@inproceedings{e3a33ed0d02a404c874f6ca27b85aa21,
title = "Intelligent sensor based on acoustic emission analysis applied to gear fault diagnosis",
abstract = "The development of intelligent and autonomous monitoring systems applied to rotating machinery, represents the evolution towards the automatic industrial plants supervision. In this regard, an acoustic emission based intelligent sensor is presented in this work. The proposed sensor records regularly the acoustic emission signal generated by gearboxes. A time domain statistical analysis is applied in order to characterize the acquired data. Afterwards, a neural network based algorithm is applied to detect gear fault patterns. Finally, the diagnosis result is sent through a wireless transceiver to the central control unit. Moreover, in order to reach a real autonomous operation, the sensor power is approached by different energy harvesting solutions.",
keywords = "Acoustic Emission, Energy Harvesting, Feature Analysis, Gear Fault Diagnosis, Neural Networks, Preventive Maintenance, Rotating Machinery, Wireless Sensor System",
author = "Daniel Zurita and Miguel Delgado and Ortega, {Juan Antonio} and Luis Romeral",
year = "2013",
doi = "10.1109/DEMPED.2013.6645713",
language = "English",
isbn = "9781479900251",
series = "Proceedings - 2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives, SDEMPED 2013",
publisher = "IEEE Computer Society",
pages = "169--176",
booktitle = "Proceedings - 2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives, SDEMPED 2013",
address = "United States",
note = "2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives, SDEMPED 2013 ; Conference date: 27-08-2013 Through 30-08-2013",
}
