Based On Clustering Fusion Control System Of Fire Alarm

Fire threat to people's lives and property, good alarm control system is essential. Currently, there are a lot of alarm system function is not perfect, when the fire broke prone to omissions, false positives, mainly due to the fire alarm system consists of a single sensor to provide information source, resulting in less than a complete fire alarm system to receive early warning of fire Signal.The fire alarm system has many drawbacks, this clustering of multi-sensor information fusion control method applied to the fire alarm system, a single sensor to solve the problem of inadequate sources of information. Information fusion is an information processing, probability and statistics, artificial intelligence, pattern recognition, cognitive science, computer science and information theory and other technology in one of a newly developed interdisciplinary. In this paper, multi-sensor information fusion, knowledge-based neural network and the neural network learning and memory ability and self-organizing and adaptive capacity, through a comprehensive judging, global analysis, the formation of a new control strategy.In the scheme, two neural networks using data fusion control, that BP neural network and the ART-1 neural network. On BP and ART-1 neural networks to study, and in MATLAB, they were trained and simulated samples. Local error BP neural network as the reason, the output value is not precise enough alarm system can not meet the requirements of high accuracy, the use of ART-1 neural network to improve the BP neural network, a more accurate value of output to meet the needs of the alarm system. Then on the BP neural network and ART-1 neural network algorithm are compared, and the preparation of the MATLAB program. Meanwhile, the introduction of the fire alarm system is running the hardware environment, and the system is running a major chip required a simple introduction.Through this research and comparison of simulation results show that ART-1 neural network clustering method is better than BP control fusion control method, and calculate the output value of more accurate, confirmed some of the correctness of theoretical research topics And the feasibility of the overall system design.