A simplified framework for prediction of sensor network coverage in real-time structural health monitoring of plate-like structures

Ghyabi, Mehrdad; Nemati, Hamidreza; Dehghan-Niri, Ehsan

doi:10.1177/14759217211033217

A simplified framework for prediction of sensor network coverage in real-time structural health monitoring of plate-like structures

Journal Article · 19 July 2021 · Structural Health Monitoring

DOI:https://doi.org/10.1177/14759217211033217· OSTI ID:1980952

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Intelligent Structures and Nondestructive Evaluation (ISNDE) Laboratory, New Mexico State University, Las Cruces, NM, USA

In this article, the coverage area prediction of piezoelectric sensor network for detecting a specific type of under-surface crack in plate-like structures is addressed. In particular, this article proposes a simplified framework to estimate the coverage of any given sensor network arrangement when a critical defect is known. Based on numerical results from finite element methods (FEM), a simplified framework to estimate coverage area of any given network arrangement is developed. Using such a simplified framework, one can avoid time-consuming procedure of evaluating numerous FEM models in estimating sensor network coverage. Back-scatter fields of partial cracks are estimated using a proposed function, whose parameters are estimated from the results of a limited number of FEM simulations. The proposed function efficiently predicts the back-scattered field of any combination of transmitters and receivers for a given crack geometry. Superposition is used to estimate the coverage area of an arbitrary piezoelectric (e.g., PZT) sensor network. It is shown that the coverage area of a sensor network depends on both sensor network geometry and defect properties (e.g., crack inclination) and it is not necessarily a linear function of the number of sensors. Furthermore, it is shown that the network arrangement has an important effect on the geometry of the coverage area. Experimental results of a network of 14 PZTs in two clusters confirm the accuracy of the method.

Research Organization:: New Mexico State Univ., Las Cruces, NM (United States)

Sponsoring Organization:: USDOE Office of Fossil Energy (FE)

DOE Contract Number:: FE0031649

OSTI ID:: 1980952

Journal Information:: Structural Health Monitoring, Vol. 21, Issue 4; ISSN 1475-9217

Publisher:: SAGE

Country of Publication:: United States

Language:: English

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