Design and implementation of a multi-octave-band audio camera for realtime diagnosis

TL;DR

This paper presents a compact, real-time multi-octave-band acoustic camera system that combines sound measurement and imaging for dynamic noise source diagnosis, utilizing MEMS microphones and GPU acceleration.

Contribution

It introduces a novel real-time acoustic imaging system using MEMS microphone arrays and GPU processing, enabling dynamic noise source localization across multiple octave bands.

Findings

Real-time acoustic imaging achieved across multiple octave bands.

System utilizes MEMS microphones for compactness and digital processing.

GPU acceleration enables handling large data for real-time analysis.

Abstract

Noise pollution investigation takes advantage of two common methods of diagnosis: measurement using a Sound Level Meter and acoustical imaging. The former enables a detailed analysis of the surrounding noise spectrum whereas the latter is rather used for source localization. Both approaches complete each other, and merging them into a unique system, working in realtime, would offer new possibilities of dynamic diagnosis. This paper describes the design of a complete system for this purpose: imaging in realtime the acoustic field at different octave bands, with a convenient device. The acoustic field is sampled in time and space using an array of MEMS microphones. This recent technology enables a compact and fully digital design of the system. However, performing realtime imaging with resource-intensive algorithm on a large amount of measured data confronts with a technical challenge. This is overcome by executing the whole process on a Graphic Processing Unit, which has recently become an attractive device for parallel computing.