Abnormal environment chip stability test method based on MiniLED display

Abstract

The invention relates to the technical field of chip testing, in particular to an abnormal environment chip stability testing method based on MiniLED display. The method comprises the following steps: acquiring a first credibility and a second credibility of each power consumption data in a power consumption data sequence, obtaining a credibility weighting factor of each power consumption data according to the first credibility and the second credibility, and performing weighted fusion on all the power consumption data sequences according to the credibility weighting factors of the power consumption data to obtain a target data sequence; and obtaining a stability test result of the batch of chips to be tested in the abnormal test environment according to the target data sequence. According to the target data sequence obtained by performing weighted fusion according to the credibility weighting factor, the obtained stability test result of the batch of chips to be tested in the abnormal test environment can be more accurate and reliable.

Description

Technical Field

[0001] The present invention relates to the field of chip testing technology, and in particular to a method for testing chip stability in an abnormal environment based on MiniLED display. Background Art

[0002] MiniLED display technology is a backlight system applied to LCD displays. MiniLED display technology achieves higher resolution, brightness, contrast and color gamut performance by using LED chips with sizes between 50 and 200 microns, while making the device thinner and more energy-efficient. In addition, due to the functions of MiniLED display technology, it has been widely used in various display devices, such as high-end monitors, large-screen TVs, laptops and tablets. Since the chips used in MiniLED display technology play an important role in display technology, the stability and reliability of the chips during use are crucial. In order to ensure or understand the stability and reliability of the chips during use, the chips used in MiniLED display technology are usually tested for stability. Since the use environment of the chips is not static, that is, the chips will also be used in abnormal environments, and the abnormal environment will particularly affect the stability and reliability of the chips, in order to evaluate the long-term reliability and stability of the chips, various extreme environmental conditions that the chips may encounter in actual use, such as high temperature, high humidity, high pressure and high light intensity, will be simulated to discover and solve potential problems in advance to ensure the stability and reliability of the chips in actual applications.

[0003] At present, a high-voltage accelerated aging test method is generally used to test the stability of chips under abnormal environments. Before testing the chip, multiple test chips are generally selected first, and then each test chip is tested using the high-voltage accelerated aging test method. The power consumption data sequence of each test chip during the test is obtained using an acquisition device, and finally the final stability test result is determined based on the average sequence of the power consumption data sequences of all test chips. However, during the test, some factors that interfere with the test process are not taken into account. For example, in a closed experimental environment, excessive light intensity will cause the temperature to rise, thereby forming a high-voltage environment in the experimental environment, and the high-voltage environment will increase electromagnetic interference and cause voltage fluctuations. Electromagnetic interference and voltage fluctuations will cause some power consumption data to be interfered with, that is, electromagnetic interference and voltage fluctuations will cause some data in the collected power consumption data sequence to deviate or have deviations. When some data in the collected power consumption data sequence deviates or has deviations, if the final stability test result is determined based on the average sequence of the power consumption data sequences of all test chips, the obtained stability test result will be unreliable and inaccurate. Therefore, how to accurately and reliably obtain the stability test result has become an urgent problem to be solved. Summary of the invention

[0004] In order to solve the above problems, the present invention provides a method for testing chip stability in an abnormal environment based on MiniLED display, and the technical solution adopted is as follows:

[0005] An embodiment of the present invention provides a method for testing chip stability in an abnormal environment based on MiniLED display, comprising the following steps:

[0006] A test chips are selected from the batch of chips to be tested, and a high-voltage accelerated aging test is performed on each test chip to obtain a power consumption data sequence corresponding to each test chip under an abnormal test environment, where A is greater than 1;

[0007] Acquire a local subsequence corresponding to each power consumption data in the power consumption data sequence, and perform linear fitting on the power consumption data sequence and the local subsequence corresponding to each power consumption data, respectively, to obtain a first fitting straight line of the power consumption data sequence and a second fitting straight line of each power consumption data, and obtain a first credibility of each power consumption data according to the first fitting straight line and the second fitting straight line;

[0008] Obtaining a volatility index value of each power consumption data according to adjacent power consumption data of each power consumption data in the power consumption data sequence and a difference between two adjacent power consumption data in the local subsequence, and obtaining a second credibility of each power consumption data according to the power consumption data in the power consumption data sequence and the volatility index value of each power consumption data;

[0009] Obtaining a credibility weighting factor of each power consumption data according to the first credibility and the second credibility, and performing weighted fusion on all the power consumption data sequences according to the credibility weighting factor of the power consumption data to obtain a target data sequence;

[0010] According to the target data sequence, a stability test result of the batch of chips to be tested under the abnormal test environment is obtained.

[0011] Beneficial effects: The present invention first selects A test chips from a batch of chips to be tested, and performs a high-voltage accelerated aging test on each test chip to obtain a power consumption data sequence corresponding to each test chip under an abnormal test environment; secondly, a local subsequence corresponding to each power consumption data in the power consumption data sequence is obtained, and linear fitting is performed on the power consumption data sequence and the local subsequence corresponding to each power consumption data, respectively, to obtain a first fitting straight line of the power consumption data sequence and a second fitting straight line of each power consumption data, and a first credibility of each power consumption data is obtained according to the first fitting straight line and the second fitting straight line; then, according to adjacent power consumption data of each power consumption data in the power consumption data sequence and the difference between two adjacent power consumption data in the local subsequence, a volatility index value of each power consumption data is obtained, and according to the power consumption data in the power consumption data sequence and the volatility index value of each power consumption data, a second credibility of each power consumption data is obtained; then, according to the first credibility and the second credibility, a credibility weighting factor of each power consumption data is obtained, and according to the credibility weighting factor of the power consumption data, all power consumption data sequences are weightedly fused to obtain a target data sequence; finally, according to the target data sequence, a stability test result of the batch of chips to be tested under an abnormal test environment is obtained. Furthermore, the target data sequence obtained by weighted fusion according to the credibility weighting factor of the present invention can make the stability test results of the batch of chips to be tested under the abnormal test environment more accurate and reliable. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] 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.

[0013] Figure 1 This is a flow chart of a method for testing chip stability in an abnormal environment based on MiniLED display according to the present invention. DETAILED DESCRIPTION

[0014] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field belong to the scope of protection of the embodiments of the present invention.

[0015] 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 pertains.

[0016] This embodiment provides a method for testing chip stability in an abnormal environment based on MiniLED display, which is described in detail as follows:

[0017] like Figure 1 As shown, the abnormal environment chip stability test method based on MiniLED display includes the following steps:

[0018] Step S001, selecting A test chips from a batch of chips to be tested, and performing a high-voltage accelerated aging test on each test chip to obtain a power consumption data sequence corresponding to each test chip under an abnormal test environment.

[0019] The main purpose of this embodiment is to accurately and reliably obtain stability test results when performing stability tests on chips under abnormal test environments, and this embodiment mainly tests chips used in MiniLED display technology. In addition, in order to facilitate understanding and analysis, this embodiment will select any batch of chips that have not been tested for stability for testing, and this embodiment will record the selected batch of chips as the chips in the batch to be tested, and the chips in the batch to be tested belong to the same type, and randomly select A chips from the batch to be tested as test chips, and the test chips are mainly used for subsequent stability tests; and in this embodiment, the implementer needs to set the value of A according to actual conditions. For example, this embodiment can set the value of A to an empirical value, or determine the value of A based on the total number of chips in the batch to be tested. If the total number of chips in the batch to be tested is A1, then the rounded value of one percent of A1 can be used as the value of A.

