Faults explanation based on a machine learning model for predictive maintenance purposes
Author:
Affiliation:
1. University of Lille, CERI Digital Systems,IMT Nord Europe,Douai,France,F-59500
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10151847/10152298/10152401.pdf?arnumber=10152401
Reference21 articles.
1. Autoencoder-driven fault detection and diagnosis in building automation systems: Residual-based and latent space-based approaches;youngwoong;Building and Environment,2021
2. A Modified DBSCAN Algorithm for Anomaly Detection in Time-series Data with Seasonality
3. Explainable AI for Machine Fault Diagnosis: Understanding Features’ Contribution in Machine Learning Models for Industrial Condition Monitoring
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