An Overview of the PES Pareto Method for Decomposing Baseline Noise Sources in Hard Disk Position Error Signals
نویسندگان
چکیده
Daniel Abramovitch Hewlett-Packard Laboratories 1501 Page Mill Road, M/S 2U-10 Palo Alto, CA 94304 Abstract– This paper describes the PES Pareto Method, a useful tool for identifying and eliminating key contributors to uncertainty in the Position Error Signal (PES) of a magnetic disk drive[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 finding ways to reduce their magnitude or by altering system components to reduce sensitivitity to the the noise 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, (2) a measurement methodology that allows for the isolation of individual noise sources, and (3) a system model that allows these sources to be recombined to simulate the drive’s Position Error Signal. The method requires the measurement of frequency 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 Company. In this disk drive, it is discovered that the two most significant contributors to PES baseline noise are the turbulent wind flow generated by the spinning disks (“Windage”) and the noise involved in the actual readback of PES (“Position Sensing Noise”).
منابع مشابه
Decomposition of Baseline Noise Sources in Hard Disk Position Error Signals Using the PES Pareto Method
This paper uses the PES Pareto Method[1] and measurement techniques for isolating noise sources[2] to decompose the Position Error Signal (PES) of a Lynx II hard disk drive manufactured by Hewlett-Packard. This accomplishes three things: it demonstrates the utility of the PES Pareto Method in a practical example, it allows us to discover which noise sources are insignificant to PES, and it iden...
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