Signal processing for guided wave structural health monitoring
The importance of Structural Health Monitoring (SHM) in several industrial fields has been continuously growing in the last few years with the increasing need for the development of systems able to monitor continuously the integrity of complex structures. In order to be competitive with conventional...
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ndltd-bl.uk-oai-ethos.bl.uk-5098062017-08-30T03:16:38ZSignal processing for guided wave structural health monitoringCicero, TindaroCawley, Peter ; Simonetti, Francesco ; Lowe, Mike2009The importance of Structural Health Monitoring (SHM) in several industrial fields has been continuously growing in the last few years with the increasing need for the development of systems able to monitor continuously the integrity of complex structures. In order to be competitive with conventional non destructive evaluation techniques, SHM must be able to effectively detect the occurrence of damage in the structure, giving information regarding the damage location. Ultrasonic guided waves offer the possibility of inspecting large areas of structures from a small number of sensor positions. However, inspection of complex structures is difficult as the reflections from different features overlap. Therefore damage detection becomes an extremely challenging problem and robust signal processing is required in order to resolve strongly overlapping echoes. In our work we have considered at first the possibility of employing a deconvolution approach for enhancing the resolution of ultrasonic time traces and the potential and the limitations of this approach for reliable SHM applications have been shown. The effects of noise on the bandwidth of the typical signals in SHM and the effects of frequency dependent phase shifts are the main detrimental issues that strongly reduce the performance of deconvolution in SHM applications. The second part of this thesis is concerned with the evaluation of a subtraction approach for SHM when changes of environmental conditions are taken into account. Temperature changes result in imperfect subtraction even for an undamaged structure, since temperature changes modify the mechanical properties of the material and therefore the velocity of propagation of ultrasonic guided waves. Compensation techniques have previously been used effectively to overcome temperature effects, in order to reduce the residual in the subtraction. In this work the performance of temperature compensation techniques has been evaluated also in the presence of other detrimental effects, such as liquid loading and different temperature responses of materials in adhesive joints. Numerical simulations and experiments have been conducted and it has been shown that temperature compensation techniques can cope in principle with non temperature effects. It is concluded that subtraction approach represents a promising method for reliable Structural Health Monitoring. Nonetheless the feasibility of a subtraction approach for SHM depends on environmental conditions.624.17Imperial College Londonhttp://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.509806http://hdl.handle.net/10044/1/5302Electronic Thesis or Dissertation |
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624.17 Cicero, Tindaro Signal processing for guided wave structural health monitoring |
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The importance of Structural Health Monitoring (SHM) in several industrial fields has been continuously growing in the last few years with the increasing need for the development of systems able to monitor continuously the integrity of complex structures. In order to be competitive with conventional non destructive evaluation techniques, SHM must be able to effectively detect the occurrence of damage in the structure, giving information regarding the damage location. Ultrasonic guided waves offer the possibility of inspecting large areas of structures from a small number of sensor positions. However, inspection of complex structures is difficult as the reflections from different features overlap. Therefore damage detection becomes an extremely challenging problem and robust signal processing is required in order to resolve strongly overlapping echoes. In our work we have considered at first the possibility of employing a deconvolution approach for enhancing the resolution of ultrasonic time traces and the potential and the limitations of this approach for reliable SHM applications have been shown. The effects of noise on the bandwidth of the typical signals in SHM and the effects of frequency dependent phase shifts are the main detrimental issues that strongly reduce the performance of deconvolution in SHM applications. The second part of this thesis is concerned with the evaluation of a subtraction approach for SHM when changes of environmental conditions are taken into account. Temperature changes result in imperfect subtraction even for an undamaged structure, since temperature changes modify the mechanical properties of the material and therefore the velocity of propagation of ultrasonic guided waves. Compensation techniques have previously been used effectively to overcome temperature effects, in order to reduce the residual in the subtraction. In this work the performance of temperature compensation techniques has been evaluated also in the presence of other detrimental effects, such as liquid loading and different temperature responses of materials in adhesive joints. Numerical simulations and experiments have been conducted and it has been shown that temperature compensation techniques can cope in principle with non temperature effects. It is concluded that subtraction approach represents a promising method for reliable Structural Health Monitoring. Nonetheless the feasibility of a subtraction approach for SHM depends on environmental conditions. |
author2 |
Cawley, Peter ; Simonetti, Francesco ; Lowe, Mike |
author_facet |
Cawley, Peter ; Simonetti, Francesco ; Lowe, Mike Cicero, Tindaro |
author |
Cicero, Tindaro |
author_sort |
Cicero, Tindaro |
title |
Signal processing for guided wave structural health monitoring |
title_short |
Signal processing for guided wave structural health monitoring |
title_full |
Signal processing for guided wave structural health monitoring |
title_fullStr |
Signal processing for guided wave structural health monitoring |
title_full_unstemmed |
Signal processing for guided wave structural health monitoring |
title_sort |
signal processing for guided wave structural health monitoring |
publisher |
Imperial College London |
publishDate |
2009 |
url |
http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.509806 |
work_keys_str_mv |
AT cicerotindaro signalprocessingforguidedwavestructuralhealthmonitoring |
_version_ |
1718521349448663040 |