基于混合遗传蚁群算法的数字微流控芯片测试路径规划

发布时间：2019-03-27 10:59

【摘要】：数字微流控芯片在生化检测领域的应用越来越广泛,为保障芯片的可靠性必须对其进行全面且高效的故障测试。随着芯片规模的扩大,故障测试问题也越来越复杂。针对数字微流控芯片的灾难性故障测试,为提高故障测试方法的时间效率,本文提出了一种基于混合遗传蚁群算法的测试路径规划方案。首先,该方案优化了芯片故障测试模型的转化过程;其次,先利用遗传算法的全局特性生成全局较优测试路径,并根据较优测试路径形成蚁群算法的初始信息素分布;最后,再利用蚁群算法搜索最优测试路径。该方案适用于离线测试和在线测试,能够兼容规则和非规则芯片。实验仿真结果表明,该方案提高了测试模型转化的效率,在获得较优测试路径的同时改善了测试算法的收敛特性,提高了测试方法的时间效率。
[Abstract]:The application of the digital micro-fluidic chip in the field of biochemical detection is becoming more and more extensive, and it is necessary to conduct a comprehensive and efficient fault test for the reliability of the chip. With the expansion of the size of the chip, the problem of fault test is becoming more and more complex. In order to improve the time efficiency of the fault test method, a test path planning scheme based on the hybrid genetic ant colony algorithm is proposed in order to improve the time efficiency of the fault test method. firstly, the scheme optimizes the transformation process of the chip fault test model; secondly, the global optimal test path is generated by using the global property of the genetic algorithm, and the initial pheromone distribution of the ant colony algorithm is formed according to the better test path; and finally, And then the ant colony algorithm is used for searching the optimal test path. The scheme is applicable to off-line testing and on-line testing, and can be compatible with regular and non-regular chips. The experimental simulation results show that the scheme improves the efficiency of the test model conversion, improves the convergence property of the test algorithm while obtaining the better test path, and improves the time efficiency of the test method.
【作者单位】：桂林电子科技大学电子工程与自动化学院;广西高校光电信息处理重点实验室;广西自动检测技术与仪器重点实验室;
【基金】：国家自然科学基金(61540014,61671164) 广西自然科学基金(2014GXNSFAA118398) 广西自动检测技术与仪器重点实验室基金(YQ16105)资助项目
【分类号】：TN492;TP18

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