scholarly journals Noisy Reverberation Suppression Using AdaBoost Based EMD in Underwater Scenario

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Kusma Kumari Cheepurupalli ◽  
Raja Rajeswari Konduri
Keyword(s):  
Signal Processing ◽  
Acoustic Signal ◽  
Probability Of Detection ◽  
Chirp Signal ◽  
Processing Scheme ◽  
Adaptive Boosting ◽  
Mode Decomposition ◽  
Crucial Problem ◽  
Filtering Technique ◽  
Simulation Results

Reverberation suppression is a crucial problem in sonar communications. If the acoustic signal is radiated in the water as medium then the degradation is caused due to the reflection coming from surface, bottom, and volume of water. This paper presents a novel signal processing scheme that offers an improved solution in reducing the effect of interference caused due to reverberation. It is based on the combination of empirical mode decomposition (EMD) and adaptive boosting (AdaBoost) techniques. AdaBoost based EMD filtering technique is used for reverberation corrupted chirp signal to decrease the noisy components present in the received signal. An improvement in the probability of detection is achieved using the proposed algorithm. The simulation results are obtained for various reverberation times at various SNR levels.

scholarly journals A Novel Approach for Acoustic Signal Processing of a Drum Shearer Based on Improved Variational Mode Decomposition and Cluster Analysis

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2949
Author(s):  
Changpeng Li ◽  
Tianhao Peng ◽  
Yanmin Zhu
Keyword(s):  
Signal Processing ◽  
Acoustic Signal ◽  
Clustering Algorithm ◽  
Pso Algorithm ◽  
Variational Mode Decomposition ◽  
Novel Approach ◽  
Mode Decomposition ◽  
Drum Shearer ◽  
Best Parameter ◽  
And Cluster Analysis

During operation, the acoustic signal of the drum shearer contains a wealth of information. The monitoring or diagnosis system based on acoustic signal has obvious advantages. However, the signal is challenging to extract and recognize. Therefore, this paper proposes an approach for acoustic signal processing of a shearer based on the parameter optimized variational mode decomposition (VMD) method and a clustering algorithm. First, the particle swarm optimization (PSO) algorithm searched for the best parameter combination of the VMD. According to the results, the approach determined the number of modes and penalty parameters for VMD. Then the improved VMD algorithm decomposed the acoustic signal. It selected the ideal component through the minimum envelope entropy. The PSO was designed to optimize the clustering analysis, and the minimum envelope entropy of the acoustic signal was regarded as the feature for classification. We then use a shearer simulation platform to collect the acoustic signal and use the approach proposed in this paper to process and classify the signal. The experimental results show that the approach proposed can effectively extract the features of the acoustic signal of the shearer. The recognition accuracy of the acoustic signal was high, which has practical application value.

scholarly journals Application of UAV in Search and Rescue Actions in Underground Mine—A Specific Sound Detection in Noisy Acoustic Signal

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3725
Author(s):  
Paweł Zimroz ◽  
Paweł Trybała ◽  
Adam Wróblewski ◽  
Mateusz Góralczyk ◽  
Jarosław Szrek ◽  
...  
Keyword(s):  
Signal Processing ◽  
Acoustic Signal ◽  
Processing Technique ◽  
Underground Mine ◽  
Search And Rescue ◽  
Reference Spectrum ◽  
Signal Processing Technique ◽  
Time Frequency ◽  
Communication Device ◽  
Frequency Representation

The possibility of the application of an unmanned aerial vehicle (UAV) in search and rescue activities in a deep underground mine has been investigated. In the presented case study, a UAV is searching for a lost or injured human who is able to call for help but is not able to move or use any communication device. A UAV capturing acoustic data while flying through underground corridors is used. The acoustic signal is very noisy since during the flight the UAV contributes high-energetic emission. The main goal of the paper is to present an automatic signal processing procedure for detection of a specific sound (supposed to contain voice activity) in presence of heavy, time-varying noise from UAV. The proposed acoustic signal processing technique is based on time-frequency representation and Euclidean distance measurement between reference spectrum (UAV noise only) and captured data. As both the UAV and “injured” person were equipped with synchronized microphones during the experiment, validation has been performed. Two experiments carried out in lab conditions, as well as one in an underground mine, provided very satisfactory results.

scholarly journals A Generalized Method for Flat Plates Impact Detection and Location

2013 ◽  
Vol 543 ◽  
pp. 171-175
Author(s):  
Jose Andrés Somolinos ◽  
Rafael Morales ◽  
Carlos Morón ◽  
Alfonso Garcia
Keyword(s):  
Signal Processing ◽  
Flat Plate ◽  
Acoustic Signal ◽  
Experimental Results ◽  
Piezoelectric Sensors ◽  
Experimental Setup ◽  
Flat Plates ◽  
Impact Detection ◽  
Timing Difference

In the last years, many analyses from acoustic signal processing have been used for different applications. In most cases, these sensor systems are based on the determination of times of flight for signals from every transducer. This paper presents a flat plate generalization method for impact detection and location over linear links or bars-based structures. The use of three piezoelectric sensors allow to achieve the position and impact time while the use of additional sensors lets cover a larger area of detection and avoid wrong timing difference measurements. An experimental setup and some experimental results are briefly presented.

Low coherence, interferometric fibre optic vibrometer using novel optical signal processing scheme

1991 ◽  
Vol 27 (18) ◽  
pp. 1658 ◽  
Author(s):  
K. Weir ◽  
W.J.O. Boyle ◽  
A.W. Palmer ◽  
K.T.V. Grattan ◽  
B.T. Meggitt
Keyword(s):  
Signal Processing ◽  
Optical Signal Processing ◽  
Optical Signal ◽  
Fibre Optic ◽  
Processing Scheme ◽  
Low Coherence
Sign in / Sign up

Export Citation Format

Share Document