Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Wireless Personal Communications
Erschienen in: Wireless Personal Communications 3/2017

01.04.2017

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

verfasst von: Yu-mei Sun, Xue-jiao Liu, Xiang-guang Chen, Qiao-yan Sun, Jun Zhao

Erschienen in: Wireless Personal Communications | Ausgabe 3/2017

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

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.
Vorheriger Artikel Pipe Defect Detection with Remote Magnetic Inspection and Wavelet Analysis
Nächster Artikel Research and Application of Wireless Security Monitoring System in Chemistry and Chemical Engineering Laboratory

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Literatur
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.
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.CrossRef
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.
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.CrossRef
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.CrossRef
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.CrossRef
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.
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.CrossRef
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.CrossRef
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).
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).
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).
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).
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).
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).
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).
Metadaten
Titel
Research and Application of a Fault Self-Diagnosis Method for Roots Flowmeter Based on WSN Node
verfasst von
Yu-mei Sun
Xue-jiao Liu
Xiang-guang Chen
Qiao-yan Sun
Jun Zhao
Publikationsdatum
01.04.2017
Verlag
Springer US
Erschienen in
Wireless Personal Communications / Ausgabe 3/2017
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-017-4104-8

Weitere Artikel der Ausgabe 3/2017

Wireless Personal Communications 3/2017 Zur Ausgabe

OriginalPaper

Performance Analysis on Filter Parameters and Sub-bands Distribution of Universal Filtered Multi-Carrier

OriginalPaper

A Delay Aware Super-Peer Selection Algorithm for Gradient Topology Utilizing Learning Automata

OriginalPaper

Research on Time Synchronization Algorithm of High Precision and Low Power Consumption Based on IRBRS WSNs

OriginalPaper

Multi-factor and Distributed Clustering Routing Protocol in Wireless Sensor Networks

OriginalPaper

The Mobile Media Based Emergency Management of Web Events Influence in Cyber-Physical Space

OriginalPaper

An Arterial Green-Wave Synchronous Coordination Model for Bus and Non-bus Lanes Based on Platoon Dispersion Theory

Neuer Inhalt

    Bildnachweise