
handle: 11693/26828
Date of Conference: 20-22 April 2008 Conference name: IEEE 16th Signal Processing, Communication and Applications Conference, SIU 2008 Bu bildiride, pasif kızılberisi sensor (PIR) tabanlı bir alev tespit sistemi sunulmaktadır. Önerilen yangın tespit sistemi oda içlerinde kullanılabilir. Kontrolsuz büyüyen yangın alevlerindeki kırpışma, oda içi gündelik insan hareketleri olan yürüme ve koşma ile birlikte, PIR sensörü işaretlerinin dalgacık dönüşümü katsayılarıyla eğitilmiş bir dizi saklı Markov modeliyle modellenmiştir. Sensör sisteminin görüş alanı içerisinde bir hareket tespit edildiğinde, sensör sinyali dalgacık domeninde çözümlenmekte ve bir dizi saklı Markov modeline beslenmektedir. En yüksek olasılık değerini üreten saklı Markov modeline göre “ateş” veya "ateş değil" kararı verilmektedir. In this paper, a flame detection system based on a pyroelectric (or passive) infrared (PIR) sensor is described. The flame detection system can be used for fire detection in large rooms. The flame flicker process of an uncontrolled fire and ordinary activity of human beings are modeled using a set of Hidden Markov Models (HMM), which are trained using the wavelet transform of the PIR sensor signal. Whenever there is an activity within the viewing range of the PIR sensor system, the sensor signal is analyzed in the wavelet domain and the wavelet signals are fed to a set of HMMs. A fire or no fire decision is reached according to the HMM producing the highest probability. ©2008 IEEE.
Signal processing, Wavelet domains, Sensor signals, Sensors, Markov processes, Fires, Flame flickers, Wavelet transforms, Fire detections, Flammability, Human beings, Hidden Markov models, Flame detections, Pir sensors, Signal detection
Signal processing, Wavelet domains, Sensor signals, Sensors, Markov processes, Fires, Flame flickers, Wavelet transforms, Fire detections, Flammability, Human beings, Hidden Markov models, Flame detections, Pir sensors, Signal detection
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