Status in the development of self-powered wireless sensor node for structural health monitoring and prognosis

Abstract

This paper discusses the development status of a self-powered wireless sensor node for steel and concrete bridges monitoring and prognosis. By the end of the third year in this four-year cross-disciplinary project, the 4-channel acoustic emission wireless node, developed by Mistras Group Inc, has already been deployed in concrete structures by the University of Miami. Also, extensive testing is underway with the node powered by structural vibration and wind energy harvesting modules developed by Virginia Tech. The development of diagnosis tools and models for bridge prognosis, which will be discussed in the paper, continues and the diagnosis tools are expected to be programmed in the node's AVR during the 4th year of the project. The impact of this development extends beyond the area of bridge health monitoring into several fields, such as offshore oil platforms, composite components on military ships and race boats, combat deployable bridges and wind turbine blades. Some of these applications will also be discussed. This project was awarded to a joint venture formed by Mistras Group Inc, Virginia Tech, University of South Carolina and University of Miami by the National Institute of Standards and Technology through its Technology Innovation Program Grant #70NANB9H007

Recent Advances in Energy Harvesting Technologies for Structural Health Monitoring Applications

“…For this reason, researchers have completed or are completing projects where the combination of multiple methods of energy harvesting is explored. A four-year cross-disciplinary project supported by Mistras Group Inc., Virginia Tech, the University of South Carolina, and the University of Miami to develop a self-powered wireless sensor node for steel and concrete bridges has been reviewed by Godínez-Azcuaga et al [51]. For the energy harvesting component of the project the research team is considering the integration of miniature wind turbines and nonlinear vertical piezoelectric windmills.…”

A Bayesian Approach to Modal Acoustic Emission Source Location

“…An amplitude threshold is used to trigger the processing of an individual AE waveform known as hit and determine the TOA. AE has become popular within the NDT community because (Shigeishi, Colombo et al 2001) it allows: i) in-service structural health monitoring that can be adopted in an online monitoring fashion; ii) adaptability to any geometry or structural element; iii) simple and economic installations; and iv) wireless communication for collection and processing of data remotely (Godinez-Azcuaga, Inman et al 2011).…”