AI/ML for Mechanical Engineers: Domains, Data, and Deployment
Use of AI for Fault Diagnosis and Anomaly Detection (AICTE ATAL FDP)
Multiclass bearing fault classification using features learned by a deep neural network
Accurate classification of fault is important for condition based maintenance (CBM) applications. Two main approaches commonly used for fault classification are model-based and …
Feature Subset Selection Using Sparse Principal Component Analysis and Multiclass Fault Classification Using Selected Features
Feature selection is one of the most important aspects of condition monitoring. The condition or health of a machinery is manifested in the form of changes to its signal features. …
Data-Driven Machinery Fault Diagnosis
Aim of this project is to produce reproducible results in condition monitoring. We will apply some of the standard machine learning techniques to publicly available machinery …