ConceptFault Classification
Fault Classification
An AI task that relies on supervised learning, training a model with historical fault samples as labels to distinguish specific equipment fault types. Commonly used algorithms include random forests, gradient boosting, and deep learning models for time series.
Timeline (last 90 days)
Oct 16
In predictive maintenance, anomaly detection usually employs unsupervised learning, such as autoencoders and isolation forests; fault classification relies on supervised learning, using random forests, gradient boosting, or time-series deep learning models.
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