CN105844077A - Testability growth test method based on timely correction strategy - Google Patents

Abstract

The invention discloses a testability growth test method based on a timely correction strategy. The objective is to solve a problem of a lack of systematical test method during conduction on a testability growth test based on a timely correction strategy. The technical scheme are: analyzing a testability initial level of a device according to early information at first, then calculating an expected change process of a device testability index during a testability growth test, and drawing a test planning curve; then calculating testability index change situations of the device after improvement; and at last, comparing the testability index actual change process with an expected process, thereby making a test process control strategy. By use of the testability growth test method, the problem of a lack of systematical test method during conduction on a testability growth test based on a timely correction strategy at present can be solved; the testability growth process of a to-be-tested system can be effectively monitored; by timely adjusting a testability growth test scheme, a test process is controlled, thereby reducing test risks and costs.

Description

A kind of testability growth test method based on timely correction strategy

Technical field

The present invention relates to the testability development test method in equipment preparation stage；The testability being based especially on timely correction strategy increases Long test method.

Background technology

Testability is to be equipped under stipulated time and regulation environment the ability with isolated fault that can correctly detect, and can use multiple survey Examination property index is weighed, including fault detect rate (FDR), Percent Isolated (FIR), false alarm rate (FAR) etc..For large-scale From the point of view of complex equipment, fault diagnosis system the most often also exists various problem, the most unpredictable fault, surveys Examination was lost efficacy, ambiguity group, inappropriate testability tolerance and threshold value etc..The testability level of equipment to be made reaches to design requirement, just Need to go to differentiate and correct testability design defect by various means, thus improve the testability index of equipment, it is achieved testability Increase.

GJB2547A " equipment Test sex work General Requirement " clearly gives the basic conception that testability increases: grind at product During system and use, by progressively correcting the testability defect of product, improve constantly product test level, thus reach pre- The process of phase target.Can be realized by design based on model and other method although testability increases, but testability increases Test remains most efficient method, for system test is had strong request all kinds of newly to grind system all the more so.Testability Growth test realizes the growth of testability index by a series of Test-amend-process of the test, until meeting the testability of system Index request.

Test and the consumption of time and resource be can not ignore, especially test period and experimental condition have a lot of uncertain because of The testability growth property test of element is all the more so, it is therefore necessary to has the test method of science, thus reduces experimentation cost, shortens examination Test the cycle.But, for the most specifically carrying out testability growth test, the most concrete rule in the relevant criterion the most announced Fixed.According to the experience of reliability growth test, growth test work includes that test planning, test are implemented, test is followed the tracks of with anticipated Four aspects.Specifically before being embodied as growth test, provide rational testing program, then according to testing program is opened exactly Exhibition direct fault location test, and the design defect exposed is improved, then utilize test data to assess in time in process of the test Increase effect, and follow the tracks of and intended result timely Adjustment Tests scheme according to increasing.Use for reference reliability growth test process, in time Correction strategy is one of test method of testability growth test employing.Examination is being increased for the testability using timely correction strategy Proved recipe face, only Zhao Chenxu (the Zhao Chenxu et al.A Markov Chain-Based Testability of the National University of Defense technology Growth Model i.e. based on Markov Chain and cost benefit function the testability of With a Cost-Benefit Function increases mould Type, is published in ieee transactions on systems, man, and cybernetics:systems, doi:10, 1109/tsmc.2015.2437837) and Li Tianmei (the T.M.Li et al.The Assessment and of engineering college of Second Artillery Force of PLA Foundation of Bell-Shaped Testability Growth Effort Functions Dependent System Testability The testability model of growth that Growth Models Based on NHPP i.e. increases Efficiency Function based on NHPP and bell type testability is built Mould and application, be specifically shown in http://dx.doi.org/10.1155/2015/613170) studied in correlative theses, but these Research exists clearly disadvantageous: 1) the most clearly provide the specific implementation method of testability growth test based on timely correction strategy； 2) carried model of growth is all parameter model, and relevant parameter needs to utilize estimation of test data to obtain, and is difficult to before test is carried out Estimate its value, therefore, it is difficult to be used for planning and the formulation of testability growth test scheme.Increase to more effectively carry out testability Long test, it is necessary to for testability growth test based on timely correction strategy, provide the test method of a kind of system.

Summary of the invention

The technical problem to be solved in the present invention: at present when carrying out testability growth test based on timely correction strategy, lack The present situation of the test method of weary system, it is provided that a kind of testability growth test method.Application the method can be implemented in on-test Before, consider installation feature, historical data, designer's technical merit factor, provide rational testability growth test Scheme, it is possible in process of the test, adjusts testing program in time according to the tracking result increasing effect, thus sternly Lattice control whole process of the test, reduce empirical risk and cost.

