The failure of both electric cable in a electric system and pipes in a gas or petroleum transportation system can cause disastrous consequence. It is important to monitoring the health of electric cable and critical pipeline in order to prevent accidents and save repair expenses. In both applications, joint time-frequency analysis is found to be an effective tool.
The Joint Time-Frequency Domain Reflectometry (JTFDR) which is based on time-frequency cross-correlation function is applied to health monitoring of XLPE, EPR and SIR insulated cables in accelerated aging tests for diagnostics and prognostics. The experimental results show that JTFDR has the prognostic potential to predict the remaining life of the cables.
In the second part of this dissertation, a new definition of cross time-frequency distribution is presented and applied to a corrosion detection problem in order to detect the location and extent of a corrosion damage on an aluminium plate. The experimental results illustrate that the proposed cross time-frequency analysis can detect the corrosion progression more accurately in comparison with three classical methods: damage index and zero-crossing which works in time domain only and cross power spectral analysis, which works in frequency domain only.
","abstract_html":"<p>The failure of both electric cable in a electric system and pipes in a gas or petroleum transportation system can cause disastrous consequence. It is important to monitoring the health of electric cable and critical pipeline in order to prevent accidents and save repair expenses. In both applications, joint time-frequency analysis is found to be an effective tool. </p> <p> The Joint Time-Frequency Domain Reflectometry (JTFDR) which is based on time-frequency cross-correlation function is applied to health monitoring of XLPE, EPR and SIR insulated cables in accelerated aging tests for diagnostics and prognostics. The experimental results show that JTFDR has the prognostic potential to predict the remaining life of the cables. </p> <p> In the second part of this dissertation, a new definition of cross time-frequency distribution is presented and applied to a corrosion detection problem in order to detect the location and extent of a corrosion damage on an aluminium plate. The experimental results illustrate that the proposed cross time-frequency analysis can detect the corrosion progression more accurately in comparison with three classical methods: damage index and zero-crossing which works in time domain only and cross power spectral analysis, which works in frequency domain only.</p>","abstract_has_math":false,"creators":["Wang, Jingjiang"],"institution":null,"degree_name":"Ph.D.","degree_level":"Campus Access Dissertation","degree_discipline":"Electrical Engineering","degree_department":null,"school":null,"contributors":["Yong-June Shin"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2010,"date_issued":"2010-01-01T08:00:00Z","date_published":"2010-01-01T08:00:00Z","updated_at":"2026-07-24T04:37:21Z","subjects":["Electrical and Computer Engineering","Electrical and Electronics","Engineering","accelerated aging test","corrosion detection","health monitoring","time-frequency analysis"],"languages":[],"rights":["© 2010, Jingjiang Wang"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarcommons.sc.edu/etd/2210","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Yong-June Shin"]},{"key":"dc:creator","label":"Author","values":["Wang, Jingjiang"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Campus Access Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Electrical and Computer Engineering","Electrical and Electronics","Engineering","accelerated aging test","corrosion detection","health monitoring","time-frequency analysis"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["© 2010, Jingjiang Wang"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarcommons.sc.edu/etd/2210"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The failure of both electric cable in a electric system and pipes in a gas or petroleum transportation system can cause disastrous consequence. It is important to monitoring the health of electric cable and critical pipeline in order to prevent accidents and save repair expenses. In both applications, joint time-frequency analysis is found to be an effective tool.
The Joint Time-Frequency Domain Reflectometry (JTFDR) which is based on time-frequency cross-correlation function is applied to health monitoring of XLPE, EPR and SIR insulated cables in accelerated aging tests for diagnostics and prognostics. The experimental results show that JTFDR has the prognostic potential to predict the remaining life of the cables.
In the second part of this dissertation, a new definition of cross time-frequency distribution is presented and applied to a corrosion detection problem in order to detect the location and extent of a corrosion damage on an aluminium plate. The experimental results illustrate that the proposed cross time-frequency analysis can detect the corrosion progression more accurately in comparison with three classical methods: damage index and zero-crossing which works in time domain only and cross power spectral analysis, which works in frequency domain only.
"]},{"key":"dc:title","label":"Title","values":["Theory and Application of Joint Time-Frequency Analysis On Health Monitoring of Electric Cable and Guided-Waves Detection of Structural Corrosion"]}]}],"canonical_facts":{"dc:contributor":["Yong-June Shin"],"dc:creator":["Wang, Jingjiang"],"dc:description.abstract":["The failure of both electric cable in a electric system and pipes in a gas or petroleum transportation system can cause disastrous consequence. It is important to monitoring the health of electric cable and critical pipeline in order to prevent accidents and save repair expenses. In both applications, joint time-frequency analysis is found to be an effective tool.
The Joint Time-Frequency Domain Reflectometry (JTFDR) which is based on time-frequency cross-correlation function is applied to health monitoring of XLPE, EPR and SIR insulated cables in accelerated aging tests for diagnostics and prognostics. The experimental results show that JTFDR has the prognostic potential to predict the remaining life of the cables.
In the second part of this dissertation, a new definition of cross time-frequency distribution is presented and applied to a corrosion detection problem in order to detect the location and extent of a corrosion damage on an aluminium plate. The experimental results illustrate that the proposed cross time-frequency analysis can detect the corrosion progression more accurately in comparison with three classical methods: damage index and zero-crossing which works in time domain only and cross power spectral analysis, which works in frequency domain only.
"],"dc:identifier":["https://scholarcommons.sc.edu/etd/2210"],"dc:rights":["© 2010, Jingjiang Wang"],"dc:subject":["Electrical and Computer Engineering","Electrical and Electronics","Engineering","accelerated aging test","corrosion detection","health monitoring","time-frequency analysis"],"dc:title":["Theory and Application of Joint Time-Frequency Analysis On Health Monitoring of Electric Cable and Guided-Waves Detection of Structural Corrosion"],"thesis:degree_discipline":["Electrical Engineering"],"thesis:degree_level":["Campus Access Dissertation"],"thesis:degree_name":["Ph.D."]},"updated_at":"2026-07-24T04:37:21Z"}