LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

High accuracy synchronous acquisition algorithm of multi-hop sensor networks for machine vibration monitoring

Photo by markusspiske from unsplash

Abstract Condition-based maintenance (CBM) is an effective way to reduce the maintenance costs and improve the reliability of machine. Considering that wireless sensor networks (WSNs) can be employed in some… Click to show full abstract

Abstract Condition-based maintenance (CBM) is an effective way to reduce the maintenance costs and improve the reliability of machine. Considering that wireless sensor networks (WSNs) can be employed in some special applications where wired mechanical vibration monitoring systems are hard to be deployed, WSNs attracts much attentions in the field of mechanical vibration monitoring. But it is still facing many challenges in this filed, synchronization data acquisition is a crucial one of them. In this paper, the synchronization acquisition algorithm of multi-hop network for mechanical vibration monitoring is focused. In this algorithm, nodes are organized as cluster network. To realize synchronization acquisition triggering, transmission delay of beacon between gateway and each acquisition node is calculated and compensated. To improve the accuracy of synchronous acquisition, crystal oscillator drift of routers and acquisition nodes are measured and calibrated. While acquiring data, the accumulatived synchronization errors between acquisition nodes can be estimate and calibrated in real time. Finally, a three-hop network is employed to test the performance of the algorithm. The results show that the maximum synchronization triggering error is 0.64 μs, the average value is 0.3663 μs. At the sampling rate of 40 ksps, the maximum synchronization acquisition error is 1.053 μs, the average value is 0.826 μs in 100 s.

Keywords: hop; acquisition; vibration monitoring; algorithm

Journal Title: Measurement
Year Published: 2017

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.