This paper presents a detailed methodology of deploying wireless sensor network in offshore structures for structural health monitoring (SHM). Traditional SHM is carried out by visual inspections and wired systems, which are complicated and requires larger installation space to deploy while decommissioning is a tedious process. Wireless sensor networks can enhance the art of health monitoring with deployment of scalable and dense sensor network, which consumes lesser space and lower power consumption. Proposed methodology is mainly focused to determine the status of serviceability of large floating platforms under environmental loads using wireless sensors. Data acquired by the servers will analyze the data for their exceedance with respect to the threshold values. On failure, SHM architecture will trigger an alarm or an early warning in the form of alert messages to alert the engineer-in-charge on board; emergency response plans can then be subsequently activated, which shall minimize the risk involved apart from mitigating economic losses occurring from the accidents. In the present study, wired and wireless sensors are installed in the experimental model and the structural response, acquired is compared. The wireless system comprises of Raspberry pi board, which is programmed to transmit the acquired data to the server using Wi-Fi adapter. Data is then hosted in the webpage for further post-processing, as desired.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.