Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.646246
Title: Digital signal processing for structural health monitoring of buildings
Author: Pentaris, Fragkiskos
ISNI:       0000 0004 5361 5201
Awarding Body: Brunel University
Current Institution: Brunel University
Date of Award: 2014
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Abstract:
Structural health monitoring (SHM) systems is a relatively new discipline, studying the structural condition of buildings and other constructions. Current SHM systems are either wired or wireless, with a relatively high cost and low accuracy. This thesis exploits a blend of digital signal processing methodologies, for structural health monitoring (SHM) and develops a wireless SHM system in order to provide a low cost implementation yet reliable and robust. Existing technologies of wired and wireless sensor network platforms with high sensitivity accelerometers are combined, in order to create a system for monitoring the structural characteristics of buildings very economically and functionally, so that it can be easily implemented at low cost in buildings. Well-known and established statistical time series methods are applied to SHM data collected from real concrete structures subjected to earthquake excitation and their strong and weak points are investigated. The necessity to combine parametric and non-parametric approaches is justified and to this direction novel and improved digital signal processing techniques and indexes are applied to vibration data recordings, in order to eliminate noise and reveal structural properties and characteristics of the buildings under study, that deteriorate due to environmental, seismic or anthropogenic impact. A characteristic and potential harming specific case study is presented, where consequences to structures due to a strong earthquake of magnitude 6.4 M are investigated. Furthermore, is introduced a seismic influence profile of the buildings under study related to the seismic sources that exist in the broad region of study.
Supervisor: Stonham, J.; Vallianatos, F. Sponsor: National Foundation of Scholarships in Greece (IKY)
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.646246  DOI: Not available
Keywords: Non parametric analysis ; Parametric analysis ; Time series ; Earthquake data ; Wireless sensor networks
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