The success of a random vibration simulation test heavily depends on how accurately service loads can be reproduced in a laboratory. Many sophisticated and expensive systems have been developed for these kinds of simulation tests. However, because of high cost and complexity, the usage of these systems is limited. In this paper, a new method that reconstructs service load histories using a time series model (autoregressive moving average (ARMA) model) is presented. This method was verified by using a road simulation test performed on a four-wheel vehicle. Comparisons between actual and reconstructed signals showed good agreement in statistical parameters, the cumulative frequency distribution (CFD) and the power spectral density (PSD). Accelerated testing with the ARMA model is also explained. The new method makes it possible to conduct highly accurate random vibration simulation tests at low cost and within a short time, which has great potential to benefit automobile and aerospace industries.

Issue Section:
Technical Papers
Topics:
Random vibration, Simulation, Stress, Time series, Aerospace industry, Automobiles, Computational fluid dynamics, Roads, Signals, Spectral energy distribution, Testing, Vehicles, Wheels
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