摘要
针对某建筑目标进行复合式传感器设置,通过火灾试验得到相应的火灾特征数据,利用基于Labview的BP神经网络分析处理所得数据进得出火灾判定结论,并且与数据融合技术所得结果进行对比分析,最后与实际火灾试验进行对比。研究结果表明:利用BP神经网络进行火灾信息处理可以提高火灾报警系统的准确性和智能化水平;数据融合技术进行的火灾判定更加有效准确地反映了火灾的实际情况。
A composite sensor was set for a building, and related fire feature data were gotten from fire experiments. The data were processed by BP neural network based on Labview to re ceive the fire determination, and the results were compared with results from data fusion technology, and then to the actual fire experiment. Results showed that, using BP neutral network to process the fire feature data can improve the accuracy and intelligent level of the fire alarm system; the data fusion technology can help reflect the actual situation more effectively.
出处
《消防科学与技术》
CAS
北大核心
2013年第2期165-167,共3页
Fire Science and Technology
基金
天津理工大学教改项目(Y1311-28)
天津市普通高等学校本科教学质量与教学改革研究计划项目(B01-0829)
