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The model is adaptable because it incorporates numerical mode shapes determined by numerically employing the finite element technique to form relevant matrices.
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Therefore, the automatic selection of the most likely numerical mode shape corresponding to a particular experimentally identified mode shape can be a difficult task.
The experimental and numerical curvature mode shapes are primarily used to detect the presence, location, and size of the delamination.
This algorithm is applied to the numerical vibration mode shapes of a cantilever plate with different types of damage to illustrate its effectiveness and viability.
The proposed study starts with the choice of the proper positions of the piezoelectric sensor and actuator through the analysis of the numerical curvature mode shapes of the composite laminated plate.
Three relatively new damage detection algorithms (i.e., simplified gapped smoothing method (GSM), generalized fractal dimension (GFD), and strain energy method (SEM)) are employed to analyze the experimental and numerical curvature mode shape data and uniform load surface (ULS) curvatures.
The rotations and curvatures are obtained by numerical differentiation of mode shapes translations using a differentiation/smoothing technique.
Apart from the numerical artifacts, the mode shapes are very similar, which supports the expectation that they are otherwise equivalent.
The FE model is calibrated by reducing the difference between the identified and numerical natural frequencies and mode shapes of the bridge.
The optimal spatial sampling for the numerical differentiation of the mode shapes are defined based on the minimization of the total error.
Numerical simulations indicate that mode shapes, natural frequencies and time responses of microcantilever beam are heavily dependent on the viscoelastic and piezoelectric properties of the samples.
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