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PubMed2002

An investigation into the spectral analysis of dielectric aging in ferroelectrics.

Aging and degradation indicate the time-dependent change of physical and electrical properties. Most studies neglect to report the effects of aging on the electromechanical properties of an electroactive material and subsequent deterioration of performance. Recent work has shown that the strain and polarization response of an electroactive device can be transformed into its harmonic spectrum (transformation from the time domain to the frequency domain) through the implementation of Fourier analysis. The ability to create this harmonic spectrum provides a new way to characterize the effects of aging by revealing subtle changes in the fundamental components that comprise the response. This study shows how Fourier analysis can be applied to an aged PMN-PT-BT composition to characterize and quantify the effects of aging. The average weak-field permittivity is measured as a function of time, temperature, and frequency. A typical "saddle" in the permittivity and dielectric loss is apparent, and the magnitude decays logarithmically with time. Harmonic analysis of the strain response reveals a slight time-dependent amplitude variation and logarithmic dependence of the phase of the 6th order harmonic. Similar analysis of the polarization response, as a function of time, fully characterizes the development of constriction or wasting seen in a typical aged electrostrictive material. Variations in the amplitudes of the 5th and higher order harmonics of polarization, logarithmic in nature, and the phase of the 5th order harmonic combine to define aging on the harmonic level.

Journal Article↗
PubMed1995

Spectral analysis of systolic blood pressure and heart rate oscillations related to respiration.

1. Non-invasive assessment of short-term systolic blood pressure (SBP) and heart rate (HR) variability was obtained with the plethysmographic finger blood pressure measurement device. Respiration was measured with a respiratory inductive plethysmograph, which was calibrated prior to each study. 2. The effects of breathing pattern on the respiratory (high frequency, HF) component of the SBP or HR spectrum were analysed by Fourier transform. 3. Our quantification of the changes in the HF (respiratory) peak of the HR or SBP spectrum with changes in tidal volume (VT) and breathing frequency (BF) indicates that the modulus of this component may be predicted for any combination of depth and frequency of breathing. 4. The modulus of this HF component for the HR or SBP spectrum was linearly related to the respiratory sinus arrhythmia (RSA) or to the SBP oscillation related to respiration.

Adult↗