1. Field of the Invention
The present invention relates to disk drives for computer systems. More particularly, the present invention relates to techniques for efficiently determining repeatable runout (RRO) in a disk drive.
2. Description of the Prior Art
With reference to
The RRO disturbance due to the disk having a non-centric alignment with the spindle motor is sinusoidal with a period equal to the rotation of the disk. This sinusoidal disturbance can be represented as:
a*cos(2πk/N)+b*sin(2πk/N)
where {a,b} are coefficients corresponding to the magnitude of the disturbance (magnitude of the non-centric offset) and k is an index representing one of N servo sectors.
There is, therefore, a need for a fast, efficient technique for learning the RRO disturbance in a disk drive that may be subjected to a physical shock causing disk slippage.
The present invention may be embodied in a method for adaptive fundamental-frequency repeatable runout (1FRRO) learning in a disk drive to reduce learn time. In the method, 1FRRO compensation information is learned over a predetermined minimum number of disk revolutions. After the predetermined minimum number of disk revolutions, the 1FRRO compensation information is monitored for convergence while learning of the 1FRRO compensation information continues. Learning is terminated upon detection of convergence of the 1FRRO compensation information.
In more detailed features of the invention, the predetermined minimum number of disk revolutions may be equal to or greater than 2, and may be less than 12. For example, the predetermined minimum number of disk revolutions may be equal to 5. The learning may be performed after each disk drive power-on, or after detection of a shock event.
In other more detailed features of the invention, the step of monitoring the 1FRRO compensation information for convergence while continuing learning of the 1FRRO compensation information may comprise at least one disk revolution. The detection of convergence of the 1FRRO compensation information may include initializing convergence monitoring values R and I; updating the convergence monitoring values according to the formulas:
R=R+PES*cos(2πi/N)
I=I+PES*sin(2πi/N)
where: i is an index representing one of N servo sectors, and PES is a position error signal; calculating a convergence value according to the formula:
DFT=DFT+(R2+I2)1/2;
and comparing the convergence value to a threshold to detect convergence of the 1FRRO compensation information.
In an additional more detailed feature of the invention, the method may further comprise concurrently learning and monitoring harmonic-frequency repeatable runout (nFRRO) compensation information for convergence. Learning of the nFRRO compensation information may be terminated upon detection of convergence of the nFRRO compensation information.
The invention also may be embodied in disk drive having a disk and a control system. The disk has a plurality of concentric data tracks defined by embedded servo wedges, and has some eccentricity exhibiting fundamental frequency runout (1FRRO). The control system is operable to perform the method steps.
The invention also may be embodied in a disk drive with adaptive fundamental-frequency repeatable runout (1FRRO) learning to reduce learn time. The disk drive includes means for learning 1FRRO compensation information over a predetermined minimum number of disk revolutions; means for monitoring, after the predetermined minimum number of disk revolutions, the 1FRRO compensation information for convergence while continuing learning of the 1FRRO compensation information; and means for terminating learning upon detection of convergence of the 1FRRO compensation information.
The accompanying drawings illustrate embodiments of the present invention and, together with the description, serve to explain the principles of the invention.
With reference to
The present invention may be particularly advantageous with smaller form-factor disk drives 30 used in mobile devices which may be subject to shock forces. The shock forces may cause a mechanical slip in the position between a disk hub and the disk 34. The slip may cause a large 1FRRO that acts as a disturbance in the disk drive's servo system. Using the adaptive learning techniques may save learning time because it may reduce the number of disk revolutions required to learn the 1FRRO.
The predetermined minimum number of disk revolutions may be equal to or greater than 2, and may be less than 12. For example, the predetermined minimum number of disk revolutions may be equal to 5. The learning may be performed after each disk drive power-on, or after detection of a shock event.
The monitoring the 1FRRO compensation information for convergence while continuing learning of the 1FRRO compensation information (step 16) may comprise at least one disk revolution. The detection of convergence (step 18) of the 1FRRO compensation information may include initializing convergence monitoring values R and I; updating the convergence monitoring values according to the formula:
R=R+PES*cos(2πi/N)
I=I+PES*sin(2πi/N)
where: i is an index representing one of N servo sectors, and PES is a position error signal; calculating a convergence value according to the formula:
DFT=DFT+(R2+I2)1/2;
and comparing the convergence value to a threshold to detect convergence of the 1FRRO compensation information.
