Anomaly detection methods for electrical equipment in the big data era
An increasing number of condition monitoring data are accumulated with the development of condition monitoring techniques for electrical equipment.Methods for effective extracting useful information from a large pool of data are becoming a concern nowadays.By taking those methods the capability of anomaly detection for equipment can be enhanced so as to ensure the reliability of power supplying.The paper summarizes two types of methods,namely trend analysis and dynamic modeling,based on which the direction for anomaly detection methods in the big data era is then presented.
big dataanomaly detectiontrend analysisdynamic modeling
NETL
NSTL
万方数据
