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Improved signal de-noising in underwater acoustic noise using S-transform: A performance evaluation and comparison with the wavelet transform

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Journal of Ocean Engineering and Science 2017年第3期2卷 172-185页

作者： Yasin Yousif Al-Aboosi Ahmad Zuri Sha’ameri Faculty of Electrical Engineering Universiti Teknologi MalaysiaSkudai 81300JohorMalaysia Faculty of Engineering University of MustansiriyahBaghdadIraq

Sound waves propagate well underwater making it useful for target locating and *** acoustic noise(UWAN)affects the reliability in applications where the noise comes from multiple *** this paper,a novel signal de-noising technique is proposed using *** the time-frequency representation,de-noising is performed using soft thresholding with universal threshold estimation which is then *** UWAN used for the validation is sea truth data collected at desaru beach on the eastern shore of Johor in Malaysia with the use of broadband *** comparison is made with the more conventionally used wavelet transform de-noising *** types of signals are evaluated:fixed frequency signals and time-varying *** results demonstrate that the proposed method shows better signal to noise ratio(SNR)by 4 dB and lower root mean square error(RMSE)by 3 dB achieved at the Nyquist sampling frequency compared to the previously proposed de-noising method like wavelet transform.

关键词： Underwater acoustic noise Time-frequency analysis Wavelet transforms S-transforms signal de-noising

Application and Simulation of Wavelet Packet Transform in Underwater Acoustic signal de-noising

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Application and Simulation of Wavelet Packet Transform in Un...

2012年计算机应用与系统建模国际会议

作者： Wu Chao Wang Juncheng Zheng Yi Wang Zhongqiu Ni Xiuhui Shandong University Of Science And Technology Shandong Academy of Sciences Institute of Oceanographic Instrumentation

In this paper, wavelet packet algorithm was used in the de-noising of underwater acoustic signal processing since wavelet packet algorithm is suitable for non-stationary signal processing. The principle of wavelet packet de-noising algorithm was described and the MSE of underwater acoustic was improved by means of wavelet packet de-noising greatly .The result of computer simulation by Matlab illustrates that de-noising algorithm is an effective signal preprocessing method.

关键词： signal de-noising wavelet wavelet packet Matlab

de-noising of radiation pressure signal generated by bubble oscillation based on ensemble empirical mode decomposition

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Journal of Hydrodynamics 2022年第5期34卷 849-863页

作者： Xiang-hao Zheng Yu-ning Zhang Key Laboratory of Power Station Energy Transfer Conversion and System(Ministry of Education) School of EnergyPower and Mechanical EngineeringNorth China Electric Power UniversityBeijing102206China

The radiation pressure signals generated by the bubble oscillation are often utilized to recognize the characteristics of the target objects in many ***,these signals are easily contaminated by complex background *** order to accurately extract the effective components of the radiation pressure signal generated by the bubble oscillation,this paper proposes a de-noising procedure for the radiation pressure signal,based on the ensemble empirical mode decomposition(EEMD),the autocorrelation function and the modified wavelet soft-threshold de-noising *** order to verify the effectiveness of the procedure,the typical radiation pressure signal generated based on the Keller-Miksis model under the acoustic excitation is employed for the subsequent de-noising *** results of the qualitative analysis show that the amplitude and the period of the bubble oscillation can be clearly observed in the time-domain diagram of the de-noised signal based on the *** the quantitative analysis,the de-noised signal based on the EEMD has better performance with higher signal-to-noise ratio(SNR),smaller root-mean-square error,and larger correlation coefficient than that based on the wavelet transform(WT)and the empirical mode decomposition(EMD).Furthermore,with the increase of the complexity of the radiation pressure signal(e.g.,the increase of the dimensionless pressure amplitude of the acoustic wave and the decrease of the SNR of the input signal),the above three evaluation indexes of the de-noised signal based on the EEMD are all better than those based on the other two *** the signal is more complex,the de-noising capabilities of the WT,the EMD are greatly reduced,but the EEMD can still maintain the good de-noising capability,which shows the superiority of the signal de-noising procedure proposed in the present paper.

关键词： Radiation pressure cavitation bubble oscillation signal de-noising ensemble empirical mode decomposition(EEMD) autocorrelation function wavelet soft-threshold de-noising

A NEW de-noising METHOD BASED ON 3-BAND WAVELET AND NONPARAMETRIC ADAPTIVE ESTIMATION

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Journal of Electronics(China) 2007年第3期24卷 358-362页

作者： Li Li Peng Yuhua Yang Mingqiang Xue Peijun School of Inform. Sci. and Eng. Shandong Univ. Jinan 250100 China School of Math. Shandong Univ. Jinan 250100 China

Wavelet de-noising has been well known as an important method of signal de-noising. Recently,most of the research efforts about wavelet de-noising focus on how to select the threshold,where Donoho method is applied widely. Compared with traditional 2-band wavelet,3-band wavelet has advantages in many aspects. According to this theory,an adaptive signal de-noising method in 3-band wavelet domain based on nonparametric adaptive estimation is proposed. The experimental results show that in 3-band wavelet domain,the proposed method represents better characteristics than Donoho method in protecting detail and improving the signal-to-noise ratio of reconstruction signal.