[0020] Then, a high-voltage accelerated aging test method is used to perform a high-voltage accelerated aging test on each test chip, and during the test, an acquisition device is used to acquire a power consumption data sequence corresponding to each test chip, and the power consumption data sequence corresponding to any test chip is composed of all power consumption data of the test chip acquired from the beginning of the test to the end of the test. The high-voltage accelerated aging test refers to using a HAST high-accelerated aging test chamber to test the stability of the chip, and the acquisition device can be a power consumption analyzer. In this embodiment, the environment simulated in the high-accelerated aging test chamber is recorded as an abnormal test environment, and the power consumption data sequence acquired above is recorded as the power consumption data sequence corresponding to each test chip under the abnormal test environment.

[0021] And the test environment is not changed during the testing of all test chips, that is, the parameters of the highly accelerated aging test chamber are not changed, and the test time of each test chip is required to be the same; it should also be noted that if there is sufficient space in the highly accelerated aging test chamber, all test chips can be put in for testing at the same time, or they can be put in for testing in batches.

[0022] In addition, the purpose of using the high-voltage accelerated aging test method to test the stability of the chip is because the HAST high-accelerated aging test chamber can simulate extreme environments of high temperature, high humidity, high air pressure and high light intensity, that is, the high-accelerated aging test chamber can simulate different abnormal test environments, and the abnormal test environment refers to high temperature, high humidity, high air pressure and high light intensity, etc.; and before conducting the test, the implementer needs to set the parameters of the HAST high-accelerated aging test chamber according to the actual situation, such as setting the temperature to 125 degrees Celsius, the pressure to 3atm, and the test time to 2 hours; and it should also be noted that in this embodiment, the collection time interval between two adjacent power consumption data in each power consumption data sequence is the same, and the implementer can also set the collection time interval between two adjacent power consumption data in the sequence according to the actual situation, such as it can be set to 1 second.

[0023] Therefore, this embodiment can obtain the power consumption data sequence corresponding to each test chip under the abnormal test environment through the above process.

[0024] Step S002, obtaining a local subsequence corresponding to each power consumption data in the power consumption data sequence, and performing linear fitting on the power consumption data sequence and the local subsequence corresponding to each power consumption data, respectively, to obtain a first fitting straight line for the power consumption data sequence and a second fitting straight line for each power consumption data, and obtaining a first credibility of each power consumption data based on the first fitting straight line and the second fitting straight line.

[0025] Because the current test process does not take into account the interference of some factors on the test process, such as in a closed experimental environment, excessive light intensity will cause the temperature to rise, thereby forming a high-voltage environment in the experimental environment, and the high-voltage environment will increase electromagnetic interference and cause voltage fluctuations, and electromagnetic interference and voltage fluctuations will cause some power consumption data to be disturbed, that is, electromagnetic interference and voltage fluctuations will cause some data in the collected power consumption data sequence to deviate or have deviations. When some data in the collected power consumption data sequence deviates or has deviations, if the final stability test result is determined based on the average sequence of the power consumption data sequences of all test chips, it will result in the obtained stability test The results are unreliable and inaccurate. In order to make the stability test results obtained in this embodiment more accurate, this embodiment will analyze the power consumption data sequence to obtain the credibility of each power consumption data in each power consumption data sequence. The credibility can reflect the possibility of deviation or bias of the corresponding data or the probability of interference with the corresponding data. Then, based on the credibility of each power consumption data in the power consumption data sequence, all power consumption data sequences are weightedly fused. Subsequently, the stability test results are analyzed based on the sequence obtained after weighted fusion. This method in this embodiment can minimize the impact of some interfered power consumption data on the stability test results.

[0026] Based on the above analysis, it can be seen that the present embodiment will then obtain the credibility of each power consumption data in the power consumption data sequence, and in the present embodiment, the first credibility of each power consumption data in the power consumption data sequence will be obtained first, but before obtaining the first credibility, it is also necessary to first obtain the local subsequence corresponding to each power consumption data in the power consumption data sequence, and perform linear fitting on the power consumption data sequence and the local subsequence corresponding to each power consumption data, respectively, to obtain the first fitting straight line of the power consumption data sequence and the second fitting straight line of each power consumption data, and then obtain the first credibility of each power consumption data according to the first fitting straight line and the second fitting straight line; it can be seen that the present embodiment needs to first obtain the local subsequence corresponding to each power consumption data in the power consumption data sequence, that is, the acquisition process of the local subsequence is:

[0027] First, a preset local window is constructed, and the size of the preset local window is set to 1×L, where L is the length of the preset local window; and in specific applications, the implementer needs to set the value of L according to actual conditions, but in this embodiment, the value of L is required to be an odd number, for example, in this embodiment, the value of L can be set to 3 or 5.

[0028] For ease of understanding, this embodiment describes the process of obtaining a local subsequence corresponding to any power consumption data b in the power consumption data sequence B corresponding to any test chip as an example. Then the process of obtaining the local subsequence corresponding to the power consumption data b is as follows: in the power consumption data sequence B corresponding to the test chip, a window containing the power consumption data b and equal to the size of the preset local window is constructed, and recorded as the local window corresponding to the power consumption data b. Then, a sequence formed by all power consumption data in the local window corresponding to the power consumption data b is recorded as the local subsequence corresponding to the power consumption data b.

[0029] The specific construction process of the local window corresponding to the power consumption data b is: if in the power consumption data sequence B, the number of power consumption data on the left side of the power consumption data b is less than Then in the local window corresponding to the constructed power consumption data b, the power consumption data b is located at the first position; if in the power consumption data sequence B, the number of power consumption data on the right side of the power consumption data b is less than Then in the local window corresponding to the constructed power consumption data b, the power consumption data b is located at the last position; if in the power consumption data sequence B, the number of power consumption data on the left and right sides of the power consumption data b is not less than Then, in the local window corresponding to the constructed power consumption data b, the power consumption data b is located in the middle position.

[0030] After obtaining the local subsequences corresponding to the various power consumption data, this embodiment then obtains the first fitting straight line of the power consumption data sequence corresponding to each test chip and the second fitting straight line of each power consumption data in the power consumption data sequence according to the power consumption data sequence corresponding to each test chip and the local subsequences corresponding to each power consumption data. The first fitting straight line and the second fitting straight line are the keys to subsequently obtaining the first credibility. Therefore, the specific process of obtaining the first fitting straight line of the power consumption data sequence corresponding to each test chip and the second fitting straight line of each power consumption data in the power consumption data sequence is as follows:

[0031] Linear fitting is performed on the power consumption data sequence corresponding to each test chip, and the straight line obtained by fitting is recorded as the first fitting straight line of the corresponding power consumption data sequence; linear fitting is performed on the local subsequences corresponding to each power consumption data in the power consumption data sequence, and the straight line obtained by fitting is recorded as the second fitting straight line of the corresponding power consumption data.

