Multiple Reference Active Noise Control
| dc.contributor.author | Tu, Yifeng | en |
| dc.contributor.committeechair | Fuller, Christopher R. | en |
| dc.contributor.committeemember | Burdisso, Ricardo A. | en |
| dc.contributor.committeemember | Saunders, William R. | en |
| dc.contributor.department | Mechanical Engineering | en |
| dc.date.accessioned | 2014-03-14T20:51:49Z | en |
| dc.date.adate | 1997-03-25 | en |
| dc.date.available | 2014-03-14T20:51:49Z | en |
| dc.date.issued | 1997-03-25 | en |
| dc.date.rdate | 1997-03-25 | en |
| dc.date.sdate | 1997-03-25 | en |
| dc.description.abstract | The major application of active noise control (ANC) has been focused on using a single reference signal; the work on multiple reference ANC is very scarce. Here, the behavior of multiple reference ANC is analyzed in both the frequency and time domain, and the coherence functions are provided to evaluate the effectiveness of multiple reference ANC. When there are multiple noise sources, multiple reference sensors are needed to generate complete reference signals. A simplified method combines those signals from multiple reference sensors into a single reference signal. Although this method could result in satisfactory noise control effects under special circumstances, the performance is generally compromised. A widely adopted method feeds each reference signal into a different control filter. This approach suffers from the problem of ill-conditioning when the reference signals are correlated. The problem of ill-conditioning results in slow convergence rate and high sensitivity to measurement error especially when the FXLMS algorithm is applied. To handle this particular problem, the decorrelated Filtered-X LMS (DFXLMS) algorithm is developed and studied in this thesis. Both simulations and experiments have been conducted to verify the DFXLMS algorithm and other issues associated with multiple reference ANC. The results presented herein are consistent with the theoretical analysis, and favorably indicate that the DFXLMS algorithm is effective in improving the convergence speed. To take the maximum advantage of the TMS320C30 DSP board used to implement the controller, several DSP programming issues are discussed, and assembly routines are given in the appendix. Furthermore, a graphical user interface (GUI) running under Windows' environment is introduced. The main purpose of the GUI is to facilitate parameters modification, real time data monitoring and DSP process control. | en |
| dc.description.degree | Master of Science | en |
| dc.identifier.other | etd-52597-0349 | en |
| dc.identifier.sourceurl | http://scholar.lib.vt.edu/theses/available/etd-52597-0349/ | en |
| dc.identifier.uri | http://hdl.handle.net/10919/36790 | en |
| dc.publisher | Virginia Tech | en |
| dc.relation.haspart | etdlast.PDF | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | eigenvalue spread | en |
| dc.subject | decorrelation filter | en |
| dc.subject | active noise cancellation | en |
| dc.subject | adaptive filter | en |
| dc.title | Multiple Reference Active Noise Control | en |
| dc.type | Thesis | en |
| thesis.degree.discipline | Mechanical Engineering | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | masters | en |
| thesis.degree.name | Master of Science | en |
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