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Journal of Sensors
Volume 2018 (2018), Article ID 4125752, 10 pages
https://doi.org/10.1155/2018/4125752
Research Article

Self-Powered Wireless Sensor Network for Automated Corrosion Prediction of Steel Reinforcement

1Tongji University, Shanghai, China
2Embry Riddle Aeronautical University, Daytona Beach, FL, USA
3Lamar University, Beaumont, TX, USA

Correspondence should be addressed to Ye Xia; nc.ude.ijgnot@aixy

Received 25 July 2017; Revised 31 October 2017; Accepted 16 November 2017; Published 8 January 2018

Academic Editor: Young-Jin Cha

Copyright © 2018 Dan Su et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Corrosion is one of the key issues that affect the service life and hinders wide application of steel reinforcement. Moreover, corrosion is a long-term process and not visible for embedded reinforcement. Thus, this research aims at developing a self-powered smart sensor system with integrated innovative prediction module for forecasting corrosion process of embedded steel reinforcement. Vibration-based energy harvester is used to harvest energy for continuous corrosion data collection. Spatial interpolation module was developed to interpolate corrosion data at unmonitored locations. Dynamic prediction module is used to predict the long-term corrosion based on collected data. Utilizing this new sensor network, the corrosion process can be automated predicted and appropriate mitigation actions will be recommended accordingly.