SF6 device secondary fault diagnosis method based on mass data parallel computation

The invention discloses an SF6 device secondary fault diagnosis method based on mass data parallel computation. According to the corresponding relationship between the SF6 decomposed gas component content and the fault type in an electrical device, firstly, a secondary fault diagnosis model of an SF6 electrical device is parallelly constructed, and the modeling efficiency is improved. Then parallel diagnosis of the SF6 electrical device is achieved, the diagnosis rapidity and accuracy in a big data environment are improved. The parallel diagnosis process of the SF6 device secondary fault diagnosis method is that each lab diagnoses different pieces of data at the same time, specifically, a decision tree model is employed to carry out primary diagnosis on the pieces of data and determine whether the device has a fault, and therefore the mass data processing speed is increased. For fault data, the fault type is accurately determined through a neural network model. By employing the SF6 device secondary fault diag