A PBI-based system-level testability design optimization method

An optimization method and testable technology, applied in software testing/debugging, computing, genetic rules, etc., can solve problems such as slow convergence speed, high time complexity, slow search speed, etc., and achieve the effect of improving the convergence speed

Active Publication Date: 2019-04-09
UNIV OF ELECTRONICS SCI & TECH OF CHINA +1
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Problems solved by technology

The NSGA-III algorithm is more typical and can find a more comprehensive non-dominated solution set. However, due to the high time complexity of the calculation

Method used

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  • A PBI-based system-level testability design optimization method
  • A PBI-based system-level testability design optimization method
  • A PBI-based system-level testability design optimization method

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Embodiment

[0043] In order to better illustrate the technical solution of the present invention, the technical principle of the present invention is first described.

[0044] figure 1 is a schematic diagram of the PBI method. like figure 1As shown, in the PBI (penalty-based boundary intersection) method, W is a pre-specified reference weight vector, which is generally automatically generated according to the number specified by the user, such as dividing a two-dimensional space (a quadrant) into 5 6 weight vectors are required, and the included angle between them is 90° / 5=18°. The multi-objective optimization based on this method is to distribute an objective function F(X) on each weight vector, which is close to the coordinate origin (minimization problem). To measure whether an objective function (1) is close to the weight vector; (2) is it close to the coordinate origin, available figure 1 shown d 1 and d 2 to express the weighted sum of :

[0045]

[0046] in,

[0047] ...

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Abstract

The invention discloses a system-level testability design optimization method based on PBI. The method includes: firstly, setting a weight vector based on a PBI method; calculating the lower limit ofthe penalty factor corresponding to each weight vector; and then iteratively searching an optimal influence factor vector based on a genetic algorithm, carrying out optimization by combining an objective function value and a PBI function value in a searching process to obtain a new population, and deleting a dominated solution in a final generation population to obtain a Pareto optimal solution set of the influence factor vector. With the adoption of the method, the convergence speed of the algorithm can be increased while the optimal solution is ensured to be obtained.

Description

technical field [0001] The invention belongs to the technical field of equipment test design optimization, and more particularly, relates to a system-level test design optimization method based on PBI. Background technique [0002] In order to reduce the difficulty of equipment maintenance in the future, the system should be designed for testability in the initial stage of design. Testability refers to the degree to which the state of a system can be accurately detected. In the problem of fault diagnosis for large-scale electronic equipment systems, how to choose a test plan, so that the fault detection rate (FDR, fault diagnosis rate), the false alarm rate (FAR, fault alarm rate) and the test costs (time, economy, etc.) Indicators that satisfy the constraints at the same time or even tend to be better are constantly explored in academic and engineering fields. [0003] In the test optimization problem, the test indicators concerned are the fault detection rate (FDR, fault...

Claims

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Application Information

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IPC IPC(8): G06F11/36G06N3/12
CPCG06F11/3672G06N3/126
Inventor 杨成林胡聪
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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