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Active Control of Impulsive Noise using Reference Weighted FxLMS Algorithm

Dhakad, Rushikesh A
http://orcid.org/0000-0002-2884-5801
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1511869912897366

Abstract Details

2017, MS, University of Cincinnati, Engineering and Applied Science: Mechanical Engineering.
Active noise control (ANC) has been an attractive solution for automobile and aerospace industry for interior noise reduction. ANC has been successfully incorporated in industry such as the automotive industry while being subject to several constraints like maximum frequency of cancellation, and evaluation criteria like convergence time, stability, mean noise reduction (MNR) etc. While engine order cancellation and road noise (which is a broadband random noise) control have been thoroughly researched upon and hence considerably commercialized as solutions, a solution for impulsive noise yet remains elusive. This is primarily due to the difficulty in ensuring a stable performance, need to extract a number of complicated parameters for incorporating into the algorithm, high computational complexity and so on. This thesis thus attempts to present a simplified solution in the form of a reference-weighted filtered reference least mean square (RWFxLMS) algorithm for active control of impulsive noise which does not compromise on performance metrics like stability, convergence time, mean noise reduction, etc. The first chapter chronicles briefly literature available in the ANC research area in general and later focuses on work done for impulsive noise ANC. The second chapter, while briefly introducing the existing algorithms that inspired the development of the proposed RWFxLMS algorithm, describes the concept of the proposed algorithm. Performance of the proposed algorithm against a variety of impulsive noise data sets is studied while noting observations regarding its convergence and cancellation. The third chapter goes on to categorize previously available algorithms for impulsive noise ANC into three categories and later compares the computational complexity and convergence performance (rate of convergence and error at convergence) of the proposed RWFxLMS algorithm with the best algorithm from each category. It also includes a discussion about practical considerations while performing impulsive noise ANC.
Jay Kim, Ph.D. (Committee Chair)
Teik Lim, Ph.D. (Committee Member)
David Thompson, Ph.D. (Committee Member)
97 p.
Mechanical Engineering
Filtered reference FxLMS; weighted step-size algorithm; Impulsive noise ANC

Recommended Citations

Citations

  • Dhakad, R. A. (2017). Active Control of Impulsive Noise using Reference Weighted FxLMS Algorithm [Master's thesis, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1511869912897366

    APA Style (7th edition)

  • Dhakad, Rushikesh. Active Control of Impulsive Noise using Reference Weighted FxLMS Algorithm. 2017. University of Cincinnati, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1511869912897366.

    MLA Style (8th edition)

  • Dhakad, Rushikesh. "Active Control of Impulsive Noise using Reference Weighted FxLMS Algorithm." Master's thesis, University of Cincinnati, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1511869912897366

    Chicago Manual of Style (17th edition)

ucin1511869912897366
717
© 2017, all rights reserved.
This open access ETD is published by University of Cincinnati and OhioLINK.