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arXiv · 2212.10032

Real-time Health Monitoring of Heat Exchangers using Hypernetworks and PINNs

Ritam Majumdar·Vishal Jadhav·Anirudh Deodhar·Shirish Karande·Lovekesh Vig·Venkataramana Runkana
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Abstract

We demonstrate a Physics-informed Neural Network (PINN) based model for real-time health monitoring of a heat exchanger, that plays a critical role in improving energy efficiency of thermal power plants. A hypernetwork based approach is used to enable the domain-decomposed PINN learn the thermal behavior of the heat exchanger in response to dynamic boundary conditions, eliminating the need to re-train. As a result, we achieve orders of magnitude reduction in inference time in comparison to existing PINNs, while maintaining the accuracy on par with the physics-based simulations. This makes the approach very attractive for predictive maintenance of the heat exchanger in digital twin environments.

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Ritam Majumdar, Vishal Jadhav, Anirudh Deodhar, Shirish Karande, Lovekesh Vig, Venkataramana Runkana. 2022-12-20. Real-time Health Monitoring of Heat Exchangers using Hypernetworks and PINNs. https://arxiv.org/abs/2212.10032

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