Multi-Feature Relational Modeling and Conditional-Memory-Augmented Anomaly Detection for Multi-Cylinder Diesel Engines Under Variable Operating Conditions
The results show that the method reduces the interference of operating-condition-induced normal-pattern drift with anomaly determination and improves the accuracy of fault warning within the range of the operating conditions covered in this study.