Online fatigue damage monitoring by ultrasonic measurements : A symbolic dynamics approach

The paper presents an analytical tool for early detection and online monitoring of fatigue damage in polycrystalline alloys that are commonly used in mechanical structures of human-engineered complex systems. Real-time fatigue damage monitoring algorithms rely on time series analysis of ultrasonic signals that are sensitive to micro-structural changes occurring inside the material during the early stages of fatigue damage; the core concept of signal analysis is built upon the principles of Symbolic Dynamics, Statistical Pattern Recognition and Information Theory. The analytical tool of statistical pattern analysis has been experimentally validated on a special-purpose test apparatus that is equipped with ultrasonic flaw detection sensors and a travelling optical microscope. The paper reports fatigue damage monitoring of 7075-T6 alloy specimens, where the experiments have been conducted under load-controlled constant amplitude sinusoidal loadings for low-cycle and high-cycle fatigue.

[1]  Shant Kenderian,et al.  Ultrasonic monitoring of dislocations during fatigue of pearlitic rail steel , 2003 .

[2]  S. Suresh.  Fatigue of materials , 1991 .

[3]  E. Keller,et al.  Real-time sensing of fatigue crack damage for information-based decision and control , 2000 .

[4]  A. Witney,et al.  Electrochemical fatigue sensor response to Ti–6 wt% Al–4 wt% V and 4130 steel , 2004 .

[5]  M. Lysak.  Development of the theory of acoustic emission by propagating cracks in terms of fracture mechanics , 1996 .

[6]  Lai,et al.  Estimating generating partitions of chaotic systems by unstable periodic orbits , 2000, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[7]  N. Yusa,et al.  Detection of embedded fatigue cracks in Inconel weld overlay and the evaluation of the minimum thickness of the weld overlay using eddy current testing , 2006 .

[8]  D. V. Ramsamooj,et al.  Analytical prediction of short to long fatigue crack growth rate using small- and large-scale yielding fracture mechanics , 2003 .

[9]  C. Finney,et al.  A review of symbolic analysis of experimental data , 2003 .

[10]  Darrell E. Schlicker,et al.  MWM eddy-current arrays for crack initiation and growth monitoring , 2003 .

[11]  Douglas Lind,et al.  An Introduction to Symbolic Dynamics and Coding , 1995 .

[12]  J. Baram,et al.  Fatigue-life prediction by an order statistics treatment of acoustic-emission signals , 1993 .

[13]  Asok Ray,et al.  Symbolic dynamic analysis of complex systems for anomaly detection , 2004, Signal Process..

[14]  Asok Ray,et al.  Real-Time Health Monitoring of Mechanical Structures , 2003 .

[15]  S. Rokhlin,et al.  In situ ultrasonic monitoring of surface fatigue crack initiation and growth from surface cavity , 2003 .

[16]  B. Yang,et al.  Thermal-imaging technologies for detecting damage during high-cycle fatigue , 2004 .

[17]  Matthew B Kennel,et al.  Estimating good discrete partitions from observed data: symbolic false nearest neighbors. , 2003, Physical review letters.

[18]  Shalabh Gupta,et al.  Symbolic time series analysis of ultrasonic data for early detection of fatigue damage , 2007 .

[19]  Jeffrey D. Ullman,et al.  Introduction to Automata Theory, Languages and Computation , 1979 .

[20]  Sébastien Grondel,et al.  Fatigue crack monitoring of riveted aluminium strap joints by Lamb wave analysis and acoustic emission measurement techniques , 2002 .

[21]  E. Ott.  Chaos in Dynamical Systems: Contents , 1993 .

[22]  RayAsok.  Symbolic dynamic analysis of complex systems for anomaly detection , 2004 .

[23]  S. Ishihara,et al.  Analysis of short fatigue crack growth in cast aluminum alloys , 2002 .

[24]  H. S. Bai,et al.  A monitoring system for contact fatigue crack testing , 1989 .

[25]  R. Badii,et al.  Complexity: Hierarchical Structures and Scaling in Physics , 1997 .

[26]  Peter B. Nagy,et al.  Fatigue damage assessment by nonlinear ultrasonic materials characterization , 1998 .

[27]  Süleyman Özekici,et al.  Reliability and Maintenance of Complex Systems , 2010, NATO ASI Series.

[28]  Yves H. Berthelot,et al.  Detection of small surface-breaking fatigue cracks in steel using scattering of Rayleigh waves , 2001 .

[29]  J. Rose.  Ultrasonic Waves in Solid Media , 1999 .

[30]  Patrick Guillaume,et al.  On-line monitoring of fatigue cracks using ultrasonic surface waves , 2003 .

[31]  William T. Yost,et al.  Nonlinear ultrasonic characterization of fatigue microstructures , 2001 .

[32]  H. L. Dunegan,et al.  Continuous monitoring of fatigue-crack growth by acoustic-emission techniques , 1974 .

[33]  K. Lee,et al.  Cyclic AE count rate and crack growth rate under low cycle fatigue fracture loading , 1992 .

[34]  Neil J. Goldfine,et al.  Early detection and monitoring of fatigue in high strength steels with MWM-Arrays , 2005 .

[35]  S. Winterstein,et al.  Random Fatigue: From Data to Theory , 1992 .

[36]  Daining Fang,et al.  Study of fatigue crack characteristics by acoustic emission , 1995 .

[37]  Asok Ray,et al.  Symbolic time series analysis for anomaly detection: A comparative evaluation , 2005, Signal Process..

[38]  S. Mallat.  A wavelet tour of signal processing , 1998 .

[39]  Christina Bjerkén,et al.  A tool to model short crack fatigue growth using a discrete dislocation formulation , 2003 .

[40]  R. C. Chivers,et al.  On the feasibility of detecting pre-cracking fatigue damage in metal-matrix composites by ultrasonic techniques , 1995 .

[41]  Asok Ray,et al.  Symbolic time series analysis via wavelet-based partitioning , 2006 .

[42]  Arch W. Naylor,et al.  Linear Operator Theory in Engineering and Science , 1971 .

[43]  Henry D. I. Abarbanel,et al.  Analysis of Observed Chaotic Data , 1995 .

[44]  C. M. Scala,et al.  Acoustic emission during fatigue crack propagation in the aluminium alloys 2024 and 2124 , 1983 .

[45]  Marco Antonio Meggiolaro,et al.  Statistical evaluation of strain-life fatigue crack initiation predictions , 2004 .

[46]  Asok Ray,et al.  Symbolic time series analysis via wavelet-based partitioning , 2006, Signal Process..

[47]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .