000 02642nam a2200241 a 4500
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003 KUKTEM
005 20251114204537.0
008 130228t2012 my dao f m 000 0 eng d
020 _aTHE0005819(Local)
039 9 _a201905131524
_baida
_c201303011001
_dFida
_y201302281539
_ztraining
040 _aUMP
090 _aTA418.84 .F37 2012 rs Bc.
100 0 _aFareez Farhan Suliman
245 1 0 _aWelding fault detection using acoustic emission technique /
_cFareez Farhan Suliman
260 _aKuantan, Pahang :
_bUMP,
_c2012
300 _axvi, 77 p. :
_bill. (some col.) ;
_c30 cm. +
_e1 CD-ROM
502 _aProject paper (Bachelorof Mechanical Engineering) -- Universiti Malaysia Pahang - 2012
504 _aBibliography: p. 72-73
520 3 _aThis 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.
650 0 _aAcoustic emission
999 _aVIRTUA40
_c3852
_d3858
999 _aVTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5040*5200*6500*9992