Model decomposition via optical delay estimation using the camera tracking in an active noise control system for creation of a movable quiet zone

authored by

Sven Höber, Christian Pape, Eduard Reithmeier

Abstract

This article presents an adaptive control system for active local reduction of broadband noise at moving locations, using the camera tracking for path model decomposition to reduce the filter lengths. To enable a dynamic placement of local quiet zones with respect to a moving target, previous works proposed the combination of the remote microphone technique with a camera-based target tracking. The estimated 3-D coordinates are used at run time for a dynamic update of the transfer paths models, which correspond to virtual microphones at predetermined locations. Nevertheless, whereas current applications like headrests feature only short distances to the target, the considered ANC system aims at larger ranges for the moving quiet zone, resulting in long impulse responses and high delays in the transfer paths. To reduce the associated model lengths, this work evaluates a decomposed identification stage that takes advantage of the camera-tracking system by estimating the acoustic path delays optically. In experiments, this method is shown to be superior to signal processing-based approaches like cross-correlation and thus enables an accurate separation of the delays. Eventually, the validation of the broadband ANC performance at a moving microphone shows that the quiet zone could be tracked over a range of 0.8 m, while using only few transfer path models and saving over 100 coefficients due to the proposed decomposition.

Organisation(s)

Institute of Measurement and Control Engineering

Type

Article

Journal

Noise Control Engineering Journal

Volume

68

Pages

247-256

No. of pages

10

ISSN

0736-2501

Publication date

01.07.2020

Publication status

Published

Peer reviewed

Yes

ASJC Scopus subject areas

Building and Construction, Automotive Engineering, Aerospace Engineering, Acoustics and Ultrasonics, Mechanical Engineering, Public Health, Environmental and Occupational Health, Industrial and Manufacturing Engineering

Sustainable Development Goals

SDG 3 - Good Health and Well-being

Electronic version(s)

https://doi.org/10.3397/1/376821 (Access: Closed)