Integrated Fatigue Damage Diagnosis and Prognosis Under Uncertainties

Tishun Peng, Jingjing He, Yongming Liu, Abhinav Saxena, Jose R. Celaya, and Kai Goebel
Submission Type: 
Full Paper
AttachmentSizeTimestamp
phmc_12_135.pdf678.92 KBSeptember 18, 2012 - 4:12pm

An integrated fatigue damage diagnosis and prognosis framework is proposed in this paper. The proposed methodology integrates a Lamb wave-based damage detection technique and a Bayesian updating method for remaining useful life (RUL) prediction. First, a piezoelectric sensor network is used to detect the fatigue crack size near the rivet holes in fuselage lap joints. Advanced signal processing and feature fusion is then used to quantitatively estimate the crack size. Following this, a small time scale model is introduced and used as the mechanism model to predict the crack propagation for a given future loading and an estimate of initial crack length. Next, a Bayesian updating algorithm is implemented incorporating the damage diagnostic result for the fatigue crack growth prediction. Probability distributions of model parameters and final RUL are updated considering various uncertainties in the damage prognosis process. Finally, the proposed methodology is demonstrated using data from fatigue testing of realistic fuselage lap joints and the model predictions are validated using prognostics metrics.

Publication Year: 
2012
Publication Volume: 
3
Publication Control Number: 
135
Page Count: 
11
Submission Keywords: 
Diagnosis; prognosis; Lamb wave; lap joints; fatigue
Submission Topic Areas: 
Structural health monitoring
Submitted by: 
  
 
 
 

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