High Frequency Acoustic Signal Analysis for Internal Surface Pipe Roughness Classification

Abstract. This research highlights the method of acoustic emission analysis to distinguish the internal surface roughness of the pipe. Internal roughness of the pipe is referred to the level of corrosion occurring, where normally it is difficult to be monitored onl...

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Bibliographic Details
Main Authors: Z. M., Hafizi, Che Ku Eddy Nizwan, Che Ku Husin
Format: Conference or Workshop Item
Language:English
Published: 2010
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/1182/1/High_Frequency_Acoustic_Signal_Analysis_for_Internal_Surface_Pipe_Roughness_Classification.pdf
http://umpir.ump.edu.my/id/eprint/1182/
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Summary:Abstract. This research highlights the method of acoustic emission analysis to distinguish the internal surface roughness of the pipe. Internal roughness of the pipe is referred to the level of corrosion occurring, where normally it is difficult to be monitored online. Acoustic Emission (AE) technique can be used as an alternative solution to the corrosion monitoring in pipes, especially for complex pipelines and difficult to achieve by other monitoring devices. This study used the hydraulic bench to provide fluid flow at two different pressures in pipes with different internal surface roughness (rough and smooth). The main source of acoustic emission was from activity in the control valve, coupled with high pressure water flow friction on the surface of the pipe. The signal from these sources was detected by using the AED-2000V instrument and assisted by the Acoustic Emission Detector (AED) software. The time domain parameter; root mean square, RMS amplitude was processed and compared at different pressures for each type of internal pipe roughness at ten different locations. It was observed that a unit less Bangi number, AB, derived from RMS values, can be used for discriminating different level of internal surface roughness. Internal surface pipe can still be considered as smooth if AB value is above than 1.0.