Defect detection in pipeline using acoustic emission

Monitoring defects in a pipeline are very important in particularly for buried pipeline. The ability to identify location, type and size of the defects are always necessary to save time and cost. Thus, this research project embarks on identifying defect location and estimating the size of the defect...

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Bibliographic Details
Main Author: Zarzoor, Ahmed Kadhim (Author)
Format: Thesis
Published: 2015.
Subjects:
Online Access:Get fulltext
LEADER 01963 am a22001573u 4500
001 48685
042 |a dc 
100 1 0 |a Zarzoor, Ahmed Kadhim  |e author 
245 0 0 |a Defect detection in pipeline using acoustic emission 
260 |c 2015. 
520 |a Monitoring defects in a pipeline are very important in particularly for buried pipeline. The ability to identify location, type and size of the defects are always necessary to save time and cost. Thus, this research project embarks on identifying defect location and estimating the size of the defect by using Acoustic Emission (AE) technology. Data were acquired from a two inch diameter pipe with 1mm thickness using low cost piezoelectric sensors. Location of the defect was estimated based on the difference on the time arrival coming from the two sensors. Results show that location of the defect can be estimated within certain degree of accuracy. In addition, different sizes of the defect have also been studied using artificially induced defect as well as the actual defect. Defects have been introduced both in the axial and radial direction on the test pipe. AE data from the pencil break has been collected for each defect size and processed using few AE parameters such as R.M.S., energy, amplitude and time-frequency domain. All of these data were then normalized to the reference value and the correlation between defect sizes and normalized AE parameters were developed. The results show that there are good correlations between normalized AE parameter and defect sizes particularly when the defect size was increased in axial direction. In short, it is shown that AE technology is capable in locating defect in pipeline as well as giving estimation on the size of the defect. 
546 |a en 
650 0 4 |a TJ Mechanical engineering and machinery 
655 7 |a Thesis 
787 0 |n http://eprints.utm.my/id/eprint/48685/ 
856 |z Get fulltext  |u http://eprints.utm.my/id/eprint/48685/1/AhmedKadhimZarzoorMFKM2015.pdf