold may be a preset threshold for clustering, which may be 1.

[0045] It should be noted that integrated electronic products often integrate a large number of accessories, and accessories in integrated electronic products are often not isolated. For example, there are often multiple resistors in integrated electronic products. The major axis distance and minor axis distance corresponding to the area where the same component is located are often similar. Therefore, the target accessory area in the same target cluster often represents the same component.

[0046] The screening module 103 is used to determine the initial radiation anomaly index corresponding to each target accessory area according to the difference in grayscale distribution changes between each target accessory area and other target accessory areas in the target cluster to which it belongs, and screen out abnormal candidate accessory areas from all target accessory areas based on all initial radiation anomaly indicators.

[0047] As an example, this step may include the following steps: In the first step, the variance of the grayscale values ​​corresponding to all pixels in each target accessory area is determined as the grayscale disorder degree corresponding to each target accessory area.

[0048] In the second step, the mean of the grayscale values ​​corresponding to all pixels in each target accessory area is determined as the grayscale representative factor corresponding to each target accessory area.

[0049] The third step is to determine the grayscale distribution characteristic value corresponding to each target accessory area according to the grayscale confusion degree and grayscale representative factor corresponding to each target accessory area.

[0050] The grayscale disorder degree may be positively correlated with the grayscale distribution characteristic value, and the grayscale representative factor may be negatively correlated with the grayscale distribution characteristic value.

[0051] In the fourth step, according to the difference between the grayscale distribution characteristic value corresponding to each target accessory area and the grayscale distribution characteristic values ​​corresponding to other target accessory areas in the target cluster to which it belongs, determining the initial radiation anomaly index corresponding to each target accessory area may include the following sub-steps: In the first sub-step, the average of the grayscale values ​​corresponding to all the pixels in the preset rectangular window corresponding to each pixel in each target accessory area is determined as the overall grayscale factor corresponding to each pixel in each target accessory area.

[0052] The preset rectangular window may be a preset rectangular area. For example, the preset rectangular window may be a 3×3 window. The pixel point may be located at the center of the corresponding preset rectangular window.

[0053] In the second sub-step, the maximum value among the overall grayscale factors corresponding to all pixels in each target accessory area is determined as the overall representative grayscale index corresponding to each target accessory area.

[0054] In the third sub-step, the initial radiation anomaly index corresponding to each target accessory area is determined based on the absolute value of the difference between the grayscale distribution characteristic value corresponding to each target accessory area and the grayscale distribution characteristic value corresponding to other target accessory areas in the target cluster to which it belongs, and the difference between the overall representative grayscale index corresponding to each target accessory area and the overall representative grayscale index corresponding to other target accessory areas in the target cluster to which it belongs.

[0055] For example, the formula for determining the initial radiation anomaly index corresponding to the target accessory area can be: ;in, It is The target cluster The initial radiation anomaly index corresponding to the target accessory area. is the sequence number of the target cluster. and It is The sequence numbers of different target accessory areas in a target cluster. is a normalization function. It is The number of target accessory regions in a target cluster. It is the absolute value function. It is The target cluster The grayscale confusion degree corresponding to the target accessory area. It is The target cluster The grayscale confusion degree corresponding to the target accessory area. It is The target cluster The grayscale corresponding to the target accessory area represents the factor. It is The target cluster The grayscale corresponding to the target accessory area represents the factor. It is The target cluster The grayscale distribution eigenvalues ​​corresponding to the target accessory area. It is The target cluster The grayscale distribution eigenvalues ​​corresponding to the target accessory area. It is The target cluster The overall representative grayscale index corresponding to the target accessory area. It is The target cluster The overall representative grayscale index corresponding to the target accessory area.

