计算机应用与软件2017，Vol.34Issue(2)：214-219,6.DOI:10.3969/j.issn.1000-386x.2017.02.038
基于FCM-ANN的化工储罐异常检测方法研究
RESEARCH ON ABNORMAL DETECTION OF CHEMICAL STORAGE TANK BASED ON FCM-ANN
杨小健 1朱月 1钱景辉1
作者信息
- 1. 南京工业大学计算机科学与技术学院 江苏南京211816
- 折叠
摘要
Abstract
How to detect the abnormal state of the operation of the storage tank is the core problem in industrial control systems.Most of the detection methods proposed so far employ a supervised-learning or unsupervised-learning technique,the former fails to detect unknown anomalies while the latter requires large amounts of learning data.In order to solve the above problems,this paper presents a hybrid algorithm named FCM-ANN which is a mixture of Fuzzy CMeans clustering and Artificial Neural Network.There are three phases involved in the algorithm,in the first phase,namely the FCM layer,FCM algorithm is used to separate the data into several clusters and most of the abnormal data gather together.In second phase,different ANNs is trained based on various clusters and at last neural network ensemble is used to combine the results of different ANNs.Some experiments are conducted on the database of storage tank operation and the results indicate the proposed algorithm is able to detect anomalies with better detection performance compared with ANN,FCM and Na(i)ve Bayes.关键词
储罐/异常检测/FCM/ANN/三层结构模型Key words
Storage tank/Anomaly detection/FCM/ANN/Three layer structure分类
信息技术与安全科学引用本文复制引用
杨小健,朱月,钱景辉..基于FCM-ANN的化工储罐异常检测方法研究[J].计算机应用与软件,2017,34(2):214-219,6.
