CN117422719B - Production quality detection method for high-end chip radiator - Google Patents
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Abstract
The invention relates to the technical field of image processing, in particular to a production quality detection method of a high-end chip radiator, which comprises the following steps: collecting a radiator thermal image of a chip radiator at each moment; obtaining the possibility of heat dissipation defects of the pixel points according to the pixel values of the pixel points in the heat sink thermal image at all moments; according to the probability of the heat radiation defect, a heat radiation defect area and an extension area of the heat radiation defect area are obtained, and then a defect trace extension index of the heat radiation defect area is calculated; calculating defect diversity coefficients of the chip radiator according to the defect trace extension index of the heat radiation defect area and the heat radiation defect possibility; calculating the production quality index of the chip radiator according to the defect diversity coefficient and the defect trace extension index; and obtaining the production quality grade of the chip radiator according to the production quality index. The invention can realize the production quality detection of the chip radiator and improve the detection accuracy.
Description
Technical Field
The application relates to the technical field of image processing, in particular to a production quality detection method of a high-end chip radiator.
Background
In modern electronic products, a chip is one of the indispensable core components, however, the high integration of the chip leads to an increase in unit power consumption, and the chip generates a large amount of heat during operation, and if the chip cannot effectively dissipate heat, the performance of the chip may be reduced or even damaged. The chip radiator realizes cooling by absorbing heat and utilizing the larger surface area of the chip radiator and surrounding fluid so as to improve the heat dissipation efficiency and ensure the normal operation of the chip. Therefore, the chip radiator may be subjected to the requirements of high-temperature environment and long-time work in the application process, if the chip radiator has quality problems, equipment faults, fire disasters and the like may be caused under extreme conditions, potential problems of the chip radiator can be found in advance by detecting the production quality of the chip radiator, the safety of equipment is ensured, and the user satisfaction is improved.
According to the basic principle of infrared radiation, the infrared thermal imaging nondestructive detection technology receives radiation from an object through an infrared thermal imager, so that the temperature field distribution of the surface of the object is measured, and then whether defects exist in the object or not is identified according to the abnormal distribution condition of the temperature field, so that the production quality of the chip radiator is detected. However, the defects of blurred edge contours, poor background contrast and the like of the target are commonly existed in the thermal infrared image, so that the accuracy of the production quality detection of the chip radiator is not high.
Disclosure of Invention
In order to solve the technical problems, the invention provides a production quality detection method of a high-end chip radiator, which aims to solve the existing problems.
The invention relates to a production quality detection method of a high-end chip radiator, which adopts the following technical scheme:
the embodiment of the invention provides a production quality detection method of a high-end chip radiator, which comprises the following steps:
collecting a radiator thermal image of a chip radiator at each moment;
obtaining the heat propagation coefficient of the pixel point according to the pixel value of the pixel point in the radiator thermal image at each moment; constructing a neighborhood window for each pixel point in the radiator thermal image, and obtaining a heat radiation defect characteristic value of the pixel point in the neighborhood window according to the pixel values and heat propagation coefficients of all the pixel points in the neighborhood window; obtaining the possibility of heat dissipation defects of each pixel point according to the heat dissipation defect characteristic values of the pixel points in the neighborhood window of each pixel point in the heat sink thermal image; obtaining a heat radiation defect binary image according to the heat radiation defect possibility of each pixel point; a heat radiation defect area in the heat radiation defect binary image is obtained, and a defect extension matrix of the heat radiation defect area is constructed according to the heat radiation defect possibility of pixel points in the heat radiation defect area; the minimum circumscribing rectangle of the heat dissipation defect area is marked as an extension area of the heat dissipation defect area; calculating a defect trace extension index of the heat dissipation defect area according to the length and the width of the extension area of the heat dissipation defect area and the defect extension matrix of the heat dissipation defect area; calculating the defect diversity coefficient of the chip radiator according to the defect trace extension index of the heat radiation defect area and the heat radiation defect possibility of the pixel points in the heat radiation defect area; calculating the production quality index of the chip radiator according to the defect diversity coefficient of the chip radiator and the defect trace extension index of all radiating defect areas;
and obtaining the production quality grade of the chip radiator according to the production quality index of the chip radiator.
Further, the obtaining the heat propagation coefficient of the pixel point according to the pixel value of the pixel point in the thermal image of the radiator at each moment includes:
for each pixel point in the radiator thermal image at the t-th moment, taking the absolute value of the difference between the pixel value of the pixel point at the t-th moment and the pixel value of the pixel point at the t-1 th moment as the front moment difference of the pixel point; taking the absolute value of the difference between the pixel value of the pixel point at the t moment and the pixel value of the pixel point at the t+1th moment as the later moment difference of the pixel point;
calculating the ratio of the sum of the front time difference value and the rear time difference value of the pixel point to twice the preset time interval, and marking the ratio as the heat transmission characteristic index of the pixel point at the t-th time;
and (5) recording the average value of the heat propagation characteristic indexes of the pixel points at all moments as the heat propagation coefficient of the pixel points.
Further, the constructing a neighborhood window for each pixel in the heat sink thermal image, and obtaining a heat dissipation defect characteristic value of the pixel in the neighborhood window according to the pixel values and the heat propagation coefficients of all the pixels in the neighborhood window, includes:
for each pixel point in the radiator thermal image at the t-th moment, constructing a neighborhood window with the side length being a preset value by taking the pixel point as the center;
each pixel point in the neighborhood window of the pixel point is respectively marked as a neighborhood pixel of the pixel point; calculating the average value of the pixel values of all pixel points in the radiator thermal image at the t-th moment, and recording the absolute value of the difference value between the pixel value of the neighborhood pixel and the average value as the heat deviation value of the neighborhood pixel; the absolute value of the difference between the heat propagation coefficient of the neighborhood pixel and the average value of the heat propagation coefficients of all pixel points in the radiator thermal image at the t moment is recorded as the heat propagation deviation value of the neighborhood pixel;
and (5) marking the sum of the heat deviation value and the heat propagation deviation value of the neighborhood pixel as the heat radiation defect characteristic value of the neighborhood pixel.
Further, the obtaining the probability of the heat dissipation defect of each pixel according to the heat dissipation defect characteristic value of the pixel in the neighborhood window of each pixel in the heat dissipation thermal image comprises:
for each pixel point in the radiator thermal image at the t moment, calculating the mean value of the heat radiation defect characteristic values of all neighborhood pixels in a neighborhood window of the pixel point, and marking the mean value as the heat radiation defect confidence coefficient of the pixel point at the t moment;
and taking the normalized value of the mean value of the confidence coefficient of the heat radiation defect of the pixel point at all times as the possibility of the heat radiation defect of the pixel point.
Further, the obtaining a heat dissipation defect binary image according to the heat dissipation defect possibility of each pixel point includes:
replacing the pixel value of each pixel point in the radiator thermal image with the possibility of heat radiation defect of each pixel point to obtain a heat radiation defect image;
and performing edge detection on the heat dissipation defect image by using a canny edge detection operator to obtain a heat dissipation defect binary image.
Further, the obtaining the heat dissipation defect area in the heat dissipation defect binary image, and constructing a defect extension matrix of the heat dissipation defect area according to the heat dissipation defect possibility of the pixel points in the heat dissipation defect area, includes:
the inner area of each closed edge line in the heat dissipation defect binary image is recorded as a heat dissipation defect area;
dividing an interval formed by the minimum value and the maximum value of the heat radiation defect possibility of all pixel points in the heat radiation defect area into a preset number of subintervals on average;
each subinterval is respectively marked as a subinterval to be analyzed;
for each heat dissipation defect area, marking pixel points with heat dissipation defect possibility in a subinterval to be analyzed as pixels in the interval to be analyzed; taking the maximum value of the number of pixels in the interval to be analyzed continuously in all preset directions as the maximum distribution of subintervals to be analyzed; the preset directions are 0 degree, 45 degrees, 90 degrees and 135 degrees;
and taking the number of subintervals as the number of rows, and constructing a defect extension matrix of the heat dissipation defect area by taking the maximum distribution of all subintervals as the number of columns.