The disk drive may include a transducer head 32, the rotating magnetic disk 34 having a plurality of concentric data tracks 36 defined by embedded servo wedges 38 that provide position information, and an actuator 40 coupled to the head. Eccentricities in the disk between a spindle 41 and the concentric data tracks may be exhibited in the form of the 1FRRO. Adaptive feed-forward cancellation (AFC) may used to cancel repeatable runout (RRO) in the disk drive 30 as shown with reference to the servo control loop 44 in
The control system 47 of the disk drive 30 (
The magnetic media surface of the disk 34 is accessed using the head 32. The tracks 36 on the media surface may be divided into storage segments. Each storage segment typically begins with a servo sector which is followed by data sectors. The servo sector for a storage segment corresponds to an intersection with the radially-extending embedded servo wedges 38. Each servo sector includes a track address for generating a coarse position for the head, and servo bursts for generating a fine position of the head with respect to the centerline of the target track. The data sectors may include data blocks, each generally storing 512 data bytes. Each data block may be addressed using a logical block address (LBA).
The invention also may be embodied in a disk drive 30 with adaptive fundamental-frequency repeatable runout (1FRRO) learning to reduce learn time. The disk drive includes means for learning 1FRRO compensation information over a predetermined minimum number of disk revolutions; means for monitoring, after the predetermined minimum number of disk revolutions, the 1FRRO compensation information for convergence while continuing learning of the 1FRRO compensation information; means for terminating learning upon detection of convergence of the 1FRRO compensation information; and means for storing the 1FRRO compensation information for use after the disk drive ready time. The control system 47 may comprise the means for performing the recited functions.
With reference to
The learning technique may be applied harmonic frequencies. Harmonic-frequency repeatable runout (nFRRO) compensation information may be learned and monitored for convergence. The detection of convergence of the nFRRO compensation information may include initializing convergence monitoring values Rn and In; updating the convergence monitoring values according to the formula:
Rn=Rn+PES*cos(2πni/N)
In=In+PES*sin(2πni/N)
where: i is an index representing one of N servo sectors, PES is a position error signal, and n is the harmonic number; calculating a convergence value according to the formula:
DFT=DFT+(R2+I2)1/2;
and comparing the convergence value to a threshold to detect convergence of the nFRRO compensation information. The harmonic frequency learning and convergence detection may occur independently from the fundamental frequency learning and convergence detection. Alternatively, the harmonic frequency learning and convergence detection may occur concurrently with the fundamental frequency learning and convergence detection. The learning may be terminated upon detection of convergence of the nFRRO compensation information, or upon detection of convergence of both the 1FRRO compensation information and the nFRRO compensation information.
Number | Name | Date | Kind |
---|---|---|---|
5949605 | Lee et al. | Sep 1999 | A |
6069764 | Morris et al. | May 2000 | A |
6141175 | Nazarian et al. | Oct 2000 | A |
6310742 | Nazarian et al. | Oct 2001 | B1 |
6437936 | Chen et al. | Aug 2002 | B1 |
6449116 | Morris et al. | Sep 2002 | B2 |
6519108 | Au et al. | Feb 2003 | B2 |
6549362 | Melrose et al. | Apr 2003 | B1 |
6556371 | Ottesen et al. | Apr 2003 | B1 |
6563663 | Bi et al. | May 2003 | B1 |
6587302 | Ahn | Jul 2003 | B2 |
6650499 | Kusumoto | Nov 2003 | B1 |
6678108 | Smith et al. | Jan 2004 | B2 |
6826006 | Melkote et al. | Nov 2004 | B1 |
6898047 | Shishida et al. | May 2005 | B2 |
6924959 | Melkote et al. | Aug 2005 | B1 |
6937420 | McNab et al. | Aug 2005 | B1 |
6937424 | Chang et al. | Aug 2005 | B2 |
6975480 | Codilian et al. | Dec 2005 | B1 |
6999267 | Melkote et al. | Feb 2006 | B1 |
7046477 | Shibata | May 2006 | B2 |
7088547 | Wang et al. | Aug 2006 | B1 |
7106547 | Hargarten et al. | Sep 2006 | B1 |
7139149 | Sun et al. | Nov 2006 | B1 |
7196864 | Yi et al. | Mar 2007 | B1 |
7304819 | Melkote et al. | Dec 2007 | B1 |
7423834 | Sun et al. | Sep 2008 | B1 |
7450336 | Wang et al. | Nov 2008 | B1 |
7576941 | Chen et al. | Aug 2009 | B1 |
7583470 | Chen et al. | Sep 2009 | B1 |
7764459 | Cho | Jul 2010 | B2 |
7894156 | Ehrlich et al. | Feb 2011 | B2 |
20030123180 | Settje et al. | Jul 2003 | A1 |
20040246619 | Zhang | Dec 2004 | A1 |
20070297088 | Sun et al. | Dec 2007 | A1 |
Entry |
---|
U.S. Appl. No. 60/782,909, filed Mar. 15, 2006, 5 pages. |