A de-noising method using the improved wavelet threshold function based on noise variance estimation

Liu, Hui; Wang, Weida; Chen, Xiang; Han, Lijin; Nie, Haizhao

doi:10.1016/j.ymssp.2017.05.034

Cited by 63 publications

(32 citation statements)

References 16 publications

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“…e hard threshold method is simple to use, but the overall function is discontinuous, which will lead to additional vibration phenomenon of the reconstructed signal. Although the soft threshold method is continuous as a whole, the wavelet with a large amplitude will generate the attenuation phenomenon, which will cause a constant deviation of the processed signal [5,25]. Given the deficiencies of hard and soft threshold methods, this paper constructs a new threshold function based on the hard and soft threshold functions.…”

Section: Wavelet Reshold Denoising Methodmentioning

confidence: 99%

“…Basic contracting functions of this method include soft threshold function and hard threshold function, both of which have achieved good effect in signal denoising field, but they still have certain deficiencies in aspects of the continuity and approximation to the original signal. Due to complicated service environment and a low signal-to-noise ratio (SNR), denoising effect using wavelet is not ideal [5]. Huang et al [6] put forward a new signal processing method, namely, empirical mode decomposition (EMD) algorithm.…”

Section: Introductionmentioning

confidence: 99%

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An EEMD-Based Denoising Method for Seismic Signal of High Arch Dam Combining Wavelet with Singular Spectrum Analysis

Zhang

et al. 2019

Shock and Vibration

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Due to complicated noise interference, seismic signals of high arch dam are of nonstationarity and a low signal-to-noise ratio (SNR) during acquisition process. The traditional denoising method may have filtered effective seismic signals of high arch dams. A self-adaptive denoising method based on ensemble empirical mode decomposition (EEMD) combining wavelet threshold with singular spectrum analysis (SSA) is proposed in this paper. Based on the EEMD result for seismic signals of high arch dams, a continuous mean square error criterion is used to distinguish high-frequency and low-frequency components of the intrinsic mode functions (IMFs). Denoised high-frequency IMF using wavelet threshold is reconstructed with low-frequency components, and SSA is implemented for the reconstructed signal. Simulation signal denoising analysis indicates that the proposed method can significantly reduce mean square error under low SNR condition, and the overall denoising effect is superior to EEMD and EEMD-Wavelet threshold denoising algorithms. Denoising analysis of measured seismic signals of high arch dams shows that the performance of denoised seismic signals using EEMD-Wavelet-SSA is obviously improved, and natural frequencies of the high arch dams can be effectively identified.

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Section: Wavelet Reshold Denoising Methodmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An EEMD-Based Denoising Method for Seismic Signal of High Arch Dam Combining Wavelet with Singular Spectrum Analysis

Zhang

et al. 2019

Shock and Vibration

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“…Since a small DC-step signal is applied to the stator winding during the test, there is a large amount of noise in the recorded armature current responses, the de-nosing of the recorded response curves is necessary so that the error during the numerical fitting process can be reduced. A well-known wavelet threshold de-noising algorithm is adopted [22]. In this algorithm, an improved compromise for soft/hard thresholds method is used to overcome the drawbacks of the hard thresholds and soft thresholds.…”

Section: A Current Responses De-noisingmentioning

confidence: 99%

Standstill Time-Domain Response Parameter Estimation of the Large Synchronous Condenser in Arbitrary Rotor Position

Zhou

Wang

2020

IEEE Access

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The necessity to align the rotor with the d-q magnetic axes is the main obstacle for the wide application of synchronous machine standstill parameter tests, especially for the high-power units. This paper presents an arbitrary rotor position parameter estimation method for standstill time-domain response (SSTRs) tests and applied on a 300 MVar, 20 kV large synchronous condenser, a DC step voltage signal is selected as the input signal. Firstly, a frequency-domain Dalton-Cameron transformation is demonstrated and used to simultaneously obtain both axes' operational inductances in an arbitrary rotor position, thus eliminating the need for the rotor prepositioning process. Then, a novel analytical parameter estimation method combined with an I/T transformation is proposed, all the parameters of both axes are determined without extra tests, the mutual leakage flux between the field winding and the d-axis damper winding is also taken in account. To validate the proposed method, this test is carried out and its parameter estimation results are compared against that of the three-phase sudden short-circuit test and the traditional SSTR test. Estimation results are given in the form of I-type and T-type circuits, the maximum relative error no more than 6% and 10%, respectively. INDEX TERMS Parameter estimation, large synchronous condenser, standstill time-domain response, arbitrary rotor position NOMENCLATURE uabc stator three-phase voltage us stator input voltage iabc stator three-phase current ud, uq d-and q-axis voltage, respectively id, iq d-and q-axis current, respectively uf field winding voltage if, iD field and damper winding current, respectively iQ1, iQ2 q-axis damper winding 1, 2 current, respectively Ld, Lq d-and q-axis synchronous inductance, respectively Lad, Laq d-and q-axis armature reaction inductance, respectively Lsl stator leakage inductance Lfl, Ldl field and damper winding leakage inductance, respectively LQl1, LQl2 q-axis damper winding 1, 2 leakage inductance, respectively L d ' , L d '' d-axis transient and sub-transient inductance, respectively L q '' , L q ''' q-axis sub-transient and sub-subtransient inductance, respectively T d ' , T d '' d-axis transient and sub-transient shortcircuit time constant, respectively T d0 ' , T d0 '' d-axis transient and sub-transient opencircuit time constant, respectively T q '' , T q ''' q-axis sub-transient and sub-subtransient short-circuit time constant, respectively T q0 '' , T q0 ''' q-axis sub-transient and sub-subtransient open-circuit time constant, respectively Tf, TD field and damper winding leakage time constant, respectively ra, rs stator and armature resistance, respectively rf, rD field and damper winding resistance, respectively rQ1, rQ2 q-axis damper winding 1, 2 resistance, respectively  rotor position angle

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“…Each channel of the receiver uses a separate AD7767, a 24 bit high-resolution and wide dynamic-range converter. The AD7767 is a − ADC with oversampling characteristics, which can reduce noise from the front end and the need for a front-end anti-alias filter, and uses its daisy chain technology to realize the multi-chip cascade connection for an efficient parallel synchronous acquisition method (Liu et al, 2017). These two circuits are shown in Figs.…”

Section: Design Of Analog Circuit Boardmentioning

confidence: 99%

Interactive comment on “The development and test research of multi-channel Synchronous transient electromagnetic receiver”

Fan¹

2018

Preprint

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A de-noising method using the improved wavelet threshold function based on noise variance estimation

Cited by 63 publications

References 16 publications

An EEMD-Based Denoising Method for Seismic Signal of High Arch Dam Combining Wavelet with Singular Spectrum Analysis

An EEMD-Based Denoising Method for Seismic Signal of High Arch Dam Combining Wavelet with Singular Spectrum Analysis

Standstill Time-Domain Response Parameter Estimation of the Large Synchronous Condenser in Arbitrary Rotor Position

Interactive comment on “The development and test research of multi-channel Synchronous transient electromagnetic receiver”

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