Towards practical application of electrical resistance change measurement for damage monitoring using an addressable conducting network

Abstract

This article considers the practical use of electrical resistance change method (ERCM) for damage detection in graphite/ polymer composites. ERCM utilizes the high electrical conductivity of graphite fibers in the composites and can detect damage by change in electrical resistance. Since the effectiveness of ERCM has been shown extensively in the literature, it is now necessary to consider how to apply ERCM into existing structures. For practical use of ERCM, a new concept of an addressable conducting network (ACN) has been proposed, which consists of two sets of conducting lines normal to each other. One set of lines resides on the top surface of the laminate and the other resides on the bottom surface. Damage can be detected by monitoring resistance change between two lines across the laminate thickness. In this article, composite panels with several sets of conducting lines are locally loaded by a static indentation test and examined to monitor the distribution of electrical resistance changes. Monitoring the changes in resistance successfully indicated the damage occurrence, but it is sometimes difficult to pinpoint the damage location due to the resistance changes caused by compressive deformation. To improve the sensitivity of ACN to damage, the relationship between damage location and electrical conductivity was investigated using a design of experiments. The changes in resistance with various damage locations and electrical conductivities were acquired from finite element analysis, and the results suggested several ways to optimize damage detection. Depending on the damage tolerance of target structure, spacing of conducting lines and the electrical conductivities can be preferably selected toward practical application of ACN.

Output-only structural health monitoring in changing environmental conditions by means of nonlinear system identification

“…Structural health monitoring (SHM) relies on the repeated observation of features that are each sensitive to a certain type of structural damage, such as quasistatic strains, 1 auto-regressive model parameters, 2 local flexibilities, 3 electromechanical impedances, 4 or electrical resistance changes. 5 Among the many possible features, modal characteristics, in particular natural frequencies, are often selected as they depend on the global and the local stiffness of the structure of interest as well as its boundary conditions. [6][7][8][9] Monitoring the evolution of the features over time allows, in principle, to detect structural damage.…”

Machine learning-based damage sensing and self-healing of carbon fiber/nylon composites via addressable conducting networks

“…Therefore, in previous works, electrical resistance change method (ERCM) was utilized to detect matrix damage of carbon fiber/nylon composite. [9][10][11] ERCM uses the carbon fibers as conducting network. By measuring the electrical resistance change, several damages in the composite such as matrix delamination, crack, or fiber breakage, can be easily evaluated because the damages in the composite materials interrupt the electric current flow, thus changing the electrical resistance.…”

Capacitance measurements on integrated conductors for detection of matrix cracks in GFRP

“…To increase reliability and cost-efficiency and to exploit higher potentials of lightweight design, various structural health monitoring (SHM) techniques have been developed to monitor the material integrity during service. Especially in carbon fibre reinforced polymers, electrical resistance measurements for strain and damage detection are an established SHM technique which enables monitoring of the whole structure [1][2][3][4][5]. However, resistive monitoring is not possible in unmodified GFRP parts like wind turbine rotor blades due to the lack of material conductivity.…”