Wavelet based flickering flame detector using differential PIR sensors

A Pyro-electric Infrared (PIR) sensor based flame detection system is proposed using a Markovian decision algorithm. A differential PIR sensor is only sensitive to sudden temperature variations within its viewing range and it produces a time-varying signal. The wavelet transform of the PIR sensor signal is used for feature extraction from sensor signal and wavelet parameters are fed to a set of Markov models corresponding to the flame flicker process of an uncontrolled fire, ordinary activity of human beings and other objects. The final decision is reached based on the model yielding the highest probability among others. Comparative results show that the system can be used for fire detection in large rooms.

► In this study, a flame detection system based on a differential PIR sensor is descirbed.
► The flame and ordinary activity of human beings are modeled using a set of Markov Models (MM).
► The sensor signal is analyzed in the wavelet domain and the wavelet signals are fed to a set of MMs.
► A fire or no fire decision is made according to the MM producing the highest probability.
► The detection range of the sensor based system is 5 m which is enough to cover most rooms.