Development of automatic surface inspection system of castings

Inspection of castings is performed manually, because castings have complic ated shapes and often include a variety of defects. However, this method of inspection is often less reliable due to reasons such as operator fatigue and changes in the environment. A method for automatic inspection of castin gs using image processing is described in this paper. Here, a method to red uce noise attributable to surface roughness is first introduced. This techn ique involves uniform illumination using several ring-shaped fluorescent la mps. Next, an image processing-based band-pass filter, which is used to dis tinguish between defect signals and surface roughness-induced noise, is dis cussed. This filter is composed of averaging and differential operators, an d improves the signal-to-noise ratio, from 1.67 to 5.35. Finally, a statist ical method, to distinguish between actual defects and 'pseudo' defects res ulting from steps, edges, dimples and embossed characters on the casting su rface, is described. In this method test pieces are compared with statistic al data obtained from several good castings. When applied on lint, the prop osed method could be used to successfully distinguish between good and defe ctive castings.