L-statistical analysis of sound signal acquired from pulse mode laser welding for characterising weld geometry

Mohd Fadhlan, Mohd Yusof and M., Ishak (2019) L-statistical analysis of sound signal acquired from pulse mode laser welding for characterising weld geometry. International Journal of Automotive and Mechanical Engineering (IJAME), 16 (3). pp. 6987-7006. ISSN 2229-8649 (Print); 2180-1606 (Online). (Published)

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Many ongoing studies have proven that statistical features extracted from the acquired sound during a laser welding process significantly yield some pictures on the weld condition, including weld geometry. However, a considerable amount of studies has underlined the use of common statistical features in which they are restricted to some limitations when dealing with non-stationary random sound signal. In the present study, the main aim is to study the correlation between the L-statistical features trend of the sound amplitude distribution with respect to the change in weld geometry during pulse mode laser welding compared to common statistical features. In an attempt to achieve this goal, a pulse mode laser welding was subjected to 22MnB5 boron steel with variations in the peak power, pulse width, and focal length. Meanwhile, the sound signal was acquired during the process, with standard deviation, interdecile range, mean absolute deviation, L-Cv (scale), and L-kurtosis extracted from the analysis. The degree of correlation between these statistical features and weld geometry was compared from the R-square value. According to the reported results, L-kurtosis yielded the strongest correlation with both weld penetration depth and bead width compared to the remaining five statistical features. This showed that the use of L-statistical features was significant to improve the correlation between sound signals and weld geometry.

Item Type: Article
Additional Information: Indexed by Scopus
Uncontrolled Keywords: Pulse mode laser welding; sound signal; statistical features; L-statistic
Subjects: Q Science > QC Physics
T Technology > TJ Mechanical engineering and machinery
T Technology > TS Manufactures
Faculty/Division: Faculty of Mechanical Engineering
Depositing User: Mrs Norsaini Abdul Samat
Date Deposited: 21 Nov 2019 02:52
Last Modified: 21 Nov 2019 02:55
URI: http://umpir.ump.edu.my/id/eprint/26026
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