Fundamental frequency

About: Fundamental frequency is a research topic. Over the lifetime, 8941 publications have been published within this topic receiving 131583 citations.

Analysis of SiC based power electronic inverters for high speed machines

Abstract: Silicon carbide (SiC) based power switching devices have been extensively studied by researchers and engineers in recent years because of their superior physical properties compared to silicon However, the benefits of using SiC devices have yet to be fully explored, especially for high-speed or high-fundamental frequency motor drive applications Hence, this paper contributes to the understanding of the benefits of SiC inverters as applied to high-speed or high-fundamental frequency drives This research investigates the high switching frequency capabilities of SiC inverter to improve the performance of high-speed machines or high fundamental frequency operation and achieve lower weight and volume of the both motor and inverter

Power System Frequency Estimation by Reduction of Noise Using Three Digital Filters

Abstract: Accurate estimation of power system frequency is essential for monitoring and operation of the smart grid. Traditionally, this has been done using discrete Fourier transform (DFT) coefficients of the positive fundamental frequency. Such DFT-based frequency estimation has been used successfully in phasor measurement units and frequency disturbance recorders in North America. Frequency errors in DFT-based algorithms for single-phase signals arise mainly due to noise and the leakage effect of the negative fundamental frequency. In this paper, a DFT-based frequency estimation algorithm is proposed to introduce three digital filters for reduction of estimate error due to noise and the leakage effect. This algorithm calculates the frequency estimate from the magnitude ratios of DFT coefficients to avoid the leakage effect. It compensates the estimate error, which is induced from the DFT magnitude ratios of three filtered outputs. The enhancement of signal-to-noise ratios is verified through simulations.

Synthesis of natural sounding pitch contours in isolated utterances using hidden Markov models

Abstract: A novel technique is introduced for characterizing prosodic structure and is used for speech synthesis. The mechanism consists of modeling a set of observations as a probabilistic function of a hidden Markov chain. It uses mixtures of Gaussian continuous probability density functions to represent the essential, perceptually relevant structure of intonation by observing movements of fundamental frequency in monosyllabic words of varying phonetic structure. High-quality speech synthesis, using multipulse excitation, is used to demonstrate the power of the HMM in preserving the naturalness of the intonational meaning, conveyed by the variation of fundamental frequency and duration. The fundamental frequency contours are synthesized using a random number generator from the models, and are imposed on a synthesized prototype word which had the intonation of a low fall. The resulting monosyllabic words with imposed synthesized fundamental frequency contours show a high level of naturalness and are found to be perceptually indistinguishable from the original recordings with the same intonation. The results clearly show the high potential of hidden Markov models as a mechanism for the representation of prosodic structure by naturally capturing its essentials.