dc.contributor.author | Sheiretov, Yanko | |
dc.contributor.author | Grundy, Dave | |
dc.contributor.author | Zilberstein, Vladimir | |
dc.contributor.author | Goldfine, Neil J. | |
dc.contributor.author | Maley, Susan | |
dc.date.accessioned | 2011-03-04T20:31:08Z | |
dc.date.available | 2011-03-04T20:31:08Z | |
dc.date.issued | 2009-10 | |
dc.date.submitted | 2009-09 | |
dc.identifier.issn | 1530-437X | |
dc.identifier.issn | 1558-1748 | |
dc.identifier.other | INSPEC Accession Number: 10914883 | |
dc.identifier.uri | http://hdl.handle.net/1721.1/61420 | |
dc.description.abstract | Utilization of America's substantial coal reserves for energy production has become a national priority. Advanced coal-fired power plants offer an environmentally friendly means to achieve that goal. These power plants, such as ultrasupercritical power plants, will provide high thermal efficiency along with greatly reduced emissions of CO[subscript 2] and other pollutants. Life cycle costs for the advanced coal-fired plants can be reduced by enhanced observability in support of condition-based maintenance. The enhanced observability can be achieved by using networks of condition-monitoring sensors that would provide component-level material condition information and through-wall temperature monitoring. This would reduce uncertainties in knowledge of material condition, at the level of individual components, and improve capability to predict remaining life of critical components. One approach being developed under the U.S. Department of Energy Small Business Innovation Research Program is to develop and implement high-temperature versions of the meandering winding magnetometer (HT-MWM) for temperatures up to 1000 degC. These patented sensors, coupled with multivariate inverse methods, would provide superior performance for in situ material condition monitoring (material degradation, flaw detection, stress relaxation, and/or creep monitoring) and through-wall temperature measurement. Networks of HT-MWMs will generate material condition information to be used by adaptive life-management algorithms for remaining life prediction and decision support. | en_US |
dc.description.sponsorship | United States. Dept. of Energy | en_US |
dc.description.sponsorship | Jentek Sensors (Firm) | en_US |
dc.language.iso | en_US | |
dc.publisher | Institute of Electrical and Electronics Engineers | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1109/jsen.2009.2019335 | en_US |
dc.rights | Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. | en_US |
dc.source | IEEE | en_US |
dc.title | MWM-Array Sensors for In Situ Monitoring of High-Temperature Components in Power Plants | en_US |
dc.type | Article | en_US |
dc.identifier.citation | Sheiretov, Y. et al. “MWM-Array Sensors for In Situ Monitoring of High-Temperature Components in Power Plants.” Sensors Journal, IEEE 9.11 (2009): 1527-1536. © 2009 IEEE. | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Laboratory for Electromagnetic and Electronic Systems | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Research Laboratory of Electronics | en_US |
dc.contributor.approver | Goldfine, Neil J. | |
dc.contributor.mitauthor | Goldfine, Neil J. | |
dc.relation.journal | IEEE Sensors Journal | en_US |
dc.eprint.version | Final published version | en_US |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
dspace.orderedauthors | Sheiretov, Y.; Grundy, D.; Zilberstein, V.; Goldfine, N.; Maley, S. | en |
mit.license | PUBLISHER_POLICY | en_US |
mit.metadata.status | Complete | |