Automatic Early Warning Technology of Automatic Pipeline Fault based on Cluster Analysis

Inhalt:
The existing automatic early warning technology has the problem of unclear security threshold, which leads to low clustering purity. This paper designs an automatic pipeline fault early warning technology based on clustering analysis. According to the current running state of the automatic pipeline equipment, the adaptive security threshold is set by clustering analysis, the automatic warning notification model is constructed, the warning function modules are divided, the particle swarm optimization algorithm is improved, the automatic warning mode is set, and the optimal clustering results are searched. Experimental results: the average clustering purity of the designed automatic early warning technology and the two conventional automatic early warning technologies are 1.229, 0.8885 and 0.921 respectively, which proves that the automatic early warning technology combined with cluster analysis technology has higher use valuet.