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Structural Health Monitoring Using Machine Learning And Synthetic Data, Michail Tzimas
Structural Health Monitoring Using Machine Learning And Synthetic Data, Michail Tzimas
Graduate Theses, Dissertations, and Problem Reports
Structural health monitoring spans many decades of research across multiple engineering fields. However, typical monitoring processes for damage detection of complex structures usually prohibit real-time or fast detection of debilitating damage to the structure. One of the major issues of real-time detection of damage is the enormity of data that needs to be processed, which is worsened by the relative inability of fast relaying of data to structural engineers. With the rapid advancement of Machine Learning, both issues can be overcome, and detection of failure is achieved with non-invasive techniques. This dissertation explores the applicability of Machine Learning as a …