Performance of short-time spectral parametric methods for reducing the variance of the Doppler ultrasound mean instantaneous frequency estimation

1999 ◽  
Vol 37 (3) ◽  
pp. 291-297 ◽  
Author(s):  
H. Sava ◽  
L. -G. Durand ◽  
G. Cloutier
Keyword(s):  
Doppler Ultrasound ◽  
Instantaneous Frequency ◽  
Frequency Estimation ◽  
Parametric Methods ◽  
Instantaneous Frequency Estimation ◽  
Short Time

Doppler Shift Removal Based on Instantaneous Frequency Estimation for Wayside Fault Diagnosis of Train Bearings

2014 ◽  
Vol 136 (2) ◽  
Author(s):  
Ao Zhang ◽  
Fei Hu ◽  
Qingbo He ◽  
Changqing Shen ◽  
Fang Liu ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Acoustic Signal ◽  
Instantaneous Frequency ◽  
Doppler Shift ◽  
High Speed ◽  
Frequency Estimation ◽  
Acoustic Signals ◽  
Instantaneous Frequency Estimation ◽  
Comparison Results ◽  
Short Time

The phenomenon of Doppler shift in the acoustic signal acquired by a microphone amounted beside the railway leads to the difficulty for fault diagnosis of train bearings with a high moving speed. To enhance the condition monitoring performance of the bearings on a passing train using stationary microphones, the elimination of the Doppler shift should be implemented firstly to correct the severe frequency-domain distortion of the acoustic signal recorded in these conditions. In this paper, a Doppler shift removal method is proposed based on instantaneous frequency (IF) estimation (IFE) for analyzing acoustic signals from train bearings with a high speed. Specifically, the IFE based on short-time Fourier transform is firstly applied to attain the IF vector. According to the acoustic theory of Morse, the data fitting is then carried out to achieve the fitting IFs with which the resampling sequence can be established as the resampling vector in time domain. The resampled signal can be finally reconstructed to realize fault diagnosis of train bearings. To demonstrate the effectiveness of this method, two simulations and an experiment with practical acoustic signals of train bearings with a crack on the outer raceway and the inner raceway have been carried out, and the comparison results have been presented in this paper.

scholarly journals Widely Linear Adaptive Instantaneous Frequency Estimation in Vector Hydrophones

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3348 ◽  
Author(s):  
Panpan Peng ◽  
Liang An
Keyword(s):  
Instantaneous Frequency ◽  
Frequency Estimation ◽  
Linear Method ◽  
Estimation Method ◽  
Frequency Resolution ◽  
Linear Filter ◽  
Instantaneous Frequency Estimation ◽  
Time Frequency ◽  
Short Time ◽  
Widely Linear

To solve the problem that the time-frequency resolution of Short-Time Fourier Transform (STFT) is constrained by the window length and the moving step of the short time window, and to utilize the merits of a widely linear method, a novel instantaneous frequency estimation method in vector hydrophone was proposed. In this paper, a complex variable was constructed. It is composed of sound pressure and particle velocity as its real part and imaginary part, respectively. The constructed variable was approved to be second order noncircular (improper). For the modelling of noncircular signals, the standard linear estimation is not adequate and the pseudo-covariance matrix should also be taken into consideration. As a result, a widely linear adaptive instantaneous frequency estimation algorithm and its three solutions based on the augmented complex least mean square (ACLMS) method are presented to estimate the instantaneous frequency in vector hydrophones. The results of simulations and laboratory experiments prove that this approach based on a widely linear model performs better compared to STFT and strict linear filter methods.

scholarly journals Analysis of adaptive short-time Fourier transform-based synchrosqueezing transform

2020 ◽  
Vol 19 (01) ◽  
pp. 71-105 ◽  
Author(s):  
Haiyan Cai ◽  
Qingtang Jiang ◽  
Lin Li ◽  
Bruce W. Suter
Keyword(s):  
Fourier Transform ◽  
Theoretical Analysis ◽  
Instantaneous Frequency ◽  
Frequency Estimation ◽  
Short Time Fourier Transform ◽  
Instantaneous Frequency Estimation ◽  
Time Frequency ◽  
Synchrosqueezing Transform ◽  
Non Stationary Signal ◽  
Short Time

Recently, the study of modeling a non-stationary signal as a superposition of amplitude and frequency-modulated Fourier-like oscillatory modes has been a very active research area. The synchrosqueezing transform (SST) is a powerful method for instantaneous frequency estimation and component separation of non-stationary multicomponent signals. The short-time Fourier transform-based SST (FSST) reassigns the frequency variable to sharpen the time-frequency representation and to separate the components of a multicomponent non-stationary signal. Very recently the FSST with a time-varying parameter, called the adaptive FSST, was introduced. The simulation experiments show that the adaptive FSST is very promising in instantaneous frequency estimation of the component of a multicomponent signal, and in accurate component recovery. However, the theoretical analysis of the adaptive FSST has not been carried out. In this paper, we study the theoretical analysis of the adaptive FSST and obtain the error bounds for the instantaneous frequency estimation and component recovery with the adaptive FSST and the second-order adaptive FSST.

scholarly journals RANSAC algorithm for instantaneous frequency estimation and reconstruction of frequency-modulated undersampled signals

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Igor Djurović
Keyword(s):  
Instantaneous Frequency ◽  
Matching Pursuit ◽  
Frequency Estimation ◽  
Consensus Algorithm ◽  
Multidimensional Space ◽  
Instantaneous Frequency Estimation ◽  
Time Frequency ◽  
Polynomial Phase ◽  
Fm Signals ◽  
Fifth Order

AbstractFrequency modulated (FM) signals sampled below the Nyquist rate or with missing samples (nowadays part of wider compressive sensing (CS) framework) are considered. Recently proposed matching pursuit and greedy techniques are inefficient for signals with several phase parameters since they require a search over multidimensional space. An alternative is proposed here based on the random samples consensus algorithm (RANSAC) applied to the instantaneous frequency (IF) estimates obtained from the time-frequency (TF) representation of recordings (undersampled or signal with missing samples). The O’Shea refinement strategy is employed to refine results. The proposed technique is tested against third- and fifth-order polynomial phase signals (PPS) and also for signals corrupted by noise.

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