Abstract:

In order to realize the multi- sensor automatic detection signal processing for the fire occurrence in confined space, a fire detection data fusion analysis system was developed based on multi- sensor detection of CO concentration, smoke particle concentration, infrared video image, etc. First, build a data fusion analysis experimental platform based on multi- sensor fire detection in a confined space. Then, the infrared image recognition algorithm is introduced according to the characteristic parameters such as the area and circularity of the fire infrared video image. Then, based on the characteristic parameters of the three fire detection methods, a fixed threshold power spectrum detection method is proposed, and data fusion is completed. Finally, based on the analysis and comparison of the system performance evaluation methods such as the response time and alarm accuracy of the fire detection system, the method of multi- sensor detection signals for data fusion and the establishment of disaster criteria is explained. The experimental results show that: after using the data fusion algorithm, the false alarm rate of the detection system is lower than the single detection mode, and the alarm time is slightly higher than the single detection alarm mode. The data fusion system basically meets the requirements of stable and reliable automatic fire detection and alarm system and low false alarm rate.

Key words:  confined space, fire detection, data fusion, infrared video