Journal of Zhejiang University-SCIENCE A

, Volume 18, Issue 6, pp 443–453 | Cite as

Research on transmission performance of a surface acoustic wave sensing system used in manufacturing environment monitoring

  • Cong-cong Luan
  • Xin-hua Yao
  • Qiu-yue Chen
  • Jian-zhong Fu
Article

Abstract

Surface acoustic wave (SAW) sensors show great promise in monitoring fast-rotating or moving machinery in manufacturing environments, and have several advantages in the measurement of temperature, torque, pressure, and strain because of their passive and wireless capability. However, very few studies have systematically attempted to evaluate the characteristics of SAW sensors in a metal environment and rotating structures, both of which are common in machine tools. Simulation of the influence of the metal using CST software and a series of experiments with an SAW temperature sensor in real environments were designed to investigate the factors that affect transmission performance, including antenna angles, orientations, rotation speeds, and a metallic plate, along with the interrogator antenna–SAW sensor antenna separation distance. Our experimental measurements show that the sensor’s optimal placement in manufacturing environments should take into account all these factors in order to maintain system measurement and data transmission capability. As the first attempt to systematically investigate the transmission characteristics of the SAW sensor used in manufacturing environment, this study aims to guide users of SAW sensor applications and encourage more research in the field of wireless passive SAW sensors in monitoring applications.

Key words

Transmission performance Surface acoustic wave (SAW) Sensor Manufacturing environment Monitoring 

声表面波传感系统制造环境监测通信性能研究

摘要

目 的

旋转和高速运动机械结构的状态监测因缺少有效的技术手段而成为制约其性能提升的关键因素。声表面波传感实现了传感器的无线和无源化,有望解决上述难题。本文旨在研究复杂制造环境中金属件和旋转运动对声表面波传感器通信性能的影响,为其应用提供理论基础和技术参考。

创新点

1. 揭示了金属件和传感器之间不同相对位置和距离对传感系统测量和通信性能的影响;2. 分析了机械结构旋转运动中影响传感系统通信性能的因素,为传感器结构设计和配置优化提供了参考依据。

方法

1. 通过仿真计算,研究金属件对声表面波传感系统的影响;2. 实验研究金属环境及旋转运动中影响声表面波传感系统通信性能的关键因素。

结论

1. 金属环境对声表面波传感系统有重要影响,传输天线下方的金属能够增强系统传输功率,但平行于天线附近的金属会削弱传输功率;2. 质询器天线与传感器天线的相对夹角对传感器通信性能有重要影响;3. 安装位置对传感器测量性能和信号传输功率均有显著影响;4. 动态实验证明了声表面波传感系统应用于主轴温度监测的可行性。

