A novel industrial wireless sensor network for condition monitoring and fault diagnosis of electrical machines

被引：4

作者：

School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia ^{[1
]}

机构：

[1] School of Information Technology and Electrical Engineering, University of Queensland, Brisbane

来源：

Aust. J. Electr. Electron. Eng. | 2013年 / 4卷 / 505-514期

关键词：

Condition monitoring; Electrical machines; Fault diagnosis; Industrial wireless sensor networks (IWSNs); principal component analysis (PCA);

D O I：

10.7158/E12-170.2013.10.4

中图分类号：

学科分类号：

摘要：

A novel industrial wireless sensor network (IWSN) for condition monitoring and fault diagnosis of electrical machines is presented, in which on-sensor fault diagnosis based on principal component analysis is explored to address the tension between the high system requirements of electrical machine monitoring and the resource constrained characteristics of IWSN sensor nodes. The prototype system is evaluated with a single phase induction motor monitoring system. Normal motor working conditions and two types of motor faults, ie. loose feet and mass imbalance, are monitored to validate the feasibility of the proposed system. The results show that using on-sensor fault diagnosis can reduce transmission data by 99.8%, decrease energy consumption, and prolong node lifetime from 106 to 153 h, an increase of 44%. The experimental results also indicate that the proposed approach has high fault diagnosis accuracy. © Institution of Engineers Australia 2013.

引用

页码：505 / 514

页数：9

共 23 条

[1]

Akyildiz I.F., Su W., Sankarasubramaniam Y., Cayirci E., Wireless sensor networks: A survey, Computer Networks, 38, 4, pp. 393-422, (2002)

[2]

Albrecht P.F., Appiarius J.C., McCoy R.M., Owen E.L., Sharma D.K., Assessment of the reliability of motors in utility applications - updated, IEEE Transactions on Energy Conversion, EC-1, 1, pp. 39-46, (1986)

[3]

Chang W.-W., Sung T.-J., Huang H.-W., Hsu W.-C., Kuo C.-W., Chang J.-J., Hou Y.-T., Lan Y.-C., Kuo W.-C., Lin Y.-Y., Yang Y.-J., A smart medication system using wireless sensor network technologies, Sensors and Actuators A: Physical, 172, pp. 315-321, (2011)

[4]

Filippetti F., Franceschini G., Tassoni C., Vas P., Recent developments of induction motor drives fault diagnosis using AI techniques, IEEE Transactions on Industrial Electronics, 47, pp. 994-1004, (2000)

[5]

Flammini A., Marioli D., Sisinni E., Taroni A., Design and implementation of a wireless fieldbus for plastic machineries, IEEE Transactions on Industrial Electronics, 56, pp. 747-755, (2009)

[6]

Essential Insight. Mesh Bently Nevada Wireless Condition Monitoring System for Essential Assets, (2010)

[7]

Gungor V.C., Hancke G.P., Industrial wireless sensor networks: Challenges, design principles, and technical approaches, IEEE Transactions on Industrial Electronics, 56, pp. 4258-4265, (2009)

[8]

Hou L., Bergmann N.W., System requirements for industrial wireless sensor networks, IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2010), pp. 1-8, (2010)

[9]

Hou L., Bergmann N.W., Induction motor condition monitoring using industrial wireless sensor networks, Sixth International Conference on Intelligent Sensors, Sensor Networks and Information Processing, pp. 49-54, (2010)

[10]

Hou L., Bergmann N.W., Induction motor fault diagnosis using industrial wireless sensor networks and Dempster-Shafer classifier fusion, Annual Conference of the IEEE Industrial Electronics Society (IECON 2011), pp. 2905-2910, (2011)

← 1 2 3 →