[0056] It should be noted that, in actual situations, during operation, the thermal radiation emitted by normal accessories of the same type is often similar, and their grayscale expressions in infrared images are often relatively similar. In addition, the embodiments of the present invention are mainly used to implement real-time abnormality monitoring of integrated electronic product accessories. During the real-time abnormality monitoring process, abnormal accessories are often discovered relatively promptly. Therefore, during the real-time abnormality monitoring process, the number of abnormal accessories that can be monitored each time is often relatively small. Therefore, during the real-time abnormality monitoring process, if the thermal radiation emitted by a certain accessory is not similar to the thermal radiation emitted by most accessories of the same type, it often indicates that the accessory is likely to have a thermal anomaly, which often means that it should be tested for parameters to facilitate subsequent maintenance. The smaller the time, the more likely it is that Target accessory areas and The more similar the overall grayscale distributions between the target accessory regions are, the more likely it is that the The target accessory region represents the accessories and the The more similar the overall thermal radiation distribution between the accessories represented by the target accessory area is, the more similar the overall thermal radiation distribution between the accessories represented by the target accessory area is. The smaller the time, the more likely it is that Target accessory areas and The more similar the overall maximum grayscale is between the target accessory regions, the more likely it is that the The target accessory region represents the accessories and the The more similar the local heat sources between the parts represented by the target parts area are. The larger the The more dissimilar the thermal radiation distribution and local heat source distribution between the accessories represented by the first target accessory area and most accessories of the same type are, the more likely it is that the The more likely the accessories represented by the target accessory area are to have thermal anomalies, the more likely the accessories are to have thermal anomalies. The more parts represented by the target parts area, the more likely it is that there is an operating abnormality.

[0057] In the fifth step, if the initial radiation anomaly index corresponding to the target accessory area is greater than a preset initial anomaly threshold, the target accessory area is determined as an abnormal candidate accessory area.

[0058] The preset initial abnormal threshold may be a threshold pre-set for roughly screening abnormal accessory regions, which may be 0.5. The abnormal candidate accessory regions are often real thermal abnormal accessory regions or normal accessory regions affected by abnormal thermal radiation from other abnormal accessories.

[0059] The self-heat source abnormality index determination module 104 is used to determine the self-heat source abnormality index corresponding to each abnormal candidate accessory area according to the grayscale confusion degree corresponding to each abnormal candidate accessory area, and the grayscale difference between the centroid of each abnormal candidate accessory area and the edge pixel points of the corresponding preset windows of different sizes.

[0060] The centroid of the abnormal candidate accessory region is the center of the abnormal candidate accessory region. The preset window can be a pre-set window of different sizes. For example, there can be a total of 4 preset windows of different sizes, which can be a 3×3 window, a 5×5 window, a 7×7 window, and a 9×9 window. The centroid can be located at the center of its corresponding preset window. The edge pixel point of the preset window is the outermost pixel point in the preset window.

[0061] As an example, the formula for determining the abnormal heat source index corresponding to the abnormal candidate accessory area can be: ;in, It is The abnormal heat source abnormality index corresponding to the abnormal candidate accessory area. is the sequence number of the abnormal candidate accessory area. It is The grayscale disorder degree corresponding to the abnormal candidate accessory area is equal to The variance of the grayscale values ​​corresponding to all pixels in the abnormal candidate accessory area. is the number of preset windows of different sizes. It is the serial number of the preset windows of different sizes. is a natural exponential function. It is The centroid of the abnormal candidate accessory region and the The maximum value of the Euclidean distances between edge pixels of preset windows of different sizes. is a normalization function. It is The gray value corresponding to the centroid of the abnormal candidate accessory area. It is The centroid of the abnormal candidate accessory region corresponds to the The mean grayscale value corresponding to all edge pixels of preset windows of different sizes.

