Optimum reduction of sensing electrodes for delamination identification with electrical resistance tomography

Abstract

Electrical resistance tomography (ERT) is a non-destructive evaluation (NDE)technique that measures the voltages when electric current is injected in a body where damage induced electrical conductivity changes occur. Accurate and efficient damage identification in carbon fiber reinforced polymer (CFRP) composites using ERT requires the optimal selection of the sensing sites. The present work uses an effective independence (EI) measure for selecting the optimally reduced set of measurements among all possible for ERT damage identification. Finite element analyses (FEA) are used to calculate the electrical potential in two CFRP laminate layups with 14 electrodes given a set of specified delamination cases that span the space of possible damage states. Measurement reduction uses two strategies based on individual or group selection about the injection site. A third strategy performs complete electrode exclusion. Inverse identification of delamination cases for the full and the reduced sets after applying the strategies estimates the effectiveness of EI reduction. Results show the lowest errors come from individual measurement elimination. Electrode elimination is attainable with acceptable accuracy loss. This work shows that the EI measure optimally reduces electrode and electrode combinations in ERT-based damage identification.

The Innovative Self-Sensing Strain Sensor for Asphalt Pavement Structure: Substitutability and Synergy Effects of Graphene Platelets With Carbon Nanotubes in Epoxy Composites

“…The transverse and longitudinal directions and distresses, such as cracks, ruts, and settlements can be efficiently measured by distributed optical fibre sensing technology (Xiang and Wang, 2016;Wang et al, 2018;Xiang and Wang, 2018;Wang et al, 2020). However, with the effect of complex construction conditions, such as heavy compaction and high-temperature of asphalt concrete, heavy vehicles, and extreme environments over its life-span, the traditional strain sensors are usually difficult to maintain in the asphalt pavement structure (Hasni et al, 2017;Escalona-Galvis and Venkataraman, 2021). Besides, the poor durability and deformation incompatibility of conventional sensing elements also restrict the development of intelligent monitoring for road engineering.…”