Use this URL to cite or link to this record in EThOS:
Title: Condition classification in underground pipes based on acoustical characteristics
Author: Feng, Zao
Awarding Body: University of Bradford
Current Institution: University of Bradford
Date of Award: 2013
Availability of Full Text:
Access from EThOS:
Access from Institution:
Acoustical characteristics are used to classify the structural and operational conditions in underground pipes with advanced signal classification methods.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Acoustics ; Condition classification ; Pipes ; Siphons ; Sewers ; Condition/defect analysis ; Sound intensity ; Signal processing ; Machine learning