This paper investigates the use of giant magneto resistive (GMR) sensor as a part of wireless sensor node to detect the vibrations of machines for equipment health monitoring purpose. In this study, a GMR sensor is connected through a signal conditioner to a wireless node. By exploiting the sensitivity of GMR sensors to near-field changes in magnetic flux, it is postulated that GMR sensor could detect vibration of a ferromagnetic structure without contact. The wireless GMR sensor node samples the signal of the sensor and transmits it wirelessly to a personal computer to display the frequency spectrum. Preliminary tests indicated that the sensor is able to detect the vibration of a 440-Hz tuning fork and the increase vibration due to imbalance of a rotor on a fault simulator. Vibration analysis is one way to observe the health condition of a machine. Moving parts of a machine generate vibrations, which can be observed in the frequency spectrum of approximately 10 Hz to S kHz. Faults of typical rotating machinery such as misalignment, imbalance and bearing wear out will produce increased amplitudes of vibration and exhibit frequency harmonics. As such, the condition of bearings and other moving components can be monitored. This study demonstrates the feasibility of using wireless GMR sensor node for detection of vibrations of a ferromagnetic structure.
[1]
T. A. Harris,et al.
Rolling Bearing Analysis - 2 Volume Set
,
2006
.
[2]
M. Perez,et al.
Detection of Bearing Faults in Cage Induction Motors Fed by Frequency Converter using Spectral Analysis of Line Current
,
2005,
IEEE International Conference on Electric Machines and Drives, 2005..
[3]
John S. Wilson,et al.
Sensor Technology Handbook
,
2004
.
[4]
J. Alberola,et al.
Vibration Detector based on GMR Sensors
,
2007,
2007 IEEE Instrumentation & Measurement Technology Conference IMTC 2007.
[5]
D.R. Munoz,et al.
Generalized Impedance Converter as a New Sensor Signal Conditioning Circuit
,
2005,
2005 IEEE Instrumentationand Measurement Technology Conference Proceedings.
[6]
Ramon Pallas-Areny,et al.
Basics of analog differential filters
,
1996
.