Decomposition of Time-varying Multicomponent Signals using Time-Frequency Based Method

A new signal processing method for phase difference estimation was proposed based on time-varying signal model, whose frequency, amplitude and phase are time-varying. And then be applied Coriolis mass flowmeter signal. First, a bandpass filtering FIR filter was applied to filter the sensor output signal in order to improve SNR. Then, the signal frequency could be calculated based on short-time frequency estimation. Finally, by short window intercepting, the DTFT algorithm with negative frequency contribution was introduced to calculate the real-time phase difference between two enhanced signals. With the frequency and the phase difference obtained, the time interval of two signals was calculated. Simulation results show that the algorithms studied are efficient. Furthermore, the computation of algorithms studied is simple so that it can be applied to real-time signal processing for Coriolis mass flowmeter.

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An IF Estimator for Multicomponent Signals from Time Frequency Distribution

2017 10th International Conference on Intelligent Computation Technology and Automation (ICICTA) ◽

10.1109/icicta.2017.63 ◽

2017 ◽

Author(s):

Li Po

Keyword(s):

Frequency Distribution ◽

Time Frequency ◽

Multicomponent Signals ◽

Time Frequency Distribution

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Time-Frequency Processing of Time-Varying Signals with Nonlinear Group Delay

Wavelets and Signal Processing ◽

10.1007/978-1-4612-0025-3_10 ◽

2003 ◽

pp. 311-359 ◽

Cited By ~ 1

Author(s):

Antonia Papandreou-Suppappola

Keyword(s):

Group Delay ◽

Time Varying ◽

Time Frequency ◽

Frequency Processing

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Wavelet multi-resolution approximation of time-varying frame structure

Advances in Mechanical Engineering ◽

10.1177/1687814018795596 ◽

2018 ◽

Vol 10 (8) ◽

pp. 168781401879559 ◽

Cited By ~ 2

Author(s):

Min Xiang ◽

Feng Xiong ◽

Yuanfeng Shi ◽

Kaoshan Dai ◽

Zhibin Ding

Keyword(s):

Parameter Estimation ◽

Degrees Of Freedom ◽

Structural Parameters ◽

Identification Problem ◽

Frame Structure ◽

Structural Parameter ◽

Time Varying ◽

Engineering Structures ◽

Time Frequency ◽

Non Parametric

Engineering structures usually exhibit time-varying behavior when subjected to strong excitation or due to material deterioration. This behavior is one of the key properties affecting the structural performance. Hence, reasonable description and timely tracking of time-varying characteristics of engineering structures are necessary for their safety assessment and life-cycle management. Due to its powerful ability of approximating functions in the time–frequency domain, wavelet multi-resolution approximation has been widely applied in the field of parameter estimation. Considering that the damage levels of beams and columns are usually different, identification of time-varying structural parameters of frame structure under seismic excitation using wavelet multi-resolution approximation is studied in this article. A time-varying dynamical model including both the translational and rotational degrees of freedom is established so as to estimate the stiffness coefficients of beams and columns separately. By decomposing each time-varying structural parameter using one wavelet multi-resolution approximation, the time-varying parametric identification problem is transformed into a time-invariant non-parametric one. In solving the high number of regressors in the non-parametric regression program, the modified orthogonal forward regression algorithm is proposed for significant term selection and parameter estimation. This work is demonstrated through numerical examples which consider both gradual variation and abrupt changes in the structural parameters.

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A generalized demodulation approach to time-frequency projections for multicomponent signals

Proceedings of The Royal Society A Mathematical Physical and Engineering Sciences ◽

10.1098/rspa.2005.1455 ◽

2005 ◽

Vol 461 (2059) ◽

pp. 2159-2179 ◽

Cited By ~ 72

Author(s):

S Olhede ◽

A.T Walden

Keyword(s):

Instantaneous Frequency ◽

Additive Noise ◽

Simulation Experiment ◽

Wavelet Packet ◽

Covariance Structure ◽

Time Instant ◽

Analytic Signal ◽

Flexible Approach ◽

Time Frequency ◽

Multicomponent Signals

In this paper, we introduce a flexible approach for the time-frequency analysis of multicomponent signals involving the use of analytic vectors and demodulation. The demodulated analytic signal is projected onto the time-frequency plane so that, as closely as possible, each component contributes exclusively to a different ‘tile’ in a wavelet packet tiling of the time-frequency plane, and at each time instant, the contribution to each tile definitely comes from no more than one component. A single reverse demodulation is then applied to all projected components. The resulting instantaneous frequency of each component in each tile is not constrained to a set polynomial form in time, and is readily calculated, as is the corresponding Hilbert energy spectrum. Two examples illustrate the method. In order better to understand the effect of additive noise, the approximate variance of the estimated instantaneous frequency in any tile has been formulated by starting with pure noise and studying its evolving covariance structure through each step of the algorithm. The validity and practical utility of the resulting expression for the variance of the estimated instantaneous frequency is demonstrated via a simulation experiment.

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