scholarly journals The Free-Swimming Device Leakage Detection in Plastic Water-filled Pipes through Tuning the Wavelet Transform to the Underwater Acoustic Signals

Water ◽  
2017 ◽  
Vol 9 (10) ◽  
pp. 731 ◽  
Author(s):  
Dileep Kumar ◽  
Dezhan Tu ◽  
Naifu Zhu ◽  
Reehan Shah ◽  
Dibo Hou ◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Acoustic Signals ◽  
Leakage Detection ◽  
Free Swimming ◽  
Underwater Acoustic

Denoising Underwater Acoustic Signals for Applications in Acoustical Oceanography

2017 ◽  
Vol 25 (02) ◽  
pp. 1750015 ◽  
Author(s):  
Michael Taroudakis ◽  
Costas Smaragdakis ◽  
N. Ross Chapman
Keyword(s):  
Wavelet Transform ◽  
Marine Environment ◽  
Acoustic Signals ◽  
Significant Part ◽  
Statistical Features ◽  
Underwater Acoustic ◽  
Signal Energy ◽  
Reliable Estimation ◽  
Signal Characterization ◽  
True Signal

A method for denoising underwater acoustic signals used in applications of acoustical oceanography is presented. The method has been introduced for imaging denoising and has been modified to be applied with acoustic signals. The method keeps the energy significant part of the raw signal and reduces the effects of noise by comparing overlapping signal windows and keeping components which resemble true signal energy. It is shown by means of characteristic experiments in connection with a statistical signal characterization scheme based on wavelet transform, that using the statistical features of the wavelet sub-band coefficients of the denoised signal, tomography or geoacoustic inversions lead to a reliable estimation of the parameters of a marine environment.

scholarly journals Locating Ships Using Time Reversal and Matrix Pencil Method by Their Underwater Acoustic Signals

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5065
Author(s):  
Daniel Chaparro-Arce ◽  
Sergio Gutierrez ◽  
Andres Gallego ◽  
Cesar Pedraza ◽  
Felix Vega ◽  
...  
Keyword(s):  
Time Reversal ◽  
Communication Channel ◽  
Matrix Pencil ◽  
Acoustic Signals ◽  
Underwater Acoustic ◽  
Low Bit Rate ◽  
Matrix Pencil Method ◽  
The Matrix ◽  
Resonance Expansion ◽  
Passive Sensors

This paper presents a technique, based on the matrix pencil method (MPM), for the compression of underwater acoustic signals produced by boat engines. The compressed signal, represented by its complex resonance expansion, is intended to be sent over a low-bit-rate wireless communication channel. We demonstrate that the method can provide data compression greater than 60%, ensuring a correlation greater than 93% between the reconstructed and the original signal, at a sampling frequency of 2.2 kHz. Once the signal was reconstituted, a localization process was carried out with the time reversal method (TR) using information from four different sensors in a simulation environment. This process sought to achieve the identification of the position of the ship using only passive sensors, considering two different sensor arrangements.

scholarly journals Underwater acoustic signals induced by intense ultrashort laser pulse

2015 ◽  
Vol 137 (4) ◽  
pp. EL288-EL292 ◽  
Author(s):  
Yohann Brelet ◽  
Amélie Jarnac ◽  
Jérôme Carbonnel ◽  
Yves-Bernard André ◽  
André Mysyrowicz ◽  
...  
Keyword(s):  
Laser Pulse ◽  
Ultrashort Laser Pulse ◽  
Acoustic Signals ◽  
Underwater Acoustic ◽  
Ultrashort Laser

scholarly journals Leakage Detection in Pipeline using Wavelet Transform Method

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Mohd Fairusham Ghazali ◽  
Abdul Kadir Samta
Keyword(s):  
Signal Processing ◽  
Wavelet Transform ◽  
Correlation Analysis ◽  
Pipeline System ◽  
Leakage Detection ◽  
Transient Method ◽  
Research Project ◽  
Transform Method ◽  
Cepstrum Analysis ◽  
Transient Methods

This research project is focusing on the leakage detection in the pipelines using wavelet and cepstrum analysis. To fully complete this research project, experimental and analysis by using signal processing are required. This research project proposed a technique which is a transient method. The basic principle is the fact that water spouting out of a leak in a pressurized pipe generates a signal, and this signal contains information to whether a leak exists and where it is located. The present transient methods for finding leaks are mainly based upon correlation analysis, where one sensing device is installed at each side of a leak. This method is hard to operate because it needs many operators to operate it due to equipment in different place. This research project proposed a wavelet transform method to detect leakage in the pipeline system. The experimental results show appears  to improve the ability of the method to identify features in the signal.

Line Spectrum Enhancement of Underwater Acoustic Signals Using Kalman Filter

2020 ◽  
Vol 19 (1) ◽  
pp. 148-154
Author(s):  
Jiao Zhang ◽  
Yaan Li ◽  
Wasiq Ali ◽  
Lian Liu
Keyword(s):  
Kalman Filter ◽  
Acoustic Signals ◽  
Line Spectrum ◽  
Underwater Acoustic

scholarly journals A Sensing and Tracking Algorithm for Multiple Frequency Line Components in Underwater Acoustic Signals

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4866 ◽  
Author(s):  
Xinwei Luo ◽  
Zihan Shen
Keyword(s):  
Signal To Noise Ratio ◽  
Acoustic Signals ◽  
Multiple Time ◽  
Time Varying ◽  
Multiple Frequency ◽  
Underwater Acoustic ◽  
Model Method ◽  
Detection And Tracking ◽  
Time Varying Frequency ◽  
Line Tracking

Reliable and efficient sensing and tracking of multiple weak or time-varying frequency line components in underwater acoustic signals is the topic of this paper. We propose a method for automatic detection and tracking of multiple frequency lines in lofargram based on hidden Markov model (HMM). Instead of being directly subjected to frequency line tracking, the whole lofargram is first segmented into several sub-lofargrams. Then, the sub-lofargrams suspected to contain frequency lines are screened. In these sub-lofargrams, the HMM-based method is used for detection of multiple frequency lines. Using image stitching and statistical model method, the frequency lines with overlapping parts detected by different sub-lofargrams are merged to obtain the final detection results. The method can effectively detect multiple time-varying frequency lines of underwater acoustic signals while ensuring the performance under the condition of low signal-to-noise ratio (SNR). It can be concluded that the proposed algorithm can provide better multiple frequency lines sensing ability while greatly reducing the amount of calculations and providing potential techniques for feature sensing and tracking processing of unattended equipment such as sonar buoys and submerged buoys.

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