Fire detection algorithm in computer rooms based on multi-sensor data fusion
Aiming at the problems of high leakage rate and low accuracy of traditional single-sensor alarm system in computer rooms,we proposed a fire detection algorithm for computer room based on multi-sensor data fusion.Firstly,the algorithm optimizes the prediction accuracy and precision of the extreme learning machine(ELM)using the sparrow search algorithm(SSA)with high optimization seeking ability.Secondly,the feature layer data fusion of temperature,smoke concentration,and CO concentration collected by multiple sensors in an engine room was performed through the SSA-ELM algorithm model to output the probability of each fire condition.Finally,the features of output probability and duration of each fire were fused in the decision layer using fuzzy reasoning to decide the fire alarm level.Simulation experiments show that the algorithm can give a reasonable alarm decision based on the results of multi-sensor data fusion and combined with different hazardous areas,which greatly improves the flexibility and accuracy of fire detection in computer rooms.
万方数据
维普
