Implementation of Wireless Temperature Sensors for Continuous Condition Monitoring of Railroad Bearings

2011 ◽  
Author(s):  
Javier A. Kypuros ◽  
Constantine M. Tarawneh ◽  
Andoni Zagouris ◽  
Sean Woods ◽  
Brent M. Wilson ◽  
...  
Keyword(s):  
Condition Monitoring ◽  
Health Monitoring ◽  
Continuous Monitoring ◽  
Sensor Nodes ◽  
Wireless Sensor Nodes ◽  
University Of Texas ◽  
Health Monitoring Systems ◽  
Pan American ◽  
Railroad Bearings ◽  
The University

At present there are no existing bearing health monitoring systems capable of continuous monitoring and tracking of railroad bearings on freight cars. Current wayside equipment is used to garner intermittent bearing cup temperatures, which at times could be every 65 km (∼40 mi) or more. Such devices are not designed to provide continuous condition monitoring which would enable users to assess the rate of bearing health degradation and predict when a bearing will require service. To this end, IONX, LLC, a subsidiary of Amsted Rail, Inc., has developed low power Wireless Sensor Nodes (WSNs) which can be retrofitted to existing bearing adapters. The WSNs provide continuous monitoring of bearing temperatures as well as the current ambient temperature. Since the nodes are affixed to the bearing adapter surface, a correlation is necessary to estimate the bearing cup temperature using the measured adapter surface temperature. This paper describes research conducted at The University of Texas-Pan American (UTPA) to devise a reliable mathematical model to correlate both temperatures. Additionally, these wireless nodes are currently in use on ten railroad cars that are part of an Australian fleet. The nodes have been collecting data since March 2010. The acquired data was used to devise and test a series of metrics that can automatically detect distressed bearings and predict time to maintenance. The development of bearing health monitoring metrics and their use to assess bearings in the Australian fleet is also discussed in this paper.

scholarly journals Use of Local Intelligence to Reduce Energy Consumption of Wireless Sensor Nodes in Elderly Health Monitoring Systems

Sensors ◽  
2014 ◽  
Vol 14 (3) ◽  
pp. 4932-4947 ◽  
Author(s):  
Thomas Lampoltshammer ◽  
Edison Pignaton de Freitas ◽  
Thomas Nowotny ◽  
Stefan Plank ◽  
João da Costa ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Health Monitoring ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Monitoring Systems ◽  
Wireless Sensor Nodes ◽  
Elderly Health ◽  
Health Monitoring Systems ◽  
Reduce Energy Consumption

Vibration Signatures of Temperature Trended Bearings in Field and Laboratory Testing

2009 ◽  
Author(s):  
Constantine M. Tarawneh ◽  
Javier A. Kypuros ◽  
Arturo A. Fuentes ◽  
Brent M. Wilson ◽  
Bertha A. Gonzalez ◽  
...  
Keyword(s):  
Friction And Wear ◽  
Vibration Signal ◽  
Laboratory Research ◽  
University Of Texas ◽  
Union Pacific ◽  
Bearing Vibration ◽  
Pan American ◽  
Testing Field ◽  
The University ◽  
Vibration Signatures

Over the past two years, a series of papers have been published concerning bearing temperature trending and a mechanism to explain this troubling phenomenon. In September of 2008, a collaborative field test between The Union Pacific Railroad (UP), Amsted Rail, Rail Sciences Inc. (RSI), and The University of Texas-Pan American (UTPA) was conducted to corroborate the findings of laboratory research and testing. Field and laboratory results confirm that temperature trended bearings exhibit vibration signals that can be distinguished from healthy bearings. Distinct primary frequencies and overtones associated with the axle, cone, cage, and rollers can be readily identified within a bearing vibration signal. In a previous paper, it was demonstrated that a trended bearing exhibits vibrations of higher magnitude. However, all characteristic frequencies appear in both healthy and trended bearings, but those that dominate, i.e., have higher magnitude, are distinct for trended bearings when compared to healthy bearings. The latter can be repeatedly demonstrated in both field and laboratory experiments. Moreover, the current work identifies and distinguishes between the primary bearing frequencies and those linked to roller misalignment, which is known to increase friction and wear, and consequently raise the bearing temperature.

