Harnessing fuzzy neural network for gear fault diagnosis with limited data labels

• Published in: International journal of advanced manufacturing technology Vol. 115; no. 4; pp. 1005 - 1019
• Main Authors: Zhou, Kai, Tang, Jiong
• Format: Journal Article
• Language: English
• Published: London Springer London 01.07.2021; Springer Nature B.V
• Subjects: Artificial neural networks; CAE) and Design; Classification; Computer-Aided Engineering (CAD; Confidence intervals; Data acquisition; Engineering; Fault diagnosis; Faults; First principles; Fuzzy logic; Industrial and Production Engineering; Machine learning; Mechanical Engineering; Media Management; Neural networks; Original Article; Principal components analysis; Statistical analysis; Training; Gear fault diagnosis; Fuzzy neural network (FNN); Kernel principal component analysis (KPCA); Unseen fault scenarios; Fuzzy classification

Diagnosis and prognosis of gear systems play an important role in modern manufacturing. While first-principle-based inverse analysis is subject to various limitations, data-driven approaches such as many machine learning techniques have shown great promise in recent years. Nevertheless, major challe...