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Research and Application of a Fault Self-Diagnosis Method for Roots Flowmeter Based on WSN Node

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Abstract

In order to diagnose whether the photoelectric encoder of Roots flow meter is working well in assuring the wireless sensor networks (WSN) work properly, this paper discusses the features of Roots flow meter and proposes an on-line fault self-diagnosis method. First, a flexible fault sensing circuit is designed as a state detection module on WSN node. Second, a fault self-diagnosis method is proposed. The fault diagnosis method is based on the vibration frequency of Roots flow meter. The failure is diagnosed by whether the relationship between the measurement of instantaneous flow and the vibration frequency is correct. Experiment results demonstrate the fault self-diagnosis method is suit to the application in WSN nodes and the WSN nodes have been successfully applied to the oil tank trucks.

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References

  1. Ashok, K. P. M., & Vaidehi, V. (2015). Anomalous event detection in traffic video based on sequential temporal patterns of spatial interval events[J]. KSII Transactions on Internet and Information Systems (TIIS), 9(1), 169–189.

    Google Scholar 

  2. Geeta, D. D., Nalini, N., & Biradar, R. C. (2013). Fault tolerance in wireless sensor network using hand-off and dynamic power adjustment approach[J]. Journal of Network and Computer Application, 36(4), 1174–1185.

    Article  Google Scholar 

  3. Yoo, S. E., Chong, P. K., Kim, S. H., & Pham, M. L. (2014). Verification and validation of the performance of WSN[J]. International Journal of Distributed Sensor Networks, 12, 1–2.

    Google Scholar 

  4. Yoo, M., Wu, F., & Qiao, C. M. (2015). Recent advances of ICT convergence on WSN applications[J]. International Journal of Distributed Sensor Networks, 5, 1–3.

    Article  Google Scholar 

  5. Tajeddine, A., Kayssi, A., Chehab, A., Elhajj, I., & Itani, W. (2015). A centralized trust-based efficient routing protocol with authentication for wireless sensor networks[J]. Sensors, 15, 3299–3333.

    Article  Google Scholar 

  6. Hou, L., & Bergmann, N. W. (2012). Novel industrial wireless sensor networks for machine condition monitoring and fault diagnosis[J]. IEEE Transactions on Instrumentation and Measurement, 61(10), 2787–2798.

    Article  Google Scholar 

  7. Mahapatro, A., & Khilar, P. M. (2014). Online fault diagnosis of wireless sensor networks[J]. Central European. Journal of Computer Science, 4(1), 30–44.

    Google Scholar 

  8. Horst, R., Jewett, D., & Lenoski, D. (1993). The risk of data corruption in microprocessor-based systems[C]. In The Twenty-Third International Symposium on Fault-Tolerant Computing, Toulouse, France, 22–24 June 1993, pp. 576–585.

  9. Avizienis, A. (2000). Design diversity and the immune system paradigm: cornerstones for information system survivability. In Third Information Survivability Workshop, ISW-2000. Boston, Massachusetts, USA, pp. 3–6.

  10. Biscarri, F., Menéndez, A., & Molina, A. (2004). Flowmeter random error estimation byan analytical variance estimation method: a simple test bed[J]. Control Engineering Practice, 12, 857–863.

    Article  Google Scholar 

  11. Garvie, M., & Thompson, A. (2003). Evolution of combinatonial and sequential on-line self-diagnosing hardware. In Proceedings of the 2003 NASA/Dod Conference on Evolvable Hardware. DC, USA, pp. 177–183.

  12. Harte, S., Rahman, A., & Razeeb, K. M. (2005). Fault tolerance in sensor networks using self-diagnosing sensor nodes. In The IEEE International Workshop on Intelligent Environments, pp. 7–12.

  13. Chen, J., Kher, S., & Somani, A. (2006). Distributed fault detection of wireless sensor networks. In Proceedings of the International Conference on Mobile Computing and Networkings, Los Angeles, CA, USA (pp. 65–72). New York, USA: ACM.

  14. Luo, X., Dong, M., & Huang, Y. (2006). On distributed fault-tolerant detection in wireless sensor networks. IEEE Transactions on Computers, 55, 58–70.

    Article  Google Scholar 

  15. Li, Z., & Cheng, X. (2013). Research on fault diagnosis of wireless sensor node on module level [J]. Chinese Journal of Scientific Instrument, 34(12), 2763–2769. (Chinese).

    Google Scholar 

  16. Shang, S.-Y., Zhao, W.-X., & Yu, X.-B. (2010). Errors analyses of Luoci flowmeters in the measurement of crude oil[J]. Technology Supervision in Petroleum Industry, 26(6), 30–31. (Chinese).

    Google Scholar 

  17. Chen, Y.-X., Wan, Y., Zhou, Q.-N., Lu, J.-M., & Zhang L. (2016). Discussion on the common test methods of gas Roots flowmeter[J]. Metrology & Measurement Technique, 43(8), 35–37. (Chinese).

    Google Scholar 

  18. Wang, K.-Y., Wu, S.-X., Shen, W.-X., & Bu, J. (2012). The basic framework of gas flow device based on double Roots type meter method[J]. Acta Metrologica Sinica, 33(5A), 159–162. (Chinese).

    Google Scholar 

  19. Shi, P., Li, X., & He, L. (2008). Diesel engine speed measuring instrument based on vibration[J]. Agricultural Mechanization Research, 8, 197–199, 205. (Chinese).

  20. Zhou, Q. (2004). Research on fault diagnosis method of turbine pump based on support vector machine and its application[D]. Haerbing: Harbin Institute of Technology. (Chinese).

    Google Scholar 

  21. Tan, C., & Yang, D. (2009) Design and implementation of vibration detection system for mechanical equipment[J]. Dazhong Keji, 9, 125–126, 90. (Chinese).

  22. Ren, X.-P., Ma, W.-S., Yang, W.-Z., & Su, F.-Q. (2008). Investigation of fault diagnosis of decelerators based on wavelet packet analysis[J]. Noise and Vibration Control, 5, 73–76. (Chinese).

    Google Scholar 

  23. Feng, Z.-G., Wang, Q., & Xu, T. (2008). Sensor fault diagnosis based on wavelet packet and support vector machines[J]. Journal of Nanjing university of science and technology, 32(5), 609–614. (Chinese).

    Google Scholar 

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Acknowledgements

The authors would like to thank the Chinese Postdoctoral Science Foundation (No. 20100480208) for financial support.

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Correspondence to Xiang-guang Chen.

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Sun, Ym., Liu, Xj., Chen, Xg. et al. Research and Application of a Fault Self-Diagnosis Method for Roots Flowmeter Based on WSN Node. Wireless Pers Commun 95, 2315–2330 (2017). https://doi.org/10.1007/s11277-017-4104-8

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