Show simple item record

dc.contributor.authorBhaduri, Sreyoshien_US
dc.date.accessioned2017-06-13T19:43:47Z
dc.date.available2017-06-13T19:43:47Z
dc.date.issued2013-12-11en_US
dc.identifier.otheretd-12242013-094021en_US
dc.identifier.urihttp://hdl.handle.net/10919/78080
dc.description.abstractWavelet intensity based algorithm developed previously at VirginiaTech has been furthered and paired with an SVM based classifier. The wavelet intensity algorithm acts as a feature extraction algorithm. The wavelet transform is an effective tool as it allows one to narrow down upon the transient, high frequency events and is able to tell their exact location in time. According to prior work done in the field of signal processing, the local regularities of a signal can be estimated using a Lipchitz exponent at each time step of the signal. The local Lipchitz exponent can then be used to generate the wavelet intensity factor values. For each vertical acceleration value, corresponding to a specific location on the track, we now have a corresponding intensity factor. The intensity factor corresponds to break-no break information and can now be used as a feature to classify the vertical acceleration as a fault or no fault. Support Vector Machines (SVM) is used for this binary classification task. SVM is chosen as it is a well-studied topic with efficient implementations available. SVM instead of hard threshold of the data is expected to do a better job of classification without increasing the complexity of the system appreciably.
dc.language.isoen_USen_US
dc.publisherVirginia Techen_US
dc.rightsI hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to Virginia Tech or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report.en_US
dc.subjectSupport Vector Machinesen_US
dc.subjectcrossing and track safetyen_US
dc.subjectrail break detectionen_US
dc.titleAlgorithm to enable intelligent rail break detectionen_US
dc.typeThesisen_US
dc.contributor.departmentMechanical Engineeringen_US
dc.description.degreeMaster of Scienceen_US
thesis.degree.nameMaster of Scienceen_US
thesis.degree.levelmastersen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineMechanical Engineeringen_US
dc.contributor.committeechairTaheri, Saieden_US
dc.contributor.committeememberAhmadian, Mehdien_US
dc.contributor.committeememberStilwell, Daniel J.en_US
dc.type.dcmitypeTexten_US
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-12242013-094021/en_US
dc.date.sdate2013-12-24en_US
dc.date.rdate2014-02-04
dc.date.adate2014-02-04en_US


Files in this item

Thumbnail
Thumbnail

This item appears in the following Collection(s)

Show simple item record