A research on fatigue crack growth monitoring based on multi-sensor and data fusion

Fatigue crack propagation is one of the main problems in structural health monitoring. For the safety and operability of the metal structure, it is necessary to monitor the fatigue crack growth pro...

[1]  B. Masserey,et al.  In-situ monitoring of fatigue crack growth using high frequency guided waves , 2015 .

[2]  Michel Castaings,et al.  The interaction of the S0 Lamb mode with vertical cracks in an aluminium plate. , 2002, Ultrasonics.

[3]  R. Benedictus,et al.  Using acoustic emission to understand fatigue crack growth within a single load cycle , 2018 .

[4]  L. P. Borrego,et al.  Evaluation of overload effects on fatigue crack growth and closure , 2003 .

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

[6]  X. Qing,et al.  A novel eddy current array sensing film for quantitatively monitoring hole-edge crack growth in bolted joints , 2018, Smart Materials and Structures.

[7]  Zhiyi Liu,et al.  Slip band formation in plastic deformation zone at crack tip in fatigue stage II of 2xxx aluminum alloys , 2016 .

[8]  Krishna R. Pattipati,et al.  Data-Driven Modeling, Fault Diagnosis and Optimal Sensor Selection for HVAC Chillers , 2007, IEEE Transactions on Automation Science and Engineering.

[9]  Armin Lechleiter,et al.  A hybrid approach for Structural Monitoring with self-organizing multi-agent systems and inverse numerical methods in material-embedded sensor networks , 2016 .

[10]  Yu Wang,et al.  A time reversal focusing based impact imaging method and its evaluation on complex composite structures , 2011 .

[11]  V. Shlyannikov,et al.  Effect of temperature on the growth of fatigue surface cracks in aluminum alloys , 2017, Theoretical and Applied Fracture Mechanics.

[12]  Masayuki Kamaya,et al.  Monitoring of inside surface crack growth by strain measurements of the outside surface: Application of multiple strain measurements technique to fatigue crack growth , 2013 .

[13]  Xinlin Qing,et al.  Piezoelectric Transducer-Based Structural Health Monitoring for Aircraft Applications , 2019, Sensors.

[14]  D. Nowell,et al.  A study of overload effect on fatigue crack propagation using EBSD, FIB–DIC and FEM methods , 2016 .

[15]  Slim Soua,et al.  Finite Element Analysis of Crack Growth for Structural Health Monitoring of Mooring Chains using Ultrasonic Guided Waves and Acoustic Emission , 2017 .

[16]  Feng Jia,et al.  An Intelligent Fault Diagnosis Method Using Unsupervised Feature Learning Towards Mechanical Big Data , 2016, IEEE Transactions on Industrial Electronics.

[17]  Shenfang Yuan,et al.  A Multi-Response-Based Wireless Impact Monitoring Network for Aircraft Composite Structures , 2016, IEEE Transactions on Industrial Electronics.

[18]  Jian Cai,et al.  Research on a Lamb Wave and Particle Filter-Based On-Line Crack Propagation Prognosis Method , 2016, Sensors.

[19]  R. Ritchie,et al.  On the theoretical modeling of fatigue crack growth , 2018, Journal of the Mechanics and Physics of Solids.

[20]  Jian-Da Wu,et al.  Development of an expert system for fault diagnosis in scooter engine platform using fuzzy-logic inference , 2007, Expert Syst. Appl..

[21]  F. Yuan,et al.  Group velocity and characteristic wave curves of Lamb waves in composites: Modeling and experiments , 2007 .

[22]  Liangxiao Jiang,et al.  Randomly selected decision tree for test-cost sensitive learning , 2017, Appl. Soft Comput..

[23]  Yang Wang,et al.  Multi-agent system design and evaluation for collaborative wireless sensor network in large structure health monitoring , 2010, Expert Syst. Appl..

[24]  Silvio Simani,et al.  Fault diagnosis of an industrial gas turbine prototype using a system identification approach , 2008 .

[25]  Martine Wevers,et al.  Crack monitoring in historical masonry with distributed strain and acoustic emission sensing techniques , 2018 .

[26]  Bo Wang,et al.  Efficient combination rule of evidence theory , 2001, International Symposium on Multispectral Image Processing and Pattern Recognition.