[0032] After obtaining the first fitting straight line of the power consumption data sequence and the second fitting straight line of each power consumption data, this embodiment obtains the first credibility of each power consumption data in each power consumption data sequence according to the first fitting straight line of the power consumption data sequence corresponding to each test chip and the second fitting straight line of each power consumption data in the power consumption data sequence, and the first credibility is one of the important indicators for subsequently obtaining the credibility weighting factor for weighted fusion, so the specific acquisition process of the first credibility of each power consumption data in each power consumption data sequence is:

[0033] First, the similarity between the second fitting straight line of each power consumption data in each power consumption data sequence and the first fitting straight line of the corresponding power consumption data sequence is calculated, and the calculation result is recorded as the fitting similarity characterization value corresponding to the corresponding power consumption data; for example, the fitting similarity characterization value corresponding to the power consumption data b in the power consumption data sequence B refers to the similarity between the first fitting straight line of the power consumption data sequence B and the second fitting straight line of the power consumption data b; then, the first label value of each power consumption data in each power consumption data sequence is obtained, and the first label value of the j-th power consumption data in different power consumption data sequences is j; and after obtaining the fitting similarity characterization value and the first label value corresponding to each power consumption data, in order to facilitate understanding, this embodiment will be based on the fitting similarity characterization value and the first label value corresponding to the acquired power consumption data, and take the acquisition process of the first credibility of the power consumption data b in the power consumption data sequence B as an example to describe, that is, the acquisition process of the first credibility of the power consumption data b in the power consumption data sequence B is:

[0034] First, in all power consumption data sequences, all power consumption data with the same first tag value as the power consumption data b are obtained, and the set constructed by all the power consumption data with the same first tag value as the power consumption data b is recorded as the characteristic power consumption data set of the power consumption data b, that is, the data in the characteristic power consumption data set of the power consumption data b come from different sequences but are all in the same position in the sequence; then, among the fitted similarity characterization values ​​corresponding to all power consumption data in the characteristic power consumption data set of the power consumption data b, the maximum fitted similarity characterization value is selected as the maximum characterization value of the power consumption data b; then, the absolute value of the difference between the fitted similarity characterization value corresponding to the power consumption data b and the maximum characterization value of the power consumption data b is calculated, and the calculation result is recorded as the first difference corresponding to the power consumption data b, and then the first difference corresponding to the power consumption data b is added to the preset first constant, and the inverse of the result obtained by the addition is recorded as the first characterization value. Next, in the characteristic power consumption data set of power consumption data b, all data except power consumption data b are obtained, and the set formed by all data except power consumption data b in the characteristic power consumption data set is recorded as the subset B1 corresponding to power consumption data b; then the first similarity index value corresponding to each power consumption data in the subset B1 is obtained, and the first similarity index value corresponding to the hth power consumption data in the subset B1 refers to the similarity between the local subsequence corresponding to the hth power consumption data and the local subsequence corresponding to the power consumption data b, and the greater the similarity between the local subsequence corresponding to the hth power consumption data and the local subsequence corresponding to the power consumption data b, the more similar the local subsequence corresponding to the hth power consumption data is to the local subsequence corresponding to the power consumption data b; then in the subset B1, the number of power consumption data whose first similarity index value is greater than the preset similarity threshold is counted and recorded as the first quantity representation value; then the ratio of the first quantity representation value to the total number of data in the subset B1 is obtained and recorded as the second representation value. Finally, the mean of the first representation value and the second representation value is recorded as the first credibility of the power consumption data b in the sequence B.

[0035] In a specific application, the implementer needs to set the preset similarity threshold and the preset first constant according to the actual situation. For example, in this embodiment, the preset similarity threshold can be set to 0.6, and the preset first constant can be set to 1. In this embodiment, dynamic time warping DTW can be used to calculate the similarity between two sequences. The method of using dynamic time warping DTW to calculate the similarity between two sequences is a well-known technology, so this embodiment will not be described similarly.

[0036] In addition, in this embodiment, a specific expression for obtaining the first credibility of the power consumption data b in the sequence B is:

[0037]

[0038] Among them, β1 is the first credibility of power consumption data b, SB,j is the fitting similarity characterization value corresponding to the power consumption data b, S1 j is the maximum characterization value of the power consumption data b, N1 is the number of power consumption data in the subset B1 whose fitting similarity characterization value is greater than the preset similarity threshold, which is also the first quantity characterization value, and N0 is the total number of data in the subset B1.

[0039] And when |S B,b -S1 b The smaller the value of | is, the more consistent the change trend of the local subsequence corresponding to the power consumption data b, that is, the corresponding local window, is with the overall change trend in sequence B. When the change trend of the local window corresponding to the power consumption data b is more consistent with the overall change trend in sequence B, it indicates that the power consumption data b is less disturbed, that is, the more reliable the power consumption data b is; when The larger the value of is, the more similar the change trend in the local window corresponding to the power consumption data b is to the change trend in the local window corresponding to the power consumption data with the same first tag value as the power consumption data b in the remaining power consumption data sequence, and the less interference the power consumption data b is, that is, the higher the credibility of the power consumption data b is; and because when |S B,b -S1 b The smaller the value of | and The larger the value of , the larger the value of β1. Based on the above analysis, it can be seen that when the value of β1 is larger, it indicates that the power consumption data b in sequence B is less interfered or the credibility of the power consumption data b is higher. The higher the credibility, the greater the reference degree of the power consumption data b in sequence B when performing weighted fusion later; conversely, when the value of β1 is smaller, it indicates that the power consumption data b in sequence B is more interfered or the credibility is lower.

[0040] Therefore, this embodiment can obtain the first credibility of each power consumption data in the power consumption data sequence corresponding to each test chip according to the method of the first credibility of the power consumption data b.

[0041] Step S003, obtaining a volatility index value of each power consumption data according to adjacent power consumption data of each power consumption data in the power consumption data sequence and a difference between two adjacent power consumption data in the local subsequence, and obtaining a second credibility of each power consumption data according to the power consumption data in the power consumption data sequence and the volatility index value of each power consumption data.

