Advanced Modeling and System Parameter Identification through Minimal Dynamic Stimulation and Digital Signal Processing.

摘要

This paper describes the Hebert-Mackin Parameter Identification Method (HMPIM). This methodology is applicable to testing both hardware and software and enables identification of system or algorithm performance modeling parameters through minimal dynamic stimulation of the hardware or software. Exposing hardware to extensive operation and testing to determine salient system or component level modeling parameters is both costly, time consuming, and potentially risky. Classical test waveforms such as steps, ramps, or sinusoids expose the asset being tested to continuous probing and shaking and each test by itself does not drive out the entire set of essential modeling parameters. The HMPIM, utilizing persistent spectral excitation and data processing, allows the analyst or modeler to determine all the essential system performance and modeling parameters with a single 5 or 10 second excitation of the hardware or software algorithm.