Quasi-random fault sampling method for airborne equipment testability experiments

Abstract

The invention discloses a quasi-random fault sampling method for airborne equipment testability experiments. The fault sample size determination method for the airborne equipment testability experiments comprises steps as follows: Step 1: fault modes of tested equipment are acquired with a fault mode effect and hazard degree analyzing method on the basis of hardware, and the number of the fault modes and the fault mode frequency ratio Cp of every corresponding fault mode are determined; Step 2: all the fault modes are mapped to a first interval, and the position relation of all the fault modes in the first interval is determined through a formula; Step 3: with the adoption of a quasi-random number generation method, N quasi-random numbers are generated in the first interval; Step 4: statistics is performed on the number of the quasi-random numbers of each fault mode in the corresponding position in the first interval. The quasi-random fault sampling method for the airborne equipment testability experiments is obviously superior to a pseudo-random sampling method and can significantly improve sampling precision and coverage and reduce dispersity.

Description

technical field [0001] The invention relates to the technical field of aviation product testing, in particular to a quasi-random fault sampling method for airborne equipment testability test and a quasi-random fault sampling system for airborne equipment testability test. Background technique [0002] The testability test of airborne equipment is to stimulate a specific number of faults in the product under test by means of fault injection, conduct actual tests with the detection method of testability design, and judge whether the test results meet expectations, so as to discover product testability design defects and evaluate product-related defects. Experimental activities for testable indicators. Among them, the fault individuals and the number of excitations required for the test determined by the fault sampling should have conformity and coverage. That is, the sampling results should conform to the law of failure and cover various situations of product failure, so as t...

AI Technical Summary

Problems solved by technology

For the fault sampling method, the existing technology usually adopts proportional stratified sampling and simple random sampling method. The evaluation results of the above two methods are highly dispersed and often inaccurate, which will directly affect the effect of engineering application.

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