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C.M. Tarawneh¹, R. Estrada², B.M. Wilson³ and A. Martin⁴

¹Mechanical Engineering Department, University of Texas-Pan American, Edinburg, Texas, USA
²Electrical Engineering Department, University of Texas-Pan American, Edinburg, Texas, USA
³Research and Development, Amsted Rail, Granite City, Illinois, USA
⁴Research and Development, IONX, West Chester, Pennsylvania, USA

Keywords: wireless sensor nodes, bearing condition monitoring, bearing temperature analysis, derailment prevention systems.

Summary

Current wayside detection methods utilized for freight wagon bearing health monitoring do not constitute a true continuous bearing condition monitoring system, and have resulted in costly false bearing setouts and removals. Consequently, efforts in this area have shifted towards more efficient forms of on-board detection. One such system uses battery-operated wireless sensor nodes (WSNs) attached to the bearing adapters and managed by a central monitoring unit (CMU). This system is capable of continuous monitoring and recording (at set sampling rates and frequencies) of the temperature of each bearing within the freight wagon along with the ambient temperature. Laboratory conducted experiments and subsequent fieldtest trials have verified that this system provides accurate bearing condition monitoring, and with the use of carefully developed criteria, can also be used to predict the onset of bearing failure. The main drawback of this system, however, is battery life. Hence, the WSN-based system has undergone several optimization processes which include prototype redesign and reductions in the data sampling rate, frequency, storage, and upload in order to prolong the battery life of the WSNs and CMU. This paper presents a detailed statistical analysis of data acquired from several field-implemented trials with varying data sampling rates, frequencies, storage, and upload. The main objective of the study presented here is to examine the effects of the latter factors on the developed WSN criteria in an attempt to determine the optimal parameters and thresholds that will provide uncompromised system accuracy while maximizing battery life.

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Front Page Browse CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Proceedings ISSN 1759-3433 CCP: 104 PROCEEDINGS OF THE SECOND INTERNATIONAL CONFERENCE ON RAILWAY TECHNOLOGY: RESEARCH, DEVELOPMENT AND MAINTENANCE Edited by: J. Pombo Paper 236 Field Implementation Statistical Analysis of an Emerging Bearing Condition Monitoring System C.M. Tarawneh¹, R. Estrada², B.M. Wilson³ and A. Martin⁴ ¹Mechanical Engineering Department, University of Texas-Pan American, Edinburg, Texas, USA ²Electrical Engineering Department, University of Texas-Pan American, Edinburg, Texas, USA ³Research and Development, Amsted Rail, Granite City, Illinois, USA ⁴Research and Development, IONX, West Chester, Pennsylvania, USA doi:10.4203/ccp.104.236 purchase the full-text of this paper Full Bibliographic Reference for this paper C.M. Tarawneh, R. Estrada, B.M. Wilson, A. Martin, "Field Implementation Statistical Analysis of an Emerging Bearing Condition Monitoring System", in J. Pombo, (Editor), "Proceedings of the Second International Conference on Railway Technology: Research, Development and Maintenance", Civil-Comp Press, Stirlingshire, UK, Paper 236, 2014. doi:10.4203/ccp.104.236 Keywords: wireless sensor nodes, bearing condition monitoring, bearing temperature analysis, derailment prevention systems. Summary Current wayside detection methods utilized for freight wagon bearing health monitoring do not constitute a true continuous bearing condition monitoring system, and have resulted in costly false bearing setouts and removals. Consequently, efforts in this area have shifted towards more efficient forms of on-board detection. One such system uses battery-operated wireless sensor nodes (WSNs) attached to the bearing adapters and managed by a central monitoring unit (CMU). This system is capable of continuous monitoring and recording (at set sampling rates and frequencies) of the temperature of each bearing within the freight wagon along with the ambient temperature. Laboratory conducted experiments and subsequent fieldtest trials have verified that this system provides accurate bearing condition monitoring, and with the use of carefully developed criteria, can also be used to predict the onset of bearing failure. The main drawback of this system, however, is battery life. Hence, the WSN-based system has undergone several optimization processes which include prototype redesign and reductions in the data sampling rate, frequency, storage, and upload in order to prolong the battery life of the WSNs and CMU. This paper presents a detailed statistical analysis of data acquired from several field-implemented trials with varying data sampling rates, frequencies, storage, and upload. The main objective of the study presented here is to examine the effects of the latter factors on the developed WSN criteria in an attempt to determine the optimal parameters and thresholds that will provide uncompromised system accuracy while maximizing battery life. purchase the full-text of this paper (price £20) go to the previous paper go to the next paper return to the table of contents return to the book description purchase this book (price £65 +P&P)
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