[0062] It should be noted that in actual situations, due to abnormal heat generation during the operation of abnormal accessories, the heat distribution is often relatively chaotic. The larger the The more chaotic the grayscale distribution of the abnormal candidate accessory area is, the more likely it is that the The more likely the accessories represented by the abnormal candidate accessory area are to have abnormal heat distribution, the more likely the accessories are to have abnormal heat distribution. The more abnormal candidate accessory regions represent, the more likely the accessories are to have operational abnormalities. Can be used as The weight of The smaller the time, the more likely it is that The smaller the size of the preset window of different sizes, the smaller the size of the preset window. The smaller the distance between the centroid of the abnormal candidate accessory area and the edge pixel point that needs to be compared in grayscale. The larger the The higher the grayscale of the centroid of the abnormal candidate accessory area is, the higher the grayscale of the centroid of the abnormal candidate accessory area is. The grayscale of the edge pixels of the preset windows of different sizes often indicates the The heat represented by the centroid of the abnormal candidate accessory area is higher than the heat represented by the surrounding edge pixels. In actual situations, the target accessory is often heated at the center. When an abnormality occurs, the heat at the center of the component often increases suddenly. Therefore, the heat at the center of the component is often much higher than the surrounding heat. The larger the The higher the heat of the center of the accessory represented by the abnormal candidate accessory region is than the heat at a shorter distance from it, it often indicates that the The more abnormal candidate accessory regions represent, the more likely abnormal sudden increases in the heat of the accessory center will occur. The larger the The more likely the accessories represented by the abnormal candidate accessory area are to have thermal anomalies, the more likely the accessories are to have thermal anomalies. The more abnormal candidate accessory regions represent accessories, the more likely they are to operate abnormally.

[0063] The other heat source impact index determination module 105 is used to determine other heat source impact indexes corresponding to each abnormal candidate accessory region according to the distance and high temperature difference between each abnormal candidate accessory region and other abnormal candidate accessory regions.

[0064] As an example, the formula for determining other heat source impact indicators corresponding to the abnormal candidate accessory area can be: ;in, It is Other heat source impact indicators corresponding to the abnormal candidate accessory areas. and It is the sequence number of different abnormal candidate accessory areas. is the number of abnormal candidate accessory regions. is a natural exponential function. It is The high temperature points in the abnormal candidate parts area are The Euclidean distance between the high temperature points in the abnormal candidate accessory region. The high temperature point in the abnormal candidate accessory region may be a pixel point with the largest overall grayscale factor in the abnormal candidate accessory region. is a normalization function. It is The overall representative grayscale index corresponding to the abnormal candidate accessory area can be used to represent the The local high temperature situation of the abnormal candidate accessory area. It is The overall representative grayscale index corresponding to the abnormal candidate accessory area can be used to represent the The local high temperature situation of the abnormal candidate accessory area.

[0065] It should be noted that in actual situations, since heat is radiative, for a normal accessory, when there is a thermal anomaly in the surrounding accessories, the abnormal heat of the surrounding accessories will often radiate to the normal accessory, which may cause the normal accessory to be misjudged as an abnormal accessory. Therefore, quantifying the thermal impact of the surrounding accessories can reduce the misjudgment of truly abnormal accessories to a certain extent. yes When The smaller the time, the more likely it is that The high temperature area of ​​the component represented by the abnormal candidate accessory area is The smaller the distance between the high temperature areas of the components represented by the first abnormal candidate parts area, the smaller the distance between the high temperature areas of the components represented by the first abnormal candidate parts area. The more abnormal candidate accessory regions represent, the more likely the parts are to be affected by the The thermal impact of the component is characterized by the abnormal candidate assembly area. The larger the The higher the local high temperature of the component represented by the first abnormal candidate component area is, the higher the local high temperature of the component represented by the first abnormal candidate component area is. The abnormal candidate accessory area represents the local high temperature of the component; it often indicates that the The parts represented by the abnormal candidate accessory regions, The more likely the component represented by the first abnormal candidate accessory area is to have thermal anomalies; The more likely the thermal anomaly of the component represented by the first abnormal candidate accessory area is to radiate and affect the Therefore, when The larger the The thermal anomaly displayed by the component represented by the abnormal candidate accessory area is more likely to be caused by the thermal anomaly of the surrounding components.

[0066] The region screening module 106 is used to screen out real abnormal accessory regions from all abnormal candidate accessory regions according to the corresponding self-heat source abnormality indicators and other heat source influence indicators of all abnormal candidate accessory regions.

