Adaptable and Generic Methods for Monitoring and Prognostics of Energy Assets

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Published Nov 11, 2024
Mohammad Badfar Ratna Babu Chinnam
Murat Yildirim

Abstract

Monitoring and prognostics of energy assets are crucial for maintaining their reliability and efficiency. Effective monitoring ensures that potential issues are identified early, preventing unexpected failures and optimizing maintenance schedules. However, several challenges complicate this process in real-world scenarios, including poor data quality, low-fidelity and sparse data, the influence of external environmental factors, and diverse operating conditions and asset types. These challenges highlight the need for adaptable and generic solutions that can handle variability and complexity across different energy systems. This Ph.D. project aims to address these challenges by developing scalable, data-driven approaches for monitoring and prognostics. By focusing on creating adaptable and generic frameworks, the research seeks to provide robust solutions for real-world monitoring and prognostic problems for energy assets.

How to Cite

Badfar, M., Chinnam, R. B., & Yildirim, M. (2024). Adaptable and Generic Methods for Monitoring and Prognostics of Energy Assets. Annual Conference of the PHM Society, 16(1). https://doi.org/10.36001/phmconf.2024.v16i1.4216
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Keywords

Prognostics, Autonomous Monitoring, Maintenance Planning, Energy Assets

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Section
Doctoral Symposium Summaries