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Deep Learning and Handheld Augmented Reality Based System for Optimal Data Collection in Fault Diagnostics Domain
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
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.
Fuzzy Generative Adversarial Networks
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.
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