[0042] In order to further make the stability results obtained subsequently more reliable and accurate, this embodiment will continue to obtain the second credibility of each power consumption data after obtaining the first credibility of each power consumption data, and the sequence obtained after weighted fusion based on the first credibility and the second credibility can be made more reliable; in addition, in this embodiment, before obtaining the second credibility of each power consumption data, it is necessary to first obtain the volatility index value of each power consumption data according to the adjacent power consumption data of each power consumption data in the power consumption data sequence and the difference between two adjacent power consumption data in the local subsequence corresponding to each power consumption data, and then obtain the second credibility of each power consumption data according to the power consumption data in the power consumption data sequence and the volatility index value of each power consumption data; therefore, this embodiment will first obtain the volatility index value of each power consumption data, and the specific acquisition process is as follows:

[0043] First, according to the adjacent power consumption data of each power consumption data in the power consumption data sequence corresponding to each test chip, the adjacent slope difference values ​​corresponding to each power consumption data in each power consumption data sequence are obtained; then, according to the difference between two adjacent power consumption data in the local subsequence corresponding to each power consumption data, the characteristic difference value sequence corresponding to each power consumption data is obtained; and after the adjacent slope difference values ​​and characteristic difference value sequence corresponding to each power consumption data are obtained, for the sake of ease of understanding, this embodiment will next be described by taking the acquisition process of the volatility index value of the power consumption data b in the power consumption data sequence B as an example based on the acquired adjacent slope difference values ​​and characteristic difference value sequence, that is, the acquisition process of the volatility index value of the power consumption data b is: first, the reciprocal of the result obtained by adding the adjacent slope difference values ​​corresponding to the power consumption data b and the preset first constant is recorded as the first characteristic value of the power consumption data b, the result obtained by subtracting the first characteristic value from the preset first constant is recorded as the second characteristic value of the power consumption data b, the mean value of the characteristic difference value sequence corresponding to the power consumption data b is recorded as the third characteristic value of the power consumption data b, and the mean value of the second characteristic value and the third characteristic value of the power consumption data b is recorded as the volatility index value of the power consumption data b.

[0044] In addition, the specific expression for calculating the volatility index value of the power consumption data b is:

[0045]

[0046] Among them, γ is the volatility index value of power consumption data b, ΔK is the adjacent slope difference value corresponding to power consumption data b, is the second eigenvalue of the power consumption data b, and D3 is the third eigenvalue of the power consumption data b; and when ΔK is larger, it indicates that the difference between the power consumption data b and its two adjacent data on the left and right is larger, that is, the more it indicates that the power consumption data b is more likely to belong to a turning point, and when the power consumption data b is more likely to belong to a turning point, the volatility of the position of the power consumption data b may be greater; when D3 is larger, it indicates that the data change in the local window corresponding to the power consumption data b is larger, and it also indicates that the fluctuation of the data in the local window corresponding to the power consumption data b is more obvious, and when the fluctuation of the data in the local window corresponding to the power consumption data b is more obvious, the volatility of the position of the power consumption data b may be greater; and because when ΔK is larger and D3 is larger, the value of γ is larger, and based on the above analysis, it can be known that when the value of γ is larger, it indicates that the volatility of the position of the power consumption data b may be greater, and conversely, when the value of γ is smaller, it indicates that the volatility of the position of the power consumption data b may be smaller.

[0047] In this embodiment, according to the adjacent power consumption data of each power consumption data in the power consumption data sequence corresponding to each test chip, the process of obtaining the adjacent slope difference values ​​corresponding to each power consumption data in each power consumption data sequence is as follows:

[0048] First, a mapping space is constructed, and the horizontal coordinate value of the data point in the constructed mapping space is the first mark value, and the vertical coordinate value is the power consumption data; then, all power consumption data and the first mark value of the power consumption data in each power consumption data sequence are mapped to the mapping space, and the data points obtained by the mapping are recorded as data points corresponding to the corresponding power consumption data, that is, each power consumption data in the power consumption data sequence corresponds to a data point, and the horizontal coordinate value of the data point corresponding to any power consumption data is the first mark value of the power consumption data, and the vertical coordinate value is the power consumption data.

[0049] On the basis of the data points corresponding to the acquired power consumption data, the following will take the acquisition process of the adjacent slope difference values ​​corresponding to the j-th power consumption data in the power consumption data sequence B as an example for description, that is, the acquisition process of the adjacent slope difference values ​​corresponding to the j-th power consumption data in the sequence B is: first, determine whether j is not equal to 1 and B0, if so, then obtain the slope of the straight line formed by the data point corresponding to the j-th power consumption data in the sequence B and the data point corresponding to the j-1-th power consumption data, and record it as the first slope, obtain the slope of the straight line formed by the data point corresponding to the j-th power consumption data in the sequence B and the data point corresponding to the j+1-th power consumption data, and record it as the second slope, and then compare the first slope with the second slope. The absolute value of the difference between the rates is taken as the adjacent slope difference value corresponding to the j-th power consumption data in sequence B, and B0 is the total number of data in sequence B; otherwise, continue to judge whether j is equal to 1. If so, the absolute value of the slope of the straight line formed by the data point corresponding to the j-th power consumption data in sequence B and the data point corresponding to the j+1-th power consumption data is taken as the adjacent slope difference value corresponding to the j-th power consumption data in sequence B; otherwise, continue to judge whether j is equal to B0. If so, the absolute value of the slope of the straight line formed by the data point corresponding to the j-th power consumption data in sequence B and the data point corresponding to the j-1-th power consumption data is taken as the adjacent slope difference value corresponding to the j-th power consumption data in sequence B.

[0050] In this embodiment, the method for obtaining the feature difference sequence corresponding to each power consumption data is as follows: for the power consumption data b in the power consumption data sequence B, the normalized value of the absolute value of the difference between two adjacent power consumption data in the local subsequence corresponding to the power consumption data b is obtained, and then a sequence constructed by the normalized values ​​of the absolute value of the difference between all two adjacent power consumption data in the local subsequence corresponding to the power consumption data b is recorded as the feature difference sequence corresponding to the power consumption data b, that is, the d-th feature difference value in the feature difference sequence corresponding to the power consumption data b is the normalized value of the absolute value of the difference between the d+1-th power consumption data and the d-th power consumption data in the local subsequence corresponding to the power consumption data, that is, the result of normalizing the absolute value of the difference between the d+1-th power consumption data and the d-th power consumption data using the normalization function norm() is the d-th feature difference value in the feature difference sequence corresponding to the power consumption data b.

[0051] Therefore, according to the above process of obtaining the volatility index value of power consumption data b, this embodiment can obtain the volatility index value of each power consumption data in each power consumption data sequence. After obtaining the volatility index value of each power consumption data, this embodiment will then obtain the second credibility of each power consumption data according to the power consumption data in the power consumption data sequence and the volatility index value of each power consumption data, and the second credibility is one of the important indicators for subsequently obtaining the credibility weighting factor for weighted fusion; in addition, for ease of understanding, this example will take the second credibility acquisition process of the j-th power consumption data in the power consumption data sequence B as an example for description, that is, the second credibility acquisition process of the j-th power consumption data in the sequence B is:

[0052] First, the first subsequence, the second subsequence, and the third subsequence of the j-th power consumption data in sequence B are obtained; then, linear fitting is performed on the data points corresponding to all power consumption data in the first subsequence, and the straight line obtained by fitting is recorded as the first data point fitting straight line, and the volatility index values ​​of all power consumption data in the first subsequence are linearly fitted, and the straight line obtained by fitting is recorded as the first volatility fitting straight line; then, the similarity between the first data point fitting straight line and the first volatility fitting straight line is calculated, and the calculation result is recorded as the first similarity value. Then, linear fitting is performed on the data points corresponding to all power consumption data in the second subsequence, and the straight line obtained by fitting is recorded as the second data point fitting straight line; linear fitting is performed on the volatility index values ​​of all power consumption data in the second subsequence, and the straight line obtained by fitting is recorded as the second volatility fitting straight line; then, the similarity between the second data point fitting straight line and the second volatility fitting straight line is calculated, and the calculation result is recorded as the second similarity value. Next, the absolute value of the difference between the first similarity value and the second similarity value is obtained, and recorded as the first similarity difference. The reciprocal of the first similarity difference plus the preset first constant is obtained, and recorded as the first characteristic ratio. The mean of the first characteristic ratio and the second similarity value is obtained, and recorded as the first characteristic mean corresponding to the j-th power consumption data in sequence B.

