Abstract
Aiming at the problem of how to quickly and accurately diagnose different types of rotating machinery faults, this paper starts with the combination of full-vector spectrum theory and feature engineering. A model of rotor imbalance faults diagnosis and identifying is constructed in the process of dealing with the data sets of multiple rotor imbalance fault. The result shows that this fault diagnosis model combined with the full vector spectrum theory and feature engineering can be used to correctly distinguish the faults of the equipment and accurately identify the types of the unbalanced faults.
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