SURFACE ROUGHNESS PREDICTION IN TURNING PROCESS BY APPLYING COMPUTER VISION METHOD

Abstract

This paper reports the utilization of computer vision and backlight techniques to determine the surface roughness of a workpiece under a variety of process parameters. A CCD (Charge-Coupled Device) camera was used to capture the image of the edge of the workpiece of the turned components using backlight technology to provide an edge roughness profile. The image was processed using SRVISION software developed in MATLAB to extract the profile of the workpiece and calculated the arithmetic average value of roughness (Ra) and root mean square roughness (Rq). The experiments are carried out with AISI 1045 (medium carbon steel), using various feed rates and cutting speeds, comparison is then made of the surface roughness values achieved through the conventional stylus probe method and the image processing technique. The comparison indicates that the vision method provides precise and consistent results with a correlation up to 0.99 with the traditional stylus method. The mean variations in Ra and Rq between the two methods were just 1.65 and 1.433 percent, respectively. As the vision method is a non-contact procedure, it can be significant potential for application without damaging the machined surfaces in the in-process inspection of the components as well as aids monitoring of the components in a shorter period.

ABSTRAK: Kajian ini menggunakan visual komputer dan teknik cahaya belakang bagi memperoleh kekasaran permukaan sesuatu bahan pada pelbagai proses parameter. Kamera jenis CCD (Peranti Terganding-Cas) telah digunakan bagi memperoleh imej tepi bagi komponen yang dipusing menggunakan teknologi cahaya belakang bagi menghasilkan profil imej tepi yang jelas. Imej ini diproses menggunakan perisian SRVISION MATLAB bagi menghasilkan profil bahan dan purata kiraan kekasaran permukaan (Ra) dan punca purata kuasa dua kekasaran permukaan (Rq). Eksperimen dijalankan menggunakan AISI 1045 (besi karbon pertengahan), menggunakan pelbagai kadar suapan dan kelajuan potongan. Perbandingan kemudian dibuat pada nilai kekasaran permukaan yang diperoleh melalui kaedah prob jarum stilus konvensional dan melalui teknik pemprosesan imej. Perbandingan menunjukkan kaedah visual memberikan ketepatan dan dapatan konsisten yang munasabah dengan korelasi sehingga 0.99 dengan kaedah prob jarum stilus tradisi. Purata variasi pada nilai Ra dan Rq antara dua kaedah adalah sebanyak 1.65 dan 1.433 peratus, masing-masing. Adapun kaedah visual adalah prosedur tanpa-sentuh, ianya sesuai dijalankan tanpa merosakkan permukaan mesin dalam proses penilaian komponen, juga membantu mengawasi komponen dalam waktu singkat.