HEMP damage probability evaluation method based on Bayesian theorem

Abstract

The invention discloses an HEMP damage probability evaluation method based on the Bayesian theorem, and solves the problem that the probability distribution of effective damage probability is difficult to obtain by the existing HEMP damage probability evaluation method of tested electronic equipment. The HEMP damage probability evaluation method based on the Bayesian theorem provided by the invention has the advantages that through a damage evaluation model, the probability distribution of the effective damage probability can be obtained; the probability distribution of the damage probability is solved by utilizing a real experimental result and adopting the Bayesian theorem, so that the probability distribution and the confidence coefficient of the damage probability can be obtained, more information of the damage probability, such as expectation, a damage probability range and the confidence coefficient, can be obtained, and the result is accurate and reliable.

Description

Technical Field

[0001] The invention relates to a HEMP damage probability assessment method, and in particular to a HEMP damage probability assessment method based on Bayesian theorem. Background Art

[0002] High altitude electromagnetic pulse (HEMP) has high field strength, wide spectrum and wide range of action. The anti-HEMP characteristics of the electronic equipment under test can be obtained through irradiation testing and pulse current injection.

[0003] At present, the HEMP test method for electronic equipment can be carried out with reference to GJB 8848 and GJB 151B. However, there are few methods for evaluating the damage probability of HEMP test for electronic equipment under test. Usually, the ratio of the number of failures to the number of test repetitions is used as the HEMP damage probability of the electronic equipment under test, but this method cannot give the confidence of the result and obtains less damage information. Summary of the invention

[0004] The purpose of the present invention is to provide a HEMP damage probability assessment method based on Bayesian theorem to solve the technical problem that the existing HEMP damage probability assessment method for the electronic equipment under test is difficult to obtain the probability distribution of the effective damage probability.

[0005] In order to achieve the above object, the present invention adopts the following technical solution:

[0006] A method for evaluating the probability of HEMP damage based on Bayesian theorem is characterized in that it includes the following steps:

[0007] Step 1: Define event A in the damage assessment model as the electronic device under test is not damaged or has no performance degradation, and define event B i is the damage probability p of the electronic equipment under test i , i=1,2,……,N,N≥2, N is event B i the number of

[0008] Step 2: Given the event B i The initial probability of occurrence is P0(B i );

[0009] Step 3: Carry out n tests in sequence, n ≥ 2; after each test, based on the result of the current test A k or Bayesian theorem is used to solve the posterior probability P of HEMP damage to the electronic equipment under test k (B i |A k )or Get P k (B i); after the first test, use P1(B i ) Correction P0(B i ), ..., after the kth test, use P k (B i ) Correction P k-1 (B i ), ..., and so on, until we get P n (B i ), where k = 1, 2, ..., n, A k There is no damage or performance degradation in the kth test. Damage or performance degradation occurs during the kth test;

[0010] Step 4: Based on P n (B i ) Obtain the evaluation result of the HEMP damage probability of the electronic equipment under test and complete the HEMP damage probability evaluation of the electronic equipment under test.

[0011] Furthermore, step 2 is specifically as follows:

[0012] If prior information is available, the event B is given by the prior information i The initial value of the probability of occurrence P0(B i );

[0013] If no prior information is available, the initial probability value P0(B i )=1 / N.

[0014] Furthermore, in step 2, the prior information includes equipment subsystem test results, electromagnetic topology analysis and / or protection design indicators.

[0015] Furthermore, in step 3, the test is a HEMP irradiation test.

[0016] Furthermore, in step 3, the test is an injection test.

[0017] Furthermore, in step 3, if the kth test result is A k ,but:

[0018]

[0019] If the result of the kth test is but:

[0020]

[0021] Where j is a positive integer, the value range of j is 1 to N, p i =(i-1) / (N-1).

[0022] Furthermore, in step 1, N=1001.

[0023] Furthermore, in step 4, the evaluation result of the HEMP damage probability of the electronic device under test includes the expectation, cumulative probability density distribution and confidence level of the HEMP damage probability.

[0024] Furthermore, in step 3, n≥12.

