Development of a Noise Filtering Algorithm for Strain Signals Using the Fast Fourier Transform

Abstract

The purpose of this study is to filter the noise in strain signals based on the fast Fourier transform. The strain signals were measured at an automotive lower arm made from the SAE 1045 carbon steel driven on paving block and asphalt. This technique removed lower amplitude cycles as much as possible due to their contribution to the minimum fatigue damage and simultaneous maintenance of cumulative fatigue damage. The filtering algorithm was able to remove up to 36.2% of the lower amplitude cycles and maintain more than 90% of the fatigue damage. This proved that the algorithm developed was successfully identified and eliminated low amplitude cycles.

New insight into the flexural rigidity of multi-filament yarn

“…To generate the smoothed displacement versus load curves shown in Figure 4(b), a fast Fourier transform (FFT) filter 18 was used. Every 20 data points (points of window, 10% of the total data on one curve) of each raw load-displacement curve were smoothed and the cutoff frequency was 0.6, which is a default parameter in Origin Pro V R (scientific graphic software).…”

Bridge Damage Identification by Ground-based Synthetic Aperture Radar Using Blind Source Separation and Noise Reduction Technology

“…where X(κ) is the frequency-domain signal and x(n) is the time-domain signal. (22) The main characteristic of FFT is that its computation speed is higher than that of DFT. The most important point is that the time-domain signal can be converted to the frequency-domain signal, and the frequency recognition has good accuracy.…”