Automatic fault detection in gearboxes by dynamic fuzzy data analysis
Fuzzy Sets and Systems
Engineering Applications of Artificial Intelligence
Evolving Intelligent Systems: Methodology and Applications
Evolving Intelligent Systems: Methodology and Applications
A lossy counting based approach for learning on streams of graphs on a budget
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Hi-index | 0.00 |
We present an unsupervised cognitive fault diagnosis framework for nonlinear dynamic systems working in the space of approximating models. The diagnosis system detects and classifies faults by relying on a fault dictionary that is empty at the beginning of the system's life and is automatically populated as faults occur. Outliers are treated as separate instances until enough confidence is built and either are integrated in existing classes or promoted to a new faults class. Simulation results show the effectiveness of the proposed approach.