There are many applications for mode detections made by operational modal analysis (OMA), most notably modal-based structural health monitoring and damage detection, and mode tracking (MT). In order not to rely solely on experimental data or need to simulate vibration time-series and process them with OMA, a simulation framework is proposed to imitate the outcome of OMA across many datasets from the same structure. The framework allows for the undamaged and damaged states of a structure to be simulated, and flexibility in transitioning from the former to the latter state. The common errors of OMA algorithms (missing, false, and duplicate mode detections) are introduced through a probabilistic approach, and environmental and operational variability can also be introduced at the user’s discretion. The framework is intended to be general and flexible, so that it may be easily adapted to the needs of the user.

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Evaluating Mode Tracking Algorithms Through an AOMA Outcome Simulation Framework

  • Anno Christian Dederichs

摘要

There are many applications for mode detections made by operational modal analysis (OMA), most notably modal-based structural health monitoring and damage detection, and mode tracking (MT). In order not to rely solely on experimental data or need to simulate vibration time-series and process them with OMA, a simulation framework is proposed to imitate the outcome of OMA across many datasets from the same structure. The framework allows for the undamaged and damaged states of a structure to be simulated, and flexibility in transitioning from the former to the latter state. The common errors of OMA algorithms (missing, false, and duplicate mode detections) are introduced through a probabilistic approach, and environmental and operational variability can also be introduced at the user’s discretion. The framework is intended to be general and flexible, so that it may be easily adapted to the needs of the user.