Systems Engineering and Electronics
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DENG Lu, XU Ai-qiang, WU Zhong-de
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Abstract:
Aiming to the cost of testability verification experiment, a method of failure sample optimization selection based on the genetic algorithm is proposed. Through the analyses of faulttest correlation and fault-fault equivalent, the alternative failure sample concentration equivalent set of each element is determined and the extension alternative failure sample set is established. On this basis the solving model of failure sample optimization selection is set up. Without reducing the sample injection quantity and the characteristics of the test conditions, the coding model of sample optimization selection is built by using the generalized chromosome. A method of failure sample selection and sequence injection is put forward based on the genetic algorithm, which takes the minimum cost as the optimization goal. Finally, an example results show that this method can effectively reduce the test cost.
DENG Lu, XU Ai-qiang, WU Zhong-de. Method of failure sample optimization selection based on genetic algorithm[J]. Systems Engineering and Electronics, doi: 10.3969/j.issn.1001-506X.2015.07.36.
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URL: https://www.sys-ele.com/EN/10.3969/j.issn.1001-506X.2015.07.36
https://www.sys-ele.com/EN/Y2015/V37/I7/1703