[0025] Beneficial effects of the present invention:

[0026] 1. The HEMP damage probability assessment method based on Bayesian theorem provided by the present invention can obtain the probability distribution of the damage probability and its confidence level through a damage assessment model, and obtain more information about the damage probability by using real experimental results and Bayesian theorem to solve the probability distribution of the damage probability.

[0027] 2. The HEMP damage probability assessment method based on Bayesian theorem provided by the present invention can calculate the statistical parameters of the damage probability, such as expectation, damage probability range and confidence level, according to the probability distribution of the damage probability of the tested electrical equipment, and the result is accurate and reliable. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a flow chart of an embodiment of a method for evaluating the probability of HEMP damage based on Bayesian theorem of the present invention;

[0029] Figure 2 is a graph of a posteriori results corresponding to different damage probabilities in an embodiment of the present invention (no damage or performance degradation occurs in n shots);

[0030] Figure 3 : is a cumulative probability density distribution curve diagram of different damage probabilities in an embodiment of the present invention (no damage or performance degradation occurs in n times). DETAILED DESCRIPTION

[0031] The technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings and embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0032] The HEMP damage probability assessment method based on Bayesian theorem provided in this embodiment is as follows: Figure 1 As shown in the figure, taking the case where no damage or performance degradation occurs to the electronic equipment under test after n tests, the specific steps are as follows:

[0033] Step 1: Define event A in the damage assessment model as the electronic device under test is not damaged or has no performance degradation, and define event B in the damage assessment model i is the damage probability p of the electronic equipment under test i =(i-1) / (N-1), i=1,2,...N,N≥2, N is event B i the number of

[0034] Among them, the value of N is related to the damage probability p i The estimated accuracy requirement is related to N = 11, which means the estimated damage probability p i The final result is 10%, 20%, 30%... Taking N=101 as an example, the damage probability is expressed as 3%, 11%, 21%... etc. Generally, when the number of tests is large, the value of N can be made larger, and when the number of tests is small, the value of N can be made smaller.

[0035] Step 2: Given event B i The initial probability value P0(B i ), that is, the probability of damage to the electronic equipment under test p i The initial probability value P0(B i ); specifically:

[0036] If prior information is available, then event B is given by the prior information i The initial probability value P0(B i ).

[0037] If no prior information is available, let the initial probability value P0(B i )=1 / N.

[0038] In this embodiment, let event B i The initial probability value P0(B i ) is 1 / N, then:

[0039] P(A|B i )=1-p i

[0040] Step 3: Carry out n tests in sequence. After each test, the result A of the current test is used as the basis. k or A k There is no damage or performance degradation in the kth test. The probability of HEMP damage of the electronic equipment under test P is solved by Bayesian theorem. k (B i |A k )or Get P k (B i); After the first test, the obtained P1(B i ) Modify the initial probability value P0(B i )...After the kth test, the obtained P k (B i ) Correct the P obtained after the k-1th test k-1 (B i ) ... and so on, until we get P n (B i );

[0041] Specifically, based on P0(B i ), the initial probability of event A occurring is P0(A):

[0042]

[0043] The p i Substituting the value of into the equation, we get:

[0044]

[0045] Likewise, That is, in the absence of any prior information, the probability of the electronic device being damaged or not being degraded is the same, both 1 / 2.

[0046] If the electronic equipment under test is not damaged or degraded after the first test, based on the a posteriori results, Bayes’ theorem yields:

[0047]

[0048] At this time, P1(B i )=P1(B i |A1), based on the assumption that the electronic equipment under test in the second round of testing also did not suffer damage or performance degradation, then:

[0049]

[0050] According to Bayes' theorem:

[0051]

[0052] And so on, recursively get the nth test case;

[0053]

[0054] The n tests are all tests that support the same experimental conclusion, such as HEMP irradiation tests with different layout settings; they can also be injection tests.

[0055] In other embodiments, the test result of the nth test may also be but:

[0056]

[0057] Step 4: Based on P n (B i ) Obtain the evaluation result of the HEMP damage probability of the electronic equipment under test and complete the HEMP damage probability evaluation of the electronic equipment under test.

