Robust Processing of Mechanical Vibration Measurements

Abstract

When performing mechanical vibration measurements, it. is often assumed that the disturbing measurement noise behaves Gaussian. In reality, this is not always the case, and therefore classical least-squares procedures can give poor results when processing the measurements. In this paper, several robust statistical procedures will be used in four selected problems in vibration measurement and analysis. It will be shown that the procedures improve the results compared to classical least-squares methods. Because fast. processing is required, a tradeoff between robustness of the methods and computation speed is made. In particular the following steps in vibration engineering were robustified: (1) positional calibration, (2) measurement post-processing, (3) system identification and (4) data classification for damage detection.