Engineered Acoustic Emission Sensing in Metallic Structures by Phononic Crystals and MEMS Sensors
thesisposted on 28.11.2018 by Minoo Kabir
In order to distinguish essays and pre-prints from academic theses, we have a separate category. These are often much longer text based documents than a paper.
The acoustic emission (AE) method is a passive SHM/NDE method that provides direct information about the presence of active defects in structures. The passive nature of this method allows continuous and real-time monitoring of structures, and eventually uninterrupted service and safety in critical civil structures. Although the AE method is a well-established technique for detecting and characterizing damage in structures, the method has two major drawbacks (background noise and attenuation), which are addressed in this research by introducing an engineered AE monitoring approach. The components of the proposed approach are: (i) phononic crystals (PCs), which are spatially periodic subsystems artificially or naturally introduced into structural elements at later or design stage, to block, redirect and strengthen propagating elastic waves, and (ii) highly narrow band piezoelectric MEMS sensors tuned to the band gap of phononic crystals. PCs exhibit unnatural features, such as band gap formation. As a result, when a wave propagates through a periodic structure, the range of frequencies within the band gap are restricted. In this study, two types of PCs are considered: (a) periodic perforated plate naturally introduced to design in order to guide the propagation of elastic waves in a predefined path to the location of the sensor, and (b) periodic stubbed plate artificially introduced to isolate background noise (e.g. friction emissions). Piezoelectric micro-electro-mechanical systems (MEMS) sensors with highly narrow band frequency response tuned to the band gap of the PC structure are designed, manufactured and characterized. The combination of phononic crystals and piezo-MEMS sensors is demonstrated numerically and experimentally to improve the performance of AE method and reduce the cost of monitoring system.