Video-based cargo fire verification system with fuzzy inference engine for commercial aircraft

Mokhtar Sadok; Radek Zakrzewski; Bob Zeliff

doi:10.1117/12.583252

24 February 2005 Video-based cargo fire verification system with fuzzy inference engine for commercial aircraft

Mokhtar Sadok, Radek Zakrzewski, Bob Zeliff

Proceedings Volume 5679, Machine Vision Applications in Industrial Inspection XIII; (2005) https://doi.org/10.1117/12.583252
Event: Electronic Imaging 2005, 2005, San Jose, California, United States

Abstract

Conventional smoke detection systems currently installed onboard aircraft are often subject to high rates of false alarms. Under current procedures, whenever an alarm is issued the pilot is obliged to release fire extinguishers and to divert to the nearest airport. Aircraft diversions are costly and dangerous in some situations. A reliable detection system that minimizes false-alarm rate and allows continuous monitoring of cargo compartments is highly desirable. A video-based system has been recently developed by Goodrich Corporation to address this problem. The Cargo Fire Verification System (CFVS) is a multi camera system designed to provide live stream video to the cockpit crew and to perform hotspot, fire, and smoke detection in aircraft cargo bays. In addition to video frames, the CFVS uses other sensor readings to discriminate between genuine events such as fire or smoke and nuisance alarms such as fog or dust. A Mamdani-type fuzzy inference engine is developed to provide approximate reasoning for decision making. In one implementation, Gaussian membership functions for frame intensity-based features, relative humidity, and temperature are constructed using experimental data to form the system inference engine. The CFVS performed better than conventional aircraft smoke detectors in all standardized tests.

Citation Download Citation

Mokhtar Sadok, Radek Zakrzewski, and Bob Zeliff "Video-based cargo fire verification system with fuzzy inference engine for commercial aircraft", Proc. SPIE 5679, Machine Vision Applications in Industrial Inspection XIII, (24 February 2005); https://doi.org/10.1117/12.583252

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