Abstract
A Practical Low-Cost Machine Vision Sensor System for Defect Classification on Air Bearing Surfaces
Highlights
In a hard disk drive (HDD), the air bearing surface (ABS) is a small but important part of a slider, which is a part of a head gimbal assembly (HGA) that holds recording heads
At the time of the development of our proposed system, we considered that using a machine vision sensor to detect ABS defects would eliminate human error and increase the number of units processed per hour
We devised techniques that worked, its function was inspired from the “wand” tool in Photoshop software, and we found it to be satisfactory for our defect detection scheme
Summary
In a hard disk drive (HDD), the air bearing surface (ABS) is a small but important part of a slider, which is a part of a head gimbal assembly (HGA) that holds recording heads. The ABS controls the flying height of the slider above a magnetic disk. For a very high density HDD, the recording head on a slider flies extremely close to the magnetic disk with a clearance of only a small fraction of a microinch.[1] Figure 2 shows a schematic of a flying slider over a spinning disk. The quality of an HDD is as good as the quality of its ABS; an effective defect detection process is necessary. The types of defects of an ABS focused on in this paper are stains, contaminating particles, and metal scratches. An effective defect detection method is detection by image processing, but a major problem with an image processing system is the inconsistent quality of acquired images in terms of intensity, contrast, and resolution
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