Study of Speed-Dependent Packet Error Rate for Wireless Sensor on Rotating Mechanical Structures

Wireless sensors on rotating mechanical structures have rich and fast changing multipath that cannot be easily predicted by conventional regression approaches in time for effective transmission coding or power control, resulting in deteriorated transmission quality. This study aims to study the speed-dependent packet error rate (PER) of wireless sensor radios on rotating mechanical structures. A series of rotating IEEE 802.15.4 sensor radio transmission experiments and vector network analyzer measurements have been conducted to derive and validate a predictive PER model for a fast rotating sensor radio channel based on channel impulse response measurements. The proposed predictive PER model, including power attenuation, bit error rate (BER) and PER sub-models, captures the channel property of rotating sensors based on the received signal strength and the radio receiving sensitivity. The PER model has accurately predicted the PER profile of sensors on a rotating machine tool spindle as well as a rotating plate of a prototype rotation system. The analysis provides an in-depth understanding of how multipath propagation causes the fast power variation and the resulting speed-dependent PER for wireless sensors on rotating mechanical structures.

[1]  T. Lindh,et al.  Applicability of ZigBee technology to electric motor rotor measurements , 2006, International Symposium on Power Electronics, Electrical Drives, Automation and Motion, 2006. SPEEDAM 2006..

[2]  Kan Yu,et al.  Reliable and Low Latency Transmission in Industrial Wireless Sensor Networks , 2011, ANT/MobiWIS.

[3]  Giuseppe Anastasi,et al.  A Comprehensive Analysis of the MAC Unreliability Problem in IEEE 802.15.4 Wireless Sensor Networks , 2011, IEEE Transactions on Industrial Informatics.

[4]  Kuang-Ching Wang,et al.  Transmission Error Avoidance for IEEE 802.15.4 Wireless Sensors on Rotating Structures , 2008, 2008 Proceedings of 17th International Conference on Computer Communications and Networks.

[5]  Luc Martens,et al.  The industrial indoor channel: statistical analysis of the power delay profile , 2008 .

[6]  Chenyang Lu,et al.  Dynamic Conflict-Free Transmission Scheduling for Sensor Network Queries , 2011, IEEE Transactions on Mobile Computing.

[7]  Jose Chilo,et al.  Industrial indoor environment characterization - Propagation models , 2011, 10th International Symposium on Electromagnetic Compatibility.

[8]  P. Levis,et al.  RSSI is Under Appreciated , 2006 .

[9]  H. M. Hashemian,et al.  Wireless sensors for predictive maintenance of rotating equipment in research reactors , 2011 .

[10]  Justin C.-I. Chuang.  The Effects of Time Delay Spread on Portable Radio Communications Channels with Digital Modulation , 1987, IEEE J. Sel. Areas Commun..

[11]  Kate A. Remley,et al.  Measurements in harsh RF propagation environments to support performance evaluation of wireless sensor networks , 2009 .

[12]  U. H. Sheikh Asrar,et al.  On the design of a wireless network in an industrial environment , 2010, 2010 IEEE International Conference on Communication Systems.

[13]  A Binder,et al.  Wireless SAW Temperature Sensor System for High-Speed High-Voltage Motors , 2011, IEEE Sensors Journal.

[14]  Yookun Cho,et al.  EARQ: Energy Aware Routing for Real-Time and Reliable Communication in Wireless Industrial Sensor Networks , 2009, IEEE Transactions on Industrial Informatics.

[15]  S.M. Elnoubi,et al.  Wideband measurements and modeling of the indoor radio channel at 10 GHz. I. Frequency domain analysis , 1998, Proceedings of the Fifteenth National Radio Science Conference. NRSC '98 (Cat. No.98EX109).

[16]  Kuang-Ching Wang,et al.  Channel Characterization and Link Quality Assessment of IEEE 802.15.4-Compliant Radio for Factory Environments , 2007, IEEE Transactions on Industrial Informatics.

[17]  Yong Huang,et al.  Error pattern analysis for data transmission of wireless sensors on rotating industrial structures , 2008, SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.

[18]  Gerhard P. Hancke,et al.  Industrial Wireless Sensor Networks: Challenges, Design Principles, and Technical Approaches , 2009, IEEE Transactions on Industrial Electronics.

[19]  Kuang-Ching Wang,et al.  Performance Evaluation and Reliable Implementation of Data Transmission for Wireless Sensors on Rotating Mechanical Structures , 2009 .

[20]  Jianzhong Fu,et al.  A Wireless Temperature Measuring System for Rotating Spindle Based on ZigBee , 2011 .

[21]  Krishnamurthy Giridhar,et al.  Robust Channel Tracking in Fast Fading MIMO channels , 2008, IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference.

[22]  R. Shanmugam.  Introduction to Time Series and Forecasting , 1997 .

[23]  Kuang-Ching Wang,et al.  Wireless sensors on rotating structures: performance evaluation and radio link characterization , 2007, WinTECH '07.

[24]  Nacer Abouchi,et al.  Wireless Sensors for Instrumented Machines: Propagation Study for Stationary Industrial Environments , 2009, 2009 IEEE 14th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks.

[25]  Richard A. Davis,et al.  Introduction to time series and forecasting , 1998 .

[26]  Francisco J. A. Cardoso,et al.  A hybrid sensor network for the real-time condition monitoring of rotating machinery , 2010, 2010 6th IEEE International Conference on Distributed Computing in Sensor Systems Workshops (DCOSSW).