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Multi-sensor Fusion Approach for Fire Alarm Using BP Neural Network

机译:使用BP神经网络的火灾报警多传感器融合方法

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Multi-sensor information fusion algorithm based on BP neural network is applied in the system of fire alarm to realize early detecting and alarming. The fire detection method based on neural network was developed using detection information for temperature, smoke density, and CO concentration to determine the probability of three representative fire conditions. The method overcomes the drawbacks of the fire alarm system using single sensor information. Results show that the proposed method can provide fire warning more accurate and timely and can effectively reduce leak-check rates and false alarms, reaching the desired purpose.
机译:基于BP神经网络的多传感器信息融合算法应用于火灾报警系统,实现早期检测和报警。使用温度,烟雾密度和CO浓度的检测信息开发了基于神经网络的火灾检测方法,以确定三种代表性火灾条件的概率。该方法克服了使用单个传感器信息的火灾报警系统的缺点。结果表明,该方法可以更准确和及时提供火灾警告,可以有效地减少泄漏检查速率和误报,达到所需的目的。

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