Research on burst detection algorithm in Internet of things-basedwelding machine monitoring system
基于物联网的焊机监测系统中突发检测算法研究

For the need of detecting and early warning of abnormal conditions in an Internet of things-based welding machine monitoring system, this paper presented a multi-population firefly based burst detection algorithm for reducing processing time and improving detection performance through optimizing the sizes of slide windows. The simulations experimental results demonstrate that the burst detection algorithm consumes less processing time in the same conditions of burst probability or maximum slide window size, and also achieves higher precision and recall rate than traditional algorithms.