This paper proposes a new way for guided wave structural health monitoring using in-plane shear (d36 type)
piezoelectric wafer active sensors phased arrays. Conventional piezoelectric wafer active sensors phased arrays based on
inducing into specific Lamb wave modes (d31 type) has already widely used for health monitoring of the thin-wall
structures. Rather than Lamb wave modes, the in-plane shear piezoelectric wafer active sensors phased arrays induces in-plane
shear horizontal (SH) guided waves. The SH guided waves are distinct with the Lamb waves with simple
waveform and less additional converted wave modes and the zero symmetric mode (SH0) is non-dispersive. In this paper,
the advantage of the shear horizontal wave and the in-plane shear piezoelectric wafers capability to generate SH waves is
first reviewed. Then finite element analysis of a 4-in-plane shear wafer active sensors phased array embedded on a
rectangular aluminium plate is performed. In addition, numerical simulations with respect to creaks with different sizes
as well as locations are implemented by the in-plane shear wafer active sensors phased array. For comparison purposes,
the same numerical simulations using the conventional piezoelectric wafer active sensors phased arrays are also
employed at the same time. Results indicate that the in-plane shear (d36 type) piezoelectric wafer active sensors phased
arrays has the potential to identify damage location and assess damage severity in structural health monitoring.
This paper proposes a novel and effective method to identify the damage in the 2-D beam via Lamb wave. Two problems in the structural damage identification: damage location and damage severity are solved based on the theory of compressive sampling (CS) which indicates that sparse or compressible signals can be reconstructed using just a few measurements. Because of the sparsity nature of the damage, a database of damage features is established via a sparse representation for damage identification and assessing. Specifically, this proposed method consists of two steps: damage database establishing and feature matching. In the first step, the features database of both the healthy structure and the damaged structure are represented by the Lamb wave which propagates in the 2-D beam. Then in the matching step, expressing the test modal feature as a linear combination of the bases of the over-complete reference feature database which is constructed by concatenating all modal features of all candidate damage locations builds a highly underdetermined linear system of equations with an underlying sparse representation, which can be correctly recovered by ℓ1-minimization based on CS theory; the non-zero entry in the recovered sparse representation directly identifies the damage location and severity. In addition, numerical simulation is conducted to verify the method. This method of identifying damage location and assessing damage severity, using limited Lamb wave features, obtains good result.
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