[0053] Then, on the second data point fitting straight line, obtain the data point with the same horizontal coordinate value as the data point corresponding to the j-th power consumption data in sequence B, and record it as the first fitting data point corresponding to the j-th power consumption data in sequence B. Then, calculate the Euclidean distance between the data point corresponding to the j-th power consumption data in sequence B and its corresponding first fitting data point, and record it as the first distance representation value; then, perform linear fitting on the data points corresponding to all power consumption data in the third subsequence, and record the straight line obtained by fitting as the third data point fitting straight line; then, on the third data point fitting straight line, obtain the data point corresponding to the j-th power consumption data in sequence B. The data points with the same horizontal coordinate value are obtained, and recorded as the second fitting data point corresponding to the j-th power consumption data in sequence B, and then the Euclidean distance between the data point corresponding to the j-th power consumption data in sequence B and the corresponding second fitting data point is calculated, and recorded as the second distance representation value; continue to obtain the absolute value of the difference between the first distance representation value and the second distance representation value, and record it as the third distance representation value, then obtain the reciprocal of the third distance representation value plus the preset first constant, and record it as the second characteristic ratio, and then obtain the mean of the second characteristic ratio and the first distance representation value, and record it as the second characteristic mean corresponding to the j-th power consumption data in sequence B.

[0054] Finally, the average of the first feature mean corresponding to the j-th power consumption data in sequence B and the second feature mean corresponding to the j-th power consumption data in sequence B is obtained, and recorded as the second credibility of the j-th power consumption data in sequence B.

[0055] In this embodiment, the process of acquiring the first subsequence, the second subsequence, and the third subsequence of the j-th power consumption data in the sequence B is as follows:

[0056] First, determine whether j is greater than the preset second constant. If so, record the data sequence formed by the 1st power consumption data to the jth power consumption data in sequence B as the first subsequence of the jth power consumption data. At this time, the first subsequence includes the jth power consumption data in sequence B. Record the data sequence formed by the 1st power consumption data to the j-1th power consumption data in sequence B as the second subsequence of the jth power consumption data. At this time, the second subsequence includes the j-1th power consumption data in sequence B but does not include the jth power consumption data. Record the data sequence formed by the j-1th power consumption data to the j-M1th power consumption data in sequence B as the third subsequence of the jth power consumption data. M1 is the preset first quantity threshold value corresponding to the jth power consumption data in sequence B. At this time, the third subsequence includes the j-1th power consumption data and the j-M1th power consumption data in sequence B. In specific applications, the implementer needs to set the preset second constant according to actual conditions. For example, the preset second constant can be set to 3 or 5. In addition, this embodiment requires that the value of the preset first quantity threshold value M1 corresponding to the jth power consumption data in sequence B should belong to the interval And it is required to be an integer. For example, if j is 10, the preset first quantity threshold M1 corresponding to the j-th power consumption data in sequence B can be set to 4.

[0057] When it is judged that j is not greater than the preset second constant, the data sequence formed by the jth power consumption data to the j+Z1th power consumption data in sequence B is recorded as the first subsequence of the jth power consumption data. At this time, the first subsequence includes the jth power consumption data and the j+Z1th power consumption data in sequence B. The data sequence formed by the j+1th power consumption data to the j+Z1th power consumption data in sequence B is recorded as the second subsequence corresponding to the jth power consumption data. At this time, the second subsequence includes the j+1th power consumption data and the j+Z1th power consumption data in sequence B. The data sequence formed by the j+1th power consumption data to the j+Z2th power consumption data in sequence B is recorded as the third subsequence corresponding to the jth power consumption data. Subsequence, the third subsequence at this time includes the j+1th power consumption data and the j+Z2th power consumption data in sequence B, Z1 is a preset first integer, Z2 is a preset second integer, that is, Z1 and Z2 are both integers; and in a specific application, the implementer needs to set the values ​​of Z1 and Z2 according to the actual situation, but requires Z2 to be less than Z1. For example, in this embodiment, the value of Z1 may be required to be greater than one-tenth of the total number of data in sequence B but less than one-third of the total number of data in sequence B, and the value of Z2 may be required to be greater than 5 but not greater than one-tenth of the total number of data in sequence B. For example, if the total number of data in sequence B is 90, then Z1 may be set to 20 and Z2 may be set to 8.

[0058] In addition, in this embodiment, a specific expression for obtaining the second credibility of the j-th power consumption data in sequence B is:

[0059]

[0060] Wherein, β2 is the second credibility of the j-th power consumption data in sequence B, U1 is the first distance characterization value, U2 is the second distance characterization value, |U1-U2| is the third distance characterization value, is the second feature mean, H2 is the first similarity value, H2 is the second similarity value, |H1-H2| is the first similarity difference, is the first eigenvalue.

[0061] And when |U1-U2| and U1 are smaller, it indicates that the trend difference of the j-th power consumption data in sequence B in a smaller range and the trend difference in a larger range are more consistent, and the j-th power consumption data in sequence B is more similar to the fitting data on the fitting line, and it also indicates that the j-th power consumption data in sequence B may be less disturbed at this time, and when the interference is less, it can also indicate that the credibility of the j-th power consumption data in sequence B is higher; when |H1-H2| is smaller and H2 is larger, it indicates that the data fluctuation trend and data change trend of the j-th power consumption data in sequence B in a smaller range or a larger range are more similar, that is, when the power consumption data change speed becomes larger, the volatility of the power consumption data will also become larger, and it also indicates that at this time in sequence B The j-th power consumption data may be less interfered with, and when the interference is less, it can also indicate that the credibility of the j-th power consumption data in sequence B is higher; and because the smaller |U1-U2| and U1 are, the smaller |H1-H2| is, and the larger H2 is, the larger the value of β2 is, and based on the above description, it can be seen that when the value of β2 is larger, the j-th power consumption data in sequence B may be less interfered with, thereby indicating that the credibility of the j-th power consumption data in sequence B is higher, and the higher the credibility, the greater the reference degree of the j-th power consumption data in sequence B when performing weighted fusion later; conversely, when the value of β2 is smaller, it indicates that the j-th power consumption data in sequence B may be more interfered with, thereby indicating that the credibility of the j-th power consumption data in sequence B is lower.