[0058] In this embodiment, N=1001. After n tests, if the electronic device under test is not damaged or performance degraded, P n (B i |A) Follow p i The changing rules are as follows Figure 2 As shown. Further, the cumulative probability density distribution of different damage probabilities (no damage or performance degradation occurs in n rounds) is obtained as follows Figure 3 shown.

[0059] according to Figure 3 The curve can give the damage probability and its confidence level (i.e. vertical axis) of different test times as shown in Table 1.

[0060] Table 1 Damage probability and confidence level of different test times

[0061] Confidence n＝1 n＝2 n＝3 n＝6 n＝12 n＝24 n＝48 65％ 40.83％ 29.52％ 23.08％ 13.92％ 7.75％ 4.11％ 2.11％ 90％ 68.37％ 53.58％ 43.76％ 28.03％ 16.22％ 8.79％ 4.58％ 95％ 77.64％ 63.16％ 52.71％ 34.81％ 20.58％ 11.29％ 5.92％ 99％ 89.99％ 78.45％ 68.37％ 48.2％ 29.87％ 16.82％ 8.96％

[0062] An example is given to illustrate the meaning of the data in the table: when 24 tests are carried out on the same section at the same intensity level, and no damage or performance degradation occurs in all tests, the probability of damage to the electronic equipment under test is less than 4.11% (confidence level is 65%); if 48 tests are carried out on the same section at the same intensity level, the probability of damage to the electronic equipment under test is less than 4.58% (confidence level is 90%), the number of tests can be selected by comprehensively considering the test cost and effect. In the absence of prior knowledge, the recommended number of tests is greater than or equal to 12.

[0063] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for evaluating the probability of HEMP damage based on Bayesian theorem, characterized in that: The following steps are involved: Step 1: Define event A in the damage assessment model as the electronic device under test is not damaged or has no performance degradation, and define event B i is the damage probability p of the electronic equipment under test i , i=1,2,……,N,N≥2, N is event B i the number of Step 2: Given the event B i The initial probability of occurrence is P0(B i ); Step 3: Carry out n tests in sequence, n ≥ 2; after each test, based on the result of the current test A k or Bayesian theorem is used to solve the posterior probability P of HEMP damage to the electronic equipment under test k (B i |A k )or Get P k (B i ); after the first test, use P1(B i ) Correction P0(B i ), ..., after the kth test, use P k (B i ) Correction P k-1 (B i ), ..., and so on, until we get P n (B i ), where k = 1, 2, ..., n, A k There is no damage or performance degradation in the kth test. Damage or performance degradation occurs during the kth test; Step 4: Based on P n (B i ) Obtain the evaluation result of the HEMP damage probability of the electronic equipment under test and complete the HEMP damage probability evaluation of the electronic equipment under test.

2. The HEMP damage probability assessment method based on Bayesian theorem according to claim 1 is characterized in that: Step 2 is as follows: If prior information is available, the event B is given by the prior information i The initial value of the probability of occurrence P0(B i ); If no prior information is available, the initial probability value P0(B i )=1 / N.

3. The HEMP damage probability assessment method based on Bayesian theorem according to claim 1, characterized in that: In step 2, the prior information includes equipment subsystem test results, electromagnetic topology analysis and / or protection design indicators.

4. The HEMP damage probability assessment method based on Bayesian theorem according to claim 1, characterized in that: In step 3, the test is a HEMP irradiation test.

5. The HEMP damage probability assessment method based on Bayesian theorem according to claim 1, characterized in that: In step 3, the test is an injection test.

6. The HEMP damage probability assessment method based on Bayesian theorem according to any one of claims 1 to 5, characterized in that: In step 3, if the result of the kth test is A k ,but: If the result of the kth test is but: Where j is a positive integer, the value range of j is 1 to N, p i =(i-1) / (N-1).

7. The HEMP damage probability assessment method based on Bayesian theorem according to claim 6 is characterized in that: In step 1, N=1001.

8. The HEMP damage probability assessment method based on Bayesian theorem according to claim 7 is characterized in that: In step 4, the evaluation result of the HEMP damage probability of the electronic device under test includes the expectation, cumulative probability density distribution and confidence level of the HEMP damage probability.

9. The HEMP damage probability assessment method based on Bayesian theorem according to claim 8, characterized in that: In step 3, n≥12.

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