The technical scheme of the testability growth test method based on timely correction strategy that the present invention proposes is:

1st step, according to system under test (SUT) fault mode, impact and HAZAN (FMECA) result (GJB1391-2006 " fault mode, impact and HAZAN guide ") determine the fault mode sum N that system under test (SUT) is had；

2nd step, collects early stage testability data, touches including testability prediction result, testability virtual test data, testability End test data, expertise, designer's designed capacity, and the testability index design required value req of system under test (SUT)；

3rd step, according to the early stage testability data of FMECA result and collection, designs entirety fault mode according to testability Updatability is divided into renewable fault mode and non-renewable fault mode two class, and system under test (SUT) is divided into two subsystems accordingly: The subsystem of renewable fault mode composition and the subsystem of non-renewable fault mode composition, then utilize Bayes method of estimation (Wang Chao, " testability test and comprehensive assessment technology that deficiency and excess combines ", National University of Defense technology's academic dissertation, 2014, the 81st Page page-the 92) calculate fault detect probability β that non-renewable subsystem has and the primary fault inspection that renewable subsystem has Survey probability α；

4th step, utilizes (1) formula to calculate primary fault undetected probability p (1) that renewable subsystem has；

P (1)=1-α (1)

5th step, utilizes (2) formula to calculate testability index growth goal value σ of renewable subsystem,

$\frac{\mathrm{\σ}\underset{j=1}{\overset{K}{\mathrm{\Σ}}}{\mathrm{\λ}}_j+\mathrm{\β}\underset{k=1}{\overset{N-K}{\mathrm{\Σ}}}{\mathrm{\λ}}_k}{\underset{i=1}{\overset{N}{\Σ}}{\mathrm{\λ}}_i}=req---\left(2\right)$

Wherein K in being renewable subsystem renewable fault mode sum, λ_iIt is i-th kind of fault mode fault rate, 1≤i≤N；

6th step, utilizes (3) formula to calculate the fault undetected probability that renewable subsystem needs to reach at the end of growth test p_end；

p_end=1-σ (3)

Increase historical experience according to similar similar system testability simultaneously, system designer and trial person determine renewable event The average coefficient f that updates of barrier pattern, allows failed direct fault location to test (GJB2547A before 0 ＜ f≤1, and each design update " equipment Test sex work General Requirement ") number of times m, 1≤m≤K/2；

7th step, makes k=1；

8th step, utilizes (4) formula to calculate the direct fault location test number (TN) r needing to carry out before kth time design improves_kExpected value E (r_k),

$E\left(r_k\right)=\frac{m}{E\left(p\right(k\left)\right)}---\left(4\right)$

E (p (k)) is the expected value of fault undetected probability p (k) of renewable subsystem before kth time design improves；

9th step, utilizes (5) formula to calculate the phase of testability index growth factor q (k) of renewable subsystem when kth time design improves Prestige value E (q (k))；

$E\left(q\right(k\left)\right)=\[1-{(1-\frac{E\left(p\right(k\left)\right)}{K})}^{E\left(r_k\right)}\]f---\left(5\right)$

10th step, utilizes (6) formula to update the fault undetected probability expected value of renewable subsystem after kth time design improves E(p(k+1))；

$\begin{array}{c}E\left(p\left(k+1\right)\right)=\[1-E\left(q\right(k\left)\right)\]E\left(p\right(k\left)\right)\\ E\left(p\right(1\left)\right)=p\left(1\right)\end{array}---\left(6\right)$

11st step, utilizes (7) formula to calculate test and proceeds to direct fault location test total degree R required during the kth stage_kExpected value E(R_k)；

$E\left(R_k\right)=\underset{j=1}{\overset{k}{\Σ}}E\left(r_j\right)---\left(7\right)$

12nd step, if E (p (k+1))≤p_req, turn the 13rd step, otherwise make k=k+1, and go to the 8th step；

13rd step, with E (R_k) it is transverse axis, it is that the longitudinal axis draws testability growth planning curve as shown in Figure 2 with 1-E (p (k)), and Renewable subsystem testing growth test scheme is formulated according to this curve；

14th step, makes k=1；

15th step, is the simple random sampling method that " maintainability test and evaluation " national military standard specifies with reference to GJB2072-94, Random choose fault mode is concentrated to carry out direct fault location test from renewable fault mode, until kth step-by-step test failure sum etc. In m；

16th step, after direct fault location off-test, before testability design update, utilizes Bayes method, according to test success or failure Type data calculate the undetectable rate of fault of renewable subsystem(Zhao Chenxu et al.A Markov Chain-Based Testability Growth Model With a Cost-Benefit Function, Zhao Chenxu etc. based on Markov Chain and cost benefit Testability model of growth Part III second trifle of function), ifTurn the 18th step, otherwise turn the 17th step；

17th step, ifI.e. process of the test deviates testing program set in advance, turn the 2nd step, otherwise, It is designed the testability design defect come out updating, after design update terminates, makes k=k+1, turn the 15th step；

18th step, off-test.

