Visualization of acoustic waves in air and subsequent audio recovery with a high-speed schlieren imaging system: Experimental and computational development of a schlieren microphone

Journal article

We present a high-speed single-mirror double-pass coincident schlieren system and corresponding algorithms for the visualization of acoustic waves and recovery of their associated audio signals. Schlieren systems are extensively used to visualize strong shockwaves, such as those from supersonic motion or explosions. Recently, they have also been used to visualize lower amplitude non-linear acoustic phenomena, such as the weak shockwaves arising from impact events including hand claps, belt snaps, and towel cracks. Time-invariant sounds produced by loudspeakers have also been imaged, in one case leading to frequency analysis, although these have been limited to high-frequency signals at very high sound pressure levels. The research presented here shifts the focus from sound-field visualization towards audio signal recovery. A comprehensive exploration of several parameters for imaging sound sources, including frequency, wave form, and amplitude, is presented. In addition, we address for the first time the recovery of phase information, which would be essential for speech intelligibility, and the more general case of non-contact sound field reconstruction. Through image and signal processing, it is shown that audio signals can be recovered from high-speed schlieren video whose acoustic waves appear to be below the limit of visibility, and were previously deemed unrecoverable by virtue of their frequency and sound pressure level. This includes sounds at frequencies and loudnesses relevant for human hearing, producing the first ‘schlieren microphone’.

Authors: Harvey, J; Smithson, H; Siviour, C

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Elsevier
• Journal: Optics and Lasers in Engineering
• Volume: 107
• Pages: 182-193
• Publication date: 2018-04-02
• Acceptance date: 2018-03-13
• DOI: 10.1016/j.optlaseng.2018.03.015
• ISSN: 0143-8166
• Keywords: image processing; visual microphone; schlieren imaging; sound visualization