Denoising low SNR percussion acoustic signal in the marine environment based on the LMS algorithm

Yang, Zhuodong; Huo, Linsheng; Wang, Jingkai; Zhou, Jing

doi:10.1016/j.measurement.2022.111848

Cited by 11 publications

(8 citation statements)

References 41 publications

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“…The next research needs to use acoustic technology to overcome the limitations of the underwater environment and achieve real-time monitoring of underwater oil spills. Further exploring the potential of acoustic technology in the field of marine detection is of great significance for the development of emergency response to marine oil spills [100].…”

Section: Discussionmentioning

confidence: 99%

Underwater Acoustic Technology-Based Monitoring of Oil Spill: A Review

Pan

Tang

Jiang

et al. 2023

JMSE

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Acoustic monitoring is an efficient technique for oil spill detection, and the development of acoustic technology is conducive to achieving real-time monitoring of underwater oil spills, providing data references and guidance for emergency response work. Starting from the research background of oil spills, this review summarizes and evaluates the existing research on acoustic technology for monitoring underwater oil spills. Underwater oil spills are more complex than surface oil spills, and further research is needed to investigate the feasibility of acoustic technology in underwater oil spill monitoring, verify the accuracy of monitoring data, and assess its value. In the future, the impact mechanism and dynamic research of acoustic technology in oil spill monitoring should be explored, and the advantages and differences between acoustic technology and other detection techniques should be compared. The significance of auxiliary mechanisms combined with acoustic technology in oil spill monitoring should be studied. Moreover, acoustic research methods and experimental techniques should be enriched and improved to fully tap into the future value of acoustic technology.

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Section: Discussionmentioning

confidence: 99%

Underwater Acoustic Technology-Based Monitoring of Oil Spill: A Review

Pan

Tang

Jiang

et al. 2023

JMSE

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“…It is a simple procedure for recursively adapting the filter coefficients after the arrival of each new input sample x(n) and its corresponding desired output sample d(n). Equations ( 3), ( 4) and (11) specify, in sequence, the three steps required to accomplish each iteration of the LMS algorithm. Equation ( 3) is known for filtering to obtain the filter output.…”

Section: Lms Adaptive Signal Processing Methods and Improvementsmentioning

confidence: 99%

“…A variety of studies on the LMS algorithm have appeared after years of development, and have continuously improved the effect of adaptive linear enhancement [11,12]. The LMS algorithm has advantages of low computational complexity, good convergence in environments with smooth signals, and good stability when the algorithms are implemented using finite step size; therefor, the LMS algorithm provides the best stability and has the most widespread application among adaptive algorithms [13,14].…”

Section: Introductionmentioning

confidence: 99%

Design and Algorithm Integration of High-Precision Adaptive Underwater Detection System Based on MEMS Vector Hydrophone

Liu,

Jing,

Zhang

et al. 2024

Micromachines

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Real-time DOA (direction of arrival) estimation of surface or underwater targets is of great significance to the research of marine environment and national security protection. When conducting real-time DOA estimation of underwater targets, it can be difficult to extract the prior characteristics of noise due to the complexity and variability of the marine environment. Therefore, the accuracy of target orientation in the absence of a known noise is significantly reduced, thereby presenting an additional challenge for the DOA estimation of the marine targets in real-time. Aiming at the problem of real-time DOA estimation of acoustic targets in complex environments, this paper applies the MEMS vector hydrophone with a small size and high sensitivity to sense the conditions of the ocean environment and change the structural parameters in the adaptive adjustments system itself to obtain the desired target signal, proposes a signal processing method when the prior characteristics of noise are unknown. Theoretical analysis and experimental verification show that the method can achieve accurate real-time DOA estimation of the target, achieve an error within 3.1° under the SNR (signal-to-noise ratio) of the X channel of −17 dB, and maintain a stable value when the SNR continues to decrease. The results show that this method has a very broad application prospect in the field of ocean monitoring.

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“…In addition, researchers also detected looseness of cuplock scaffolds [25] bolt looseness [26], wood moisture levels, internal cavities of timber columns [27,28], concrete humidity, among others through the processing and analysis of the impact acoustic signals [29]. These studies have demonstrated the utility of the percussion detection method.…”

Section: Introductionmentioning

confidence: 98%

A pipeline corrosion detecting method using percussion and residual neural network

Yang,

Ji,

Wang

et al. 2024

Meas. Sci. Technol.

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Corrosion of pipeline walls can lead to serious safety accidents such as leaks, fires and even explosions. This paper proposes a corrosion detection method using deep learning based on percussion sound for pipelines. The percussion induced acoustic signals are processed by wavelet threshold noise reduction and double threshold endpoint detection to generate the Mel spectrograms, and then an 18-layer Residual Network (ResNet18) is used to mine the depth information and classify the degree of pipeline corrosion. We conducted experiments to verify the validity of the approach. Seven working conditions are generated by electrochemical corrosion of a pipe specimen, and percussions are applied at five different positions under the same working conditions to collect the impact acoustic signals. The test results show that the method can quickly, efficiently and accurately detect the degree of pipeline corrosion, classify the degree of pipe corrosion without being affected by the striking position Therefore, the model has great potential for application in detecting the internal corrosion of pipelines based on percussion sounds.

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Denoising low SNR percussion acoustic signal in the marine environment based on the LMS algorithm

Cited by 11 publications

References 41 publications

Underwater Acoustic Technology-Based Monitoring of Oil Spill: A Review

Underwater Acoustic Technology-Based Monitoring of Oil Spill: A Review

Design and Algorithm Integration of High-Precision Adaptive Underwater Detection System Based on MEMS Vector Hydrophone

A pipeline corrosion detecting method using percussion and residual neural network

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