Developing TRACKER - Portable Monitoring System using Kalman Filtering to Track Rotational Movement of Bridges
Faulkner, K
Date: 7 February 2022
Thesis or dissertation
Publisher
University of Exeter
Degree Title
PhD in Engineering
Abstract
The combined effects of flooding and scour are the primary causes of bridge failure over flowing water. Improvements in structural health monitoring and inertial sensors have led to the development of advanced monitoring systems that can provide bridge owners with detailed information on the performance of the structure and allow ...
The combined effects of flooding and scour are the primary causes of bridge failure over flowing water. Improvements in structural health monitoring and inertial sensors have led to the development of advanced monitoring systems that can provide bridge owners with detailed information on the performance of the structure and allow informed decisions to be made about time-critical safety issues following a storm event. However, such systems remain prohibitively expensive for the majority of smaller structures which make up the wider transport network. This thesis details the development of a robust, portable data acquisition logger (TRACK ER), which can be used to target vulnerable infrastructure during a storm event to increase the resilience of the wider transport network.
TRACKER uses condition monitoring, recording quasi-static and dynamic deformations, to track the performance of a bridge under the combined effects of storm loading. A benefit of this method is that it requires no direct input force or prior knowledge of the bridge model. Traditionally, tiltmeters or accelerometers are used to measure rotation for structural health monitoring purposes but such sensors can struggle to isolate rotation from translational acceleration if the structure is linearly accelerating. Gyroscopes offer improved rotational measurement capabilities but gyroscope measurements are known to drift over time as a result of the iterative process of converting rate gyroscope data. This thesis will explore gyroscopes as a complementary sensor to accelerometers and introduce a Kalman filter that combines both inertial sensors measurement data to obtain optimised rotation data. To improve the performance of the Kalman filter, the filter is adapted to automatically update the process and noise measurement values.
TRACKER, a robust, portable data acquisition logger, was developed and equipped with inertial sensors to provide a stand-alone system that can be rapidly deployed to target vulnerable infrastructure. Verification of the new logger was performed under controlled laboratory conditions to prove the validity of the new logger. The rotational data showed good agreement with rotational measurements obtained from an industry gold-standard vision-based measurement system. TRACKER was deployed on a variety of in-service bridges using different loading scenarios to demonstrate the ability of the new logging system, including loading from ambient weather conditions. TRACKER successfully tracked the performance of the structures, proving the ability of the logger to track the quasi-static and dynamic deformations of a structure during loading from traffic and environmental conditions.
Doctoral Theses
Doctoral College
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