Detection of a predefined acoustic pattern by a measurement system on a drone and its application to search for a missing man in an underground mine

Abstract

Abstract Due to the very difficult working conditions and a certain number of hazards that do not occur in other industries, the operation of rescue units in underground mines is necessary. The area of exploitation is usually very large, thus determining the location of a person, which may be in need due to the accident, is not an easy task. As the time for reaching such a person is crucial, there is a strong need for a solution that would provide a quick establishment of the victims’ location. Moreover, conducting a rescue mission is always associated with risk exposure for rescuers’ life and health. Thus, in this paper, we propose a solution based on an unmanned aerial vehicle (UAV) for a predefined acoustic pattern detection to support rescue units in human location assessment in the underground mine. The presented method is based on measuring the dissimilarity between the subsequent short-time power spectra and the referential spectrum characterizing the UAV’s ego-noise. This relatively general and data-driven approach is applied both to generated narrowband harmonic patterns and to the human voice. As the analyzed signals of interest are of specific frequency content they can be selected from the background noise with the use of band-pass filtering.