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改进的多元数据融合算法在矿井火灾检测系统中的应用

Application of mine fire detection system based on improved multi - data fusion algorithm
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摘要 为了可靠地实现矿井火灾报警,准确地探测到着火点位置,在矿井火灾检测系统中提出了多元数据融合算法。利用数字滤波技术,对单个传感器的采集数据进行预处理,再经过一次同类传感器的数据融合技术,得到一组较为准确的火灾特征参数值,并把这组参数值代入改进的火灾预测模型进行二次数据融合,最终实现火灾灾情和位置的的探测。实验表明:该方法能够抑制环境变化对传感器的干扰,且预测虚警率低、性能稳定。 In order to achieve the mine fire alarm and detect the exact location of ignition point,multiple data fusion algorithm was proposed and applied in mine fire detection system.The data collection of single sensor was pre-processed by using digital filtering techniques.And then following similar sensors' data fusion technology,more accurate characteristic parameters of mine fire was acquired.Applied the set of parameters to improved fire prediction model for secondary data fusion,the detection of the disaster and the location of fire was realized ultimately.A large number of experiments show that this method is fully capable of inhibiting changes in ambient environment interference and have low predicted false alarm rate and stable performance.
出处 《工业仪表与自动化装置》 2010年第4期94-97,共4页 Industrial Instrumentation & Automation
基金 黑龙江教育厅科学技术指导项目(11544047)
关键词 数据融合 特征参数 自适应 智能算法 相对差值函数 data fusion characteristic parameter self-adapted intelligent arithmetic relative difference function
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