Engineering Science and Technology, an International Journal (May 2023)

Distributed fibre optic inclinometer with cloud-based monitoring system

  • Hisham Mohamad,
  • Aizat Akmal A.M. Beddelee,
  • Muhammad Farid Ghazali,
  • Hsiu Eik Lee,
  • Krisada Chaiyasarn,
  • Muhammad Yusoff M. Nasir

Journal volume & issue
Vol. 41
p. 101406

Abstract

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Geotechnical instrumentation and monitoring are important aspect of controlling subsurface ground movement, particularly in deep excavations and forewarning of geological disasters such as landslides, land subsidence, ground fissure, and surface collapse. A borehole inclinometer is an example of the established method to monitor such ground movements. For real-time data, a series of in-placed inclinometer probes are installed inside the borehole casing to provide the lateral displacement response over time. The limitation of the conventional system is the high cost and the practicality of inserting a high number of sensing probes into the casing for better measurement accuracy. Recent advancement in Distributed Optical Fibre Strain Sensing (DOFS) enables the incorporation of DOFS as a fibre optic (FO) inclinometer with lateral displacements to be plotted at centimetres spacing and is unaffected by the gauge lengths between the probes. This study enhances the FO inclinometer by developing a web-based application (SmartGeopipe©) to automate data acquisition which also includes complex data processing for the final pipe deflection profile visualisation. The FO inclinometer comprised of optical cables attached externally onto a remodified inclinometer casing and connected to a Brillouin Optical Time Domain Analysis (BOTDA) strain analyser. A standard installation procedure was established to safely secure the sensors during the casing installation process inside the borehole. SmartGeopipe© software is written using a predominantly monolithic Python / Cython backend and a multi-page frontend built with HTML, CSS, and JavaScript ES5 languages. All the computation work and data storing are done in a cloud server and SQL database, respectively. A case study of a station box excavation as part of the Mass Rapid Transit (MRT) tunnelling project was chosen to validate the performance of the FO inclinometer and the web application. Data from the FO inclinometer corroborated well with the manual measurements of the inclinometer probe. This ability supports the realization of an early warning system as an engineering control for hazard management in civil engineering infrastructure projects.

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