Further, the defect trace extension index of the heat dissipation defect area is calculated according to the length and the width of the extension area of the heat dissipation defect area and the defect extension matrix of the heat dissipation defect area, and the expression is as follows:
wherein,is->Defect mark extension index of individual heat dissipation defect areas, < ->Is->Defect extension matrix of each heat dissipation defect region +.>Line->Element value of column,/->Row number of defect extension matrix for each heat dissipation defect area, < >>Is->Column number of defect extension matrix of each heat dissipation defect area, < >>Is->Length of extension area of each heat dissipation defect area, < ->Is->Width of the extended area of each heat dissipation defect area.
Further, the calculating the defect diversity factor of the chip radiator according to the defect trace extension index of the heat radiation defect area and the heat radiation defect possibility of the pixel points in the heat radiation defect area includes:
for each heat dissipation defect area, the average value of heat dissipation defect possibility of all pixel points in the heat dissipation defect area is recorded as the heat dissipation defect average value of the heat dissipation defect area;
recording any two heat dissipation defect areas as a combination, and recording the absolute value of the difference value of the heat dissipation defect mean values of the two heat dissipation defect areas as the heat dissipation difference of the combination; the absolute value of the difference value of the defect trace expansion indexes of the two heat dissipation defect areas is recorded as the combined expansion difference;
taking the average value of the sum of all the combined heat dissipation differences and the extension differences as the defect diversity coefficient of the chip heat radiator.
Further, the calculating the production quality index of the chip radiator according to the defect diversity coefficient of the chip radiator and the defect trace extension index of all the radiating defect areas comprises the following steps:
for each heat dissipation defect area, marking the product of the heat dissipation defect mean value of the heat dissipation defect area and the defect trace extension index as the heat dissipation defect degree of the heat dissipation defect area;
calculating the sum of the heat radiation defect degrees of all the heat radiation defect areas, and recording the product of the sum and the defect diversity coefficient of the chip radiator as the fault risk of the chip radiator; taking an exponential function taking a natural constant as a base and the opposite number of the fault risk of the chip radiator as an index as a production quality excellent index of the chip radiator.
Further, the obtaining the production quality grade of the chip radiator according to the production quality index of the chip radiator comprises:
judging the production quality grade of the chip radiator with the production quality index smaller than or equal to the qualification threshold value as disqualification;
judging the production quality grade of the chip radiator with the production quality index being larger than the qualification threshold and smaller than the good threshold as qualification;
judging that the production quality grade of the chip radiator with the production quality index being greater than or equal to a good threshold value is good;
wherein the pass threshold is less than the good threshold.
The invention has at least the following beneficial effects:
according to the heat spreading coefficient and the heat spreading defect characteristic value of the pixel point, according to the characteristics of different heat spreading speeds of a defect area and a normal area and different infrared radiation intensities, the time domain and space domain characteristics of heat spreading on the chip heat spreader are synthesized, the heat spreading defect possibility of the pixel point is calculated, the possibility that the pixel point is in the defect area is evaluated, and the reliability of determining the heat spreading defect possibility is improved; the heat dissipation defect possibility of the pixel points is used for replacing pixel values of the pixel points in the heat dissipation thermal image to obtain a heat dissipation defect image, and then an edge detection operator is used for obtaining a heat dissipation defect area, so that the reliability of obtaining the heat dissipation defect area is improved; the method comprises the steps of constructing a defect extension matrix, calculating a defect trace extension index and a heat dissipation defect mean value of a heat dissipation defect area, obtaining a defect diversity coefficient of the chip radiator, comprehensively considering defect degree of the heat dissipation defect area on the chip radiator, ductility of defects and diversity of the defects, calculating a production quality excellent index of the chip radiator, improving accuracy of production quality detection of the chip radiator, and solving the problem that the accuracy of production quality detection of the chip radiator is low due to the defects of fuzzy target edge profile, poor background contrast and the like in a thermal infrared image.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions and advantages of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of steps of a method for detecting the production quality of a high-end chip heat sink according to the present invention;
FIG. 2 is a schematic diagram of the production quality index acquisition.
