Fatigue damage diagnosis using statistical, spectral, and wavelet analysis techniques

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The objective of this work is to illustrate a comparative investigation into the signatures of crack initiation and propagation using vibration and displacement signals. Experimental tests were performed on low carbon steel specimen under fully reversed bending cycles in a cantilever support configuration. Accelerometer and displacement-sensor vibration signals were collected using a National Instrument data acquisition system. Several methods, such as statistical moments, FFT, Wavelets, and short-time-frequency analysis techniques, were used to analyze the collected signals. It was found that the wavelet analysis gave the most consistent patterns in tracking crack initiation and propagation. For the wavelet analysis, extensive comparative investigation was conducted to select the optimum combination of wavelet packets for crack detection and monitoring.

Original languageEnglish (US)
Title of host publicationDynamics, Vibration and Control
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Print)9780791856246
DOIs
StatePublished - Jan 1 2013
EventASME 2013 International Mechanical Engineering Congress and Exposition, IMECE 2013 - San Diego, CA, United States
Duration: Nov 15 2013Nov 21 2013

Publication series

NameASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)
Volume4 A

Other

OtherASME 2013 International Mechanical Engineering Congress and Exposition, IMECE 2013
CountryUnited States
CitySan Diego, CA
Period11/15/1311/21/13

Fingerprint

Wavelet analysis
Fatigue damage
Crack initiation
Spectrum analysis
Crack propagation
Statistical methods
Crack detection
Low carbon steel
Accelerometers
Fast Fourier transforms
Data acquisition
Monitoring
Sensors

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering

Cite this

Abu-Mahfouz, I., Banerjee, A., & Abu-Ayyad, M. A. (2013). Fatigue damage diagnosis using statistical, spectral, and wavelet analysis techniques. In Dynamics, Vibration and Control (ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE); Vol. 4 A). American Society of Mechanical Engineers (ASME). https://doi.org/10.1115/IMECE2013-66518
Abu-Mahfouz, Issam ; Banerjee, Amit ; Abu-Ayyad, Ma'moun Abdel. / Fatigue damage diagnosis using statistical, spectral, and wavelet analysis techniques. Dynamics, Vibration and Control. American Society of Mechanical Engineers (ASME), 2013. (ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)).
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Abu-Mahfouz, I, Banerjee, A & Abu-Ayyad, MA 2013, Fatigue damage diagnosis using statistical, spectral, and wavelet analysis techniques. in Dynamics, Vibration and Control. ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE), vol. 4 A, American Society of Mechanical Engineers (ASME), ASME 2013 International Mechanical Engineering Congress and Exposition, IMECE 2013, San Diego, CA, United States, 11/15/13. https://doi.org/10.1115/IMECE2013-66518

Fatigue damage diagnosis using statistical, spectral, and wavelet analysis techniques. / Abu-Mahfouz, Issam; Banerjee, Amit; Abu-Ayyad, Ma'moun Abdel.

Dynamics, Vibration and Control. American Society of Mechanical Engineers (ASME), 2013. (ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE); Vol. 4 A).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abu-Mahfouz I, Banerjee A, Abu-Ayyad MA. Fatigue damage diagnosis using statistical, spectral, and wavelet analysis techniques. In Dynamics, Vibration and Control. American Society of Mechanical Engineers (ASME). 2013. (ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)). https://doi.org/10.1115/IMECE2013-66518