Anomaly Monitoring of Chemical Storage Tank Based on Principal Component Analysis
Online monitoring in the storage tank area can effectively reflect the operating status of the operation in the storage tank area,but the process variables of the operation in the storage tank area usually have strong correlation.In view of the problem that the threshold monitoring of a single variable cannot reflect the operating status of the storage tank area,this paper presents the unsupervised learning method to analyze the multiple variables of the storage tank area,and adopts the principal component analysis method to reduce the dimensions.Then anomaly monitoring is carried out based on statistical parameter method.The experimental results show that the original 7-dimensional parameter information in ben-zene material flow chart is reduced to 3-dimensional by principal component analysis,and more than 85%parameter infor-mation in the original data is retained.This method performs well in the detection of abnormal operating status in the stor-age tank area,and successfully realizes the abnormal monitoring of the operating status of the storage tank area.
万方数据
维普