[0062] Therefore, according to the above process of acquiring the second credibility of the j-th power consumption data in the sequence B, this embodiment can acquire the second credibility of each power consumption data in each power consumption sequence. In addition, in the present embodiment, linear fitting is performed multiple times and the similarity between any two straight lines is calculated multiple times. In a specific application, the implementer needs to select a method for linear fitting and calculating the similarity between any two straight lines according to actual conditions. For example, in the present embodiment, the least square method can be selected for linear fitting, and the angle between the two straight lines is used to measure the similarity between the two straight lines. It should be noted that when the angle between the two straight lines is used to measure the similarity between the two straight lines, the angle between the two straight lines is negatively correlated with the similarity between the two straight lines, that is, the angle between the two straight lines needs to be normalized first. The purpose of normalization is to eliminate the dimension. Then, the normalized angle is negatively mapped, and the mapping result is used as the similarity between the corresponding two straight lines. For example, if the angle between two straight lines is 30 degrees, the angle between the two straight lines is first normalized by 180 degrees, that is, the ratio of 30 degrees to 180 degrees is the normalization result, and then exp(-X) is used as the similarity between the two straight lines, exp() is an exponential function with a constant e as the base, and X is the normalized value of the angle between the two straight lines.

[0063] Step S004: Obtain credibility weighting factors of the respective power consumption data according to the first credibility and the second credibility, and perform weighted fusion on all the power consumption data sequences according to the credibility weighting factors of the power consumption data to obtain a target data sequence.

[0064] After obtaining the first credibility and the second credibility of each power consumption data, this embodiment will then perform weighted fusion. Since both the first credibility and the second credibility can reflect the credibility of the power consumption data, in order to facilitate the subsequent weighted fusion, this embodiment will first integrate the first credibility and the second credibility of each power consumption data to obtain a credibility weighting factor for subsequent weighted fusion. That is, this embodiment first obtains the credibility weighting factor of each power consumption data according to the first credibility and the second credibility of each power consumption data, which is specifically:

[0065] For the power consumption data b in the power consumption data sequence B: first, obtain the cumulative sum of the target credibility corresponding to all power consumption data in the characteristic power consumption data set of the power consumption data b, and record it as the comprehensive credibility; then obtain the ratio of the target credibility corresponding to the power consumption data b to the comprehensive credibility, and record it as the credibility weighting factor of the power consumption data b; and the target credibility corresponding to the power consumption data refers to the average of the first credibility and the second credibility of the corresponding power consumption data.

[0066] This embodiment can obtain the credibility weighting factor of each power consumption data according to the above-mentioned process of obtaining the credibility weighting factor of the power consumption data b. After obtaining the credibility weighting factor of the power consumption data, this embodiment will perform weighted fusion on all power consumption data sequences according to the credibility weighting factor of each power consumption data in the power consumption data sequence, and obtain the target data sequence according to the weighted fusion result. The specific process of obtaining the target data sequence is: first, obtain the weighted value of each power consumption data in each power consumption data sequence, and record the sequence composed of the weighted values ​​of each power consumption data in the power consumption data sequence as the weighted value sequence of the corresponding power consumption data sequence, then add all the obtained weighted value sequences, and record the sequence obtained after adding the sequences as the target data sequence, and the weighted value of any power consumption data refers to the product of the credibility weighting factor of the power consumption data and the power consumption data.

[0067] Therefore, this embodiment can obtain the target data sequence according to the above process, and all data in the target data sequence are recorded as target data.

[0068] Step S005: acquiring stability test results of the batch of chips to be tested under the abnormal test environment according to the target data sequence.

[0069] After obtaining the target data sequence, this embodiment will analyze the target data sequence to obtain the stability test results of the batch of chips to be tested under the abnormal test environment, specifically:

[0070] First, the sequence to be analyzed in the target data sequence is obtained, and the specific acquisition process of the sequence to be analyzed is: if the t-1th target data in the target data sequence is not greater than the preset limit power consumption threshold, and all the data behind the t-1th data are greater than the preset limit power consumption threshold, the data behind the t-1th data refers to the tth target data in the target data sequence and all the target data behind the tth target data in the target data sequence, then the sequence formed by the tth target data and all the target data behind the tth target data in the target data sequence is recorded as the sequence to be analyzed, and all the data in the sequence to be analyzed exceeds the maximum power consumption value of the chip type being tested. In addition, in specific applications, the implementer needs to determine the preset limit power consumption threshold according to the type of the batch of chips to be tested, and the preset limit power consumption threshold also refers to the maximum power consumption of the specified chip. If the batch of chips to be tested is a medium-power chip, the preset limit power consumption threshold can be set to 0.5 watts.

[0071] Then, the unit time length is obtained, and the unit time length is the collection time interval between two adjacent data in the power consumption data sequence, and in the present embodiment, the collection time interval between two adjacent data in each power consumption data sequence is consistent; then, the product of the total number of data in the sequence to be analyzed and the unit time length is obtained, and recorded as the abnormal time length, and the abnormal time length refers to the time length that the chip power consumption during the test exceeds the preset limit power consumption threshold.

[0072] Next, the ratio of the abnormal time length to the total test time of any test chip is obtained, and recorded as the first ratio, and in this embodiment, the total test time of each test chip is equal; then the difference between the preset first constant and the first ratio is obtained, and recorded as the first indicator value; then the normalized ratio sequence corresponding to the sequence to be analyzed is obtained, and the mean of the normalized ratio sequence is recorded as the first mean, and the difference between the preset first constant and the first mean is recorded as the second indicator value; and the rth normalized ratio in the normalized ratio sequence corresponding to the sequence to be analyzed refers to the normalized value of the second ratio corresponding to the rth target data in the sequence to be analyzed, and the second ratio corresponding to the rth target data refers to the ratio of the difference to be analyzed of the rth target data and the preset limit power consumption threshold, then the difference to be analyzed of the rth target data refers to the absolute value of the difference between the rth target data and the preset limit power consumption threshold, and the normalization function norm() is used here to perform normalization.

[0073] Finally, the average of the first index value and the second index value is obtained and used as the stability index value of the batch of chips to be tested under the abnormal test environment; in addition, the specific expression for obtaining the stability index value of the batch of chips to be tested under the abnormal test environment is:

[0074]

[0075] Where W is the stability index value of the batch of chips to be tested under the abnormal test environment, T1 is the abnormal time length, T2 is the total test time, n1 is the first mean value, is the first index value, (1-n1 is the second index value; and when The smaller the value of W is and the smaller the value of n1 is, the larger the value of W is. The larger the value of W is, the longer the time that the chips in the tested batch are in normal operation under the abnormal test environment is, and the better the stability of the chips in the tested batch is under the abnormal test environment. Conversely, the smaller the value of W is, the worse the stability of the chips in the tested batch is under the abnormal test environment.

[0076] Therefore, the present embodiment can obtain the stability index value of the batch of chips to be tested under the abnormal test environment through the above process, and based on the obtained stability index value of the batch of chips to be tested under the abnormal test environment, the stability of the batch of chips to be tested under the abnormal test environment can be analyzed, for example, a preset stability threshold is obtained, when the obtained stability index value of the batch of chips to be tested under the abnormal test environment is less than the preset stability threshold, it is determined that the stability of the batch of chips to be tested under the abnormal test environment is poor, or it is determined that the stability of the batch of chips to be tested does not meet the requirements, on the contrary, when the obtained stability index value of the batch of chips to be tested under the abnormal test environment is not less than the preset stability threshold, it is determined that the stability of the batch of chips to be tested under the abnormal test environment is good, or it is determined that the stability of the batch of chips to be tested meets the requirements; and in specific applications, the implementer needs to set the preset stability threshold according to actual conditions, such as 0.4; in addition, it should be noted that the obtained sequence to be analyzed may be an empty set, and when it is an empty set, it indicates that the data in the target data sequence does not exceed the preset limit power consumption threshold, then it indicates that the power consumption data in the target data sequence all meet the prescribed power consumption requirements, so it is directly determined that the stability of the batch of chips to be tested meets the requirements.

