Search Results for author: Rahul Rai

Found 8 papers, 1 papers with code

Deep Learning and Handheld Augmented Reality Based System for Optimal Data Collection in Fault Diagnostics Domain

no code implementations15 Jun 2022 Ryan Nguyen, Rahul Rai

The framework is composed of three components: (1) a reinforcement learning algorithm for data collection to develop a training dataset, (2) a deep learning algorithm for diagnosing faults, and (3) a handheld augmented reality application for data collection for testing data.


Physics-Infused Fuzzy Generative Adversarial Network for Robust Failure Prognosis

no code implementations15 Jun 2022 Ryan Nguyen, Shubhendu Kumar Singh, Rahul Rai

Results on a bearing problem showcases the efficacy of adding a physics-based aggregation in a fuzzy logic model to improve GAN's ability to model health and give a more accurate system prognosis.

Decision Making Generative Adversarial Network

Fuzzy Generative Adversarial Networks

no code implementations27 Oct 2021 Ryan Nguyen, Shubhendu Kumar Singh, Rahul Rai

This paper shows that adding a fuzzy logic layer can enhance GAN's ability to perform regression; the most desirable injection location is problem-specific, and we show this through experiments over various datasets.


IH-GAN: A Conditional Generative Model for Implicit Surface-Based Inverse Design of Cellular Structures

1 code implementation3 Mar 2021 Jun Wang, Wei Wayne Chen, Daicong Da, Mark Fuge, Rahul Rai

Results show that our method can 1) generate various unit cells that satisfy given material properties with high accuracy ($R^2$-scores between target properties and properties of generated unit cells $>98\%$) and 2) improve the optimized structural performance over the conventional variable-density single-type structure.

Generative Adversarial Network

Hybrid modeling: Applications in real-time diagnosis

no code implementations4 Mar 2020 Ion Matei, Johan de Kleer, Alexander Feldman, Rahul Rai, Souma Chowdhury

In this paper, we outline a novel hybrid modeling approach that combines machine learning inspired models and physics-based models to generate reduced-order models from high fidelity models.

BIG-bench Machine Learning

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