ML Algorithms
Physics-Informed AI
A physics-informed approach was developed (defect-free model was built)
Physics-Informed features were extracted using residual and cross-sample-entropy analysis
Random forest model integrated with SHAP algorithm was implemented to rank the extracted features
Sensor Fusion Using CNN-LSTM Network
What is the best way to integrate data from various sources?
A integrative deep learning approach to fuse data from different sensors
The algorithms is based on two parts:
CNN are used to extract features from different time serieses
LSTM are used to rank and select the extracted features from different sources
Publications: IEEE
Embedding Dimension Diagnostic Method
How can we measure a system's dimensionality?
A novel method was developed during my doctoral work
Based on the information in the embedding dimension of a given signal
Capable of distinguishing various nonlinear responses within the system (chaos, multi-periodic, etc.)
Applied to gear-train setup to identify cracks
Transfer Learning for Nonlinear Pendulum
Develop a transfer learning approach to update fault identifier when the system changes
Structural change in the system
A large amount of data available before the structural change
Limited data after the structural change
Change in operation scenario
A large amount of data for previous operation scenario
Limited data for new operation scenario
Phase Space Topology Family of Methods
Industrial machinery applications reported nonlinear phenomena such multi-periodic, quasi periodic and chaotic that were originating from defects or due to their nonlinear nature.
How can we characterize system response and get insight using nonlinear dynamics?
A novel family of methods was developed during the my doctoral work
Based on extracting information from the phase space domain
Generalized on various range on real mechanical and electrical systems
A patent was filled
Ranked Recurrence Diagnostic Method
Based on integrating mutual information and recurrence quantification analysis
Recurrence plots reveals all the times when a dynamic system visits roughly the same area in the phase space (repeating different kinds of behavior)
Publications: JSEA