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This presentation discusses the rational behind using wavelets for damage detection in bridges. It covers the technique of wavelet transform and its performance with different wavelets.
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USING WAVELETS ON THE RESPONSE OF A BEAM TO A CALIBRATED VEHICLE FOR DAMAGE DETECTION David Hester Arturo Gonzalez Nantes, 2nd July 2009
Overview of presentation • Rational behind research / Introduction to technique • Computer models used • Description of Continuous Wavelet Transform (CWT) • Performance of different wavelets • Approach for detecting small damage 01
Rational behind study • Research in Structural Health Monitoring (SHM) increasing, typically requires Non Destructive Testing • Bridges are a particularly interesting set of structures, in service for long period, traffic loads are steadily increasing • Financially beneficial if service life of existing bridges can be maximised • Reliable early damage detection technique significant step toward achieving this 02
Introduction to technique • Ultimately would like to be able to detect damage in a bridge by monitoring it’s dynamic response • Fundamental principal: Damage causes change in mechanical properties of structure • Potential to use Wavelets to detect damage in a beam by performing a wavelet transform on the deflection signal of the beam Wavelet Coefficient Wavelet Transform Deflection 03 Time Damage Deflection gauge Normalised Position of Load
2 3 1 4 Modelling of the Structural Response to a Moving Load • Discretized model of a simply supported beam L [Kg], [Mg] 04
Crack Modelling • Crack = Loss of Stiffness 05
Sinha’s method • Sinha approximates the exponential curve of Christides and Barr with a straight line. • lc= 1.5d Load Modelling Vehicle modelled as a constant moving Load [Mg]{d2y/dt2}+[Kg]{y}={F} 06
Introduction to wavelets • Wavelet transform was developed to extract Time-Frequency information from a signal • A wavelet is a waveform of limited duration Mexican hat Db 5 Gauss 2 Morlet 07 Figures taken from MATLAB
Outline of Wavelet Transform • Wavelet compared to a section at start of the original signal • Calculate wavelet coefficient ‘C’, which represents how closely correlated the wavelet is with this section of the signal. • Shift the wavelet to the right and repeat steps 1 & 2 • Scale (stretch) the wavelet and repeat steps 1 through 3 • Repeat steps 1-4 for all scales. Result of the WT are many wavelet coefficients ‘C’ 08 Figures taken from MATLAB
Using wavelets to detect damage • Wavelets can detect local discontinuities in a signal • Discontinuity in deflection-time response of a bridge as load passes over cracked section • Basic principal is to use wavelet to detect the discontinuity in the signal and thereby locate damage 09
Mid-span deflection response of a beam cracked at the 1/3 point subject to moving P-Load (1st beam freq=0.9Hz) 10 Deflection sensor Crack
WT applied to the midspan deflection signal of a beam subject to P-Load. Beam has a crack at 1/3rd point, Wavelet Transform Deflection Signal Scale=27 ≈ 0.9Hz Increase in wavelet coefficients at 0.33L →There is a localised discontinuity in deflection signal at 0.33L →There is damage at 0.33L 11
Performance of different wavelets in detecting damage 12 Gauss 2 Mex hat
Coefficient line plot Delta= Crack height / Beam depth Delta=0.2 Delta=0.4 Delta=0.6 Damage at 1/3 point 13
Improvement by using multiple measurements • Use of one single measurement, delta=0.2 • Use of multiple measurements Min not at damage location Deflection Sensors Average Crack Min at damage location 14
Conclusions • Possible to use a moving load as a form of non destructive testing to detect damage • Wavelet transform applied to Deflection-Time response can identify and locate damage • In presence of noise detects large cracks relatively easily • Multiple measuring locations give better results when detecting small cracks Locate Damage Wavelet Transform 15 Deflection Signal Deflection Gauge Crack
Acknowledgements • This investigation has been carried out as part of work program 7 of the ASSET project, Sustainable Surface Transport ASSET(Advanced Safety and Driver Support in Efficient Road Transport), 16