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Algorithm for fault localization on a digital microfluidic biochip using particle swarm optimization technique

机译:基于粒子群优化技术的数字微流控生物芯片故障定位算法

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Commercial digital microfluidic biochip is facing an urge for design automation and test because of its complex multi-tasking paradigm. This work presents particle swarm optimization based technique for multiple fault detection in DMFB. The main objective of the algorithm is to localize the faults on a 2D biochip by circulation wash droplet, treated as the particle. PSO framework is modeled with the 2D biochip board as the search space for the particles. Multiple particles are generated from the reservoir and are circulated over the search space. Paths of the particles are guided by the velocity, which is decided upon previous knowledge of the particles' motion. The proposed work tries to find a time efficient procedure for fault localization with minimal number of particle encountered in the process. Simulation study shows that the process will enhance the reliability and accuracy in fault detection of the operational digital microfluidic biochips.
机译:商用数字微流控生物芯片由于其复杂的多任务范例而面临着设计自动化和测试的冲动。这项工作提出了基于粒子群优化的技术,用于DMFB中的多故障检测。该算法的主要目的是通过循环冲洗液滴(被视为颗粒)将故障定位在二维生物芯片上。 PSO框架以2D生物芯片板为粒子的搜索空间进行建模。多个粒子从储层中生成,并在搜索空间中循环。粒子的路径由速度引导,该速度取决于粒子运动的先前知识。拟议的工作试图找到一种在故障定位过程中遇到的粒子数量最少的故障定位程序。仿真研究表明,该过程将提高可操作数字微流控生物芯片故障检测的可靠性和准确性。

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