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ANC of UAS Rotor Noise using Virtual Error Sensors

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dc.contributor.authorPolen, Melissa Adrienneen
dc.contributor.committeechairFuller, Christopher R.en
dc.contributor.committeememberSouthward, Steve C.en
dc.contributor.committeememberTarazaga, Pablo Albertoen
dc.contributor.departmentMechanical Engineeringen
dc.date.accessioned2021-03-13T09:00:24Zen
dc.date.available2021-03-13T09:00:24Zen
dc.date.issued2021-03-12en
dc.description.abstractTraditional active noise control (ANC) systems rely on a physical sensor to measure the error signal at the desired location of attenuation. The error signal is then used to update an adaptive controller, which ultimately attenuates the measured response. However, it is not always practical to use traditional ANC in real-world applications. For example, as small unmanned aerial systems (UAS) become more commonly used, community noise exposure also increases, along with the desire to reduce UAS noise. Traditional ANC systems that rely on physical sensors at observer locations are impractical, since a UAS does not typically have real-time access to the response at an observer's ears, which is realistically in the far-field. Virtual error sensing (VES) can augment an ANC system using near-field measurements to estimate the response at a desired far-field location. In this way, the VES technique effectively shifts the zone of quiet from the location of the physical sensor(s) to a different "virtual" location. This thesis begins by outlining past work that used traditional ANC methods and virtual error sensing techniques. Numerical modeling results showing the predicted spatial change in SPL achieved using a virtual sensor will be presented. Experimental tests used ANC to attenuate the noise from a single UAS rotor at far-field locations using a near-field microphone and the remote microphone technique (RMT) to develop the VES. The results of the VES alone and with an ANC approach at several far-field virtual locations will be presented and discussed.en
dc.description.abstractgeneralSmall unmanned aerial systems (sUAS) are becoming increasingly common for private, military, and commercial use, and as such, community noise exposure is increasing. Reducing the noise produced by UAS could help improve community acceptance. Active noise control (ANC) might be used to attenuate noise produced by sUAS, however, traditional ANC systems would require a physical sensor in the far-field, which is not feasible. A virtual error sensor (VES) could eliminate the need for a far-field sensor. This thesis describes the proposed VES strategy, and presents numerical simulations and experimental results that highlight both the benefits and limitations of the approach. Results of the VES system with and without an ANC approach are discussed. Experimental testing focused on attenuating the tonal noise produced by one 2-bladed rotor with a tip radius of 4.7 inches. Pressure variations caused by the blade rotation were measured in the near and far-field using electret microphones and externally polarized condenser microphones, respectively. The ANC system used the filtered-x least mean squares algorithm in conjunction with the VES system to estimate the far-field response. A 2-inch diameter speaker served as the secondary source to provide the appropriate control input to the system. Experimental results show reductions between 6-13 dB at varying far-field locations and rotation rates.en
dc.description.degreeMaster of Scienceen
dc.format.mediumETDen
dc.identifier.othervt_gsexam:29315en
dc.identifier.urihttp://hdl.handle.net/10919/102681en
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectactive noise controlen
dc.subjectvirtual error sensingen
dc.subjecttonal noiseen
dc.subjectunmanned aerial systemen
dc.subjectfeedforward controlen
dc.titleANC of UAS Rotor Noise using Virtual Error Sensorsen
dc.typeThesisen
thesis.degree.disciplineMechanical Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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