Vibration energy harvesting based monitoring of an operational bridge undergoing forced vibration and train passage
| Autor: | Budhaditya Hazra, Alan Mathewson, Raid Karoumi, Paul Cahill, Vikram Pakrashi |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Full-scale testing
Sequential Karhunen Loeve transform Aerospace Engineering Bridge structure 02 engineering and technology Automotive engineering Bridge (nautical) Hilbert transform 0203 mechanical engineering Ambient vibration Empirical mode decomposition Civil and Structural Engineering Structural health monitoring Energy harvesting Mechanical Engineering Vibration energy harvesting 021001 nanoscience & nanotechnology Scalogram Computer Science Applications Vibration 020303 mechanical engineering & transports Control and Systems Engineering Signal Processing Environmental science 0210 nano-technology Civil infrastructure Energy (signal processing) |
| Popis: | The application of energy harvesting technology for monitoring civil infrastructure is a bourgeoning topic of interest. The ability of kinetic energy harvesters to scavenge ambient vibration energy can be useful for large civil infrastructure under operational conditions, particularly for bridge structures. The experimental integration of such harvesters with full scale structures and the subsequent use of the harvested energy directly for the purposes of structural health monitoring shows promise. This paper presents the first experimental deployment of piezoelectric vibration energy harvesting devices for monitoring a full-scale bridge undergoing forced dynamic vibrations under operational conditions using energy harvesting signatures against time. The calibration of the harvesters is presented, along with details of the host bridge structure and the dynamic assessment procedures. The measured responses of the harvesters from the tests are presented and the use the harvesters for the purposes of structural health monitoring (SHM) is investigated using empirical mode decomposition analysis, following a bespoke data cleaning approach. Finally, the use of sequential Karhunen Loeve transforms to detect train passages during the dynamic assessment is presented. This study is expected to further develop interest in energy-harvesting based monitoring of large infrastructure for both research and commercial purposes. Irish Research Council Science Foundation Ireland |
| Databáze: | OpenAIRE |
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