Hard disk drive having a built-in self-test for measuring...

Dynamic magnetic information storage or retrieval – Monitoring or testing the progress of recording

Reexamination Certificate

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C360S025000, C360S046000, C360S053000

Reexamination Certificate

active

06208477

ABSTRACT:

BACKGROUND OF THE INVENTION
1. Field of the Invention
This invention relates to a hard disk drive that provides a built-in self test (“BIST”) for measuring readback signal distortion attributable to certain sources including intersymbol interference (“ISI”).
2. Description of the Prior Art
A huge market exists for hard disk drives for mass-market computer systems (“hosts”) such as servers, desktop computers, and laptop computers. To be competitive in this market, a hard disk drive must be relatively inexpensive, and must accordingly embody a design that is adapted for low-cost mass production. In addition, it must provide substantial capacity, rapid access to data, and reliable performance. Numerous manufacturers compete in this huge market and collectively conduct substantial research and development, at great annual cost, to design and develop innovative hard disk drives to meet increasingly demanding customer requirements.
Each of numerous contemporary mass-market hard disk drive models provides relatively large capacity, often in excess of 1 gigabyte per drive. Nevertheless, there exists substantial competitive pressure to develop mass-market hard disk drives having even higher capacities.
Satisfying these competing constraints of low-cost and high capacity requires a design that provides high areal storage density. Areal storage density relates to the amount of data storage capacity per unit of area on the recording surfaces of the disks. The available areal density may be determined from the product of the track density measured radially and the linear bit density measured along the tracks.
The available linear bit density depends on numerous factors including the performance capability of the transducer heads, the media, and certain circuitry that is commonly referred to as a “read channel. “One type of read channel is referred to as a peak-detecting channel; another type is referred to as a sampled-data channel. The type referred to as a sampled-data channel is a category including a partial response, maximum likelihood (“PRML”) channel, a EPR4 channel, and a E
2
PR4 channel.
In a hard disk drive having any of these read channels, the read channel receives an analog read signal from a head during a read operation. The analog read signal is characterized by a “channel frequency.” As used in this art, “channel frequency” is the reciprocal of a time period “T,” where the “T” is the time period consumed while an elemental-length magnet passes under the transducer during a read operation with the disk spinning at a constant angular velocity. In this regard, the length of each magnet recorded along a track as a result of a write operation is, to a first order of approximation, either an elemental length or an integer multiple of the elemental length. Each elemental length magnet can be referred to as a “bit cell” that is defined during a write operation.
In a hard disk drive employing a peak detecting channel, digital data are represented in the media by transitions between oppositely magnetized bit cells. Provided that the transitions between oppositely magnetized bit cells do not unduly interfere with each other, each such transition causes a peak in the analog read signal, and a peak-detecting channel employs a peak detector that detects such peaks, and produces digital signal in the form of a serial, binary-valued signal. Interference between adjacent transitions referred to as ISI has a relatively high adverse effect on performance of a peak detecting channel, particularly in the environment of a relatively high channel rate.
A sampled-data channel employs sampling circuitry that processes an analog read signal to produce a sequence of digital samples. The digital samples so produced are supplied in sequence to a detector such as a so-called ‘Viterbi detector” that internally produces symbols and maps the internally-produced symbols to binary-valued symbols. In a PRML channel, such internally-produced symbols are often referred to as: “−1”; “0”; and “+1”; and the binary-valued symbols are supplied to a deserializer to produce a parallel-by-bit digital signal.
The analog read signal contains random noise, and otherwise departs from ideal as a result of numerous effects such as ISI. A paper containing useful background information concerning such distortions has been authored by Palmer, D and Ziperovich, P., and is titled
Identification Of Nonlinear Write Effects Using Pseudorandom Sequences
, IEEE Transactions On Magnetics, Vol. Mag-23, No. 5, September 1987, pp 2377-2379 (the “Palmer paper”). The Palmer paper discusses linear and nonlinear distortions that occur in read channels, and describes a technique for separating linear and nonlinear effects, based on the unique properties of a type of codeword referred to as a maximal-length psuedorandom sequence (a “PN sequence”) of data.
The Palmer paper sets forth the following description of an experimental procedure for carrying out the disclosed technique for measuring nonlinear distortion separately from linear distortion:
“Several tracks around the test track are AC-erased by writing with a short-wavelength constant-frequency pattern. A maximal-length 63 bit pseudorandom sequence is written over the selected overwrite condition. A complete period of the readback waveform is captured and averaged with a digitizing oscilloscope. The Fourier transform of the readback waveform is divided by the transform of the discrete-time pseudorandom sequence to obtain the channel transfer function. The inverse transform yields a time domain response which in the absence of nonlinear distortion would be a simple dipulse. However, for a channel with nonlinerities there are a number of smaller perturbations or echoes on either side of the main dipulse . . . . By determining which echoes are present and measuring the amplitudes relative to the main dipulse, the physical mechanisms can be inferred and quantified. The same result can be obtained by a least-squares method.”
Another paper containing useful background information is titled
Nonlinear Distortion Measurement Techniques
, Partial Response Maximum Likelihood (PRML) Working Group of the International Disk Drive Equipment and Materials Association (IDEMA), September, 1995. (the “IDEMA Working paper”). A copy of the IDEMA Working paper is being submitted as part of the prosecution history hereof. One section of the IDEMA paper concerns a technique referred to therein as “Dipulse Extraction.” The IDEMA paper sets forth the following 11-step procedure for performing the dipulse extraction measurement:
“1) Select a maximal length pseudorandom bit sequence (PRBS).
2) Record several consecutive repetitions of the PRBS on the disk.
3) Using a digital oscilloscope capture and instantaneous average more than one period of the playback waveform.
4) Download the digitized waveform to a computer.
5) In the computer resample the waveform so that there are N samples per bit, where N is an integer. A typical value of N is 8 or 10.
6) Calculate the discrete Fourier Transform of exactly one period of the digitized and resampled PRBS playback waveform.
7) Create an oversampled version of the PRBS in which (N−1) zeros are inserted between each bit of the original PRBS.
8) Calculate the discrete Fourier Transform (DFT) of the oversampled PRBS.
9) Divide the DFT of the waveform by the DFT of the oversampled PRBS and take the inverse DFT of the result. The result is composed of a dipulse and several smaller, shifted dipulse responses which are referred to as echoes.
10) (optional) Circularly rotate the result of step 9 so that the dipulse is centered. Refer to the center as time zero.
11) Measure the ratio of the amplitudes of the main pulse to the various echoes. Each ratio indicates the amount of nonlinearity present in the recording system.”
The procedures described in the Palmer paper and in the IDEMA paper have limited practical application (e.g., in an engineering laboratory), but are too complex, time-consuming, and labor-intensive for practical application in unit-by-unit testing

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