Use the present invention can obtain following beneficial effect:

1, before carrying out testability growth test based on timely correction strategy, the method utilizing the present invention to propose can be formulated rationally Testability growth test planning, obtain testability growth test planning curve, determine testability growth test scheme, thus solve Certainly it is currently based on the problem that the testability growth test of timely correction strategy lacks test planing method；

2, during test is carried out, utilize method that the present invention proposes can with effective monitoring system under test (SUT) testability propagation process, By the way of adjusting testability growth test scheme in time, Control experiment process, reduce empirical risk and cost.

In sum, the testability growing method that the present invention provides has considered the feature of subjects fault mode, and system sets The information such as the technical merit of meter personnel, historical data and experience, what the method utilizing the present invention to provide can be scientific and reasonable instructs base In the carrying out of testability growth test of timely correction strategy, contribute to improving testability growth test in current engineering practice and face The problem of shortage system test method.

Accompanying drawing explanation

Fig. 1 is overview flow chart of the present invention；

Fig. 2 is that the testability that the present invention the 14th step is drawn increases planning curve synoptic diagram.

Detailed description of the invention

Fig. 1 is overview flow chart of the present invention, specifically comprises the following steps that

1st step, determines, according to system under test (SUT) FMECA result, the fault mode sum N that system under test (SUT) is had；

2nd step, collects early stage testability data, touches including testability prediction result, testability virtual test data, testability End test data, expertise, designer's designed capacity, and the testability index design required value req of system under test (SUT)；

3rd step, utilizes the testability information that the 1st step and the 2nd step obtain, by system under test (SUT) entirety fault mode according to testability Design updatability is divided into renewable fault mode and non-renewable fault mode two class, and the most renewable fault mode sum is K, Non-renewable fault mode sum is N-K, and system under test (SUT) is divided into two subsystems accordingly: renewable fault mode composition Subsystem and the subsystem of non-renewable fault mode composition, then utilize Bayes method of estimation to calculate non-renewable subsystem tool Primary fault detection probability α that some fault detect probability β and renewable subsystem have；

4th step, utilizes (1) formula to calculate the primary fault undetected probability that renewable subsystem has；

5th step, utilizes (2) formula to calculate testability index growth goal value σ of renewable subsystem；

6th step, utilizes (3) formula to calculate the fault undetected probability that renewable subsystem needs to reach at the end of growth test p_end；Collect similar similar system testability simultaneously and increase historical information, system designer and trial person determine renewable Failed direct fault location test number (TN) is allowed before the average renewal coefficient of fault mode and each design update；

7th step, makes k=1；

8th step, utilizes (4) formula to calculate the direct fault location test number (TN) expected value E (r needing to carry out before kth time design improves_k)；

9th step, utilizes (5) formula to calculate the testability index growth factor expected value of renewable subsystem when kth time design improves E(q(k))；

10th step, utilizes (6) formula to update the fault undetected probability expected value of renewable subsystem after kth time design improves E(p(k+1))；

11st step, utilizes (7) formula to calculate test and proceeds to the direct fault location test total degree R needed for the kth stage_k；

12nd step, if E (p (k+1))≤p_req, turn the 13rd step, otherwise make k=k+1, and go to the 8th step；

13rd step, draws testability and increases planning curve, and formulate renewable subsystem testing growth test scheme；

14th step, makes k=1；

15th step, carries out direct fault location test, until kth step-by-step test failure sum is equal to m；

16th step, utilizes Bayes method to calculate the undetectable rate of fault of renewable subsystem according to test success failure type data IfTurn the 18th step, otherwise turn the 17th step；

17th step, ifTurn the 2nd step, otherwise, the testability design defect come out is set Meter updates, and after design update terminates, makes k=k+1, turns the 15th step.

18th step, off-test.

Fig. 2 is that the testability utilizing the present invention to draw increases planning curve synoptic diagram, and wherein the 1st article of horizontal vertical coordinate represents Testability growth test carry out before the testability index initial value 1-E (p (1)) that had of equipment, abscissa starting point is 0, and terminal is E(R₁)；Remaining kth, the horizontal vertical coordinate in k >=2 be equipped in kth time design update before the testability index that has 1-E (p (k)), abscissa starting point is E (R_k-1)+1, terminal is E (R_k)；The step of adjacent two horizontal linears represents testability and sets After meter improves, equipment Test is risen to.

