论文标题
拓扑优化增强了基于电阻断层扫描的传感器的区分性和重构性
Topology optimization enhances the distinguishability and reconstructability of electrical resistance tomography based sensors
论文作者
论文摘要
在大多数应用电阻断层扫描（ERT）的应用中，估计问题包括在现有背景上空间电导率变化的估计，或者是对整个目标的电导率的空间分布的估计，包括背景。但是，在某些情况下，可以设计背景电导率。这种应用的一个示例是设计基于ERT的传感器，可以设计背景电导率。在这种应用中，自然的问题是，是否可以通过这种方式来设计背景电导率，以提高传感器的区分性和进一步的重构性。本文使用拓扑优化来设计背景电导率以实现最佳的区分性。然后，ERT重建建议使用拓扑优化传感器增强可重构性。
In the majority of applications of electrical resistance tomography (ERT) the estimation problem consists of either the estimation of spatial conductivity change over an existing background or the estimation of spatial distribution of conductivity of the entire target, including the background. In some instances however, it is possible to design the background conductivity; an example of such application is the design of ERT-based sensors where the background conductivity can be engineered. In such applications the natural question is whether the background conductivity can be engineered in such a way to increase the distinguishability and further reconstructability of the sensor. The present paper, uses topology optimization to design the background conductivity to achieve optimal distinguishability. Then, ERT reconstructions suggest the enhancements of reconstructability using topology optimized sensor.
