Mel-frequency cepstral and spectral flux analysis of the acoustic signal for real-time status monitoring of laser cleaning

• Main Authors: Syafiq Ahmad, Abdul Aleem, Mohd Fadhlan, Mohd Yusof, Quazi, M. M., Aiman, Mohd Halil, M., Ishak
• Format: Article
• Language: English
• Published: IOP Publishing Ltd 2023
• Subjects: TJ Mechanical engineering and machinery
• Online Access: http://umpir.ump.edu.my/id/eprint/38676/1/Mel-Frequency%20Cepstral%20and%20Spectral%20Flux%20Analysis.pdf; http://umpir.ump.edu.my/id/eprint/38676/; https://doi.org/10.1088/2053-1591/acfd10; https://doi.org/10.1088/2053-1591/acfd10

Due to the fact that the laser-based cleaning process is quick, efficient, and environmentally friendly, it has been utilized in a various industry, which has increased the number of studies pertaining to this process. In addition to process optimization, the real-time monitoring system was essential in preventing the overexposure of the laser beam to the cleansed surface, which would result in an engraving effect. This article demonstrated the analysis of the acquired sound signal to identify an overexposed laser beam during laser cleaning. In order to accomplish the aim of this work, the corroded boron steel plate was prepared. The laser cleaning procedure involved a four-loop laser scan. Variable scanning speeds between 100 and 1,000 mm/s were configured. Concurrently, the acoustic signal within the frequency range of 20 Hz to 10 kHz was acquired. The results indicate that the process with a scanning speed of 1000 mm/s recorded the clear surface without morphological change on the cleaned area, whereas an unacceptable deep gouge was formed during the second and third loops of the process with speeds of 100 mm/s and 300 mm/s, respectively. According to an analysis of the acquired sound signal, the trend of the Mel Frequency Cepstral Coefficient (MFCC) was indicative of the existence of the ablated corroded substrate. In addition, the spectral flux can provide important information regarding the formation of a deep groove on a cleansed surface. This research demonstrates the feasibility of using the auditory signal to monitor the laser cleaning process. By characterizing the acoustic signal feature, it is possible to detect the completion of the cleaning process before the morphological change of the cleaned area existed. With further development, it was possible that this method would become the most efficient, resilient, and demanding in the future.