%0 Conference Paper %1 chen2003 %A Chen, Shaohua %A Bao, Hong %A Zeng, Xianyun %A Yang, Yimin %D 2003 %J Systems, Man and Cybernetics, 2003. IEEE International Conference on %K data-fusion %P 3775-3780 vol.4 %T A fire detecting method based on multi-sensor data fusion %V 4 %X In this paper, a fire detection system is designed based on multi-sensor data fusion technology. According to the fire signal's inherent character, the around temperature, smoke density and CO density are considered as the chief fire detecting signals. By introducing the "feedback" of cybernetics, a new algorithm that extracts the fire data-fitting characteristic is presented. The algorithm may improve the accuracy and quickness of early warning with a tendency feedback signal. In this fire detecting system, the fire experiential characteristic and the fire data-fitting characteristic of fire signal data are fused by the fuzzy inference system to get the last fire probability. Finally simulation experiments are done for typical flaming fire, typical smoldering fire and the fire under typical disturbance signals in kitchen environment. And satisfactory results are obtained.

@inproceedings{chen2003, abstract = { In this paper, a fire detection system is designed based on multi-sensor data fusion technology. According to the fire signal's inherent character, the around temperature, smoke density and CO density are considered as the chief fire detecting signals. By introducing the "feedback" of cybernetics, a new algorithm that extracts the fire data-fitting characteristic is presented. The algorithm may improve the accuracy and quickness of early warning with a tendency feedback signal. In this fire detecting system, the fire experiential characteristic and the fire data-fitting characteristic of fire signal data are fused by the fuzzy inference system to get the last fire probability. Finally simulation experiments are done for typical flaming fire, typical smoldering fire and the fire under typical disturbance signals in kitchen environment. And satisfactory results are obtained.}, added-at = {2009-04-11T23:53:40.000+0200}, author = {Chen, Shaohua and Bao, Hong and Zeng, Xianyun and Yang, Yimin}, biburl = {https://www.bibsonomy.org/bibtex/25d6a773701b7150e58a25d8bb49cc9cd/thau}, description = {Welcome to IEEE Xplore 2.0: A fire detecting method based on multi-sensor data fusion}, interhash = {3d2726a4a0d53f891e062eb37509d093}, intrahash = {5d6a773701b7150e58a25d8bb49cc9cd}, issn = {1062-922X}, journal = {Systems, Man and Cybernetics, 2003. IEEE International Conference on}, keywords = {data-fusion}, month = {Oct.}, pages = { 3775-3780 vol.4}, timestamp = {2009-04-11T23:53:40.000+0200}, title = {A fire detecting method based on multi-sensor data fusion}, volume = 4, year = 2003 }