### Project Title:

Adaptive Nonlinear Polynomial Networks for Rotorcraft Cabin Noise Reduction

02.10-4400
901887
Adaptive Nonlinear Polynomial Networks for Rotorcraft Cabin Noise Reduction

### Abstract:

This project addresses the use of adaptive nonlinear polynomial network prediction
and noise cancellation algorithms to reduce rotorcraft cabin noise and vibration
via active anti-sound techniques. In recent years, there has been a considerable
amount of work on the use of statistical signal-processing techniques to produce
anti-sound acoustic fields for reducing vibration and noise in enclosed spaces. These
basic techniques employ adaptive linear prediction algorithms to the noise field
as sensed from an array of speakers to cancel the predictable part of the noise in
the array. The adaptive linear prediction and control methods used in the reduction
of cabin noise for propeller-driven appear to be quite successful. Although the noise
field produced by a propeller can be will-modeled as a Gaussian process (and thus
linear prediction is optimum), rotor noise typically has significant impulsive components
and cannot be well-modeled as a Gaussian process. Therefore, nonlinear predictors
are needed to achieve the desired cabin noise reduction. The Phase I work emphasize
the development of polynomial network predictor architectures to minimize the noise
residuals from an array of sensors within the cabin. In Phase II, a more detailed
multiple-error noise abatement system will be designed and evaluated using actual
rotorcraft data.
This work could be applied to areas of noise reduction in aircraft cabins and vibration
reduction in airframes. In a more general context, the modeling and processing techniques
could be applied in nonlinear signal processing for speech processing, data transmission,
and seismic signal processing.
impulsive noise, adaptive nonlinear prediction, rotor impulsive noise, noise cancellation,
rotorcraft cabin noise cancellation, anti-sound, statistical signal processing, non-gaussian
signal processing