Research on multi-detector real-time fire alarm technology based on signal similarity

Abstract

Accurate and timely fire detection is the focus of fire prevention, fire control and fire safety. However, fire detectors have a high false alarm rate in structures. To effectively realize real-time fire monitoring, a multi-detector fire detection model based on the asynchronous spatiotemporal signal similarity of different detectors was developed in this study. Firstly, the correlation coefficients of prediction signals and correlation signals were calculated based on the Pearson-Derivative dynamic time warping method. Secondly, a real-time fire detection model based on the signal correlation coefficient was constructed to realize the early detection of fire warnings. Besides, a calculation rule of the correlation coefficient for multi-detector signals was proposed, and the alarm threshold values in fire detection under different numbers of responding detectors were determined by the Support Vector Classification (SVC) algorithm. Finally, the effectiveness of the proposed fire detection model was verified by the fire experiment data from the National Institute of Standards and Technology (NIST) and the kitchen cooking nuisance tests.