JOURNAL PAPERS

Damage Classification Structural Health Monitoring in Bolted Structures Using Time-frequency Techniques

Authors: Debejyo Chakraborty, Narayan Kovvali, Jun Wei, Antonia Papandreou-Suppappola, Douglas Cochran, Aditi Chattopadhyay

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Cite: Journal of Intelligent Material Systems and Structures, special issue on Structural Health Monitoring,  March, 23, 2009, doi:10.1177/1045389X08100044.

Off-Line and On-Line Fatigue Crack Growth Prediction Using Multivariate Gaussian Process

Authors: Subhasish Mohanty, Aditi Chattopadhyay, Pedro Peralta and Santanu Das

About: Bayesian approach based Gaussian process probabilistic Off-line and On-line models are proposed to either predict/estimate the future/current damage states (crack growth or its rate). The off-line model uses the fatigue affecting physical parameters such as loading information, number of cycles, etc. to predict the crack growth or its rate, where as the on-line model uses the piezoelectric sensor signal based features to estimate the crack growth or its rate. Both the algorithm is tested for Aluminum 2024 compact-tension (CT) specimens under variable loading.

Cite: AIAA Journal, 2008, submitted

Gaussian Process Time Series Model for Life Prognosis of Metallic Structure

Authors: Subhasish Mohanty, Santanu Das, Aditi Chattopadhyay, and Pedro Peralta

About: Bayesian approach based Gaussian process probabilistic model proposed for predicting crack growth prediction under variable loading. The probabilistic predictive model is an off-line data driven model, which can be used in an integrated SHM and Prognosis approach to forecast the future crack growth.

Cite: Journal of Intelligent Material Systems and Structures, DOI: 10.1177/1045389X08099602., 2008, accepted

Adaptive Residual Useful Life Estimation of a Structural Hotspot

Authors: Subhasish Mohanty, Aditi Chattopadhyay, and Pedro Peralta

About: Bayesian approach based Gaussian process probabilistic model used to adaptively estimate the fatigue life of a structural hot-spot (AL-2024 Lug Joint). In this paper both on-line state estimation (SHM) model is combined with a state predictive (prognosis) model to adaptively estimate the residual useful life. The current state (crack length) estimates from on-line model are regularly fed to off-line model as changing initial conditions.

Cite: Journal of Intelligent Material Systems and Structures, special issue on Structural Health Monitoring, 2009, submitted,

Experimental quantification of the plastic blunting process for stage II fatigue crack growth in one-phase metallic materials

Authors: P. Peralta, S.-H. Choi, J. Gee

About: experimental measurements of displacement fields ahead of stage II cracks in polycrystalline nickel were used to quantify length scales associated to mechanisms of fatigue crack advance via plastic blunting

Cite: Int. J. Plasticity (2007), doi:10.1016/j.ijplas.2007.03.009.

Classification of Damage in Composite Structures using Hidden Markov Models for Integrated Vehicle Health Management

Authors: Wenfan Zhou, Narayan Kovvali, Antonia Papandreou-Suppappola, Douglas Cochran, Aditi Chattopadhyay, and Whitney Reynolds

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Cite: Journal of Intelligent Material Systems and Structures, special issue on Structural Health Monitoring, 2007. submitted

Monte Carlo Simulation Matching Pursuit Decomposition Method for Damage Quantification in Composite Structures

Authors: S. Das, I. Kyriakides, A. Chattopadhyay, and A. Papandreou-Suppappola

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Cite: Journal of Intelligent Material Systems and Structures, 2007. submitted

Nonlinear Effects on Impurity Segregation in Edge Dislocation Strain Fields

Authors: J.B. Spicer

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Cite: Scripta Materialia (2007). accepted for publication

Dynamic Effects in Nonlinearly Coupled Elastic Deformation and Diffusion Fields in Solids

Authors: J.B. Spicer,  Y. Dikmelik

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Cite: Journal of Applied Physics (2007). submitted for publication

High Spatial Resolution, Acoustic Microscopy in Mesoscale Structures Using a Laser Based Ultrasonic Technique

