@inproceedings{eced7154af9b45ffbaceee2cc73f5ad6,
title = "Detection of patterns in pressure signal of compressed air system using wavelet transform",
abstract = "This paper investigates detecting patterns in the pressure signal of a compressed air system (CAS) with a load/unload control using a wavelet transform. The pressure signal of a CAS carries useful information about operational events. These events form patterns that can be used as `signatures' for event detection. Such patterns are not always apparent in the time domain and hence the signal was transformed to the time-frequency domain. Three different CAS operating modes were considered: idle, tool activation and faulty. The wavelet transforms of the CAS pressure signal reveal unique features to identify events within each mode. Future work will investigate creating machine learning tools for that utilize these features for fault detection in CAS.",
author = "Mohamad Thabet and David Sanders and Nils Bausch",
year = "2021",
month = apr,
day = "30",
doi = "10.1007/978-3-030-63916-7_8",
language = "English",
isbn = "978-3-030-63916-7",
series = "Springer Proceedings in Energy",
publisher = "Springer International Publishing AG",
pages = "61--67",
editor = "Iosif Mporas and Pandelis Kourtessis and Amin Al-Habaibeh and Abhishek Asthana and Vladimir Vukovic and John Senior",
booktitle = "Energy and Sustainable Futures",
address = "Switzerland",
}