Statistical Signal Processing by Using the Higher‐Order Correlation between Sound and Vibration and Its Application to Fault Detection of Rotational Machine | Zendy

Hisako Masuike | Zendy; Akira Ikuta | Zendy

Open Access

Statistical Signal Processing by Using the Higher‐Order Correlation between Sound and Vibration and Its Application to Fault Detection of Rotational Machine

Author(s) -

Hisako Masuike,

Akira Ikuta

Publication year - 2008

Publication title -

advances in acoustics and vibration

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.237

H-Index - 14

eISSN - 1687-627X

pISSN - 1687-6261

DOI - 10.1155/2008/828562

Subject(s) - vibration , signal (programming language) , nonlinear system , fault (geology) , signal processing , series (stratigraphy) , time domain , conditional probability , domain (mathematical analysis) , computer science , algorithm , acoustics , engineering , electronic engineering , mathematics , physics , mathematical analysis , statistics , digital signal processing , computer vision , quantum mechanics , paleontology , seismology , biology , programming language , geology

In this study, a stochastic diagnosis method based on the changing information of not only a linear correlation but also a higher-order nonlinear correlation is proposed in a form suitable for online signal processing in time domain by using a personal computer, especially in order to find minutely the mutual relationship between sound and vibration emitted from rotational machines. More specifically, a conditional probability hierarchically reflecting various types of correlation information is theoretically derived by introducing an expression on the multidimensional probability distribution in orthogonal expansion series form. The effectiveness of the proposed theory is experimentally confirmed by applying it to the observed data emitted from a rotational machine driven by an electric motor

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