Authors: O. Balogun, G.D. Cole, R. Huber, D. Chinn, T.W. Murray, and J.B. Spicer

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Cite: IEEE Ultrasonics Ferroelectrics and Frequency Control (2007). submitted for publication

Damage diagnosis using a kernel-based method

Authors: A. Chattopadhyay, S. Das, and C.K. Coelho

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Cite: Insight - Non-Destructive Testing and Condition Monitoring, Vol. 49, 451-458, 2007

Laser Ultrasonic Inspection of the Microstructural State of Thin Metal Foils

Authors: O. Balogun, R. Huber, D. Chinn, and J.B. Spicer

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Cite: Journal of Applied Physics (2008). to be submitted

Real time Damage State Estimation and Condition Based Residual Useful Life Estimation of a Metallic Specimen under Biaxial Loading

Authors: S.Mohanty, A. Chattopadhyay, J.Wei and P. Peralta

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Cite: SDHM: Structural Durability & Health Monitoring, vol.5, no.1, pp.33-55, 2009.

CONFERENCE PAPERS

Particle Filter Based Matching Pursuit Decomposition for Damage Quantification in Composite Structures

Authors: S. Das, I. Kyriakides, A. Chattopadhyay, and A. Papandreou-Suppappola
 
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Cite: 47th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, pp. 1-12, Newport, RI, May 2006.

A Multidisciplinary Approach to Structural Health Monitoring and Prognosis of Metallic Aerospace Systems

Authors: Aditi Chattopadhyay and Antonia Papandreou-Suppappola
 
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Cite: Integrated Systems Health Management Conference, Cincinnati, Ohio, August 2006.

Hidden Markov Model based Classification of
Structural Damage

Authors: Wenfan Zhou, Narayan Kovvali, Antonia Papandreou-Suppappola, Douglas Cochran, and Aditi Chattopadhyay
 
About: A novel approach based on Hidden Markov Models (HMMs) for the classification of structural damage. Our approach here is based on using HMMs for modeling the time-frequency features extracted from time-varying structural data.
 
Cite: 14th International Symposium on Smart structures and Materials & Nondestructive Evaluation and Health Monitoring (SPIE/NDE), San Diego, California, March 2007. Vol. 6523, 652311

Detection of Fatigue Cracks and Torque Loss in Bolted Joints

Authors: Clyde K. Coelho, Santanu Das, Aditi Chattopadhyay, Antonia Papandreou-Suppappola, Pedro Peralta
 
About: This paper presents a procedure for classification and detection of cracks generated in bolted joints which are used at numerous locations in aircraft structures. Single lap bolted joints were equipped with surface mounted piezoelectric (pzt) sensors and actuators and were subjected to cyclic loading. Crack length measurements and sensor data were collected at different number of cycles and with different torque levels. A classification algorithm based on Support Vector Machines (SVMs) was used to compare signals from a healthy and damaged joint to classify fatigue damage at the bolts. The algorithm was also used to classify the amount of torque in the bolt of interest and determine if the level of torque affected the quantification and localization of the crack emanating from the bolt hole.
 
Cite: Proc. SPIE Int. Soc. Opt. Eng. 6532, 653204 (2007)

Time-Frequency based Classification of Structural Damage

Authors: Narayan Kovvali, Santanu Das, Debejyo Chakraborty, Douglas Cochran,
Antonia Papandreou-Suppapola, Aditi Chattopadhyay

About: This paper deals with detection and localization of structural (loose bolt) damage using Time-frequency Classifier and Modified Matching Pursuit Classifier. Our approach is based on matching damage features in the time-frequency plane using highly localized Gabor functions and time-varying received signals from real experimental measurements.

Cite: 48th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference 23 - 26 April 2007, Honolulu, Hawaii, AIAA 2007-2055

Matching Pursuit Decomposition for Damage Quantification in Composite Structures

Authors: S. Das, A. Papandreou-Suppappola, and A. Chattopadhyay
 
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Cite: Data Mining in Aeronaunics, Science and Exploration Systems, Mountain View, California, June, 2007.

Materials Defect Chracterization Using Mesoscopic Laser Ultrasonic Methods

Authors: O. Balogun, R. Huber, D. Chinn, and J.B. Spicer
 
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Cite: 18th AeroMat Conference and Exposition. Baltimore, Maryland. June 27, 2007.