Organic Functional Group Conversion

2013 ◽  
Author(s):  
Douglass F. Taber
Keyword(s):  
Hong Kong ◽  
Allylic Alcohol ◽  
Primary Alcohols ◽  
National Chemical Laboratory ◽  
Chemical Laboratory ◽  
University Of Texas ◽  
University Of Wisconsin ◽  
Pan American ◽  
Acetate Formation ◽  
The University

Pradeep Kumar of the National Chemical Laboratory, Pune, developed (Tetrahedron Lett. 2010, 51, 744) a new procedure for the conversion of an alcohol 1 to the inverted chloride 3. Michel Couturier of OmegaChem devised (J. Org. Chem. 2010, 75, 3401) a new reagent for the conversion of an alcohol 4 to the inverted fluoride 6. For both reagents, primary alcohols worked as well. Patrick H. Toy of the University of Hong Kong showed (Synlett 2010, 1115) that diethyl-lazodicarboxylate (DEAD) could be used catalytically in the Mitsunobu coupling of 7. Employment of 8 minimized competing acetate formation. In another application of hyper-valent iodine chemistry, Jaume Vilarrasa of the Universitat de Barcelona observed (Tetrahedron Lett. 2010, 51, 1863) that the Dess-Martin reagent effected the smooth elimination of a pyridyl selenide 10. Ken-ichi Fujita and Ryohei Yamaguchi of Kyoto University extended (Org. Lett. 2010, 12, 1336) the “borrowed hydrogen” approach to effect conversion of an alcohol 12 to the sulfonamide 13. Dan Yang, also of the University of Hong Kong, developed (Org. Lett. 2010, 12, 1068, not illustrated) a protocol for the conversion of an allylic alcohol to the allylically rearranged sulfonamide. Shu-Li You of the Shanghai Institute of Organic Chemistry used (Org. Lett. 2010, 12, 800) an Ir catalyst to effect rearrangement of an allylic sulfinate 14 to the sulfone. Base-mediated conjugation then delivered 15. K. Rama Rao of the Indian Institute of Chemical Technology, Hyderabad, devised (Tetrahedron Lett. 2010, 51, 293) a La catalyst for the conversion of an iodoalkene 16 to the alkenyl sulfide 17. Alkenyl selenides could also be prepared. James M. Cook of the University of Wisconsin, Milwaukee, described (Org. Lett. 2010, 12, 464, not illustrated) a procedure for coupling alkenyl iodides and bromides with N-H heterocycles and phenols. Hansjörg Streicher of the University of Sussex showed (Tetrahedron Lett. 2010, 51, 2717) that under free radical conditions, the carboxylic acid derivative 18 could be decarboxylated to the alkenyl iodide 19. Bimal K. Banik of the University of Texas–Pan American found (Synth. Commun. 2010, 40, 1730) that water was an effective solvent for the microwave-mediated addition of a secondary amine 21 to a Michael acceptor 20.

scholarly journals Vibration energy harvesting to power condition monitoring sensors for industrial and manufacturing equipment

2012 ◽  
Vol 227 (6) ◽  
pp. 1187-1202 ◽  
Author(s):  
Andrew C Waterbury ◽  
Paul K Wright
Keyword(s):  
Machine Tool ◽  
Condition Monitoring ◽  
Metal Cutting ◽  
Mechanical Vibration ◽  
Sensor Nodes ◽  
Vibration Energy ◽  
Vibration Energy Harvesting ◽  
Wireless Sensor Nodes ◽  
Vibration Energy Harvester ◽  
Cutting Vibrations

To enable self-sustaining long-lasting wireless condition monitoring sensors, a small mechanical vibration energy harvester using electromagnetic transduction was constructed and used to harvest vibrations from large industrial pump motors and machine tool. The prototype harvester was roughly the size of a cube with 2.5 cm long sides. Power ranging from 0.2 to 1.5 mW was harvested from 15 to 30 kW water pump motors. For a machine tool, metal cutting vibrations and rapid jog events were explored as possible harvestable sources of energy. Power ranging from 0.9 to 1.9 mW was harvested during facemilling operations, and it was shown that rapid jog events could be harvested. The power levels harvested from the pump motors and machine tools are sufficient to provide the time-averaged power requirements of commercial wireless sensor nodes, enabling sensor nodes to overcome the finite life of replaceable batteries.

