Effects of aliasing on numerical integration

During the course of processing acceleration data from mechanical systems it is often desirable to integrate the data to obtain velocity or displacement waveforms. However, those who have attempted these operations may be painfully aware that the integrated records often yield unrealistic residual values. This is true whether the data has been obtained experimentally or through numerical simulation such as Runge–Kutta integration or the explicit finite element method. In the case of experimentally obtained data, the integration errors are usually blamed on accelerometer zero shift or amplifier saturation. In the case of simulation data, incorrect integrations are often incorrectly blamed on the integration algorithm itself. This work demonstrates that seemingly small aliased content can cause appreciable errors in the integrated waveforms and explores the unavoidable source of aliasing in both experiment and simulation—the sampling operation. Numerical analysts are often puzzled as to why the integrated acceleration from their simulation does not match the displacement output from the same simulation. This work shows that these strange results can be caused by aliasing induced by interpolation of the model output during sampling regularisation.