Damage Diagnosis of Complex Structures Using One-Class Support Vector Machines and Hidden Markov Models

Authors: Aditi Chattopadhyay, Antonia Papandreou-Suppappola,Clyde Coelho, Sunilkumar Soni, Debejyo Chakraborty, Wenfan Zhou, Narayan Kovvali, Santanu Das, Pedro Peralta
 
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Cite: Integrated Systems Health Management Conference, Cincinnati, Ohio, August 2007.

Damage Classification for Structural Health Monitoring Using Time-Frequency Feature Extraction and Continuous Hidden Markov Models

Authors: W. Zhou, D. Chakraborty, N. Kovvali, A. Papandreou-Suppappola, D. Cochran, and A. Chattopadhyay
 
About: Our approach employs hidden Markov models (HMMs) to model time-frequency damage features extracted from structural data using the matching pursuit decomposition algorithm. We investigate modeling with continuous observationdensity HMMs and discuss the trade-offs involved as compared to the discrete HMM case. A variational Bayesian method is employed to automatically estimate the HMM state number and adapt the classifier for real-time use.

Cite: Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, California, November, 848-852, 2007.

A Void Growth and a Cyclic Model in Ductile Material using Mechanism-Based Strain Gradient Crystal Plasticity Theory

Authors: Chuntao Luo, Jun Wei, Aditi Chattopadhyay, Hanqing Jiang
About: 

Cite: ASME International Mechanical Engineering COngress and Exposition, Seattle, Washington, November, 2007

Mixed Gaussian Process and State-Space Approach for Fatigue Crack Growth Prediction

Authors: Mohanty, S., Teale, R., Chattopadhyay, A., Peralta, P., and Willhauck, C.,

About: An hyprid physics and stochastic approach for crack growth prediction in metalic structure

Cite: Page 1108-1115, Vol-2, Structural Health Monitoring 2007, Edited by Prof. Fu-Kuo Chang, DEStech Publications, Inc., PA, USA 2007.

Ultrasonic Sensing and Time-Frequency Analysis for Detecting Plastic Deformation in an Aluminum Plate

Authors: Lindsey Channels, Debejyo Chakraborty, Donna Simon, Narayan Kovvali, James Spicer, Antonia Papandreou-Suppappola, Douglas Cochran, Pedro Peralta, and Aditi Chattopadhyay
 
About: In this paper, we describe a structural damage identification approach based on ultrasonic sensing and time-frequency techniques. A parsimonious representation is first constructed for the ultrasonic signals using the modified matching pursuit decomposition (MMPD) method. This decomposition is then employed to compute projections onto the various damage classes, and classification is performed based on the magnitude of these projections. Results are presented for the detection of fatigue damage in Al-6061 and Al-2024 plates tested under 3-point bending.

Cite: Modeling, Signal Processing, and Control for Smart Structures 2008, edited by Douglas K. Lindner Proc. of SPIE Vol. 6926, 69260P, (2008) 0277-786X/08/$18 doi: 10.1117/12.776625

Physics based Modeling for Time-Frequency Damage Classification

Authors: D. Chakraborty, S. Soni, J. Wei, N. Kovvali, A. Papandreou-Suppappola, D. Cochran, and A. Chattopadhyay
 
About: This method is based on the use of hidden Markov models with preselected feature vectors obtained from the time-frequency based matching pursuit decomposition. In order to investigate the performance of the classifier for different signal-to-noise ratios (SNR), we simulate the response of a lug joint sample with different crack lengths using finite element modeling (FEM).

Cite: Modeling, Signal Processing, and Control for Smart Structures 2008, edited by Douglas K. Lindner Proc. of SPIE Vol. 6926, 69260M, (2008) 0277-786X/08/$18 doi: 10.1117/12.776628

Binary Tree SVM Based Framework for Mining Fatigue Induced Damage Attributes in Complex Lug Joints

Authors: Clyde K. Coelho, Santanu Das, Aditi Chattopadhyay,
 
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Cite: International Symposium on Smart structures and Materials & Nondestructive Evaluation and Health Monitoring (SPIE/NDE), San Diego, California, March 2008.