[0067] As an example, this step may include the following steps: In the first step, the target abnormality index corresponding to each abnormal candidate accessory area is determined according to the own heat source abnormality index and other heat source influence indexes corresponding to each abnormal candidate accessory area.

[0068] Among them, the self-heat source abnormality index can be positively correlated with the target abnormality index, and other heat source impact indicators can be negatively correlated with the target abnormality index.

[0069] For example, the formula for determining the target abnormality index corresponding to the abnormal candidate accessory area can be: ;in, It is The target anomaly indicator corresponding to the abnormal candidate accessory area. is the sequence number of the abnormal candidate accessory area. is a normalization function. It is The abnormal heat source abnormality index corresponding to the abnormal candidate accessory area. is a natural exponential function. It is Other heat source impact indicators corresponding to the abnormal candidate accessory areas.

[0070] It should be noted that when The larger the The more likely the accessories represented by the abnormal candidate accessory area are to have thermal anomalies, the more likely the accessories are to have thermal anomalies. The more abnormal candidate parts the area represents, the more likely it is that the parts are running abnormally. The larger the The thermal anomaly of the component represented by the abnormal candidate accessory area is more likely to be caused by the thermal anomaly of the surrounding components. The larger the The more likely the accessory represented by the first abnormal candidate accessory region is to have thermal anomalies, and the The more likely the thermal anomaly of an accessory represented by the first abnormal candidate accessory area is to be caused by itself, it often indicates that the The more likely the accessories represented by the abnormal candidate accessory area are to have abnormal operation, the more likely it is that the first The accessories represented by the abnormal candidate accessory area are tested for parameters to facilitate subsequent maintenance.

[0071] In the second step, if the target abnormality index corresponding to the abnormal candidate accessory area is greater than the preset target abnormality threshold, the abnormal candidate accessory area is determined as the real abnormal accessory area.

[0072] The preset target abnormality threshold may be a preset threshold for screening real abnormal accessory areas, which may be 0.7.

[0073] The parameter testing module 107 is used to perform parameter testing on the accessories represented by each real abnormal accessory region.

[0074] As an example, performing parameter testing on the accessories represented by the real abnormal accessory area may include the following steps: The first step is to individually connect the accessories represented by the real abnormal accessories area, and use multi-dimensional electronic testing software to collect multi-dimensional and comprehensive information on the accessories represented by the real abnormal accessories area.

[0075] The second step is to transmit the collected comprehensive information to the computer, and analyze the difference between the test information of the accessories represented by the real abnormal accessories area and the normal test information of accessories of the same model through template matching, and determine the difference as the abnormal difference corresponding to the real abnormal accessories area.

[0076] The third step is to analyze the abnormal parameters of the accessories represented by the real abnormal accessory area through the abnormal differences corresponding to the real abnormal accessory area, and record them.

[0077] Optionally, parameter testing of the accessories represented by the real abnormal accessory area can also be achieved by the following steps: The first step is to place the accessories represented by the real abnormal accessories area in the standard fixture, scan the barcode of the accessories represented by the real abnormal accessories area and register them.

[0078] The second step is to send the test instructions pre-stored in the computer to the standard fixture according to the test requirements.

[0079] In the third step, after the control board in the standard fixture receives the test instruction about the accessories representing the real abnormal accessories area, it starts the test of the accessories representing the real abnormal accessories area and displays the test results in the multi-function meter. The multi-function meter synchronizes the test results to the computer for the computer to perform comparative analysis and form an analysis report.

[0080] refer to Figure 2 Based on the same inventive concept as the above method embodiment, the present invention provides an integrated electronic product accessory parameter testing method based on computer automatic analysis, comprising the following steps: Step 201 : acquiring a target infrared image corresponding to the integrated electronic product to be inspected, and extracting target accessory regions representing different target accessories from the target infrared image.

[0081] Step 202 : clustering all target accessory regions according to the major axis distances and minor axis distances corresponding to all target accessory regions to obtain target clusters.

