Smart Structures and Systems

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Sensor placement strategy for high quality sensing in machine health monitoring

  • Gao, Robert X. (Department of Mechanical and Industrial Engineering, University of Massachusetts) ;
  • Wang, Changting (Global Research Center, General Electric Corporation) ;
  • Sheng, Shuangwen (Department of Mechanical and Industrial Engineering, University of Massachusetts)
  • Received : 2004.08.30
  • Accepted : 2005.03.23
  • Published : 2005.04.25
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Abstract

This paper presents a systematic investigation of the effect of sensor location on the data quality and subsequently, on the effectiveness of machine health monitoring. Based on an analysis of the signal propagation process from the defect location to the sensor, numerical simulations using finite element modeling were conducted on a bearing test bed to determine the signal strength at several representative sensor locations. The results showed that placing sensors closely to the machine component being monitored is critical to achieving high signal-to-noise ratio, thus improving the data quality. Using millimeter-sized piezoceramic plates, the obtained results were evaluated experimentally. A comparison with a set of commercial vibration sensors verified the developed structural dynamics-based sensor placement strategy. It further demonstrated that the proposed shock wave-based sensing technique provided an effective alternative to vibration measurement, while requiring less space for sensor installation.

Keywords

References

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