Several measurements may be used as error signals to determine how to appropriately control a sound field. These include pressure, particle velocity, energy density and intensity. In this thesis, numerical models are used to show which signals perform best in is free-field active noise control (ANC) using error sensors located in the near field of the sound sources. The second is equalization in a free field and a semi-free field. Minimized energy density total power output (MEDToPO) plots are developed; these indicate the maximum achievable attenuation for a chosen error sensor as a function of location. A global listening area equalization coefficient (GLAEC) is found to evaluate the performance of the equalization methods. It is calculated by finding the average of the spectral standard deviation of several frequency response measurements in a specified listening area. For free-field ANC employing error sensors located in the near field, pressure-based measurements perform the best. For free-field equalization over an extended listening region, total energy density performs best. Equalization of an extended listening region is more successful over a limited low-frequency bandwidth.
College and Department
Physical and Mathematical Sciences; Physics and Astronomy
BYU ScholarsArchive Citation
Chester, Ryan T., "Error Sensor Strategies for Active Noise Control and Active Acoustic Equalization in a Free Field" (2008). Theses and Dissertations. 1321.
active noise control, ANC, equalization, error sensor, acoustic, near field, energy density, GLAEC, global listening area equalization coefficient, MEDToPO, minimized energy density total power output, active sound control, sound control