TY - JOUR
T1 - Self-powered wireless sensor applied to gear diagnosis based on acoustic emission
AU - Delgado Prieto, Miguel
AU - Zurita Millan, Daniel
AU - Wang, Wensi
AU - Machado Ortiz, Anderson
AU - Ortega Redondo, Juan Antonio
AU - Romeral Martinez, Luis
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2016/1
Y1 - 2016/1
N2 - Advanced sensing strategies in the industrial sector are becoming a valued technological answer to increase the performance and competitiveness. The development of enhanced sensing solutions considering both technology and monitoring requirements is, nowadays, subject of concern in the industrial maintenance field. In this context, this paper presents a novel self-powered wireless sensor applied to condition monitoring of gears. The proposed sensor is based on a modular architecture, offering multipoint sensing, local wireless communication, multisource energy harvesting, and embedded diagnosis algorithm for mechanical fractures detection based on acoustic emission analysis. The developments are complemented by means of a remote management interface, from which the user can configure the functionalities of the sensors, visualize the network status as well as analyze the diagnosis evolution. The sensor performance, in terms of power consumption and fault detection, has been analyzed by means of experimental results.
AB - Advanced sensing strategies in the industrial sector are becoming a valued technological answer to increase the performance and competitiveness. The development of enhanced sensing solutions considering both technology and monitoring requirements is, nowadays, subject of concern in the industrial maintenance field. In this context, this paper presents a novel self-powered wireless sensor applied to condition monitoring of gears. The proposed sensor is based on a modular architecture, offering multipoint sensing, local wireless communication, multisource energy harvesting, and embedded diagnosis algorithm for mechanical fractures detection based on acoustic emission analysis. The developments are complemented by means of a remote management interface, from which the user can configure the functionalities of the sensors, visualize the network status as well as analyze the diagnosis evolution. The sensor performance, in terms of power consumption and fault detection, has been analyzed by means of experimental results.
KW - Acoustic emission (AE)
KW - Health monitoring
KW - Intelligent sensor
KW - Power harvesting
KW - Remote monitoring
KW - Wireless sensor network
UR - https://www.scopus.com/pages/publications/84959242568
U2 - 10.1109/TIM.2015.2476278
DO - 10.1109/TIM.2015.2476278
M3 - Article
AN - SCOPUS:84959242568
SN - 0018-9456
VL - 65
SP - 15
EP - 24
JO - IEEE Transactions on Instrumentation and Measurement
JF - IEEE Transactions on Instrumentation and Measurement
IS - 1
M1 - 2476278
ER -