Damage detection using the Lipschitz exponent estimated by the wavelet transform: applications to vibration modes of a beam

By Junshik Hong, Yoon Young Kim, Hyunmi Lee, Yuyoung Lee. 2002

225 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Computer Vision and Pattern Recognition, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/543e48c49d5c19e88dde3d12ee686a03cc09af4b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Civil and Structural Engineering

1. Arcangelo Messina
2. Chen Yang
3. S. Olutunde Oyadiji

In Computer Vision and Pattern Recognition

1. Arcangelo Messina
2. Chen Yang
3. S. Olutunde Oyadiji

In Control and Systems Engineering

1. Arcangelo Messina
2. Chen Yang
3. S. Olutunde Oyadiji

Citations in the corpus

• Damage detection using modal frequency curve and squared residual wavelet coefficients-based damage indicator (2017, methodology): “[19] investigated damage detection based on Mexican hat wavelet coefficients of the fundamental mode shape that were derived using continuous wavelet transform (CWT) and discrete wavelet transform (DWT).”
• Refinements of damage detection methods based on wavelet analysis of dynamical shapes (2008, methodology): “…this approach by using several approaches (e.g. Yuen, 1985; Pandey et al., 1991; Ratcliffe, 1997; Ratcliffe and Bagaria, 1998; Wang and Deng, 1999; Hong et al., 2002; Gentile and Messina, 2002, 2003; Loutridis et al., 2004; Messina, 2004; Han et al., 2005; Yoon et al., 2005; Rucka and Wilde,…”