[0082] Step 203, determining the initial radiation anomaly index corresponding to each target accessory region according to the difference in grayscale distribution changes between each target accessory region and other target accessory regions in the target cluster to which it belongs, and screening out abnormal candidate accessory regions from all target accessory regions based on all initial radiation anomaly indicators.

[0083] Step 204, according to the grayscale disorder degree corresponding to each abnormal candidate accessory region and the grayscale difference between the centroid of each abnormal candidate accessory region and the edge pixel points of the corresponding preset windows of different sizes, determine the corresponding self-heat source abnormality index of each abnormal candidate accessory region.

[0084] Step 205 , determining other heat source impact indicators corresponding to each abnormal candidate accessory region according to the distance and high temperature difference between each abnormal candidate accessory region and other abnormal candidate accessory regions.

[0085] Step 206 , based on the self-heat source abnormality indexes and other heat source influence indexes corresponding to all abnormal candidate accessory regions, the real abnormal accessory regions are screened out from all abnormal candidate accessory regions.

[0086] Step 207 , performing parameter testing on the accessories represented by each real abnormal accessory region.

[0087] Figure 3 is a schematic diagram of the structure of a computer device provided by an embodiment of the present invention. Figure 3 As shown, the computer device 300 includes: a memory 301, a processor 302, and a computer program 303 stored in the memory 301 and running on the processor 302, wherein when the processor 302 executes the computer program 303, the computer device can execute the aforementioned integrated electronic product accessory parameter testing method based on computer automatic analysis.

[0088] Based on the same inventive concept as the above method embodiment, the present invention provides a server, including a memory and a processor. The memory is used to store executable program code, and the processor is used to call and run the executable program code from the memory, so that the device executes the above-mentioned integrated electronic product accessory parameter testing method based on computer automatic analysis.

[0089] Based on the same inventive concept as the above-mentioned method embodiment, the present invention provides a computer program product, which includes: computer program code, when the computer program code runs on a computer, the computer executes the above-mentioned integrated electronic product accessory parameter testing method based on computer automatic analysis.

[0090] Based on the same inventive concept as the above-mentioned method embodiment, the present invention provides a computer-readable storage medium, which stores a computer program code. When the computer program code runs on a computer, the computer executes the above-mentioned integrated electronic product accessory parameter testing method based on computer automatic analysis.

[0091] In summary, compared to manual parameter testing of accessories in integrated electronic products, the present invention comprehensively considers multiple indicators related to abnormal operation of accessories during parameter testing of accessories in integrated electronic products, such as initial radiation abnormality indicators, own heat source abnormality indicators and other heat source impact indicators, thereby screening out abnormal accessories that need to be parameter tested in the real abnormal accessory area representation, reducing to a certain extent the time waste caused by parameter testing of normal accessories, thereby improving the efficiency of parameter testing of accessories of integrated electronic products.

[0092] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments can still be modified, or some of the technical features can be replaced by equivalents. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. An integrated electronic product accessory parameter testing system based on computer automatic analysis, characterized in that: The system comprises: An image acquisition and extraction module is used to acquire a target infrared image corresponding to the integrated electronic product to be inspected, and to extract target accessory areas representing different target accessories from the target infrared image; A region clustering module is used to cluster all target accessory regions according to the major axis distances and minor axis distances corresponding to all target accessory regions to obtain target clusters; A screening module is used to determine the initial radiation anomaly index corresponding to each target accessory region according to the difference in grayscale distribution change between each target accessory region and other target accessory regions in the target cluster to which it belongs, and screen out abnormal candidate accessory regions from all target accessory regions based on all initial radiation anomaly indicators; The self-heat source abnormality index determination module is used to determine the self-heat source abnormality index corresponding to each abnormal candidate accessory area according to the grayscale disorder degree corresponding to each abnormal candidate accessory area and the grayscale difference between the centroid of each abnormal candidate accessory area and the edge pixel points of the corresponding preset windows of different sizes; Other heat source impact index determination module, used to determine other heat source impact index corresponding to each abnormal candidate accessory area according to the distance and high temperature difference between each abnormal candidate accessory area and other abnormal candidate accessory areas; A region screening module is used to screen out real abnormal accessory regions from all abnormal candidate accessory regions according to their own heat source abnormality indicators and other heat source influence indicators corresponding to all abnormal candidate accessory regions; The parameter testing module is used to perform parameter testing on the accessories represented by each real abnormal accessory area.

