Advanced Sensor Dynamic Measurement and Heuristic Data Analysis Model for Bridge Health Monitoring System
G. R. Vijay Shankar1, S. Deepa2, M. Arun3, G.Vignesh4
1Dr. G. R. Vijay Shankar *, Associate Professor, Department of Civil Engineering, Karpagam Academy of Higher Education, Coimbatore, India.
2Dr. S. Deepa, Associate Professor, Department of ECE, Karpagam college of Engineering, Coimbatore, India.
3M. Arun, Junior Research Fellow, Department of Mechanical Engineering, Karpagam Academy of Higher Education, Coimbatore, India.
4G. Vignesh, Assistant Professor, Department of Mechanical Engineering, Karpagam Academy of Higher Education, Coimbatore, India.
Manuscript received on 5 August 2019. | Revised Manuscript received on 11 August 2019. | Manuscript published on 30 September 2019. | PP: 1907-1912 | Volume-8 Issue-3 September 2019 | Retrieval Number: C4467098319/19©BEIESP | DOI: 10.35940/ijrte.C4467.098319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Presently the health and safety monitoring of a bridge is considered as a significant area of research where the attention has been paid by many researchers. In this article the bridge structural damages due to environmental fluctuations and other parameters has been analyzed using cutting-edge technologies. In this research the technology of advanced Intelligent Internet of Things (IIoT) sensors with signal processing systems is designed and developed to monitor the health condition of the bridge using data analytic techniques. In the recent past these sensor systems has been used collect the vibration signal sets caused by the vehicles movement on the bridge. Further, these collected data sets are analyzed with the help data analytic approach using traditional independent analysis models which fails to produce optimum results in terms of reliability, efficiency, stability, corrosion and crack of the bridge. In this article to overcome this issue an improved heuristic nonlinear model has been developed to analyze the data sets using non-linear and linear separation analogy. This optimized data analytics technique with advanced sensing mechanisms is validated experimentally and the outcomes shows promising solutions to monitor bridge health in effective manner than traditional strategies.
Keywords: Intelligent Internet of Things Sensors, Data Analytic Techniques, Corrosion and Crack, Bridge Health, non-linear and linear separation
Scope of the Article: Measurement & Performance Analysis