A Multivariate Normal Distribution Data Generative Model in Small-Sample-Based Fault Diagnosis: Taking Traction Circuit Breaker as an Example

• Published in: IEEE transactions on intelligent transportation systems Vol. 25; no. 6; pp. 5825 - 5841
• Main Authors: Ma, Qinghua, Dong, Ming, Xia, Changjie, He, Xinyi, Chen, Rongfa, Ren, Ming, Song, Meiyan
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.06.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Circuit breakers; Circuit faults; Covariance matrix; Data models; Fault diagnosis; Feature extraction; generative model; Integrated circuit modeling; Maximum likelihood estimation; Multivariate analysis; Noise generation; Normal distribution; Probability density functions; Small sample; Statistical analysis; Training

Data-driven approaches have been widely used in the field of traction system and equipment fault diagnosis. However, limited training samples can cause data-driven models to face the dilemma of overfitting. In order to supplement sufficient training data in small-sample case, this paper proposes a d...