Singularity distribution entropy analysis of impulsive acoustic signals

WANG Lu; CHEN Zhifei; CHEN Xi; ZHAO Qijun; BAO Ming

doi:10.11729/syltlx20230037

Volume 38 Issue 1

Feb. 2024

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Article Navigation > Journal of Experiments in Fluid Mechanics > 2024 > 38(1): 91-102

WANG L, CHEN Z F, CHEN X, et al. Singularity distribution entropy analysis of impulsive acoustic signals[J]. Journal of Experiments in Fluid Mechanics, 2024, 38(1): 91-102 doi: 10.11729/syltlx20230037

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Singularity distribution entropy analysis of impulsive acoustic signals

doi: 10.11729/syltlx20230037

WANG Lu^{1, 2
,},
CHEN Zhifei²,
CHEN Xi³,
ZHAO Qijun³,
BAO Ming^{2, 4, 5
,
,}

1.
The School of aerospace Information, Space Engineering University, Beijing　101416, China
2.
Key Laboratory of Noise and Vibration Research, Institute of Acoustics, Chinese Academy of Sciences, Beijing　100190, China
3.
National Key Laboratory of Rotorcraft Aeromechanics, Nanjing University of Aeronautics and Astronautics, Nanjing　210016, China
4.
The School of Automation, Northwestern Polytechnical University, Xi'an　710072, China
5.
The School of Materials Science and Intelligent Engineering, Nanjing University, Nanjing　215163, China

Received Date: 2023-03-23
Accepted Date: 2023-06-01
Rev Recd Date: 2023-05-17

Available Online: 2024-04-08

Publish Date: 2024-02-25

Abstract

Abstract

In order to effectively analyze and calibrate the singularity difference of impulsive acoustic signals in complex environment with low signal-to-noise ratio, a singularity distribution entropy features analysis model based on the mode maximum theory is proposed. Firstly, the impulsive signal is normalized and wavelet transform is carried out to calculate the mode maximum and its specific distribution at each scale, which can reflect the family of mode maximum curves with singular differences. In order to describe the difference quantitatively, entropy is used to describe the distribution of the maximum points which constitute the family of modal maximum curves, and a singular distribution entropy feature model which can effectively analyze the singularity difference of impulsive signals is constructed. The model can describe the singularity difference of signals at low signal-to-noise ratio. Experiments show that the accuracy of 89.25% and 87.63% of typical helicopter impulsive signals (blade-vortex interaction signals and high-speed impulsive signals) can be obtained when the signal to noise ratio is −6dB.
- impulsive acoustic signals,
- blade-vortex interaction signal,
- high-speed impulsive signal,
- singularity,
- feature analysis

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References(21)

References

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