Various non-destructive testing (NDT) methods have been developed to extract information about state of a structure. Two of them: vibration-based and guided wave-based techniques are one of the most commonly used and well developed. Both approaches can be implemented using Scanning Laser Doppler Vibrometer measurements and excitation by means of piezoelectric transducer. In this paper authors present a combined approached for NDT using successive and simultaneous measurement of both mode shapes and guided waves. Vibration-based damage detection is focused on detection of mode shape singularity, created by material discontinuity. This method utilizes wavelet transform and Teager energy operator for damage indication. Guided wave-based damage detection uses propagating elastic wave energy variation on the specimen surface as well as any changes in wave propagation pattern due to its interaction with material discontinuity as a tool for structural health assessment. Combining this two different techniques can give higher accuracy in defect detection. At the same time any additional specimen preparation are necessary, any set-up changes are required and the all the data can be registered in the same amount of time (simultaneous excitation). To confirm proposed technique a honeycomb core sandwich aluminum plate with debonding is tested. A results obtained with both techniques and combined approach are presented.
Curvature mode shape is an effective feature for damage detection in beams. However, it is susceptible to measurement
noise, easily impairing its advantage of sensitivity to damage. To deal with this deficiency, this study formulates an
improved curvature mode shape for multiple damage detection in beams based on integrating a wavelet transform (WT)
and a Teager energy operator (TEO). The improved curvature mode shape, termed the WT - TEO curvature mode shape,
has inherent capabilities of immunity to noise and sensitivity to damage. The proposed method is experimentally
validated by identifying multiple cracks in cantilever steel beams with the mode shapes acquired using a scanning laser
vibrometer. The results demonstrate that the improved curvature mode shape can identify multiple damage accurately
and reliably, and it is fairly robust to measurement noise.
The main objective of this study is to present a novel method for damage detection in plate-type structures using twodimensional (2D) continuous wavelet transforms. For this purpose, the 2D Mexican wavelet is employed to remold the equation of motion for transverse vibration of a plate. The remolded vibration equation of a plate can serve as a multiscale damage detection scheme that characterizes damage using an indicator of multiscale pseudo-load. Effects of multiscale pseudo-load can pinpoint the location of the damage as well as revealing its configuration; moreover, the strong solid mechanics foundation of the method results in the identified damage with an explicit physical implication. The performance of the proposed technique is validated through an experimental program of using a scanning laser vibrometer (SLV) to measure the transverse deflection of an aluminum plate bearing a cross-like notch and an added small mass. The results confirm the robustness and superior capability of the proposed method in detecting damage in plate-type structures.
Vibration-based nondestructive damage detection relying on modal curvatures has been investigated in various
applications. An intrinsic deficiency of a modal curvature is its susceptibility to the noise inevitably present in a
measured mode shape. This adverse effect of noise is likely to mask actual features of damage, resulting in false results
of damage detection. To circumvent this deficiency, a Teager energy operator (TEO), aided by a wavelet transform, is
adopted for the treatment of mode shapes to produce a new algorithm for damage identification. After wavelet-transform-
based preprocessing to separate the effective components of modal curvatures from noise interference, a TEO
is employed as a singularity detector, acting on the separated effective components, to reveal and characterize the
features of damage. The capacity of the TEO is demonstrated analytically in cases of cracked beams. The applicability of
the algorithm is experimentally validated using a scanning laser vibrometer to acquire mode shapes of an aluminum
beam bearing a crack. The analytical and experimental results show that the TEO, aided by wavelet transforms, has
stronger sensitivity to slight damage and greater robustness to noise than modal-curvature- and wavelet-transform-based
damage detection methods.