To Kang

Damage detection on composite structures with standing wave excitation and wavenumber analysis

This paper describes the use of wavenumber filtering for damage detection with a signal-frequency standing wave excitation on composite structures. Using a single, fixed frequency excitation from a mounted piezoelectric transducer, the full steady-state wavefield could be obtained using a Laser Doppler Vibrometer with a mirror-tilting device. After completing the scanning, a wavenumber filtering is applied to determine dominant wavenumber components of the measured wavefield, which could be used for indicative of structural damage. Mapping processes based on local wavenumber filtering is then carried out for damaged area visualization. Also introduced are the comparison of two methods for damage identification and visualization: the local wavenumber mapping and acoustic wavenumber spectroscopy. To demonstrate the proposed techniques, several experiments are performed on composite structures with different types of damage, including debonding and delamination on composite plates. The results demonstrate that the techniques are very effective in localizing damage with the potential for the quick inspection of a variety of composite structural components.

Comparison of guided and standing waves based full field laser scanning techniques for damage detection using wavenumber analysis (Conference Presentation)

This paper presents the comparison study of wavenumber-based defect detection performance in full field laser scanning techniques. Two types of wave excitation are used for damage detection; guided waves and standing waves. A piezoelectric actuator is mounted on surface of the thin plate to generate guided and standing waves with a single excitation frequency. Subsequent responses on each grid point are measured using a Laser doppler vibrometer (LDV) with a mirror tilting device. Full field wave image is then generated from the measured wave signals. After the laser scanning, wavenumber based processing is applied to the measurements to generate two types of full wave field images and to detect structural damage. Three wavenumber based signal processing are applied to the wave filed images to estimate damage size and depth, including the Local wavenumber mapping, Acoustic Wavenumber Spectroscopy, 2D wavelet based wavenumber spectroscopy. For the comparison of these two techniques, several experiments are performed on thin walled structures with several different types of damage, including corrosion in an aluminum plate and debonding on composite plates. This paper outlines pros and cons of these two excitation techniques in terms of several parameters, including damage sensitivity, processing time and their applicability.

Wavelet-Based Wavenumber Filtering for Damage Detection and Thickness Estimation with Laser-Scanning

This paper presents the use of wavelet-based wavenumber filtering for damage detection and thickness estimation with Laser-scanning sensing. A piezoelectric transducer provides an excitation at a fixed, single frequency to a structure. Laser Doppler Vibrometer (LDV) with a mirror-tilting device measures subsequent steadystate structural responses, resulting in the full standing wavefield of the structure at the excitation frequency. After then, wavelet-based wavenumber filtering is performed to obtain dominant wavenumber components, which could be used for indicative of structural damage. Mapping processes based on the dominant wavelet-based wavenumber is carried out for damaged area visualization. To estimate the depth of damages, Lamb wave equation is transformed into the wavenumber-thickness equation with the known structural parameters. With this process, the thickness and the thickness reduction by corrosion was accurately identified. Several experiments are performed on thin walled structures, including pipes and plates, with different types of damage, including corrosion and cracks. The experimental investigation into quantitative assessment of welded joints are also performed. The results show that the techniques are very effective in damage size and depth estimation with improved speed.

Fault Diagnosis of Rotating System Mass Unbalance Using Hidden Markov Model

In recent years, pattern recognition methods have been widely used by many researchers for fault diagnoses of mechanical systems. The soundness of a mechanical system can be checked by analyzing the variation of the system vibration characteristic along with a pattern recognition method. Recently, the hidden Markov model has been widely used as a pattern recognition method in various fields. In this paper, the hidden Markov model is employed for the fault diagnosis of the mass unbalance of a rotating system. Mass unbalance is one of the critical faults in the rotating system. A procedure to identity the location and size of the mass unbalance is proposed and the accuracy of the procedure is validated through experiment.