Correcting data from an unknown accelerometer using recursive least squares and wavelet de-noising

摘要: Non-linear finite element analyses of structures that are subject to seismic actions require high quality accelerogram data. Raw data needs be adjusted remove the influence transfer function instrument itself. This process is known as correction. Unfortunately, information about recording often unknown or unreliable. most case for older analogue recordings. paper uses a recursive least squares (RLS) algorithm identify characteristics even when completely unknown. The results presented in implement modern approach de-noising by employing wavelet transform. technique removes only those components signal whose amplitudes below certain threshold and not therefore frequency selective. It supersedes some extent conventional band pass filtering which requires careful selection cut-off frequencies, now unnecessary.