sensitivity evaluation of subspace-based damage detection technique saeid allahdadian dr. carlos...
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![Page 1: Sensitivity Evaluation of Subspace-based Damage Detection Technique Saeid Allahdadian Dr. Carlos Ventura PhD Student, The University of British Columbia,](https://reader036.vdocuments.mx/reader036/viewer/2022062518/56649ddc5503460f94ad42d0/html5/thumbnails/1.jpg)
Sensitivity Evaluation of Subspace-based Damage Detection Technique
Saeid AllahdadianDr. Carlos Ventura
PhD Student, The University of British Columbia, Vancouver, Canada
The 5th Tongji-UBC Symposium on Earthquake Engineering “Facing Earthquake Challenges Together” May 4-8 2015, Tongji University, Shanghai, China
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2
• Subspace based damage detection
• Damage detection approach
• Investigation of sensitivity
• Case study
• Damage and noise simulation
• Results
• Conclusion
Outline
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• Benefits:• Rapid assessment of whether or not a system has
changed its dynamic behavior.• Upload a new measurement file and get a Yes or
No whether a significant change has happened. Applicable for real time monitoring of structures.
• Limited user interaction once the system is set for testing.
Subspace based damage detection
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Yes
- 4
Structure healthy
Measurement in healthy state
Measurement in current state
Statistical comparison concerning
the vibration characteristics
Significant change?
No
Damage(or something else?)
Damage detection approach
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¿1 2
2 3 1
1 2
...
...
q
q
p p p q
RR R
R R R
R R R
H
vec( ),Tn nζ S H 12 ,T
n n ζ ζ Tn n E ζ ζ
Formulation
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Sensitivity analysis of the damage detection approach to:
◦Damage location◦Damage ratio◦Noise ratio
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S101 bridge structure
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Pier settlement as controlled damage
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• Natural frequencies of the bridge structure in undamaged condition obtained from the measured data and finite element model
Data analysis
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Damage ratio
Minor damage 20%
Intermediate damage 40%
Severe damage 80%
• The damage is simulated only in one finite element corresponding to the center of the main girder by reducing a ratio of its section dimension around the strong axis
• The imposed noise on the data is created using a random generation algorithm with evenly distributed probability distribution
Nr: noise ratiomi: maximum value measured for each channel
random( ,even)i r iN mR
Damage and noise simulation
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Noise superposition
i i i ND D R
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Noise characteristics• The effect of the noise in the data is more visible on low
amplitude parts of the signal
High effect
Low effect
zoom
Freq. domain
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• Measuring-points corresponding to sensor locations in ARTeMIS® software and spectral densities
Operational modal analysis
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Girder center Deck
Bearings Cap beams
Damage location and ratio effect
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Noise and damage ratio effect
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• The minimum of the value occurs when there is equivalent noise ratio in the measured and reference data
• To have a comparison regardless of this effect the results with equal noise ratio in the reference state and measured data are compared
• The optimum range of noise ratio in this set of data is from 2% to 30% equal in reference and measured data with a peak about 5%
Discussion on results
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• When there is noise in the reference data, there should be more samples and measurements performed in order to acquire a reliable safety threshold.
• Not only the higher noise in the measured data than the reference state can be interpreted as damage but also the lower noise in the measured data considering the reference state noise ratio can also affect the outcome of the damage detection technique
• Results are stable for the region between 2% and 30% noise on the outputs
• In most of the cases, even with very high noise ratios the damage can be identified using the SSDD technique. The reason: evaluation of the changes in the eigen-structure of the model.
Conclusion
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18
Certificate of Structural
Engineering Program
Thanks for your attention!