Thermographic non-destructive testing damage detection for metals and cementitious materials

Shih, J.K.C.; Delpak, R.; Hu, Chang-Fu; Plassmann, P.; Wawrzynek, A.; Kogut, M. S.

doi:10.1080/13682199.2000.11784343

Cited by 12 publications

(8 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…If the location of the damage is known a priori, the practitioner may rely on interrogating the structure using ultrasound [1], eddy current [2], X-ray [3], and thermography [4]. The more general vibration-based approach to SHM assumes no such knowledge and requires only that observations of the structure's healthy dynamic response be made in order to classify subsequent data as coming from a damaged structure.…”

Section: Introductionmentioning

confidence: 99%

A Wavelet-based, Distortion Energy Approach to Structural Health Monitoring

Bukkapatnam

Nichols

Seaver

et al. 2005

Structural Health Monitoring

View full text Add to dashboard Cite

A method for quantifying damage-induced distortions to the vibrational response of an experimental plate is presented. By examining a wavelet representation of the difference in strain response between the damaged and the undamaged structures, the distortion energy may be computed on multiple timescales. This feature is tested in its ability to detect both the presence and the location of degradation of the plate. In addition, the effects of competing excitation mechanisms, including the outputs of Lorenz and Rossler systems, as well as a 0-225 Hz Gaussian noise are studied. The results indicate that the distortion energies, statistically speaking, are significantly higher under damaged conditions compared to those extracted under undamaged conditions, implying that the new distortion energy approach will yield adequate features for detecting the presence as well as possibly the location of damage in a structure.

show abstract

Section: Introductionmentioning

confidence: 99%

A Wavelet-based, Distortion Energy Approach to Structural Health Monitoring

Bukkapatnam

Nichols

Seaver

et al. 2005

Structural Health Monitoring

View full text Add to dashboard Cite

show abstract

“…Some of these procedures are: the acoustic emission (Li et al, 2011), infrared thermography (Shih et al, 2000), ultrasound (Voigt et al, 2003), image processing (Nishikawa et al, 2012), eddy currents (Banks et al, 2002), and radiographs (Vossoughi et al, 2007); which are all used in assessing structural damage. However, the aforementioned methods possess several disadvantages; for instance, it is required that the location of the damage be known a priori, the section of the structure under inspection needs to be easily accessible and in several cases, the structures must be closed temporarily during its inspection (Curadelli et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

Fused empirical mode decomposition and wavelets for locating combined damage in a truss-type structure through vibration analysis

García-Pérez

Amezquita-Sanchez

Domínguez-González

et al. 2013

J. Zhejiang Univ. Sci. A

View full text Add to dashboard Cite

Structural health monitoring (SHM) is a relevant topic for civil systems and involves the monitoring, data processing and interpretation to evaluate the condition of a structure, in order to detect damage. In real structures, two or more sites or types of damage can be present at the same time. It has been shown that one kind of damaged condition can interfere with the detection of another kind of damage, leading to an incorrect assessment about the structure condition. Identifying combined damage on structures still represents a challenge for condition monitoring, because the reliable identification of a combined damaged condition is a difficult task. Thus, this work presents a fusion of methodologies, where a single wavelet-packet and the empirical mode decomposition (EMD) method are combined with artificial neural networks (ANNs) for the automated and online identification-location of single or multiple-combined damage in a scaled model of a five-bay truss-type structure. Results showed that the proposed methodology is very efficient and reliable for identifying and locating the three kinds of damage, as well as their combinations. Therefore, this methodology could be applied to detection-location of damage in real truss-type structures, which would help to improve the characteristics and life span of real structures.

show abstract

“…Nowadays, several classical and dynamical methods have been proposed for assessing structural damage. The classical methods consist of visual or experimental localization procedures, such as the acoustic emission (Li et al, 2011), infrared thermography (Shih et al, 2000), ultrasound (Tuzzeo and di Scalea, 2002), eddy currents (Banks et al, 2002), radiographs (Vossoughi et al, 2007), and image processing (Nishikawa et al, 2012). However, the aforementioned methods need not only a priori knowledge of the damaged region, but also accessibility to the vicinity of damage (Curadelli et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

MUSIC‐ANN Analysis for Locating Structural Damages in a Truss‐Type Structure by Means of Vibrations

Osornio-Ríos

Amezquita-Sanchez

Romero-Troncoso

et al. 2012

Computer aided Civil Eng

View full text Add to dashboard Cite

This article presents a methodology for damage detection, location, and quantification based on vibration signature analysis and a comprehensive experimental study to assess the utility of the proposed structural health monitoring applied to a five‐bay truss‐type structure. The MUSIC algorithm introduced first by Jiang and Adeli for health monitoring of structures in 2007 is fused with artificial neural networks for an automated result. The developed methodology is based on feeding the amplitude of the natural frequencies as input of an artificial neural network, being the novelty of the proposed methodology its ability to identify, locate, and quantify the severity of damages with precision such as: external and internal corrosion and cracks in an automated monitoring process. Results show the proposed methodology is effective for detecting a healthy structure, a structure with external and internal corrosion, and a structure with crack. Therefore, the proposed fusion of MUSIC‐ANN algorithms can be regarded as a simple, effective, and automated tool without requiring sophisticated equipment, toward establishing a practical and reliable structural health monitoring methodology, which will help to evaluate the condition of the structure, in order to detect damages early and to make the corresponding maintenance decisions in the structures.

show abstract

Thermographic non-destructive testing damage detection for metals and cementitious materials

Cited by 12 publications

References 2 publications

A Wavelet-based, Distortion Energy Approach to Structural Health Monitoring

A Wavelet-based, Distortion Energy Approach to Structural Health Monitoring

Fused empirical mode decomposition and wavelets for locating combined damage in a truss-type structure through vibration analysis

MUSIC‐ANN Analysis for Locating Structural Damages in a Truss‐Type Structure by Means of Vibrations

Contact Info

Product

Resources

About