关键词： Nonparametric Adaptive estimation 3-band wavelet signal de-noising

Mechanical Fault Diagnosis and signal Feature Extraction Based on Fuzzy Neural Network

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Mechanical Fault Diagnosis and Signal Feature Extraction Bas...

第二十七届中国控制会议

作者： Jia Ruijuan,Xu Chunxia Hebei University of Engineering,Handan 056038,P.R.China

To improve the limitation of applying traditional fault diagnosis method to the diagnosis of multi-concurrent vibrant faults of aeroengine,a new diagnosis approach combining the wavelet transform with fuzzy theory is proposed.A novel method based on the statistic rule is brought forward to determine the threshold of each order of wavelet space and the decomposition level adaptively,increasing the *** effective eigenvectors are acquired by binary discrete wavelet transform and the fault modes are classified by fuzzy diagnosis equation based on correlation *** fault diagnosis model of aeroengine is established and the extended Kalman filter(EKF) algorithm is used to fulfill the network structure and the robustness of fault diagnosis equation is *** means of choosing enough samples to train the fault diagnosis equation and the information representing the faults is input into the trained diagnosis equation,and according to the output result the type of fault can be *** applications show that the proposed method can effectively diagnose multi-concurrent fault for aeroengine vibration and the diagnosis result is correct.

关键词： Wavelet transform Fuzzy theory Fault diagnosis signal de-noising Aeroengine

Multi-Concurrent Fault Diagnosis Approach for Aeroengine Based on Wavelet Fuzzy Network

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Multi-Concurrent Fault Diagnosis Approach for Aeroengine Bas...

2009中国控制与决策会议

作者： Dungen Chen School of Automation Science and Electrical Engineering Beijing University of Aeronautics and Astronautics Beijing,100083,China Guangbin Ding School of Water Conservancy and Electric Power Hebei University of Engineering Handan,056021,China

＜正＞To improve the limitation of applying traditional fault diagnosis method to the diagnosis of multi-concurrent vibrant faults of aeroengine,a new diagnosis approach combining the wavelet transform with fuzzy theory is proposed. A novel method based on the statistic rule is brought forward to determine the threshold of each order of wavelet space and the decomposition level adaptively,increasing the signal-noise-ratio （SNR）.The effective eigenvectors are acquired by binary discrete wavelet transform and the fault modes are classified by fuzzy diagnosis equation based on correlation *** fault diagnosis model of aeroengine is established and the extended Kalman filter（EKF） algorithm is used to fulfill the network structure and the robustness of fault diagnosis equation is *** means of choosing enough samples to train the fault diagnosis equation and the information representing the faults is input into the trained diagnosis equation,and according to the output result the type of fault can be *** applications show that the proposed method can effectively diagnose multi-concurrent fault for aeroengine vibration and the diagnosis result is correct.

关键词： Wavelet transform fuzzy theory fault diagnosis signal de-noising aeroengine

Feature Extraction Method in Fault Diagnosis Based on Wavelet Fuzzy Network for Power System Rotating Machinery

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Feature Extraction Method in Fault Diagnosis Based on Wavele...

第二十六届中国控制会议

作者： Kang Shanlin,Pang Peilin,Fan Feng,Ding Guangbin Hebei University of Engineering,Handan 056038,P.R.China

A new combined fault diagnosis approach for turbo-generator set based on wavelet fuzzy network is *** wavelet transform is used to extract fault characteristics and neural network is used to diagnose the *** improve the performance of applying traditional fault diagnosis method to the vibrant faults,a novel method based on the statistic rule is brought forward to determine the threshold of each order of wavelet space and the decomposition level adaptively,increasing the signal-noise-ratio（SNR）.The fault modes are classified by fuzzy diagnosis equation based on correlation matrix which shows good ability of self-adaption and *** improved least squares algorithm（LSA）is used to fulfill the net-work structure and the robustness of fault diagnosis equation is *** means of choosing enough samples to train the fault diagnosis equation and the information representing the faults is input into the trained diagnosis equation,and according to the output result the type of fault can be *** applications show that the proposed method can effectively di-agnose multi-concurrent fault for stator temperature fluctuation and rotor vibration and the diagnosis result is cor-rect,increasing the accuracy of the fault diagnosis for rotating machinery.

关键词： Wavelet transform fuzzy theory Fault diagnosis signal de-noising Turbo-generator set