Non-parametric damage detection and characterization using smart piezoceramic material

By K. Tseng, A. Naidu. 2002

274 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Mechanics of Materials, Pollution

View Paper: https://www.semanticscholar.org/paper/1577251e451001c022ab45cc1d387e2863ddb6c1

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. Charles R. Farrar
2. Victor Giurgiutiu
3. Gyuhae Park
4. Hoon Sohn
5. Andrei Zagrai
6. Daniel J. Inman
7. Wongi S. Na
8. Jongdae Baek

In Mechanics of Materials

1. Victor Giurgiutiu
2. Charles R. Farrar
3. Gyuhae Park
4. Hoon Sohn
5. Andrei Zagrai
6. Xinlin Qing
7. Wongi S. Na
8. Jongdae Baek

In Pollution

1. Victor Giurgiutiu
2. Andrei Zagrai
3. Charles R. Farrar
4. Gyuhae Park
5. Wongi S. Na
6. Jongdae Baek
7. Xinlin Qing
8. Hoon Sohn

Citations in the corpus

• An overheight vehicle–bridge collision monitoring system using piezoelectric transducers (2007, background): “Tseng and Naidu (2002) presented the damage index by calculating the RMSD between the impedance of the PZT transducer mounted on aluminium specimens.”
• A Review of the Piezoelectric Electromechanical Impedance Based Structural Health Monitoring Technique for Engineering Structures (2018, methodology): “Tseng and Naidu [38] investigated the performance of the 4 different statistical metrics, and it was found through experiments that RMSD and MAPD were more suitable for locating and characterizing the growth of damage, whereas covariance and CC were more suitable for identifying the increase in dama”
• Damage Detection in Thin Plates and Aerospace Structures with the Electro-Mechanical Impedance Method (2005, background): “[6] who used an overall statistics approach to quantify the presence of damage, and found that the correlation coefficient gave best results.”
• Overview of Piezoelectric Impedance-Based Health Monitoring and Path Forward (2003, background): “Tseng and Naidu (2002) investigated several aluminum specimens with the impedance method.”
• A Review of Vibration-Based Damage Detection in Civil Structures: From Traditional Methods to Machine Learning and Deep Learning Applications (2020, methodology): “Unlike parametric approaches which rely on system identification, non-parametric SDD methods utilize statistical means to detect structural damage directly from the measured accelerations [125].”
• Electro-Mechanical Impedance Method for Crack Detection in Thin Plates (2001, background): “Other damage metrics, based on alternative statistical formulae (absolute percentage deviation, the covariance, the correlation coefficient, etc.) have also been tried (Tseng et al. 2001; Monaco et al., 2001).”
• Piezoelectric Transducer-Based Structural Health Monitoring for Aircraft Applications (2019, background): “Choi et al. proposed an optimal smoothing and filtering algorithm based on distributed built-in piezoelectric sensors to reconstruct the force history of impact on composite beams [128].”