Fault diagnosis based on deep belief networks and fisher discriminant analysis

Abstract

With the development of data mining technology, it becomes vital to extract fault features effectively in fault diagnosis. This paper is mainly concerned about a hybrid method for fault diagnosis. Firstly, train the data with the deep belief networks (DBN) to get the weighting vectors for all the fault class. And then, weight for fault data with responding… (More)

Topics

Figures and Tables

Sorry, we couldn't extract any figures or tables for this paper.

Slides referencing similar topics