Internal noise reduction combining microphones and a piezoelectric device under blind condition

Mitsuharu Matsumoto*, Tomomi Abe, Shuji Hashimoto

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    2 Citations (Scopus)

    Abstract

    This paper introduces internal noise reduction combining microphones and a piezoelectric device attached to the internal noise source under blind condition. An acoustical array combining microphones and piezoelectric devices is an acoustical sensor fusion to reduce the internal noise coming from the inside of the system such as machines, vehicles or robots. It can reduce the internal noise effectively, while it is difficult to reduce the internal noise by employing the conventional microphone array and blind source separation (BSS) algorithms such as ICA or sparseness approach because the internal noise is extremely close to the microphone and not always stationary, statistically independent or sparse. However, when the acoustical array combining microphones and piezoelectric devices are utilized, it is necessary to estimate the gains of microphones and piezoelectric devices concerning the internal noise source in advance. Our aim is to simplify this process. In this paper, we formulate the problem and show the methodology of the proposed method. Experimental results are also demonstrated to confirm the effectiveness of the proposed method.

    Original languageEnglish
    Title of host publicationIEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems
    Pages498-502
    Number of pages5
    DOIs
    Publication statusPublished - 2008
    Event2008 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI - Seoul
    Duration: 2008 Aug 202008 Aug 22

    Other

    Other2008 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI
    CitySeoul
    Period08/8/2008/8/22

    ASJC Scopus subject areas

    • Control and Systems Engineering
    • Software
    • Computer Science Applications

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