[0077] In summary, this embodiment first selects A test chips from the batch of chips to be tested, and performs a high-voltage accelerated aging test on each test chip to obtain a power consumption data sequence corresponding to each test chip under an abnormal test environment; secondly, a local subsequence corresponding to each power consumption data in the power consumption data sequence is obtained, and linear fitting is performed on the power consumption data sequence and the local subsequence corresponding to each power consumption data, respectively, to obtain a first fitting straight line for the power consumption data sequence and a second fitting straight line for each power consumption data, and a first credibility of each power consumption data is obtained according to the first fitting straight line and the second fitting straight line; then, according to adjacent power consumption data of each power consumption data in the power consumption data sequence and the difference between two adjacent power consumption data in the local subsequence, a volatility index value of each power consumption data is obtained, and according to the power consumption data in the power consumption data sequence and the volatility index value of each power consumption data, a second credibility of each power consumption data is obtained; then, according to the first credibility and the second credibility, a credibility weighting factor of each power consumption data is obtained, and according to the credibility weighting factor of the power consumption data, all power consumption data sequences are weightedly fused to obtain a target data sequence; finally, according to the target data sequence, a stability test result of the batch of chips to be tested under an abnormal test environment is obtained. Furthermore, the target data sequence obtained by weighted fusion according to the credibility weighting factor in this embodiment can make the stability test results of the batch of chips to be tested under the abnormal test environment more accurate and reliable.

[0078] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application 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 may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for testing chip stability in abnormal environment based on MiniLED display, characterized in that: The method comprises the following steps: A test chips are selected from the batch of chips to be tested, and a high-voltage accelerated aging test is performed on each test chip to obtain a power consumption data sequence corresponding to each test chip under an abnormal test environment, where A is greater than 1; Acquire a local subsequence corresponding to each power consumption data in the power consumption data sequence, and perform linear fitting on the power consumption data sequence and the local subsequence corresponding to each power consumption data, respectively, to obtain a first fitting straight line of the power consumption data sequence and a second fitting straight line of each power consumption data, and obtain a first credibility of each power consumption data according to the first fitting straight line and the second fitting straight line; Obtaining a volatility index value of each power consumption data according to adjacent power consumption data of each power consumption data in the power consumption data sequence and a difference between two adjacent power consumption data in the local subsequence, and obtaining a second credibility of each power consumption data according to the power consumption data in the power consumption data sequence and the volatility index value of each power consumption data; Obtaining a credibility weighting factor of each power consumption data according to the first credibility and the second credibility, and performing weighted fusion on all the power consumption data sequences according to the credibility weighting factor of the power consumption data to obtain a target data sequence; According to the target data sequence, a stability test result of the batch of chips to be tested under the abnormal test environment is obtained.

2. The abnormal environment chip stability testing method based on MiniLED display according to claim 1, characterized in that: The method for acquiring the local subsequences corresponding to each power consumption data includes: For any power consumption data b in any power consumption data sequence B, a window containing the power consumption data b and equal to the preset local window size is constructed on the power consumption data sequence B, and recorded as the local window corresponding to the power consumption data b. The sequence formed by all data in the local window corresponding to the power consumption data b is recorded as the local subsequence corresponding to the power consumption data b.

3. The abnormal environment chip stability testing method based on MiniLED display according to claim 1, characterized in that: The method for obtaining the first credibility of each power consumption data includes: Calculate the similarity between the second fitting straight line of each power consumption data in the power consumption data sequence and the first fitting straight line of the corresponding power consumption data sequence, and record the calculation result as the fitting similarity characterization value corresponding to the corresponding power consumption data; obtain the first label value of each power consumption data in the power consumption data sequence, and the first label value of the j-th power consumption data in the power consumption data sequence is j; For any power consumption data b in any power consumption data sequence B: in all the power consumption data sequences, a set constructed by all power consumption data having the same first tag value as the power consumption data b is recorded as the characteristic power consumption data set of the power consumption data b; among the fitting similarity characterization values ​​corresponding to all the power consumption data in the characteristic power consumption data set, the maximum fitting similarity characterization value is selected as the maximum characterization value of the power consumption data b; the absolute value of the difference between the fitting similarity characterization value corresponding to the power consumption data b and the maximum characterization value is taken as the first difference; the reciprocal of the value obtained by adding the first difference to the preset first constant is recorded as the first characterization value; the value of the characteristic power consumption data set except the first difference is recorded as the first characterization value. The set formed by the data other than the power consumption data b is recorded as subset B1; the first similarity index value corresponding to each power consumption data in the subset B1 is obtained, and the first similarity index value corresponding to the h-th power consumption data in the subset B1 is the similarity between the local subsequence corresponding to the h-th power consumption data and the local subsequence corresponding to the power consumption data b; in the subset B1, the number of power consumption data whose first similarity index value is greater than the preset similarity threshold is counted and recorded as the first quantity representation value; the ratio of the first quantity representation value to the total number of data in the subset B1 is recorded as the second representation value; the average of the first representation value and the second representation value is recorded as the first credibility of the power consumption data b.

4. The abnormal environment chip stability testing method based on MiniLED display according to claim 3 is characterized in that: The method for obtaining the volatility index value of each power consumption data includes: According to adjacent power consumption data of each power consumption data in the power consumption data sequence, adjacent slope difference values ​​corresponding to each power consumption data are obtained; a feature difference value sequence corresponding to each power consumption data is obtained, wherein the dth feature difference value in the feature difference value sequence corresponding to the power consumption data is a normalized value of the absolute value of the difference between the d+1th data and the dth data in the local subsequence corresponding to the corresponding power consumption data; For any power consumption data b in any power consumption data sequence B, the inverse of the result obtained by adding adjacent slope difference values ​​corresponding to the power consumption data b and a preset first constant is recorded as the first eigenvalue of the power consumption data b, the result obtained by subtracting the first eigenvalue from the preset first constant is recorded as the second eigenvalue of the power consumption data b, the mean of the characteristic difference value sequence corresponding to the power consumption data b is recorded as the third eigenvalue of the power consumption data b, and the mean of the second eigenvalue and the third eigenvalue is recorded as the volatility index value of the power consumption data b.

