Real-time fatigue life monitoring based on thermodynamic entropy

This article presents a methodology for real-time monitoring of fatigue life in machinery components that utilizes the accumulation of entropy to assess the severity of degradation associated with fatigue. Using this concept, a prototype called the fatigue monitoring unit that automatically shuts down the machine prior to the onset of fatigue fracture based on a user-specified factor of safety is developed. The method is applicable to variable loading and does not require the specification of the loading history or loading sequence. The results of a series of laboratory fatigue tests pertaining to Al 6061-T6 and SS 304 specimens, which show the utility of the approach and its suitability for implementation in the field, are provided.

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

[2]  Guo Tong,et al.  Fatigue Life Prediction of Welded Joints in Orthotropic Steel Decks Considering Temperature Effect and Increasing Traffic Flow , 2008 .

[3]  J. Morrow.  Cyclic Plastic Strain Energy and Fatigue of Metals , 1965 .

[4]  Ali Fatemi,et al.  Cumulative fatigue damage and life prediction theories: a survey of the state of the art for homogeneous materials , 1998 .

[5]  Christer Sjöström.  Overview of Methodologies for Prediction of Service Life , 1985 .

[6]  Michael M. Khonsari,et al.  An experimental approach to low-cycle fatigue damage based on thermodynamic entropy , 2010 .

[7]  M. Naderi,et al.  On the thermodynamic entropy of fatigue fracture , 2010, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

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

[9]  Jan Ming Ko,et al.  Fatigue analysis and life prediction of bridges with structural health monitoring data — Part I: methodology and strategy , 2001 .

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

[11]  Jan Ming Ko,et al.  Fatigue analysis and life prediction of bridges with structural health monitoring data — Part II: application , 2001 .

[12]  Hamid Nayeb-Hashemi,et al.  Constitutive relations and fatigue life prediction for anisotropic Al-6061-T6 rods under biaxial proportional loadings , 1992 .

[13]  S. J. Kline,et al.  Describing Uncertainties in Single-Sample Experiments , 1953 .

[14]  R. Ritchie,et al.  Ambient- to elevated-temperature fracture and fatigue properties of Mo-Si-B alloys: Role of microstructure , 2005 .

[15]  Zhen Li,et al.  Fatigue performance of old bridge steel and the procedures for life prediction with given survivability , 1996 .

[16]  F. F. Ling,et al.  An experimental study of the correlation between wear and entropy flow in machinery components , 2000 .

[17]  Michel Grédiac,et al.  Applying infrared thermography to study the heating of 2024-T3 aluminium specimens under fatigue loading , 2008 .

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

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

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

[21]  Jan Drewes Achenbach,et al.  Structural Health Monitoring and Damage Prognosis in Fatigue , 2008 .

[22]  R. Brook,et al.  Cumulative Damage in Fatigue: A Step towards Its Understanding , 1969 .

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

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

[25]  Drew V. Nelson,et al.  Evaluation of an energy-based approach and a critical plane approach for predicting constant amplitude multiaxial fatigue life , 2000 .

[26]  Michael M. Khonsari,et al.  On the thermodynamics of degradation , 2008, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[27]  J. Schijve.  Predictions on Fatigue Life and Crack Growth as an Engineering Problem. A State of the Art Survey , 1996 .

[28]  G. R. Halford,et al.  Practical implementation of the double linear damage rule and damage curve approach for treating cumulative fatigue damage , 1981 .

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

[30]  B. Yang,et al.  Frequency Effects on Fatigue Behavior and Temperature Evolution of Steels , 2003 .

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

[32]  Shalabh Gupta,et al.  Online fatigue damage monitoring by ultrasonic measurements : A symbolic dynamics approach , 2007 .

[33]  B. Yang,et al.  Thermographic detection of fatigue damage of pressure vessel steels at 1,000 Hz and 20 Hz , 2000 .

[34]  Henning Agerskov,et al.  Fatigue in Steel Highway Bridges under Random Loading , 2000 .

[35]  G. R. Halford,et al.  Re-examination of cumulative fatigue damage analysis—an engineering perspective , 1986 .

[36]  Larry W. Masters,et al.  Problems in service life prediction of building and construction materials , 1985 .

[37]  J. Kohout,et al.  Temperature dependence of stress–lifetime fatigue curves , 2000 .

[38]  Michael M. Khonsari,et al.  An Experimental Approach to Evaluate the Critical Damage , 2011 .

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

[40]  Asok Ray,et al.  Stochastic Measure of Fatigue Crack Damage for Health Monitoring of Ductile Alloy Structures , 2004 .