Detailed Description
In order to further describe the technical means and effects adopted by the present invention to achieve the preset purposes, the following detailed description refers to the specific implementation, structure, characteristics and effects of a method for detecting the production quality of a high-end chip heat sink according to the present invention, which is described in detail below with reference to the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" means that the embodiments are not necessarily the same. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.
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.
The following specifically describes a specific scheme of the production quality detection method of the high-end chip radiator provided by the invention with reference to the accompanying drawings.
The method for detecting the production quality of the high-end chip radiator provided by the embodiment of the invention specifically provides a method for detecting the production quality of the high-end chip radiator, referring to fig. 1, the method comprises the following steps:
step S001, collecting a radiator thermal image, and preprocessing the radiator thermal image.
The bottom of the chip radiator is heated by using a heating source, an infrared camera is arranged above the chip radiator, the temperature field distribution of the surface of the chip radiator is collected once every 2s, and the temperature field distribution is collected togetherSecondary acquisition->In order to eliminate the influence caused by partial noise and external environment interference, the accuracy of subsequent analysis is enhanced, and the heat radiator thermal image is denoised by using bilateral filtering. Each moment corresponds to a radiator thermal image, the time interval between two adjacent momentsAnd arranging the heat radiator thermal image at all the moments according to the time sequence of acquisition.
So far, a heat sink thermal image at each moment is obtained.
Step S002, according to the heat radiation thermal image, the heat transmission coefficient and the heat radiation defect characteristic value of the pixel point are obtained, the heat radiation defect possibility is calculated, the heat radiation defect area is obtained, the defect extension matrix is constructed, the defect trace extension index and the heat radiation defect mean value of the heat radiation defect area are calculated, according to the defect trace extension index and the heat radiation defect mean value of all the heat radiation defect areas, the defect diversity coefficient of the chip heat radiator is obtained, and the production quality excellent index of the chip heat radiator is calculated.
Because the heat conductivity of the defect area and the heat conductivity of the normal area on the chip radiator are different, when the chip radiator is heated by the heating source, if the chip radiator has defects, the heat diffusion speed and the heat distribution on the surface of the chip radiator are different, and the corresponding infrared radiation intensities are also different. Based on the above analysis, as shown in fig. 2, the production quality of the chip heat sink was evaluated by constructing an index of the production quality of the chip heat sink.
According to the pixel values of the pixel points in all the radiator thermal image diagrams, the heat propagation characteristic indexes of the pixel points are expressed as follows:
wherein,is pixel dot +.>In->Heat transmission characteristic index at each moment +.>Is->Pixel point in thermal image of radiator>Pixel value of>Is->Pixel point in thermal image of radiator>Is used for the display of the display panel,is->Pixel point in thermal image of radiator/>Pixel value of>Is the time interval between two adjacent moments.
The pixel value of the pixel point in the heat radiator thermal image represents the temperature of the position of the pixel point on the heat radiator, and when the pixel value difference of the pixel point on the same position in two adjacent heat radiator thermal images is larger, the larger the temperature difference is, the faster the heat is spread, and the heat spreading characteristic index value of the pixel point is larger.
The average value of the heat propagation characteristic index of each pixel at all times is recorded as the heat propagation coefficient of each pixel. To avoid accidental errors, for each pixel in the thermal image of the heat sink, a pixel is used as the center to construct a pixel with the size ofNeighborhood window of window side length +.>Is 5. The probability of heat dissipation defect of the pixel is expressed as follows:
wherein,is pixel dot +.>Is subject to heat dissipation defect>As an exponential function with a base of natural constant,is->Pixels in thermal image of radiator at each moment +.>Within the neighborhood window->Individual pixel dot->Heat dissipation defect characteristic value of->Is->Pixels in thermal image of radiator at each moment +.>Within the neighborhood window->Individual pixel dot->Pixel value of>Is->Average value of pixel values of all pixel points in radiator thermal image at each moment, +.>Is->Pixels in thermal image of radiator at each moment +.>Within the neighborhood window->Individual pixel dot->Heat transmission coefficient of>Is->Mean value of heat propagation coefficients of all pixel points in radiator thermal image at each moment, +.>For the side length of the neighborhood window, +.>Is the number of thermal image maps of the heat sink.
The heat spreading coefficient of the pixel point represents the spreading speed of heat on the chip radiator along with time, and the pixel value of the pixel point in the thermal image of the radiator reflects the spreading of heat on the chip radiator in space. When the pixel value and the heat propagation coefficient of each pixel point in the neighborhood window of the pixel point are different from those of the pixel point and the heat propagation coefficient in the heat radiator thermal image, the more the difference degree is, the more the thermal conductivity of the area where the pixel point is located is likely to be different from that of the normal area, the more defects are likely to be generated, and the greater the heat dissipation defect probability value of the pixel point is.
According to the characteristics of different heat propagation speeds and different infrared radiation intensities of the defect area and the normal area, the time domain and space domain characteristics of heat propagation on the chip radiator are synthesized, and the heat dissipation defect possibility of the pixel point is calculated to evaluate the possibility that the pixel point is in the defect area, so that the reliability of determining the heat dissipation defect possibility is improved.
In order to improve the accuracy of edge detection, the pixel value of the pixel point in the thermal image of the radiator is replaced by the probability of heat dissipation defect of the pixel point to obtainObtaining heat dissipation defect image. And performing edge detection on the heat dissipation defect image by using a canny edge detection operator to acquire edge information of the heat dissipation defect image, and obtaining a heat dissipation defect binary image.
Defects such as scraping, abrasion and poor welding can possibly occur in the production process of the radiator, after the radiator is put into use, the defect degree of a defect area can deepen along with the increase of the use times, so that the radiating effect is affected, the risk of equipment failure is increased, and therefore the ductility of the radiating defect area is considered when the radiating defect area is analyzed.
The area inside each closed edge in the two-value image of the heat radiation defect is recorded as a heat radiation defect area, the value range of the heat radiation defect possibility of all pixel points in the heat radiation defect area is an integer between 0 and 1, the minimum value a and the maximum value b of the heat radiation defect possibility of all pixel points in the heat radiation defect area are obtained, and the intervals [ a, b ] are obtained]Average division intoSubintervals. Each subinterval is marked as a defect order, the number of pixels which are positioned at the same defect order and continuously appear in the same direction in a heat dissipation defect area is counted, and a defect extension matrix is constructed>The number of lines of the defect extension matrix is the number of defect orders, the number of lines is the maximum value of the number of pixel points which are positioned in all defect orders continuously in all directions, and the matrix element is ∈ ->Representing the successive occurrence of +.>The pixel is at the +.>Defects ofNumber of orders. />The empirical value is 4, and only the number of the same defect order continuously appearing in the directions of 0 degree, 45 degrees, 90 degrees and 135 degrees is counted in order to reduce the calculated amount.
The minimum circumscribing rectangle of the heat dissipation defect area is marked as an extension area of the heat dissipation defect area, and the defect trace extension index of the heat dissipation defect area is expressed as follows according to the defect extension matrix of the heat dissipation defect area and the length and the width of the extension area of the heat dissipation defect area:
wherein,is->Defect mark extension index of individual heat dissipation defect areas, < ->Is->Defect extension matrix of each heat dissipation defect region +.>Line->Element value of column,/->Row number of defect extension matrix for each heat dissipation defect area, < >>Is->Column number of defect extension matrix of each heat dissipation defect area, < >>Is->Length of extension area of each heat dissipation defect area, < ->Is->Width of the extended area of each heat dissipation defect area.
When the defect order is higher and the number of the same order continuously appears is larger, the longer the defect length is, the more likely the defect is to continue to extend, the higher the weight is given, and the larger the defect trace extension index value of the heat dissipation defect area is; when the length and width of the extension area of the heat dissipation defect area are larger, the larger the defect area is, the more likely the extension is continued, and the larger the defect trace extension index value of the heat dissipation defect area is.
