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Smoothing and differentiating load–displacement data using a low‐pass filter for improved crack opening load estimates
Author(s) -
Daniewicz
Publication year - 1999
Publication title -
fatigue and fracture of engineering materials and structures
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.887
H-Index - 84
eISSN - 1460-2695
pISSN - 8756-758X
DOI - 10.1046/j.1460-2695.1999.00164.x
Subject(s) - smoothing , displacement (psychology) , filter (signal processing) , noise (video) , structural engineering , function (biology) , hodrick–prescott filter , computer science , mathematics , engineering , statistics , psychology , artificial intelligence , evolutionary biology , computer vision , image (mathematics) , psychotherapist , biology , business cycle , keynesian economics , economics
The presence of even small amounts of noise in experimental data significantly influences numerically determined derivatives. Dynamic programming is used to construct a low‐pass filter enabling the smoothing and differentiation of noisy data. The filter is used to smooth and differentiate load–displacement data for a propagating fatigue crack to obtain smoothed compliance as a function of applied load. The smoothed compliance is shown to allow for improved subsequent estimates of the crack opening load.