Eventos Anais de eventos
COBEM 2021
26th International Congress of Mechanical Engineering
Digital processing and statistical analysis of audio signals measured through smartphone devices for the application in tool wear monitoring
Submission Author:
Ana Carolina Porto , SP
Co-Authors:
Ana Carolina Porto, Sidney Bruce Shiki, Armando Ítalo Sette Antonialli
Presenter: Ana Carolina Porto
doi://10.26678/ABCM.COBEM2021.COB2021-1756
Abstract
Since the industrial revolutions, new production methods have been studied and, machining process monitoring techniques became a way to improve manufacturing systems. Therefore, this paper proposes to reduce costs of the machining process by testing a low-cost wear monitoring system composed of a simple smartphone device used to capture audible signals emitted during the metal cutting process. As an experimental study, a lathe machine and a tool holder with insert specially applied for processing steel at high temperatures were used while sound signals in the audible range were captured with the smartphone and computationally analyzed for verification of the applicability of mobile devices to monitor cutting tool wear. Before turning and between the process passes, pictures were captured with a microscope to serve as a reference for the tool wear sate and for verification of visible wear levels on the cutting edges. Primarily, with the aid of the Matlab software, amplitude variation and RMS values of the sound signals were calculated using techniques of signal processing. The discrete Fourier transform of the signal was taken in order to verify the main oscillatory components of the audio signals by analyzing the frequency domain. Thereby, the main peak frequencies and the area below the graph were also analyzed by statistical methods. With the pictures obtained during turning and studied under a microscope to these results, it was possible to observe that the audio signals captured by smartphones were able to track and generate wear-sensitive indexes on the course of cutting tool wear. As smartphones are becoming increasingly popular and they are more economically viable than the expensive sensors currently used in the manufacturing environment, these devices have an interesting potential for the optimization of machining monitoring techniques. Also, optimizing the incurred cost and having potential to be used, although with some restrictions on the sensitivity of the methodology. In the conclusions of the paper, the main advantages and drawbacks of the proposed methodology are presented.
Keywords
signal processing, Tool wear monitoring, Turning, Mobile devices
