Welding fault detection using acoustic emission technique
This project was carried out as a welding fault detection using Acoustic Emission technique. The objective of this study is to study welding fault detection on welding joints using the Acoustic Emission Technique and to classify and analyse the Acoustic Emission signal between joint with defect and...
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| Format: | Undergraduates Project Papers |
| Language: | English English English English |
| Published: |
2012
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| Online Access: | http://umpir.ump.edu.my/id/eprint/4603/ http://umpir.ump.edu.my/id/eprint/4603/ http://umpir.ump.edu.my/id/eprint/4603/1/Welding%20fault%20detection%20using%20acoustic%20emission%20technique%20%28Table%20of%20content%29.pdf http://umpir.ump.edu.my/id/eprint/4603/2/Welding%20fault%20detection%20using%20acoustic%20emission%20technique%20%28Abstract%29.pdf http://umpir.ump.edu.my/id/eprint/4603/3/Welding%20fault%20detection%20using%20acoustic%20emission%20technique%20%28Chapter%201%29.pdf http://umpir.ump.edu.my/id/eprint/4603/4/Welding%20fault%20detection%20using%20acoustic%20emission%20technique%20%28References%29.pdf |
| Summary: | This project was carried out as a welding fault detection using Acoustic Emission technique. The objective of this study is to study welding fault detection on welding joints using the Acoustic Emission Technique and to classify and analyse the Acoustic Emission signal between joint with defect and non-defect material using the AcousticEmission Technique. The material that uses to conduct this project is Mild Steel. Using the MIG welding machine, the material was joints together then the material tested by dye penetration testing before the material is test by the Acoustic Emission to determine the defect and non-defect by the defects that occur at the surface of the material. During the experiment, 40N load was put on to the material to give the material stresses for the Acoustic Emission Signal occurs. The USB AE Node Physical Acoustic instrument is used to collect the signal that occurs from the material that undergoing stresses. AEWin Software was used to interpret the signal into .txt for easy reading and to transfer the data into Matlab software for further analyse. The value of hits, counts, and peak amplitude is recorded and analysed. Statistical analysis is made to find the kurtosis and skewness of the data using Matlab sofware. The result shows that the defect material has high peak amplitude compare to the low peak amplitude of the non-defect materials. The hits and counts for defect also high compare to the non-defect material. Most of the non-defect material shows low amplitudes and long duration signal which one of the characteristic of friction noise. The conclusion show there are significant different of the signal that occur on the welding joint between the defect material and non-defect material. |
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