Simple and robust speckle detection method for fire and heat detection in harsh environments

TL;DR

This paper introduces a speckle-based laser fire detection method that remains effective in dusty, harsh environments by analyzing refractive index fluctuations rather than light intensity.

Contribution

The study presents a novel fire detection approach using speckle pattern analysis that is robust against dust, steam, and mechanical noise, suitable for harsh environments.

Findings

Successfully detected fires in dusty environments

Operates effectively without relying on visible flames

Uses low-cost laser and simple hardware

Abstract

Standard laser based fire detection systems are often based on measuring variation of optical signal amplitude. However, mechanical noise interference and loss from dust and steam can obscure the detection signal, resulting in faulty results or inability to detect a potential fire. The presented fire detection technology will allow the detection of fire in harsh and dusty areas, which are prone to fires, where current systems show limited performance or are unable to operate. It is not the amount of light nor its wavelength that is used for detecting fire, but how the refractive index randomly fluctuates due to the heat convection from the fire. In practical terms this means that light obstruction from ambient dust particles will not be a problem as long as a small fraction of the light is detected and that fires without visible flames can still be detected. The standalone laser system consists of a Linux-based Red Pitaya system, a cheap 650 nm laser diode, and a PIN photo-detector. Laser light propagates through the monitored area and reflects off a retroreflector generating a speckle pattern. Every 3 seconds time traces and frequency noise spectra are measured and 8 descriptors are deduced to identify a potential fire. Both laboratory and factory acceptance tests have been performed with success.