The average value of the heat radiation defect probability of all pixel points in the heat radiation defect area is recorded as the heat radiation defect average value of the heat radiation defect area, and the defect diversity coefficient of the chip heat radiator is expressed as follows according to the heat radiation defect average value and the defect trace extension index of all the heat radiation defect areas:
wherein,for the defect diversity coefficient of the chip radiator, +.>Is->Mean value of heat dissipation defects of the heat dissipation defect areas, +.>Is->Mean value of heat dissipation defects of the heat dissipation defect areas, +.>Is->Defect mark extension index of individual heat dissipation defect areas, < ->Is->Defect mark extension index of individual heat dissipation defect areas, < ->For the number of heat dissipation defect areas, < > and->The representation will->The number of the combinations of every two heat dissipation defect areas.
When the difference of the mean value of the heat radiation defects and the expansion index of the defect marks of any two heat radiation defect areas on the chip radiator is larger, the more likely that the heat radiation defect areas are not the same defect, the more the types of the defects, the larger the defect diversity coefficient value of the chip radiator.
The production quality index of the chip radiator is expressed as follows by integrating the heat radiation defect mean value, defect trace extension index and defect diversity coefficient of all heat radiation defect areas on the chip radiator:
wherein,is the production quality index of the chip radiator, < >>As an exponential function based on natural constants, < +.>For the defect diversity coefficient of the chip radiator, +.>Is->Mean value of heat dissipation defects of the heat dissipation defect areas, +.>Is->Defect mark extension index of individual heat dissipation defect areas, < ->The number of defective areas is the number of defective areas.
When the defect diversity coefficient of the chip radiator is larger, the defect variety of the chip radiator is more, and the production quality excellent index value of the chip radiator is smaller; the average value of the heat radiation defects of the heat radiation defect areas represents the defect degree of the heat radiation defect areas, the average value of the heat radiation defects of the heat radiation defect areas represents the ductility of the heat radiation defect areas, and when the defect degree and the ductility of each heat radiation defect area on the chip radiator are higher, the risk of equipment failure is larger, and the production quality excellent index value of the chip radiator is smaller.
So far, the production quality index of the chip radiator is obtained.
Step S003, the production quality of the chip radiator is classified into three grades of disqualification, qualification and good according to the production quality index of the chip radiator.
When the production quality index of the chip radiator is smaller than or equal to the qualification threshold valueWhen the production quality grade of the chip radiator is judged to be unqualified; when the production quality index of the chip radiator is larger than the qualification threshold value +.>Is less than the good threshold +.>When the production quality grade of the chip radiator is judged to be qualified; when the production quality index of the chip radiator is greater than or equal to the good threshold value +.>And when the production quality grade of the chip radiator is judged to be good.
Wherein the qualification thresholdThe empirical value is 0.3, good threshold +.>The empirical value was 0.6. It should be noted that, the setting implementation of the qualification threshold and the good threshold can be selected according to the actual situation.
Thus, the production quality detection of the chip radiator is completed.
It should be noted that: the sequence of the embodiments of the present invention is only for description, and does not represent the advantages and disadvantages of the embodiments. And the foregoing description has been directed to specific embodiments of this specification. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
In this specification, each embodiment is described in a progressive manner, and the same or similar parts of each embodiment are referred to each other, and each embodiment mainly describes differences from other embodiments.
The above embodiments are only for illustrating the technical solution of the present application, and are not limiting; the technical solutions described in the foregoing embodiments are modified or some of the technical features are replaced equivalently, so that the essence of the corresponding technical solutions does not deviate from the scope of the technical solutions of the embodiments of the present application, and all the technical solutions are included in the protection scope of the present application.
