Caldero Bardaji P, Zoeke D (2019)
Publication Type: Journal article
Publication year: 2019
Book Volume: 19
Article Number: 5398
Journal Issue: 24
DOI: 10.3390/s19245398
While there is a wide range of approaches to monitor industrial machinery through their static components, rotating components are usually harder to monitor, since sensors are difficult to be mounted on them and continuously read during operation. However, the characteristics of rotating components may provide useful information about the machine condition to be included in monitoring algorithms, specially for long-term data analysis. In this work, wireless vibration monitoring of rotating machine parts is investigated using surface acoustic wave (SAW) radio frequency identification (RFID) tags coupled with sensors. The proposed augmented transponder solution, combined with low-latency interrogation and signal processing, enables real-time identification and wideband vibration sensing. On top of that, a multi-channel interrogation approach is used to compensate motion effects. This approach enhances the signal-to-noise ratio of low-power high-frequency components present on the vibration signatures and enables discriminant information extraction from rotating machine parts. Final feasibility is evaluated with induction motors and vibration measurements on rotating shafts are verified. In addition, a condition classification algorithm is implemented in an experimental setup based on different motor states. The results of this work open the possibility to feed predictive maintenance algorithms using new features extracted in real-time from wideband vibration measurements on rotating components.
APA:
Caldero Bardaji, P., & Zoeke, D. (2019). Multi-channel real-time condition monitoring system based on wideband vibration analysis of motor shafts using SAW RFID tags coupled with sensors. Sensors, 19(24). https://dx.doi.org/10.3390/s19245398
MLA:
Caldero Bardaji, Pau, and Dominik Zoeke. "Multi-channel real-time condition monitoring system based on wideband vibration analysis of motor shafts using SAW RFID tags coupled with sensors." Sensors 19.24 (2019).
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