关键词

通信性能 声表面波 传感器 制造环境 监测 

CLC number

TP212.11 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Binder, A., Fachberger, R., 2011. Wireless SAW temperature sensor system for high-speed high-voltage motors. IEEE Sensors Journal, 11(4):966–970. http://dx.doi.org/10.1109/JSEN.2010.2076803CrossRefGoogle Scholar
  2. Binder, A., Fachberger, R., Kaldjob, E., et al., 2009. Packaging and antenna design for wireless SAW temperature sensors in metallic environments. Sensors IEEE, p.807–810. http://dx.doi.org/10.1109/ICSENS.2009.5398549Google Scholar
  3. Boccard, J.M., Reindl, L., 2012. Ceramic and magnetic loop antennas for wireless interrogation of SAW resonators on rotating machinery. IEEE International Workshop on Antenna Technology, p.112–115. http://dx.doi.org/10.1109/IWAT.2012.6178411Google Scholar
  4. Boccard, J.M., Katus, P., Renevier, R., et al., 2013. Near-field interrogation of SAW resonators on rotating machinery. Journal of Sensors and Sensor Systems, 2(2):147–156. http://dx.doi.org/10.5194/jsss-2-147-2013CrossRefGoogle Scholar
  5. Borrero, G.A., Bravo, J.P., Mora, S.F., et al., 2013. Design and fabrication of SAW pressure, temperature and impedance sensors using novel multiphysics simulation models. Sensors and Actuators A: Physical, 203: 204–214. http://dx.doi.org/10.1016/j.sna.2013.08.021CrossRefGoogle Scholar
  6. Dixon, B., Kalinin, V., Beckley, J., et al., 2006. A second generation in-car tire pressure monitoring system based on wireless passive SAW sensors. International Frequency Control Symposium and Exposition, p.374-380.CrossRefGoogle Scholar
  7. Fachberger, R., Erlacher, A., 2009. Monitoring of the temperature inside a lining of a metallurgical vessel using a SAW temperature sensor. Procedia Chemistry, 1(1): 1239–1242. http://dx.doi.org/10.1016/j.proche.2009.07.309CrossRefGoogle Scholar
  8. Haslett, C., 2008. Essentials of Radio Wave Propagation. Cambridge University Press, UK.Google Scholar
  9. Hirtenfelder, F., 2007. Effective antenna simulations using CST MICROWAVE STUDIO®. 2nd International ITG Conference on Antennas, p.239. http://dx.doi.org/10.1109/INICA.2007.4353972CrossRefGoogle Scholar
  10. Hu, J.X., Zhao, J., He, L.S., et al., 2014. Temperature monitoring system for switchgear based on surface acoustic wave. Piezoelectrics & Acoustooptics, 36(2):214–216.Google Scholar
  11. Hudak, N.S., Amatucci, G.G., 2008. Small-scale energy harvesting through thermoelectric, vibration, and radiofrequency power conversion. Journal of Applied Physics, 103(10):101301–101324. http://dx.doi.org/10.1063/1.2918987CrossRefGoogle Scholar
  12. Kim, J., Luis, R., Smith, M.S., et al., 2015. Concrete temperature monitoring using passive wireless surface acoustic wave sensor system. Sensors and Actuators A: Physical, 224: 131–139. http://dx.doi.org/10.1016/j.sna.2015.01.028CrossRefGoogle Scholar
  13. Li, S., Yao, X., Fu, J., 2014. Power output characterization assessment of thermoelectric generation in machine spindles for wire-less sensor driving. Sensor Review, 34(2):192–200. http://dx.doi.org/10.1108/SR-03-2013-642CrossRefGoogle Scholar
  14. Liu, B., Han, T., Zhang, C., 2015. Error correction method for passive and wireless resonant SAW temperature sensor. IEEE Sensors Journal, 15(6):3608–3614. http://dx.doi.org/10.1109/JSEN.2015.2394776CrossRefGoogle Scholar
  15. Marian, V., Allard, B., Vollaire, C., et al., 2012. Strategy for microwave energy harvesting from ambient field or a feeding source. IEEE Transactions on Power Electronics, 27(11):4481–4491. http://dx.doi.org/10.1109/TPEL.2012.2185249CrossRefGoogle Scholar
  16. Marinescu, I., Axinte, D.A., 2011. An automated monitoring solution for avoiding an increased number of surface anomalies during milling of aerospace alloys. International Journal of Machine Tools and Manufacture, 51(4): 349–357. http://dx.doi.org/10.1016/j.ijmachtools.2010.10.005CrossRefGoogle Scholar
  17. Sandacci, S., Gilkes, J.E., 2007. Rotary Signal Couplers. US Pantent 20070024387.Google Scholar
  18. Stoney, R., Donohoe, B., Geraghty, D., et al., 2012. The development of surface acoustic wave sensors (SAWs) for process monitoring. Procedia CIRP, 1: 569–574. http://dx.doi.org/10.1016/j.procir.2012.05.001CrossRefGoogle Scholar
  19. Stoney, R., Pullen, T., Aldwell, B., et al., 2014. Observations of surface acoustic wave strain and resistive strain measurements on broaching tools for process monitoring. Procedia CIRP, 14: 66–71. http://dx.doi.org/10.1016/j.procir.2014.03.024CrossRefGoogle Scholar
  20. Szarka, G.D., Stark, B.H., Burrow, S.G., 2012. Review of power conditioning for kinetic energy harvesting systems. IEEE Transactions on Power Electronics, 27(2):803–815. http://dx.doi.org/10.1109/TPEL.2011.2161675CrossRefGoogle Scholar
  21. Tang, L., Wang, K.C., Huang, Y., 2009. Performance evaluation and reliable implementation of data transmission for wireless sensors on rotating mechanical structures. Structural Health Monitoring, 8(2):113–124. http://dx.doi.org/10.1177/1475921708094795CrossRefGoogle Scholar
  22. Tang, L., Liu, M., Wang, K.C., et al., 2012. Study of path loss and data transmission error of IEEE 802.15.4 compliant wireless sensors in small-scale manufacturing environments. The International Journal of Advanced Manufacturing Technology, 63(5):659–669. http://dx.doi.org/10.1007/s00170-012-3928-3CrossRefGoogle Scholar
  23. Wang, K.C., Jacob, J., Tang, L., et al., 2008. Transmission error avoidance for IEEE 802.15.4 wireless sensors on rotating structures. Proceedings of 17th International Conference on the Computer Communications and Networks.Google Scholar
  24. White, R., Voltmer, F., 1965. Direct piezoelectric coupling to surface elastic waves. Applied Physics Letters, 7(12):314–316. http://dx.doi.org/10.1063/1.1754276CrossRefGoogle Scholar
  25. Xia, C.H., Fu, J.Z., Xu, Y.T., et al., 2014. A novel method for fast identification of a machine tool selected point temperature rise based on an adaptive unscented Kalman filter. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 15(10):761–773. http://dx.doi.org/10.1631/jzus.A1400074CrossRefGoogle Scholar
  26. Yao, X., Li, S., Fu, J., 2015. Heat exchanger design for a thermoelectric module to drive wireless sensors in spindle monitoring. Sensor Review, 35(1):51–61. http://dx.doi.org/10.1108/SR-08-2013-720CrossRefGoogle Scholar
  27. Zhang, D., Fan, Y., Shimotori, T., et al., 2012. Performance evaluation of power management systems in microbial fuel cell-based energy harvesting applications for driving small electronic devices. Journal of Power Sources, 217: 65–71. http://dx.doi.org/10.1016/j.jpowsour.2012.06.013CrossRefGoogle Scholar
  28. Zhang, D., Ming, Z., Liu, G., et al., 2014. An empirical study of radio signal strength in sensor networks using MICA2 nodes. Journal of Shenzhen University Science and Engineering, 31(1):63–70. http://dx.doi.org/10.3724/SP.J.1249.2014.01063CrossRefGoogle Scholar

Copyright information

© Zhejiang University and Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Cong-cong Luan
    • 1
  • Xin-hua Yao
    • 1
    • 2
  • Qiu-yue Chen
    • 1
  • Jian-zhong Fu
    • 1
    • 2
  1. 1.State Key Laboratory of Fluid Power and Mechatronic Systems, College of Mechanical EngineeringZhejiang UniversityHangzhouChina
  2. 2.Key Laboratory of 3D Printing Process and Equipment of Zhejiang Province, College of Mechanical EngineeringZhejiang UniversityHangzhouChina

Personalised recommendations