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Sensitivity-based characterization of the bias errors in frequency based substructuring
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DOI：10.1016/j.ymssp.2021.108800.png)
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Abstract
En 中文
A reliable experimental application of frequency based substructuring requires very accurate acquisition of frequency response functions (FRFs). Even a relatively small error introduced during the measurement can result in erroneous substructuring results. The measurement errors can be either random or systematic, with the latter often referred to as bias. Impact excitation is popular in dynamic substructuring due to the rapid FRF calculation for each separate location. However, deviations in the location of the excitation affect the FRFs across the whole frequency range. This paper proposes a novel methodology to characterize the bias errors in frequency based substructuring using the small deviations in impact excitation from typical experimental measurements. The small deviations are utilized to reconstruct a range of FRFs, which are directly used in the global sensitivity analysis. The sensitivity analysis is utilized to characterize how each impact location affects an arbitrary quality indicator, such as reciprocity or passivity. Therefore, the effect of the bias can be evaluated directly from a single series of measurements, without the need for a numerical model. The proposed approach is first shown on a synthetic numerical example, where the advantages and limitations are outlined. Finally, an application involving experimental frequency based substructuring on a beam-like structure is depicted.
Keywords:
Frequency based substructuring
Virtual point transformation
Bias error
Global sensitivity analysis
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