skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Automated Health Monitoring of Rail Cars and Railroad Bridges Using Embedded Sensors.


Abstract not provided.

Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
Report Number(s):
DOE Contract Number:
Resource Type:
Resource Relation:
Conference: Proposed for presentation at the Internatioanl Workshop on SHM for Railway Systems held October 12-14, 2016 in Qingdao, Shandong, China.
Country of Publication:
United States

Citation Formats

Roach, Dennis P. Automated Health Monitoring of Rail Cars and Railroad Bridges Using Embedded Sensors.. United States: N. p., 2016. Web.
Roach, Dennis P. Automated Health Monitoring of Rail Cars and Railroad Bridges Using Embedded Sensors.. United States.
Roach, Dennis P. Thu . "Automated Health Monitoring of Rail Cars and Railroad Bridges Using Embedded Sensors.". United States. doi:.
title = {Automated Health Monitoring of Rail Cars and Railroad Bridges Using Embedded Sensors.},
author = {Roach, Dennis P.},
abstractNote = {Abstract not provided.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu Sep 01 00:00:00 EDT 2016},
month = {Thu Sep 01 00:00:00 EDT 2016}

Other availability
Please see Document Availability for additional information on obtaining the full-text document. Library patrons may search WorldCat to identify libraries that hold this conference proceeding.

Save / Share:
  • The Automated Radioxenon Analyzer/Sampler (ARSA) is a radioxenon gas collection and analysis system operating autonomously under computer control. The ARSA systems are deployed as part of an international network of sensors, with individual stations feeding radioxenon concentration data to a central data center. Because the ARSA instrument is complex and is often deployed in remote areas, it requires constant self-monitoring to verify that it is operating according to specifications. System performance monitoring is accomplished by over 200 internal sensors, with some values reported to the data center. Several sensors are designated as safety sensors that can automatically shut down themore » ARSA when unsafe conditions arise. In this case, the data center is advised of the shutdown and the cause, so that repairs may be initiated. The other sensors, called state of health (SOH) sensors, also provide valuable information on the functioning of the ARSA and are particularly useful for detecting impending malfunctions before they occur to avoid unscheduled shutdowns. Any of the sensor readings can be displayed by an ARSA Data Viewer, but interpretation of the data is difficult without specialized technical knowledge not routinely available at the data center. Therefore it would be advantageous to have sensor data automatically evaluated for the precursors of malfunctions and the results transmitted to the data center. Artificial Neural Networks (ANN) are a class of data analysis methods that have shown wide application to monitoring systems with large numbers of information inputs, such as the ARSA. In this work supervised and unsupervised ANN methods were applied to ARSA SOH data recording during normal operation of the instrument, and the ability of ANN methods to predict system state is presented.« less
  • After Apr. 1978 hearings, the U.S. National Transportation Safety Board recommended a speedup in retrofitting tank cars to meet Federal regulations requiring steel head shields, insulated steel jackets, and shelf couplers, despite testimony that derailments are caused by deteriorating railbeds and equipment. When the secretary of the U.S. Department of Transportation proposed a speedup in retrofitting, he stated flatly that ''faulty rail tracks'' were the most frequent cause of 10,000 derailments in 1977 involving 500 tank cars transporting hazardous materials. Testimony given indicates that retrofits cost up to $13,000/car; that adding a 1400 lb steel plate at each end ofmore » a car not designed for such a weight is a problem; that repair facilities cannot handle 22,000 retrofits by 12/25/78; and that the cars are necessary for continuing supply of fertilizer and propane. Industry cannot design a wreck-proof car; the real need is to eliminate the cause of derailments, namely the unsafe railroad track. However, the actions taken leave the basic cause of derailment untouched.« less
  • The Pacific Northwest National Laboratory (PNNL) has conducted R&D for the US Army on prognostics health monitoring (PHM). The main focus of the work was to demonstrate the feasibility of developing an onboard PHM system for the gas turbine engine used on the M1 Abrams tank. Research was performed on methods for real time, onboard prognostics/engine life expectancy forecasting, and a prototype system was designed, developed, and installed on several test tanks. The purpose of this presentation is to review the approaches to PHM employed in this research, to provide an overview of the PHM prototype and results obtained tomore » date with data collected in the field, and to describe current work aimed at developing a PHM capability for diesel engines.« less