Noisy Reverberation Suppression Using AdaBoost Based EMD in Underwater Scenario

Cheepurupalli, Kusma Kumari; Konduri, Raja Rajeswari

doi:10.1155/2014/563780

Cited by 4 publications

(2 citation statements)

References 11 publications

(11 reference statements)

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“…EMD decomposes a complex signal into a finite of Advances in Mechanical Engineering 3 single component signal called IMF under characteristic time scale [17][18][19]. These IMFs could represent the temporal mode present in the data.…”

Section: Emd Methodmentioning

confidence: 99%

An Improved Method Based on CEEMD for Fault Diagnosis of Rolling Bearing

Wang

Tang

et al. 2014

Advances in Mechanical Engineering

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In order to improve the effectiveness for identifying rolling bearing faults at an early stage, the present paper proposed a method that combined the so-called complementary ensemble empirical mode decomposition (CEEMD) method with a correlation theory for fault diagnosis of rolling element bearing. The cross-correlation coefficient between the original signal and each intrinsic mode function (IMF) was calculated in order to reduce noise and select an effective IMF. Using the present method, a rolling bearing fault experiment with vibration signals measured by acceleration sensors was carried out, and bearing inner race and outer race defect at a varying rotating speed with different degrees of defect were analyzed. And the proposed method was compared with several algorithms of empirical mode decomposition (EMD) to verify its effectiveness. Experimental results showed that the proposed method was available for detecting the bearing faults and able to detect the fault at an early stage. It has higher computational efficiency and is capable of overcoming modal mixing and aliasing. Therefore, the proposed method is more suitable for rolling bearing diagnosis.

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Section: Emd Methodmentioning

confidence: 99%

An Improved Method Based on CEEMD for Fault Diagnosis of Rolling Bearing

Wang

Tang

et al. 2014

Advances in Mechanical Engineering

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“…In the case of reverberation, some methods are used to enhance SRR. Cheepurupalli and Konduri combined empirical mode decomposition (EMD) with adaptive boosting (AdaBoost), which is a learning algorithm, to process the echo signal in reverberation environment [2]. And as a result of AdaBoost, the accuracy and robustness of targets detection method are improved significantly.…”

Section: Introductionmentioning

confidence: 99%

Multiple Moving Targets Detection and Parameters Estimation in Strong Reverberation Environments

Piao

2016

Shock and Vibration

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This paper considers the problem of multiple moving targets detection and parameters estimation (direction of arrival and range) in strong reverberation environments. As reverberation has a strong correlation with target echo, the performance of target detection and parameters estimation is significantly degraded in practical underwater environments. In this paper, we utilize two uniform circular arrays to receive plane wave of the linear frequency modulation signal reflected from far-field targets. On the basis of received signal, we build a variance matrix of multiple beams by using modal decomposition, conventional beamforming, and fractional Fourier transform (FrFT). We then propose a novel detection method and an estimation method of parameters based on the constructed image. A significant feature of the proposed methods is that our design does not involve any a priori knowledge about targets number and parameters of marine environments. Finally, we demonstrate via numerical simulation examples that the detection probability and the accuracy of estimated parameters of the proposed method are higher than the existing methods in both low signal-to-reverberation ratio and signal-to-noise ratio environment.

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Underwater broadband source detection using an Acoustic Vector Sensor with an adaptive passive matched filter

Gulliver

Zhao

et al. 2019

Applied Acoustics

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Noisy Reverberation Suppression Using AdaBoost Based EMD in Underwater Scenario

Cited by 4 publications

References 11 publications

An Improved Method Based on CEEMD for Fault Diagnosis of Rolling Bearing

An Improved Method Based on CEEMD for Fault Diagnosis of Rolling Bearing

Multiple Moving Targets Detection and Parameters Estimation in Strong Reverberation Environments

Underwater broadband source detection using an Acoustic Vector Sensor with an adaptive passive matched filter

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