A new sliding discrete Fourier transform phase difference measurement method for extreme frequency signals.

While there are many ultralow frequency signals and ultrahigh frequency signals in the vibration engineering field, the existing discrete Fourier transform (DFT) spectrum analysis methods bring about significant phase difference errors when measuring these extreme frequency signals. In order to improve the performance of these methods, a new sliding DFT phase difference measurement method for extreme frequency signals is proposed. First, the spectrum of extreme frequency signals is analyzed, which is used to illuminate the contribution of negative frequency.

A phase match based frequency estimation method for sinusoidal signals.

Accurate frequency estimation affects the ranging precision of linear frequency modulated continuous wave (LFMCW) radars significantly. To improve the ranging precision of LFMCW radars, a phase match based frequency estimation method is proposed. To obtain frequency estimation, linear prediction property, autocorrelation, and cross correlation of sinusoidal signals are utilized.

A new phase difference measurement algorithm for extreme frequency signals based on discrete time Fourier transform with negative frequency contribution.

For the ultralow frequency signals or adjacent Nyquist frequency signals, which widely exist in vibration engineering domain, the traditional discrete time Fourier transform (DTFT) algorithms show poor performance for phase difference measurement. To improve the accuracy of phase difference measurement for these extreme frequency signals, the phase difference measurement error of DTFT algorithm is analyzed, which indicates that the negative frequency contribution is the main cause of the bias. By considering the negative frequency contribution, a new phase difference measurement algorithm for extreme frequency signals is proposed based on DTFT, and the new formulas for phase difference calculation with different windows are derived in detail.

A novel time varying signal processing method for Coriolis mass flowmeter.

The precision of frequency tracking method and phase difference calculation method affects the measurement precision of Coriolis Mass Flowmeter directly. To improve the accuracy of the mass flowrate, a novel signal processing method for Coriolis Mass Flowmeter is proposed for this time varying signal, which is comprised of a modified adaptive lattice notch filter and a revised sliding recursive discrete-time Fourier transform algorithm. The method cannot only track the change of frequency continuously, but also ensure the calculation accuracy when measuring phase difference.