Debaditya Dutta

Automated detection of delamination and disbond from wavefield images obtained using a scanning laser vibrometer

The paper presents signal and image processing algorithms to automatically detect delamination and disbond in composite plates from wavefield images obtained using a scanning laser Doppler vibrometer (LDV). Lamb waves are excited by a lead zirconate titanate transducer (PZT) mounted on the surface of a composite plate, and the out-of-plane velocity field is measured using an LDV. From the scanned time signals, wavefield images are constructed and processed to study the interaction of Lamb waves with hidden delaminations and disbonds. In particular, the frequency–wavenumber (f–k) domain filter and the Laplacian image filter are used to enhance the visibility of defects in the scanned images. Thereafter, a statistical cluster detection algorithm is used to identify the defect location and distinguish damaged specimens from undamaged ones.

A Nonlinear Acoustic Technique for Crack Detection in Metallic Structures

A crack detection technique based on nonlinear acoustics is investigated in this study. Acoustic waves at a chosen frequency are generated using an actuating lead zirconate titanate (PZT) transducer, and they travel through the target structure before being received by a sensing PZT wafer. Unlike an undamaged medium, a cracked medium exhibits high acoustic nonlinearity which is manifested as harmonics in the power spectrum of the received signal. Experimental results also indicate that the harmonic components increase nonlinearly in magnitude with increasing amplitude of the input signal. The proposed technique identifies the presence of cracks by looking at the two aforementioned features: harmonics and their nonlinear relationship to the input amplitude. The effectiveness of the technique has been tested on aluminum and steel specimens. The behavior of these nonlinear features as crack propagates in the steel beam has also been studied.

An unsupervised learning algorithm for fatigue crack detection in waveguides

Ultrasonic guided waves (UGWs) are a useful tool in structural health monitoring (SHM) applications that can benefit from built-in transduction, moderately large inspection ranges, and high sensitivity to small flaws. This paper describes an SHM method based on UGWs and outlier analysis devoted to the detection and quantification of fatigue cracks in structural waveguides. The method combines the advantages of UGWs with the outcomes of the discrete wavelet transform (DWT) to extract defect-sensitive features aimed at performing a multivariate diagnosis of damage. In particular, the DWT is exploited to generate a set of relevant wavelet coefficients to construct a uni-dimensional or multi-dimensional damage index vector. The vector is fed to an outlier analysis to detect anomalous structural states. The general framework presented in this paper is applied to the detection of fatigue cracks in a steel beam. The probing hardware consists of a National Instruments PXI platform that controls the generation and detection of the ultrasonic signals by means of piezoelectric transducers made of lead zirconate titanate. The effectiveness of the proposed approach to diagnose the presence of defects as small as a few per cent of the waveguide cross-sectional area is demonstrated.

Delamination Detection in Composite Structures using Laser Vibrometer Measurement of Lamb Waves

In this study, the feasibility of using a scanning laser vibrometer for detecting hidden delamination in multi-layer composites is explored. First, Lamb waves are excited by Lead Zirconate Titanate (PZT) transducers mounted on the surface of a composite plate, and the out-of-plane ultrasonic velocity field is measured using a 1D scanning laser vibrometer. From the scanned time signals, wave field images are constructed and processed to study the interaction of Lamb waves with hidden delamination. In order to highlight the defect area in the image, the performance of different image processing tools were investigated. In particular, the Laplacian image filter was found to accentuate the visual indications of the ultrasound-defect interaction by suppressing the presence of incident waves in the wave field images. The performance of the proposed scheme is investigated using experimental data collected from a 1.8 mm thick multilayer composite plate and a 10 mm thick composite wing structure.

A nonlinear acoustic technique for crack detection in metallic structures

A crack detection technique based on nonlinear acoustics is developed in this study. Acoustic waves at a chosen frequency are generated using an actuating lead zirconate titanate (PZT) transducer, and they travel through the target structure before being received by a sensing PZT wafer. Unlike an undamaged medium, a cracked medium exhibits high acoustic nonlinearity which is manifested as harmonics in the power spectrum of the received signal. Experimental results also indicate that the harmonic components increase non-linearly in magnitude with increasing amplitude of the input signal. The proposed technique identifies the presence of cracks by looking at the two aforementioned features: harmonics and their nonlinear relationship to the input amplitude. The effectiveness of the technique has been tested on aluminum and steel specimens. The behavior of these nonlinear features as crack propagates in the steel beam has also been studied.

Outlier analysis and principal component analysis to detect fatigue cracks in waveguides

Ultrasonic Guided Waves (UGWs) are a useful tool in structural health monitoring (SHM) applications that can benefit from built-in transduction, moderately large inspection ranges and high sensitivity to small flaws. This paper describes a SHM method based on UGWs, discrete wavelet transform (DWT), outlier analysis and principal component analysis (PCA) able to detect and quantify the onset and propagation of fatigue cracks in structural waveguides. The method combines the advantages of guided wave signals processed through the DWT with the outcomes of selecting defectsensitive features to perform a multivariate diagnosis of damage. The framework presented in this paper is applied to the detection of fatigue cracks in a steel beam. The probing hardware consists of a PXI platform that controls the generation and measurement of the ultrasonic signals by means of piezoelectric transducers made of Lead Zirconate Titanate. Although the approach is demonstrated in a beam test, it is argued that the proposed method is general and applicable to any structure that can sustain the propagation of UGWs.

Advanced Ultrasonic Structural Monitoring of Waveguides

Ultrasonic Guided Waves (UGWs) are a useful tool in those structural health monitoring applications that can benefit from built-in transduction, moderately large inspection ranges and high sensitivity to small flaws. This paper describes two methods, based on linear and nonlinear acoustics for structural damage detection based on UGWs. The linear method combine the advantages of UGW inspection with the outcomes of the Discrete Wavelet Transform (DWT) that is used for extracting defect-sensitive features that can be combined to perform a multivariate diagnosis of damage. In particular, the DWT is exploited to generate a set of relevant wavelet coefficients to construct a uni-dimensional or multi-dimensional damage index that, in turn is fed to an outlier algorithm to detect anomalous structural states. The nonlinear acoustics method exploits the circumstance that a cracked medium exhibits high acoustic nonlinearity which is manifested as harmonics in the power spectrum of the received signal. Experimental results also indicate that the harmonic components increase non-linearly in magnitude with increasing amplitude of the input signal. The proposed nonlinear technique identifies the presence of cracks by looking at the harmonics and their nonlinear relationship to the input amplitude. The general framework presented in this paper is applied to the detection of fatigue cracks in an I-shaped steel beam. The probing hardware consists of Lead Zirconate Titanate (PZT) materials used for both ultrasound generation and detection at chosen frequency. The effectiveness of the proposed methods for the structural diagnosis of defects that are small compared to the waveguide cross-sectional area is discussed.