Defect Prognostics Models for Spall Growth in Railroad Bearing Rolling Elements

2018 ◽  
Author(s):  
Nancy De Los Santos ◽  
Constantine M. Tarawneh ◽  
Robert E. Jones ◽  
Arturo Fuentes
Keyword(s):  
Monitoring System ◽  
Health Monitoring ◽  
Safety Concern ◽  
Continuous Growth ◽  
Health Monitoring System ◽  
Bearing Condition Monitoring ◽  
Railroad Bearings ◽  
Railroad Bearing ◽  
The University ◽  
Proactive Maintenance

Prevention of railroad bearing failures, which may lead to catastrophic derailments, is a central safety concern. Early detection of railway component defects, specifically bearing spalls, will improve overall system reliability by allowing proactive maintenance cycles rather than costly reactive replacement of failing components. A bearing health monitoring system will provide timely detection of flaws. However, absent a well verified model for defect propagation, detection can only be used to trigger an immediate component replacement. The development of such a model requires that the spall growth process be mapped out by accumulating associated signals generated by various size spalls. The addition of this information to an integrated health monitoring system will minimize operation disruption and maintain maximum accident prevention standards enabling timely and economical replacements of failing components. An earlier study done by the authors focused on bearing outer ring (cup) raceway defects. The developed model predicts that any cup raceway surface defect (i.e. spall) once reaching a critical size (spall area) will grow according to a linear correlation with mileage. The work presented here investigates spall growth within the inner rings (cones) of railroad bearings as a function of mileage. The data for this study were acquired from defective bearings that were run under various load and speed conditions utilizing specialized railroad bearing dynamic test rigs owned by the University Transportation Center for Railway Safety (UTCRS) at the University of Texas Rio Grande Valley (UTRGV). The experimental process is based on a testing cycle that allows continuous growth of railroad bearing defects until one of two conditions are met; either the defect is allowed to grow to a size that does not jeopardize the safe operation of the test rig, or the change in area of the spall is less than 10% of its previous size prior to the start of testing. The initial spall size is randomly distributed as it depends on the originating defect depth, size, and location on the rolling raceway. Periodic removal and disassembly of the railroad bearings was carried out for inspection and defect size measurement along with detailed documentation. Spalls were measured using optical techniques coupled with digital image analysis, as well as, with a manual coordinate measuring instrument with the resulting field of points manipulated in MatLab™. Castings were made of spalls using low-melting, zero-shrinkage bismuth-based alloys, so that a permanent record of the spall geometry and its growth history can be retained. The main result of this study is a preliminary model for spall growth, which can be coupled with bearing condition monitoring tools that will allow economical and effective scheduling of proactive maintenance cycles that aim to mitigate derailments, and reduce unnecessary train stoppages and associated costly delays on busy railways.

Health monitoring of urban rail corrugation by wireless rechargeable sensor nodes

2018 ◽  
Vol 18 (3) ◽  
pp. 838-852 ◽  
Author(s):  
Jun Lu ◽  
Mingyuan Gao ◽  
Yifeng Wang ◽  
Ping Wang
Keyword(s):  
Health Monitoring ◽  
Interaction Model ◽  
Field Testing ◽  
Sensor Nodes ◽  
Wireless Sensor Nodes ◽  
Rail Corrugation ◽  
Induction Principle ◽  
Urban Rail ◽  
Acceleration Signals

This article presents a prototype of wireless rechargeable sensor nodes for the health monitoring of urban rail corrugation. The proposed system includes a local energy generator constructed based on the electromagnetic-induction principle, a DC–DC booster converter, wireless sensor nodes, and an analysis interface using Littlewood–Paley wavelet transform methods. A vehicle–track interaction model is established that considers the rail corrugation as an irregularity excitation source to predict the dynamic response of railway tracks with rail corrugation. To verify the theoretical prediction, field testing was conducted, and the power consumption of the sensor nodes was evaluated. Finally, a case study showed that rail corrugation defects can be identified by measuring the rail acceleration signals and using Littlewood–Paley wavelet analysis.

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