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http://dx.doi.org/10.12815/kits.2019.18.5.112

Acoustic Signal-Based Tunnel Incident Detection System  

Jang, Jinhwan (Dept. of Highway Res., Korea Inst. of Civil Eng. and Building Tech.)
Publication Information
The Journal of The Korea Institute of Intelligent Transport Systems / v.18, no.5, 2019 , pp. 112-125 More about this Journal
Abstract
An acoustic signal-based, tunnel-incident detection system was developed and evaluated. The system was comprised of three components: algorithm, acoustic signal collector, and server system. The algorithm, which was based on nonnegative tensor factorization and a hidden Markov model, processes the acoustic signals to attenuate noise and detect incident-related signals. The acoustic signal collector gathers the tunnel sounds, digitalizes them, and transmits the digitalized acoustic signals to the center server. The server system issues an alert once the algorithm identifies an incident. The performance of the system was evaluated thoroughly in two steps: first, in a controlled tunnel environment using the recorded incident sounds, and second, in an uncontrolled tunnel environment using real-world incident sounds. As a result, the detection rates ranged from 80 to 95% at distances from 50 to 10 m in the controlled environment, and 94 % in the uncontrolled environment. The superiority of the developed system to the existing video image and loop detector-based systems lies in its instantaneous detection capability with less than 2 s.
Keywords
Acoustic signal; Tunnel; Incident;
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