Source Separation method of Machine Faults Based on Post-Nonlinear Blind Source Separation

Li, Zhinong; Zeng, Yanjun; Fan, Tao; Lv, Yaping; Ren, Jinge

doi:10.1109/wcica.2008.4594464

Cited by 5 publications

(2 citation statements)

References 6 publications

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“…Damping vibration and harmonic vibration is different, its amplitude over time and become smaller and smaller (figure 1). After the forced vibration, String is due to the gradual attenuation amplitude, energy gradually disappears, and voice is becoming weaker [7]. So, the faster string vibration is to stop, the greater the attenuation of sound.…”

Section: String Vibration Mode: Damping Vibrationmentioning

confidence: 99%

Research on the Piano String Sound Reconstruction with Computer Technology Based on the Theory of String Vibration

2014

AMM

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The vibration of the string is a series of different frequency and different amplitude and phase of harmonic vibration superposition. These different frequencies are including fundamental frequency, double or triple frequency, and more integer time’s frequency. It is composed of string segment of vibration. The piano sound is spread by the string vibration, through the string to the soundboard that is by the soundboard to air, and then is introduced to the process of the human ear. String vibration is sound energy generated link, its energy is the key to the size of the sound vibration energy; therefore, the sound propagation attenuation problem in the first part is crucial, how to improve the strings attenuation becomes a key problem to be solved. This article aim is that the application of the string vibration theory in the piano strings sound reconstruction and its implementation are discussed.

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Section: String Vibration Mode: Damping Vibrationmentioning

confidence: 99%

Research on the Piano String Sound Reconstruction with Computer Technology Based on the Theory of String Vibration

2014

AMM

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“…However, the existing nonlinear blind separation algorithm [4][5][6] is more complicated, and the post-nonlinearity is always required to be invertible function. Considering that the linear blind separation algorithm is very mature, therefore linear blind separation algorithm can be expected to solve the nonlinear blind source separation problem of mechanical faults in a new feature space.…”

Section: Introductionmentioning

confidence: 99%

Kernel Independent Component Analysis and its Application in Blind Separation of Mechanical Faults

Xiao

et al. 2014

AMM

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A nonlinear blind separation method of mechanical fault sources is proposed. In the proposed method, the signal is transformed from the low-dimensional nonlinear original space into a high-dimensional linear feature space by the kernel function, so that nonlinear mixture mechanical fault sources can be separated by the linear ICA method in a new feature space. The simulation result shows that the proposed method is superior to the traditional ICA method in processing nonlinear blind separation problem. Finally the proposed method is applied to the nonlinear blind separation of bearing faults. The experiment result further verifies the validity of the proposed method.

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An Advanced Scheme for Range Ambiguity Suppression of Spaceborne SAR Based on Blind Source Separation

Chang

Deng

Zhang

et al. 2022

IEEE Trans. Geosci. Remote Sensing

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Source Separation method of Machine Faults Based on Post-Nonlinear Blind Source Separation

Cited by 5 publications

References 6 publications

Research on the Piano String Sound Reconstruction with Computer Technology Based on the Theory of String Vibration

Research on the Piano String Sound Reconstruction with Computer Technology Based on the Theory of String Vibration

Kernel Independent Component Analysis and its Application in Blind Separation of Mechanical Faults

An Advanced Scheme for Range Ambiguity Suppression of Spaceborne SAR Based on Blind Source Separation

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