@inproceedings{c20e353f8d884372ab08a1c3591ef698,
title = "Underdetermined blind source separation based condition monitoring",
abstract = "A common technique of mechanical vibration measurement requires an operator to use vibrometer by attaching the accelerometer directly to a machine. The technique, however, poses a unsafe operation and involves significant man-power. This paper proposes a non-contact vibration measurement for machines condition monitoring by using acoustic emission information. It essentially uses the emitted signal to identify machinery condition. The measurement setup is an array of microphones is placed on critical operation at a power plant by assuming that the number of the sound sources are more than that of the sensors (underdetermined case). This approach is closely related to the sparse representation based on the signals in the time-frequency domain. These suggest that the proposed technique may accurately measure the vibration using acoustical emission. The paper also presents comparative results between baseline, estimated acoustic and vibration signals.",
keywords = "acoustic emission, blind source separation, condition monitoring, underdetermined",
author = "Vinaya, {Anindita Adikaputri} and Dhany Arifianto",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; International Conference on Science in Information Technology, ICSITech 2015 ; Conference date: 27-10-2015 Through 28-10-2015",
year = "2016",
month = feb,
day = "16",
doi = "10.1109/ICSITech.2015.7407775",
language = "English",
series = "Proceedings - 2015 International Conference on Science in Information Technology: Big Data Spectrum for Future Information Economy, ICSITech 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "47--52",
editor = "Yana Hendriana and Andri Pranolo and Adhi Prahara and Ismi, {Dewi Pramudi}",
booktitle = "Proceedings - 2015 International Conference on Science in Information Technology",
address = "United States",
}