Optimization Acceleration Integral Method Based on Power Spectrum Estimation

Abstract

Abstract. Due to the excellent performance of the frequency domain integration method, it is widely used for acceleration integral calculations. However, the frequency-domain integration needs to select the effective integration frequency band to achieve its optimal integration performance. This paper proposes the method with power spectrum density (PSD) estimation to realize the optimization integral of the acceleration signal. By analysing the power spectrum density of the acceleration signal, the optimal low frequency cut-off frequency is obtained. Combined with frequency domain integration algorithm, it can effectively remove low-frequency noise and improve integral accuracy. Then, the novel algorithm tested by an experiment platform with a vibration bench. Experiment results show that this algorithm can adaptively select the low-frequency cut-off frequency and realize frequency domain integration optimization and the integration error is controlled within ±0.2mm.

Examination of a Magnetorheological Damper Control System with Vibration Energy Harvesting

“…They can be divided into two categories of numerical integration, in the frequency domain and in the time domain. The frequency method is to convert the acceleration signal to the frequency domain using Fourier transforms, and then determine the velocity using the transfer functions and the inverse Fourier transform [27][28][29]. The key issue in the method of time domain integration is to remove the constant component resulting from numerical integration [29][30][31].…”

Refactoring and Optimization of Bridge Dynamic Displacement Based on Ensemble Empirical Mode Decomposition

“…In order to eliminate the influence of low-frequency trend terms and high-frequency noise on the integration process, filtering is usually performed in the frequency domain. However, frequency domain filtering has the problem of cutoff frequency selection and truncation error, and it is easy to generate a large displacement calculation error when the original signal spectrum is unknown [11]. Time domain integration avoids problems such as cutoff frequency selection, but displacement signals obtained by quadratic integration in the time domain using a micro-electro-mechanical system (MEMS) accelerometer can be severely offset or even lead to erroneous results.…”