Claims (1)

1. a testability growth test method based on timely correction strategy, it is characterised in that comprise the following steps:

According to system under test (SUT) fault mode, impact and HAZAN i.e. FMECA result, 1st step, determines that system under test (SUT) is had Some fault mode sum N；

2nd step, collects early stage testability data, touches including testability prediction result, testability virtual test data, testability End test data, expertise, designer's designed capacity, and the testability index design required value req of system under test (SUT)；

3rd step, according to the early stage testability data of FMECA result and collection, designs entirety fault mode according to testability Updatability is divided into renewable fault mode and non-renewable fault mode two class, and system under test (SUT) is divided into two subsystems accordingly: The subsystem of renewable fault mode composition and the subsystem of non-renewable fault mode composition, then utilize Bayes method of estimation Calculate fault detect probability β that non-renewable subsystem has and primary fault detection probability α that renewable subsystem has；

4th step, utilizes (1) formula to calculate primary fault undetected probability p (1) that renewable subsystem has；

P (1)=1-α (1)

5th step, utilizes (2) formula to calculate testability index growth goal value σ of renewable subsystem,

$\frac{\mathrm{\σ}\underset{j=1}{\overset{K}{\Σ}}{\mathrm{\λ}}_j+\mathrm{\β}\underset{k=1}{\overset{N-K}{\Σ}}{\mathrm{\λ}}_k}{\underset{i=1}{\overset{N}{\Σ}}{\mathrm{\λ}}_i}=req---\left(2\right)$

Wherein K in being renewable subsystem renewable fault mode sum, λ_iIt is i-th kind of fault mode fault rate, 1≤i≤N；

6th step, utilizes (3) formula to calculate the fault undetected probability that renewable subsystem needs to reach at the end of growth test p_end；

p_end=1-σ (3)

Meanwhile, increase historical experience according to similar similar system testability, determine that the average of renewable fault mode updates coefficient f, Failed direct fault location test number (TN) m, 1≤m≤K/2 is allowed before 0 ＜ f≤1, and each design update；

7th step, makes k=1；

8th step, utilizes (4) formula to calculate the direct fault location test number (TN) r needing to carry out before kth time design improves_kExpected value E (r_k),

$E\left(r_k\right)=\frac{m}{E\left(p\right(k\left)\right)}---\left(4\right)$

E (p (k)) is the expected value of fault undetected probability p (k) of renewable subsystem before kth time design improves；

9th step, utilizes (5) formula to calculate the phase of testability index growth factor q (k) of renewable subsystem when kth time design improves Prestige value E (q (k))；

$E\left(q\right(k\left)\right)=\[1-{(1-\frac{E\left(p\right(k\left)\right)}{K})}^{E\left(r_k\right)}\]f---\left(5\right)$

10th step, utilizes (6) formula to update the fault undetected probability expected value of renewable subsystem after kth time design improves E(p(k+1))；

$\begin{array}{c}E\left(p\right(k+1\left)\right)=\[1-E\left(q\right(k\left)\right)\]E\left(p\right(k\left)\right)\\ E\left(p\right(1\left)\right)=p\left(1\right)\end{array}---\left(6\right)$

11st step, utilizes (7) formula to calculate test and proceeds to direct fault location test total degree R required during the kth stage_kExpected value E(R_k)；

$E\left(R_k\right)=\underset{j=1}{\overset{k}{\Σ}}E\left(r_j\right)---\left(7\right)$

12nd step, if E (p (k+1))≤p_req, turn the 13rd step, otherwise make k=k+1, and go to the 8th step；

13rd step, with E (R_k) it is transverse axis, it is that the longitudinal axis draws testability growth planning curve with 1-E (p (k)), and according to this curve Formulate renewable subsystem testing growth test scheme；

14th step, makes k=1；

15th step, is the simple random sampling method that " maintainability test and evaluation " national military standard specifies with reference to GJB2072-94, Random choose fault mode is concentrated to carry out direct fault location test from renewable fault mode, until kth step-by-step test failure sum etc. In m；

16th step, after direct fault location off-test, before testability design update, utilizes Bayes method, according to test success or failure Type data calculate the undetectable rate of fault of renewable subsystemIfTurn the 18th step, otherwise turn the 17th step；

17th step, ifI.e. process of the test deviates testing program set in advance, turn the 2nd step, otherwise, It is designed the testability design defect come out updating, after design update terminates, makes k=k+1, turn the 15th step；

18th step, off-test.