Claims (6)
1. The production quality detection method of the high-end chip radiator is characterized by comprising the following steps of:
collecting a radiator thermal image of a chip radiator at each moment;
obtaining the heat propagation coefficient of the pixel point according to the pixel value of the pixel point in the radiator thermal image at each moment; constructing a neighborhood window for each pixel point in the radiator thermal image, and obtaining a heat radiation defect characteristic value of the pixel point in the neighborhood window according to the pixel values and heat propagation coefficients of all the pixel points in the neighborhood window; obtaining the possibility of heat dissipation defects of each pixel point according to the heat dissipation defect characteristic values of the pixel points in the neighborhood window of each pixel point in the heat sink thermal image; obtaining a heat radiation defect binary image according to the heat radiation defect possibility of each pixel point; a heat radiation defect area in the heat radiation defect binary image is obtained, and a defect extension matrix of the heat radiation defect area is constructed according to the heat radiation defect possibility of pixel points in the heat radiation defect area; the minimum circumscribing rectangle of the heat dissipation defect area is marked as an extension area of the heat dissipation defect area; calculating a defect trace extension index of the heat dissipation defect area according to the length and the width of the extension area of the heat dissipation defect area and the defect extension matrix of the heat dissipation defect area; calculating the defect diversity coefficient of the chip radiator according to the defect trace extension index of the heat radiation defect area and the heat radiation defect possibility of the pixel points in the heat radiation defect area; calculating the production quality index of the chip radiator according to the defect diversity coefficient of the chip radiator and the defect trace extension index of all radiating defect areas;
obtaining the production quality grade of the chip radiator according to the production quality index of the chip radiator;
the obtaining the heat propagation coefficient of the pixel point according to the pixel value of the pixel point in the radiator thermal image at each moment comprises the following steps: for each pixel point in the radiator thermal image at the t-th moment, taking the absolute value of the difference between the pixel value of the pixel point at the t-th moment and the pixel value of the pixel point at the t-1 th moment as the front moment difference of the pixel point; taking the absolute value of the difference between the pixel value of the pixel point at the t moment and the pixel value of the pixel point at the t+1th moment as the later moment difference of the pixel point; calculating the ratio of the sum of the front time difference value and the rear time difference value of the pixel point to twice the preset time interval, and marking the ratio as the heat transmission characteristic index of the pixel point at the t-th time; the average value of the heat propagation characteristic indexes of the pixel points at all moments is recorded as the heat propagation coefficient of the pixel points;
constructing a neighborhood window for each pixel point in the radiator thermal image, and obtaining a heat radiation defect characteristic value of the pixel point in the neighborhood window according to the pixel values and heat propagation coefficients of all the pixel points in the neighborhood window, wherein the method comprises the following steps: for each pixel point in the radiator thermal image at the t-th moment, constructing a neighborhood window with the side length being a preset value by taking the pixel point as the center; each pixel point in the neighborhood window of the pixel point is respectively marked as a neighborhood pixel of the pixel point; calculating the average value of the pixel values of all pixel points in the radiator thermal image at the t-th moment, and recording the absolute value of the difference value between the pixel value of the neighborhood pixel and the average value as the heat deviation value of the neighborhood pixel; the absolute value of the difference between the heat propagation coefficient of the neighborhood pixel and the average value of the heat propagation coefficients of all pixel points in the radiator thermal image at the t moment is recorded as the heat propagation deviation value of the neighborhood pixel; the sum of the heat deviation value and the heat propagation deviation value of the neighborhood pixels is recorded as a heat radiation defect characteristic value of the neighborhood pixels;
the obtaining the heat dissipation defect possibility of each pixel point according to the heat dissipation defect characteristic value of the pixel point in the neighborhood window of each pixel point in the heat dissipation thermal image comprises the following steps: for each pixel point in the radiator thermal image at the t moment, calculating the mean value of the heat radiation defect characteristic values of all neighborhood pixels in a neighborhood window of the pixel point, and marking the mean value as the heat radiation defect confidence coefficient of the pixel point at the t moment; taking a normalized value of the mean value of the confidence coefficient of the heat radiation defect of the pixel point at all moments as the heat radiation defect possibility of the pixel point;
the calculating the defect diversity coefficient of the chip radiator according to the defect trace extension index of the heat radiation defect area and the heat radiation defect possibility of the pixel points in the heat radiation defect area comprises the following steps: for each heat dissipation defect area, the average value of heat dissipation defect possibility of all pixel points in the heat dissipation defect area is recorded as the heat dissipation defect average value of the heat dissipation defect area; recording any two heat dissipation defect areas as a combination, and recording the absolute value of the difference value of the heat dissipation defect mean values of the two heat dissipation defect areas as the heat dissipation difference of the combination; the absolute value of the difference value of the defect trace expansion indexes of the two heat dissipation defect areas is recorded as the combined expansion difference; taking the average value of the sum of all the combined heat dissipation differences and the extension differences as the defect diversity coefficient of the chip heat radiator.
