AN OVERVIEW OF THE PES PARETO METHOD FOR DECOMPOSING BASE-LINE NOISE SOURCES IN HARD-DISK POSITION ERROR SIGNALS

This paper gives an overview of the PES Pareto Method, a useful tool f or identifying and eliminating key contributors to uncertainty in the Position Error Signal (PES) of a magnetic disk drive servo system [1, 2, 3]. Once identified and ranked according to their overall effect on PES, the top-ranking sources can be worked on first, either by findin g ways to reduce their magnitude or by altering system components to r educe sensitivity to the contributors. The PES Pareto Method is based on three ideas: (1) an understanding of how Bode's Integral Theorem [4 ] applies to servo system noise measurements, a measurement methodolog y that allows for the Isolation of individual noise sources, and tem m odel that allows these sources to be recombined to simulate the drive' s Position Error Signal. The method requires the measurement of freque ncy response functions and output power spectra for each servo system element. Each input noise spectrum can then be inferred and applied to the closed loop model to determine its effect on PES uncertainty. The PES Pareto Method is illustrated by decomposing PES signals that were obtained from a hard disk drive manufactured by Hewlett-Packard Compa ny. In this disk drive, it is discovered that the two most significant contributors to PES baseline noise are the turbulent wind flow genera ted by the spinning disks (''Windage'') and the noise involved in the actual read-back of the Position Error Signal (''Position Sensing Nois e'').