Title :
Intelligent sensor based on acoustic emission analysis applied to gear fault diagnosis
Author :
Zurita, D. ; Delgado, M. ; Ortega, J.A. ; Romeral, Luis
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; condition monitoring; electric machines; fault diagnosis; gears; intelligent sensors; neural nets; statistical analysis; time-domain analysis; acoustic emission based intelligent sensor; autonomous monitoring systems; central control unit; energy harvesting solutions; gear fault diagnosis; gear fault patterns; gearboxes; intelligent monitoring systems; neural network based algorithm; rotating machinery; time domain statistical analysis; wireless transceiver; Acoustic emission; Algorithm design and analysis; Feature extraction; Gears; Signal processing algorithms; User interfaces; Zigbee; Acoustic Emission; Energy Harvesting; Feature Analysis; Gear Fault Diagnosis; Neural Networks; Preventive Maintenance; Rotating Machinery; Wireless Sensor System;
Conference_Titel :
Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED), 2013 9th IEEE International Symposium on
Conference_Location :
Valencia
DOI :
10.1109/DEMPED.2013.6645713