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Quantitative Comparison of Vibration Testing Methods

  • Celvi Lisy,
  • Gerrit Vander Wiel,
  • Tharwat Elkabani,
  • Peter Fickenwirth,
  • Sandra Jo Zimmerman,
  • Thomas N. Thompson

摘要

Dynamic environmental testing is an essential part of qualifying aerospace structures and components for transportation and flight. Traditional environmental testing subjects test articles to three single-input single-output tests, orthogonally exciting test specifications to approximate a three-dimensional field input to the article. However, altered boundary conditions between the laboratory and the field result in differing environments imparted onto the article. Furthermore, uncontrolled motion out of axis from the direction of excitation still imparts energy onto the test article. The dynamic environmental testing community has begun to explore multi-axis testing to better approximate field environments and save time on testing. Challenges in single-axis tests include ignoring certain stress states and failure modes that should otherwise exist in the test. Multi-input multi-output testing has the potential to reduce over and under testing and test times as the environments are tested simultaneously. Baseline field data is used as an input for random environmental testing in both single- and multi-axis tests. The structure analyzed in vibration tests was the Box Assembly with Removable Component (BARC) developed at Sandia National Laboratory and Kansas City National Security Campus, as a benchmark for dynamic testing [1]. Random field data was gathered by transporting the BARC structure in a vehicle across bumpy roads. Metrics must be developed to compare single-axis and multi-axis tests to quantitatively represent advantages and disadvantages seen in single axis and multi-axis for a given experimental setup. This project seeks to develop metrics that effectively and quantitatively compare the fidelity of dynamic environmental testing methods. Metrics used to compare testing methods include Fatigue Damage Spectrum (FDS) and Root Mean Square (RMS) of the acceleration power spectral densities (PSDs). These metrics encompass the success of the test at control locations and uncontrolled locations and throughout the different frequency ranges tested.