Paper Conference

Proceedings of Building Simulation 2017: 15th Conference of IBPSA

     

Preventive Maintenance of Centralized HVAC Systems: Use of Acoustic Sensors, Feature Extraction, and Unsupervised Learning

Ravi Srinivasan1, Md Tamzeed Islam2, Bashima Islam2, Zeyu Wang1, Tamim Sookoor3, Omprakash Gnawali4, Shahriar Nirjon2
1Rinker School of Construction Management, University of Florida
2Department of Computer Science, University of North Carolina - Chapel Hill
3G2 Inc.
4 Department of Computer Science, University of Houston


DOI: https://doi.org/10.26868/25222708.2017.715
Abstract: In this paper, we propose a predictive maintenance scheme for centralized HVAC systems by autonomous monitoring and analyzing their acoustic emissions. Our proposed solution allows a building to be retrofitted to monitor its HVAC without having to modify the existing infrastructure. Our approach is to employ an energy-efficient, low-cost, and distributed acoustic sensing platform to capture and process audio signals from HVAC systems. As part of this project, we develop audio models of a running HVAC system using a combination of unsupervised and supervised machine learning techniques with a human-in-the-loop for fault identification and prediction.
Pages: 2518 - 2524
Paper:
BS2017_715