Simulation of Damage-Features in Complex Joint using Guided Waves

Authors: Sunilkumar Soni, Santanu Das, Sourav Banerjee, Aditi Chattopadhyay, Pedro Peralta
 
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Cite: International Symposium on Smart structures and Materials & Nondestructive Evaluation and Health Monitoring (SPIE/NDE), San Diego, California, March 2008.

Stochastic crack growth under variable loading for health monitoring and prognosis

Authors: Christina Willhauck, Subhasish Mohanty, Aditi Chattopadhyay, Pedro Peralta
 
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Cite: International Symposium on Smart structures and Materials & Nondestructive Evaluation and Health Monitoring (SPIE/NDE), San Diego, California, March  2008.

Fatigue Life Prediction Using Multivariate Gaussian Process

Authors: Subhasish Mohanty, Aditi Chattopadhyay, Pedro Peralta, Santanu Das, and Christina Willhauck

About: This paper presents Multivariate Gaussian process based model for off-line and on-line crack growth and its rate prediction/estimation. For the off-line prediction the input space of the model is trained with parameters that affect fatigue crack growth, such as number of fatigue cycles, minimum load, maximum load, and load ratio. For the case of online prediction, the model input space is trained using features found from piezoelectric sensor signals rather than training the input space with loading parameters, which are difficult to measure in a real flight-worthy structure. In both the off-line and on-line case the output space is trained with known associated crack lengths. Once the Gaussian process model is trained, a new output space for which the corresponding crack length or damage state is not known is predicted using the trained Gaussian process model.

Cite: 49th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, 7 - 10 April 2008, Schaumburg, IL,

Signal Processing Methods for Structural Health Monitoring

Authors: A. Papandreou-Suppappola, D. Cochran, N. Kovvali, D. Chakraborty, W. Zhou, and D. Simon
 
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Cite: Integrated Systems Health Management Conference, Cincinnati, Ohio, August 2008.

On-Line Life Prediction of a Structural HotSpot

Authors: Subhasish Mohanty, Aditi Chattopadhyay, and Pedro Peralta

About: The present paper discusses the use of an adaptive hybrid prognosis model, which estimates the residual useful life of a structural hotspot using information on the damage condition obtained in real time. The hybrid prognosis model has two modules: an off-line prognosis module that forecasts the future damage state, and an on-line state estimation module, which regularly predicts the current damage state and feeds into the off-line module in real time. Both the off-line and on-line modules are probabilistic models and use the concept of Bayesian inference based on input-output mapping through a Gaussian process.

Cite: ASME Conference on Smart Materials, Adaptive Structures and Intelligent Systems, paper no: SMASIS2008-646, October 28-30, 2008, Ellicot City, MD,

A Comparative Study of Fatigue Damage Sensing in Aluminum Alloys using Electrical Impedance and Laser Ultrasonic Methods

Authors: Lindsey Channels, Debejyo Chakraborty, Brad Butrym, Narayan Kovvali, James Spicer, Antonia Papandreou-Suppappola, Mana Afshari, Daniel Inman and Aditi Chattopadhyay

About: In this work, we present electrical impedance and ultrasonic measurements in aluminum alloy 2024 that has been fatigued under high cycle conditions. We have used laser ultrasonic methods to investigate changes in ultrasonic attenuation since simultaneous measurement of longitudinal and shear properties provides opportunities to develop classification algorithms that can estimate the degree of damage. Electrical impedance measurements are sensitive to changes in the conductivity and permittivity of materials - both are affected by the microstructural damage processes related to fatigue. By employing spectral analysis of impedance over a range of frequencies, resonance peaks can be identified that directly reflect the damage state in the material. We process the measurements to extract time-frequency features and estimate stochastic variation properties to be used in robust classification algorithms. Results are presented for fatigue damage identification in aluminum lug joint specimens.

Cite: Health Monitoring of Structural and Biological Systems 2009, edited by Tribikram Kundu, Proc. of SPIE Vol. 7295, 72950Q, doi: 10.1117/12.815980, San Diego, Calirfornia, March 2009