An algorithm to minimize errors in displacement measurements via double integration of noisy acceleration signals
| Autor: | José Geraldo Telles Ribeiro, J.T.P. Castro, Marco Antonio Meggiolaro |
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| Rok vydání: | 2021 |
| Předmět: |
Mechanical Engineering
Applied Mathematics Noise spectral density General Engineering Aerospace Engineering Filter (signal processing) Noise (electronics) Industrial and Manufacturing Engineering Displacement (vector) Numerical integration Root mean square Acceleration Square root Automotive Engineering Algorithm Mathematics |
| Zdroj: | Journal of the Brazilian Society of Mechanical Sciences and Engineering. 43 |
| ISSN: | 1806-3691 1678-5878 |
| Popis: | This paper presents analyses of noise effects in displacement histories measured by double numerical integration of acceleration data. Since such noise-induced errors tend to be highly random, they must be estimated statistically. The noise root mean square (RMS) value can be used to estimate its effect on the actual resolution of acceleration measurements, and a good low-pass filter can improve this resolution. This RMS value can be estimated by multiplying the noise density by the square root of the cutoff frequency of the filter used. However, this information alone cannot estimate the displacement resolution directly. To mitigate this problem, this study proposes suitable parameters to estimate the error induced in displacements measured by double integration of noisy acceleration data and shares a code that can be used to minimize such errors. |
| Databáze: | OpenAIRE |
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