Carbon/Epoxy Laminate Compression After Impact Load Carbon/Epoxy Laminate Compression After Impact Load Prediction from Ultrasonic C-Scan DataPrediction from Ultrasonic C-Scan Data
Eric v. K. Hill, Christopher D. Hess and Yi ZhaoEric v. K. Hill, Christopher D. Hess and Yi Zhao
OBJECTIVES
•Three sets of 3.5 x 6 inch 16-ply AS4/3501-5A carbon/epoxy coupons impacted from 0-20 ft-lbf with 5/8 inch diameter hemispherical tup to create barely visible impact damage (BVID)
•Back-propagation neural network (BPNN) prediction of compression after impact (CAI) load from transformed ultrasonic (UT) C-scan image
•Goal:Goal: Worst case prediction error within ±15%±15%
APPROACH/TECHNICAL CHALLENGES
• AE data too noisy: Train BPNN using 50 data points representing column summation data from UT C-scan image and known CAI loads as input
• Test BPNN using column summation UT C-scan image to predict CAI loads on remaining coupons
ACCOMPLISHMENTS/RESULTS• UT image data alone used to predict ultimate
compressive strengths with worst case errors worst case errors of -12.12%, 16.62%, and -11.83% for the three sets-12.12%, 16.62%, and -11.83% for the three sets• BPNN able to predict accurately without known predict accurately without known
impact energyimpact energy – valid for real world applications such as impact damaged aircraft wings
C/Ep Coupon C/Ep Coupon in Boeing in Boeing BS-7260 BS-7260
Compression Compression After Impact After Impact Test Fixture Test Fixture with Three with Three Acoustic Acoustic Emission Emission
Transducers Transducers AttachedAttached
Instron Dynatup Instron Dynatup 9250 Calibrated 9250 Calibrated
ImpactorImpactor
Delaminations in Delaminations in Coupon Due to Coupon Due to Impact DamageImpact Damage
MATLAB Data TransformationMATLAB Data Transformation
• Pixel color and location is represented by a matrix array of numbers (0-16)
• Numerical values represent hue color• Image data summed and normalized in the
column direction • 50-100 data points surrounding the
maximum used as inputs to BPNNUltraPAC II C-Scan Imaging System:• Water Couplant Immersion• 5 MHz Unfocused Transducer
16 Color Format0-15 Color Format0-15 Color Format Digital Representation of 0-15 Color FormatDigital Representation of 0-15 Color Format
Data Set Specimen Impact Energy (ft-lbf)Compressive
Load (lbf)Predicted Compressive
Load (lbf)% Error
Training
A2 0 2865.6 2865.60 0.00
A3 2.23 6531.9 6531.90 0.00
A5 21.43 3910.1 3910.10 0.00
A4 20.2 3042.4 3042.40 0.00
TestingA6 20.75 4174.8 4492.73 7.62
A1 0 4936.5 4338.07 -12.12-12.12
BPNN Predictions for “Batch A” CouponsBPNN Predictions for “Batch A” Coupons
Optimized BPNN SettingsOptimized BPNN Settings
Digital Ultrasonic Digital Ultrasonic C-ScanC-Scan
Image DataImage Data
PredictedPredictedCAI LoadCAI Load
NeuralWorksNeuralWorksProfessional II/PLUSProfessional II/PLUS® ®
SoftwareSoftware
Summary of BPNN Training and Test Summary of BPNN Training and Test ResultsResults
Worst Case ErrorWorst Case Error