Detection of vibrations on windows and doors excited by a speaker using video cameras

Abstract

Algorithms were developed and tested to estimate acoustic coupled vibrations on doors and windows in a small building using data from commercial video cameras. The building was excited with a speaker that emitted low frequency tones. Image processing based algorithms were developed to estimate the frequency, amplitude, and signal-to-interference-plus-noise ratio (SINR) of the tones. Sensors such as Laser Doppler Vibrometers (LVDs) and accelerometers are much more sensitive than video cameras for measuring small vibrations and have a higher cutoff frequency. However, video cameras are ubiquitous, passive, and can potentially monitor a large area. Their performance is limited by the target range due to increased pixel size and atmospheric turbulence, lighting conditions, the contrast of the object of interest and the sample rate of the camera. Given these limitations, there are still potential new applications and niches for using video cameras to remotely measure vibrations of objects.