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<p>Structural health monitoring is more efficient than traditional visual interval-based structural inspection because structural assessments are implemented when a sensor, such as an accelerometer, measures the vibration of the structure and detects any abnormal readings outside of a safety threshold. These vibrations tend to be atypical when there is damage to the structure. Processing the collected data from an accelerometer using Fast Fourier Transformation (FFT) allows for a graphical visualization of visualizing these atypical measurements in the frequency domain. The comparison and analysis of vibration frequency incurred from three different scenarios (damage, no damage, and impact) in the steel truss prototype has resulted in fundamental knowledge necessary to differentiate an abnormality in accelerometer readings resulting from a vehicular crash against one in which there is actual structural damage. The primary outcome of this work will lead to avoiding unnecessary inspection costs due to possible faulty diagnostics and determining the reliability of the structural health monitoring method.</p>
Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/20415822 |
Date | 07 September 2022 |
Creators | Maeve Bruna Cucolotto (13184868) |
Source Sets | Purdue University |
Detected Language | English |
Type | Text, Thesis |
Rights | CC BY 4.0 |
Relation | https://figshare.com/articles/thesis/DIAGNOSING_FAULTY_STRUCTURAL_HEALTH_MONITORING_SHM_IN_THE_EVENT_OF_AN_AUTOMOBILE_ACCIDENT/20415822 |
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