2. The integrated electronic product accessory parameter testing system based on computer automatic analysis according to claim 1, characterized in that: The step of extracting target accessory regions representing different target accessories from the target infrared image includes: Acquire a target RGB image corresponding to the integrated electronic product to be detected; Filtering reference accessory regions representing different target accessories from the target RGB image; According to the correspondence between the target RGB image and the target infrared image, an accessory region corresponding to each reference accessory region is screened out from the target infrared image as a target accessory region.

3. The integrated electronic product accessory parameter testing system based on computer automatic analysis according to claim 1, characterized in that: The method clusters all target accessory regions according to the major axis distances and minor axis distances corresponding to all target accessory regions to obtain a target cluster, including: The distance between every two edge pixels on each target accessory area is determined as a reference distance, and a reference distance set corresponding to each target accessory area is obtained; Determine the maximum value in the reference distance set corresponding to each target accessory area as the major axis distance corresponding to each target accessory area; Determine the minimum value in the reference distance set corresponding to each target accessory area as the short axis distance corresponding to each target accessory area; The major axis distance and the minor axis distance corresponding to each target accessory area are used to form a binary vector corresponding to each target accessory area; The target accessory areas whose Euclidean distance between corresponding binary vectors is less than a preset distance threshold are divided into the same cluster, and each obtained cluster is determined as a target cluster.

4. The integrated electronic product accessory parameter testing system based on computer automatic analysis according to claim 1, characterized in that: Determining the initial radiation anomaly index corresponding to each target accessory region according to the difference in grayscale distribution change between each target accessory region and other target accessory regions in the target cluster to which it belongs includes: The variance of the grayscale values ​​corresponding to all the pixels in each target accessory area is determined as the grayscale disorder degree corresponding to each target accessory area; The mean of the grayscale values ​​corresponding to all the pixels in each target accessory area is determined as the grayscale representative factor corresponding to each target accessory area; According to the grayscale disorder degree and grayscale representative factor corresponding to each target accessory area, the grayscale distribution characteristic value corresponding to each target accessory area is determined, wherein the grayscale disorder degree is positively correlated with the grayscale distribution characteristic value, and the grayscale representative factor is negatively correlated with the grayscale distribution characteristic value; According to the difference between the grayscale distribution characteristic value corresponding to each target accessory area and the grayscale distribution characteristic values ​​corresponding to other target accessory areas in the target cluster to which it belongs, the initial radiation anomaly index corresponding to each target accessory area is determined.

5. The integrated electronic product accessory parameter testing system based on computer automatic analysis according to claim 4, characterized in that: Determining the initial radiation anomaly index corresponding to each target accessory region according to the difference between the grayscale distribution characteristic value corresponding to each target accessory region and the grayscale distribution characteristic values ​​corresponding to other target accessory regions in the target cluster to which it belongs includes: The average of the grayscale values ​​corresponding to all the pixels in the preset rectangular window corresponding to each pixel in each target accessory area is determined as the overall grayscale factor corresponding to each pixel in each target accessory area; The maximum value among the overall grayscale factors corresponding to all pixels in each target accessory area is determined as the overall representative grayscale index corresponding to each target accessory area; The initial radiation anomaly index corresponding to each target accessory area is determined based on the absolute value of the difference between the grayscale distribution eigenvalue corresponding to each target accessory area and the grayscale distribution eigenvalues ​​corresponding to other target accessory areas in the target cluster to which it belongs, and the difference between the overall representative grayscale index corresponding to each target accessory area and the overall representative grayscale index corresponding to other target accessory areas in the target cluster to which it belongs.