2. The method for detecting the production quality of a high-end chip heat sink according to claim 1, wherein the obtaining a heat dissipation defect binary image according to the heat dissipation defect probability of each pixel point comprises:
replacing the pixel value of each pixel point in the radiator thermal image with the possibility of heat radiation defect of each pixel point to obtain a heat radiation defect image;
and performing edge detection on the heat dissipation defect image by using a canny edge detection operator to obtain a heat dissipation defect binary image.
3. The method for detecting the production quality of a high-end chip heat sink according to claim 1, wherein the step of obtaining a heat dissipation defect area in the heat dissipation defect binary image, and constructing a defect extension matrix of the heat dissipation defect area according to the heat dissipation defect probability of the pixel points in the heat dissipation defect area, comprises:
the inner area of each closed edge line in the heat dissipation defect binary image is recorded as a heat dissipation defect area;
dividing an interval formed by the minimum value and the maximum value of the heat radiation defect possibility of all pixel points in the heat radiation defect area into a preset number of subintervals on average;
each subinterval is respectively marked as a subinterval to be analyzed;
for each heat dissipation defect area, marking pixel points with heat dissipation defect possibility in a subinterval to be analyzed as pixels in the interval to be analyzed; taking the maximum value of the number of pixels in the interval to be analyzed continuously in all preset directions as the maximum distribution of subintervals to be analyzed; the preset directions are 0 degree, 45 degrees, 90 degrees and 135 degrees;
and taking the number of subintervals as the number of rows, and constructing a defect extension matrix of the heat dissipation defect area by taking the maximum distribution of all subintervals as the number of columns.
4. The method for detecting the production quality of a high-end chip heat sink according to claim 1, wherein the defect trace extension index of the heat dissipation defect area is calculated according to the length and the width of the extension area of the heat dissipation defect area and the defect extension matrix of the heat dissipation defect area, and is expressed as follows:
wherein,is->Defect mark extension index of individual heat dissipation defect areas, < ->Is->Defect extension matrix of each heat dissipation defect region +.>Line->Element value of column,/->Row number of defect extension matrix for each heat dissipation defect area, < >>Is->Column number of defect extension matrix of each heat dissipation defect area, < >>Is->Length of extension area of each heat dissipation defect area, < ->Is->Width of the extended area of each heat dissipation defect area.
5. The method for detecting the production quality of the high-end chip heat sink as claimed in claim 1, wherein the calculating the production quality index of the chip heat sink according to the defect diversity coefficient of the chip heat sink and the defect trace extension index of all heat dissipation defect areas comprises:
for each heat dissipation defect area, marking the product of the heat dissipation defect mean value of the heat dissipation defect area and the defect trace extension index as the heat dissipation defect degree of the heat dissipation defect area;
calculating the sum of the heat radiation defect degrees of all the heat radiation defect areas, and recording the product of the sum and the defect diversity coefficient of the chip radiator as the fault risk of the chip radiator; taking an exponential function taking a natural constant as a base and the opposite number of the fault risk of the chip radiator as an index as a production quality excellent index of the chip radiator.
6. The method for detecting the production quality of the high-end chip radiator according to claim 1, wherein the step of obtaining the production quality grade of the chip radiator according to the production quality index of the chip radiator comprises the following steps:
judging the production quality grade of the chip radiator with the production quality index smaller than or equal to the qualification threshold value as disqualification;
judging the production quality grade of the chip radiator with the production quality index being larger than the qualification threshold and smaller than the good threshold as qualification;
judging that the production quality grade of the chip radiator with the production quality index being greater than or equal to a good threshold value is good;
wherein the pass threshold is less than the good threshold.
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