Prediction of Surface Roughness using Spectral Analysis and Image Comparison of Audio Signals

摘要

The aim of this work is to design an off-line system, method and experimental set-up for predicting surface roughness (Ra) of metal surfaces with the help of audio signals. The frictional contact between a metal surface and sharp pencil like scratching tool will produce audio signals which vary based on the roughness of the surface. The samples considered to design and validate the concept are work pieces machined with metal cutting processes such as Turning and Grinding. Several audio signals are generated from various types of metal surfaces produced by these processes after the completion of the machining process away from the machining area in an enclosed chamber. The audio waves are captured with the help of a microphone fixed inside the chamber. These audio signals are processed to generate the surface pattern of the relevant surface. The audio signals are then converted to spectrogram and normalized histogram plots with the help of MATLAB, based on which the roughness of the surfaces is predicted. An experimental set-up is designed which provides a sound-proof environment to capture and record the audio signals. The proposed system, method and set-up are validated with the actual surface roughness of the chosen surfaces measured with the help of a surface roughness measurement instrument.