Aiming at the problem of untimely fire prevention and control due to missed and false alarms in the traditional fire early warning system of substations, an intelligent fire classification and early warning algorithm based on multi-sensor information fusion is proposed in this paper. Different from the fire warning with a single sensor, firstly, the algorithm proposed in this paper combines the temperature, CO concentration and smoke sensors to build a multi-sensing fusion layer of the fire detection model, which improves the detection sensitivity to a certain extent. Then, the algorithm uses support vector machine (SVM) to classify and warn fires based on the feature information collected by the multi-sensor fusion layer. Finally, the experimental verification is carried out based on the national standard test fire dataset. The experimental results show that the proposed model can effectively and accurately classify and predict the occurrence of fire, and improve the accuracy of fire early warning decision-making to a certain extent.
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