5. The abnormal environment chip stability testing method based on MiniLED display according to claim 4, characterized in that: The method for obtaining adjacent slope difference values ​​corresponding to each power consumption data includes: Constructing a mapping space, in which the horizontal coordinate value of a data point in the mapping space is the first mark value and the vertical coordinate value is the power consumption data; mapping all the power consumption data and the first mark value of the power consumption data in the power consumption data sequence to the mapping space to obtain a data point corresponding to each power consumption data in the power consumption data sequence; For the j-th power consumption data in the power consumption data sequence B: if j is equal to 1, the absolute value of the slope of the straight line formed by the two data points corresponding to the j-th power consumption data and the j+1-th power consumption data in the sequence B is used as the adjacent slope difference value corresponding to the j-th power consumption data in the sequence B; if j is equal to B0, the absolute value of the slope of the straight line formed by the two data points corresponding to the j-th power consumption data and the j-1-th power consumption data in the sequence B is used as the adjacent slope difference value corresponding to the j-th power consumption data in the sequence B, and B0 is the total number of data in the sequence B; if j is not equal to 1 and B0, the slope of the straight line formed by the two data points corresponding to the j-th power consumption data and the j-1-th power consumption data in the sequence B is recorded as the first slope, the slope of the straight line formed by the two data points corresponding to the j-th power consumption data and the j+1-th power consumption data in the sequence B is recorded as the second slope, and the absolute value of the difference between the first slope and the second slope is used as the adjacent slope difference value corresponding to the j-th power consumption data in the sequence B.

6. The abnormal environment chip stability testing method based on MiniLED display according to claim 5, characterized in that: The method for obtaining the second credibility of the power consumption data includes: For the jth power consumption data in any power consumption data sequence B: Obtain a first subsequence, a second subsequence, and a third subsequence of the j-th power consumption data in the power consumption data sequence B; The straight line obtained by linearly fitting the data points corresponding to all the power consumption data in the first subsequence is recorded as the first data point fitting straight line, the straight line obtained by linearly fitting the volatility index values ​​of all the power consumption data in the first subsequence is recorded as the first volatility fitting straight line, the similarity between the first data point fitting straight line and the first volatility fitting straight line is calculated, and the calculation result is recorded as the first similarity value; the straight line obtained by linearly fitting the data points corresponding to all the power consumption data in the second subsequence is recorded as the second data point fitting straight line, the straight line obtained by linearly fitting the volatility index values ​​of all the power consumption data in the second subsequence is recorded as the second volatility fitting straight line, the similarity between the second data point fitting straight line and the second volatility fitting straight line is calculated, and the calculation result is recorded as the second similarity value; the absolute value of the difference between the first similarity value and the second similarity value is recorded as the first similarity difference, and the reciprocal of the sum of the first similarity difference and the preset first constant is recorded as the first characteristic ratio; the mean of the first characteristic ratio and the second similarity value is recorded as the first characteristic mean; The data point corresponding to the j-th power consumption data in the sequence B is recorded as a characteristic data point; on the second data point fitting straight line, a data point with a horizontal coordinate value equal to that of the characteristic data point is obtained and recorded as a first fitting data point; the Euclidean distance between the characteristic data point and the first fitting data point is recorded as a first distance characterization value; the straight line obtained by linearly fitting the data points corresponding to all power consumption data in the third subsequence is recorded as a third data point fitting straight line, and on the third data point fitting straight line, a data point with a horizontal coordinate value equal to that of the characteristic data point is obtained and recorded as a second fitting data point; the Euclidean distance between the characteristic data point and the second fitting data point is recorded as a second distance characterization value; the absolute value of the difference between the first distance characterization value and the second distance characterization value is recorded as a third distance characterization value, and the reciprocal of the sum of the third distance characterization value and a preset first constant is recorded as a second characteristic ratio; the mean of the second characteristic ratio and the first distance characterization value is recorded as a second characteristic mean; The average of the first feature mean and the second feature mean is recorded as the second credibility of the j-th power consumption data in the sequence B.

7. The abnormal environment chip stability testing method based on MiniLED display according to claim 6, characterized in that: The method for obtaining the first subsequence, the second subsequence and the third subsequence includes: If j is greater than the preset second constant, the sequence formed by the 1st power consumption data to the jth power consumption data in the sequence B is recorded as the first subsequence corresponding to the jth power consumption data, the sequence formed by the 1st power consumption data to the j-1th power consumption data in the sequence B is recorded as the second subsequence corresponding to the jth power consumption data, and the sequence formed by the j-1th power consumption data to the j-M1th power consumption data in the sequence B is recorded as the third subsequence corresponding to the jth power consumption data, and M1 is the preset first quantity threshold corresponding to the jth power consumption data in the sequence B ; If j is not greater than the preset second constant, the sequence formed by the jth power consumption data to the j+Z1th power consumption data in the sequence B is recorded as the first subsequence corresponding to the jth power consumption data, the sequence formed by the j+1th power consumption data to the j+Z1th power consumption data in the sequence B is recorded as the second subsequence corresponding to the jth power consumption data, and the sequence formed by the j+1th power consumption data to the j+Z2th power consumption data in the sequence B is recorded as the third subsequence corresponding to the jth power consumption data, Z1 is the preset first integer, and Z2 is the preset second integer.

8. The abnormal environment chip stability testing method based on MiniLED display according to claim 3, characterized in that: The method for obtaining the credibility weighting factor includes: For the power consumption data b: the cumulative sum of the target credibility corresponding to all power consumption data in the characteristic power consumption data set of the power consumption data b is recorded as the comprehensive credibility; the ratio of the target credibility corresponding to the power consumption data b to the comprehensive credibility is recorded as the credibility weighting factor of the power consumption data b, and the target credibility corresponding to the power consumption data is the average of the first credibility and the second credibility of the corresponding power consumption data.

9. The abnormal environment chip stability testing method based on MiniLED display according to claim 1, characterized in that: The method for acquiring the target data sequence includes: The product of the credibility weighting factor of the power consumption data and the corresponding power consumption data is recorded as the weighted value of the corresponding power consumption data; the sequence composed of the weighted values ​​of each power consumption data in the power consumption data sequence is recorded as the weighted value sequence of the corresponding power consumption data sequence; and the sequence obtained by adding all the weighted value sequences is recorded as the target data sequence.

10. The abnormal environment chip stability testing method based on MiniLED display according to claim 1, characterized in that: The method for obtaining the stability test results of the batch of chips to be tested under the abnormal test environment comprises: If the t-1th data in the target data sequence is not greater than the preset limit power consumption threshold, and all data after the t-1th data are greater than the preset limit power consumption threshold, then the sequence formed by all data after the t-1th data in the target data sequence is recorded as the sequence to be analyzed; the unit time length is obtained, and the unit time length is the collection time interval between two adjacent data in the power consumption data sequence; the product of the total number of data in the sequence to be analyzed and the unit time length is recorded as the abnormal time length; The ratio of the abnormal time length to the total test time of the test chip is recorded as the first ratio; the result of subtracting the first ratio from the preset first constant is recorded as the first index value; the normalized ratio sequence corresponding to the sequence to be analyzed is obtained, the mean of the normalized ratio sequence is recorded as the first mean, and the result of subtracting the first mean from the preset first constant is recorded as the second index value; the rth normalized ratio value in the normalized ratio sequence corresponding to the sequence to be analyzed is the normalized value of the second ratio corresponding to the rth data in the sequence to be analyzed, the second ratio corresponding to the rth data is the ratio of the difference to be analyzed of the rth data and the preset limit power consumption threshold, and the difference to be analyzed of the rth data is the absolute value of the difference between the rth data and the preset limit power consumption threshold; the mean of the first index value and the second index value is used as the stability index value of the batch of chips to be tested under the abnormal test environment.

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