6. The integrated electronic product accessory parameter testing system based on computer automatic analysis according to claim 5, characterized in that: The formula corresponding to the initial radiation anomaly index of the target accessory area is: ;in, It is The target cluster The initial radiation anomaly index corresponding to the target accessory area; is the serial number of the target cluster; and It is The serial numbers of different target accessory regions in a target cluster; is the normalization function; It is The number of target accessory regions in a target cluster; It is the absolute value function; It is The target cluster The grayscale confusion degree corresponding to the target accessory area; It is The target cluster The grayscale confusion degree corresponding to the target accessory area; It is The target cluster The grayscale representative factor corresponding to the target accessory area; It is The target cluster The grayscale representative factor corresponding to the target accessory area; It is The target cluster Grayscale distribution eigenvalues ​​corresponding to the target accessory area; It is The target cluster Grayscale distribution eigenvalues ​​corresponding to the target accessory area; It is The target cluster The overall representative grayscale index corresponding to the target accessory area; It is The target cluster The overall representative grayscale index corresponding to the target accessory area.

7. The integrated electronic product accessory parameter testing system based on computer automatic analysis according to claim 1, characterized in that: Based on all initial radiation anomaly indicators, abnormal candidate accessory areas are screened out from all target accessory areas, including: If the initial radiation anomaly index corresponding to the target accessory area is greater than a preset initial anomaly threshold, the target accessory area is determined as an abnormal candidate accessory area.

8. The integrated electronic product accessory parameter testing system based on computer automatic analysis according to claim 1, characterized in that: The formula corresponding to the abnormal heat source abnormal index of the abnormal candidate accessory area is: ;in, It is The abnormal heat source abnormality index corresponding to each abnormal candidate accessory area; is the sequence number of the abnormal candidate accessory area; It is The grayscale disorder degree corresponding to the abnormal candidate accessory area is equal to The variance of the grayscale values ​​corresponding to all pixels in the abnormal candidate accessory area; is the number of preset windows of different sizes; is the serial number of the preset windows of different sizes; is a natural exponential function; It is The centroid of the abnormal candidate accessory region and the The maximum value of the Euclidean distances between edge pixels of preset windows of different sizes; is the normalization function; It is The gray value corresponding to the centroid of the abnormal candidate accessory area; It is The centroid of the abnormal candidate accessory region corresponds to the The mean grayscale value corresponding to all edge pixels of preset windows of different sizes.

9. The integrated electronic product accessory parameter testing system based on computer automatic analysis according to claim 5, characterized in that: The formulas corresponding to other heat source impact indicators corresponding to the abnormal candidate accessory area are: ;in, It is Other heat source impact indicators corresponding to the abnormal candidate accessory areas; and is the serial number of different abnormal candidate accessory areas; is the number of abnormal candidate accessory regions; is a natural exponential function; It is The high temperature points in the abnormal candidate parts area are The Euclidean distance between the high temperature points in the abnormal candidate accessory area; the high temperature point in the abnormal candidate accessory area is the pixel point with the largest overall grayscale factor in the abnormal candidate accessory area; is the normalization function; It is The overall representative grayscale index corresponding to the abnormal candidate accessory area is used to represent the Local high temperature conditions in the abnormal candidate accessory area; It is The overall representative grayscale index corresponding to the abnormal candidate accessory area is used to represent the The local high temperature situation of the abnormal candidate accessory area.

10. The integrated electronic product accessory parameter testing system based on computer automatic analysis according to claim 1, characterized in that: The method of screening out the real abnormal accessory regions from all abnormal candidate accessory regions according to the corresponding self-heat source abnormality indexes and other heat source influence indexes of all abnormal candidate accessory regions includes: According to the own heat source abnormality index and other heat source influence indexes corresponding to each abnormal candidate accessory area, the target abnormality index corresponding to each abnormal candidate accessory area is determined, wherein the own heat source abnormality index is positively correlated with the target abnormality index, and the other heat source influence index is negatively correlated with the target abnormality index; If the target abnormality index corresponding to the abnormal candidate accessory area is greater than the preset target abnormality threshold, the abnormal candidate accessory area is determined to be a real abnormal accessory area.

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