Research on Automatic Detection Technology of Acetylene Gas Concentration in Transformer Oil Based on Big Data Analysis
In order to effectively grasp the current fault state of transformer,the automatic detection technology of transformer oil-soluble acetylene gas concentration based on big data analysis was studied.The time series of oil-sol-uble acetylene is decomposed and reconstructed by using the singular spectrum analysis method,the above time se-ries is divided into a training set and a test set,and the two datasets are taken as inputs,and the convolutional neu-ral network in the big data analysis algorithm is used to establish an automatic detection model of transformer oil-soluble acetylene gas concentration,the training set and the test set are mapped and feature extracted,and the output layer of the model is used to output the automatic detection results of gas concentration.Experiments show that this method has a strong ability to analyze the singular spectrum of transformer oil-soluble acetylene time series,and can realize the automatic detection results of transformer oil-soluble acetylene gas concentration in different test environ-ments,and has good applicability.
big data analysistransformeroil soluble acetylenegas concentrationautomated detection technologysin-gular spectrum analysis
NETL
NSTL
万方数据
