Source localization of turboshaft engine broadband noise using a three-sensor coherence method

Blacodon, Daniel; Léwy, S.

doi:10.1016/j.jsv.2014.10.019

Cited by 8 publications

(4 citation statements)

References 12 publications

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“…e principle of calculation is to find a direction through system learning, so that W can obtain a weighted vector w i and map as y i � w T i x with the greatest Gaussianity. e formula taken by negative entropy is shown as (9), where G is an arbitrary quadratic function, y i is a random variable with zero mean and unit variance, and v is a Gauss random variable with zero mean and unit variance. Substituting y i � w T i x into the negative entropy approximation gives…”

Section: T)mentioning

confidence: 99%

“…e wavelet partial coherence analysis is also applied to identify the sources of acoustic signals for diesel locomotives [2]. Blacodon and Lewy [9] adopt the three-sensor coherence method to identify the acoustics source of the turboshaft engine. ese methods can identify the acoustics sources according to the coherence values calculated from the signals measured by multiple sensors.…”

Section: Introductionmentioning

confidence: 99%

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Acoustics Source Identification of Diesel Engines Based on Variational Mode Decomposition, Fast Independent Component Analysis, and Hilbert Transformation

Chen

Lin

Jin

et al. 2021

Shock and Vibration

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Diesel engines are widely used in railway systems, particularly in freight trains. Despite their high efficiency in energy conversion, they usually generate high levels of acoustics pollution during operation. In order to mitigate this problem, a series of active/passive acoustics control methods are used to reduce noise. Most of these methods are only effective if the prior knowledge of sources is given. In other words, it is essential to recognize the acoustics source. Variational mode decomposition (VMD) is a signal processing method that enhances the signal corrupted by background noise. However, the decomposed results of VMD depend on their mode parameter and penalty parameter. Therefore, an evaluation method based on system modal parameters (natural frequency and damping ratio) is proposed to select the mode parameter, and the penalty parameter can be selected from the power spectra of signals. In order to increase the accuracy of decomposition for diesel engines and find out the sources of acoustics, a method combining VMD, fast independent component analysis, and Hilbert transformation (VMD-FastICA-HT) is proposed for the separation and identification of different sources for diesel engines. The optimization results indicate that when the penalty parameter value is 1.5 to 16 times the maximum signal amplitude, better decomposition results can be achieved. Therefore, the separated independent acoustics are more accurate in source identification. Furthermore, both simulation data and in situ operational data of diesel engines for vehicles are used to validate the effectiveness of the proposed method.

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Section: T)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Acoustics Source Identification of Diesel Engines Based on Variational Mode Decomposition, Fast Independent Component Analysis, and Hilbert Transformation

Chen

Lin

Jin

et al. 2021

Shock and Vibration

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show abstract

“…The important efforts carried out during the last decades to reduce jet and fan noise in turbojet engines led to the emergence of additional noise sources, previously masked, among which combustion noise stands out [1,2]. Combustion noise issues are even more important for turboshaft engines where jet and fan noises are absent [3,4]. Two different mechanisms are involved in combustion noise.…”

Section: Introductionmentioning

confidence: 99%

Influence of viscosity on entropy noise generation through a nozzle

Huet

Emmanuelli

Ducruix

2021

Journal of Sound and Vibration

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“…e noise source identification methods based on modern signal processing technology are mainly included multichannel separation method and singlechannel separation method. For multichannel separation method, it mainly includes independent component analysis method [8,9], filtering method [10,11], wavelet transform and partial coherence analysis method [12], multiple regression analysis method [13][14][15][16], coherence method [17,18], binaural sound localization method [19], and so on. Multichannel method requires multiple channels of sensors.…”

Section: Introductionmentioning

confidence: 99%

Research on Experimental Method for Obtaining Independent Combustion Noise of Internal Combustion Engine

Xiang

Yao

Zhou

et al. 2018

Shock and Vibration

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Internal combustion engine noise sources are complex and changeable. Combustion noise is usually drowned out by mechanical noise and aerodynamic noise. Traditional noise source identification methods can only qualitatively identify combustion noise. In order to quantitatively obtain the independent pure combustion noise of an internal combustion engine, it is necessary to design and build a separate noise source simulation test bench. In this paper, the combustion noise separation test bench based on transfer function method is designed and implemented. In the test, a pressure pulse device is installed in the combustion chamber. When the piston is at top dead center (TDC), pulse pressure is generated to excite the internal combustion engine to radiate noise. The pressure signal and noise signal are utilized to obtain the transfer function of combustion pressure and noise. Then, according to the cylinder pressure and transfer function, the combustion noise can be directly calculated. The test was carried out on 4120SG diesel engine. Experimental results show that when the internal combustion engine is under 1500 rpm and no-load condition and 800 rpm and no-load condition, the frequency components of independent pure combustion noise are both mainly concentrated at 1100 Hz, 1400 Hz, and 3000 Hz. Furthermore, the internal combustion engine vibration test method and the combustion noise empirical formula calculation method are both carried out to show accuracy and effectiveness of the obtained independent combustion noise through the combustion noise separation test based on transfer function method.

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Source localization of turboshaft engine broadband noise using a three-sensor coherence method

Cited by 8 publications

References 12 publications

Acoustics Source Identification of Diesel Engines Based on Variational Mode Decomposition, Fast Independent Component Analysis, and Hilbert Transformation

Acoustics Source Identification of Diesel Engines Based on Variational Mode Decomposition, Fast Independent Component Analysis, and Hilbert Transformation

Influence of viscosity on entropy noise generation through a nozzle

Research on Experimental Method for Obtaining Independent Combustion Noise of Internal Combustion Engine

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