Zheng Wenbin, Shi Jinlong, Wang Anqi, Fu Ping, Jiang Hongyuan
School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, China.
School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China.
Micromachines (Basel). 2020 Nov 28;11(12):1052. doi: 10.3390/mi11121052.
Digital microfluidic biochips (DMFBs) are attractive instruments for obtaining modern molecular biology and chemical measurements. Due to the increasingly complex measurements carried out on a DMFB, such chips are more prone to failure. To compensate for the shortcomings of the module-based DMFB, this paper proposes a routing-based fault repair method. The routing-based synthesis methodology ensures a much higher chip utilization factor by removing the virtual modules on the chip, as well as removing the extra electrodes needed as guard cells. In this paper, the routing problem is identified as a dynamic path-planning problem and mixed path design problem under certain constraints, and an improved Dijkstra and improved particle swarm optimization (ID-IPSO) algorithm is proposed. By introducing a cost function into the Dijkstra algorithm, the path-planning problem under dynamic obstacles is solved, and the problem of mixed path design is solved by redefining the position and velocity vectors of the particle swarm optimization. The ID-IPSO routing-based fault repair method is applied to a multibody fluid detection experiment. The proposed design method has a stronger optimization ability than the greedy algorithm. The algorithm is applied to , , and fault-free chips. The proposed ID-IPSO routing-based chip design method saves 13.9%, 14.3%, and 14.5% of the experiment completion time compared with the greedy algorithm. Compared with a modular fault repair method based on the genetic algorithm, the ID-IPSO routing-based fault repair method has greater advantages and can save 39.3% of the completion time on average in the completion of complex experiments. When the ratio of faulty electrodes is less than 12% and 23%, the modular and ID-IPSO routing-based fault repair methods, respectively, can guarantee a 100% failure repair rate. The utilization rate of the electrodes is 18% higher than that of the modular method, and the average electrode usage time is 17%. Therefore, the ID-IPSO routing-based fault repair method can accommodate more faulty electrodes for the same fault repair rate; the experiment completion time is shorter, the average number of electrodes is lower, and the security performance is better.
数字微流控生物芯片（DMFBs）是用于进行现代分子生物学和化学测量的有吸引力的仪器。由于在DMFB上进行的测量日益复杂，此类芯片更容易出现故障。为弥补基于模块的DMFB的缺点，本文提出一种基于路由的故障修复方法。基于路由的合成方法通过去除芯片上的虚拟模块以及作为保护单元所需的额外电极，确保了更高的芯片利用率。本文将路由问题识别为特定约束下的动态路径规划问题和混合路径设计问题，并提出了一种改进的迪杰斯特拉算法和改进的粒子群优化（ID-IPSO）算法。通过将成本函数引入迪杰斯特拉算法，解决了动态障碍物下的路径规划问题，并通过重新定义粒子群优化的位置和速度向量解决了混合路径设计问题。基于ID-IPSO路由的故障修复方法应用于多体流体检测实验。所提出的设计方法比贪婪算法具有更强的优化能力。该算法应用于有故障和无故障的芯片。与贪婪算法相比，所提出的基于ID-IPSO路由的芯片设计方法分别节省了13.9%、14.3%和14.5%的实验完成时间。与基于遗传算法的模块化故障修复方法相比，基于ID-IPSO路由的故障修复方法具有更大优势，在完成复杂实验时平均可节省39.3%的完成时间。当故障电极比例小于12%和23%时，基于模块化和ID-IPSO路由的故障修复方法分别可保证100%的故障修复率。电极利用率比模块化方法高18%，平均电极使用时间为17%。因此，基于ID-IPSO路由的故障修复方法在相同的故障修复率下可以容纳更多的故障电极；实验完成时间更短，平均电极数量更少，安全性能更好。
