About this document
Advanced Anomaly Detection For Condition-Based Predictive Monitoring of Rotating Machinery Using Multi-Sensor Time-Series Data by Ansh Bakliwal is a document available to read on EtoBox.
The document discusses advanced anomaly detection techniques for condition-based predictive monitoring (CBPM) of rotating machinery using multi-sensor time-series data. It emphasizes the effectiveness of hybrid architectures, particularly LSTM Autoencoders and Transformer-based models, for learning normal behavior and identifying anomalies based on reconstruction errors. Additionally, it outlines the importance of data preprocessing, feature engineering, and model training strategies to enhance the accuracy
- Author
- Ansh Bakliwal
- Language
- EN