November 2019
Spotlight Summary by Abbie Watnik
Simple and robust speckle detection method for fire and heat detection in harsh environments
Distinguishing between fire, dust, pollution, or other noise sources can be quite a challenge for laser-based fire detection systems. Conventional optical-based fire detection systems rely on changes in light intensity due to the flames, heat, gasses, or particulates during a fire. Authors Christensen et al. state that these prior approaches may show limited performance, inability to operate, and/or frequent false alarms due to mechanical noise or interference from dust or pollution particles. This paper describes an alternative approach based on the detection of dynamical laser speckle and the calculation of the noise power spectrum. The researchers were able to distinguish between fire and noise sources through differences in the noise power spectrum; the authors were able to show that broad frequency noise with a linear trend was characteristic of representative fire sources, while narrow linewidth sources from other contributions can be filtered out. Tests at a factory site showed a 94% accuracy of detecting a fire, even in these harsh conditions. The researchers believe this new, robust approach will bring down false alarms for fire detection.
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Article Information
Simple and robust speckle detection method for fire and heat detection in harsh environments
Charles N. Christensen, Yevgen Zainchkovskyy, Salvador Barrera-Figueroa, Antoni Torras-Rosell, Giorgio Marinelli, Kim Sommerlund-Thorsen, Jan Kleven, Kristian Kleven, Erlend Voll, Jan C. Petersen, and Mikael Lassen
Appl. Opt. 58(28) 7760-7765 (2019) View: Abstract | HTML | PDF