Magnetic Recording RRO Interpolation With Fewer Samples
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Solution Overview
Problem
Existing data processing systems for magnetic recording devices are inefficient in obtaining accurate data, particularly for repeatable run out (RRO) information, requiring extensive sampling that prolongs acquisition time.
Innovation Solution
A data processing device utilizing an acquisitor and processor that employs a learning model with adjustable parameters to interpolate and correct data processing, reducing the difference between sampled and actual RRO data, enabling efficient and accurate data representation with fewer samples.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If extensive sampling is performed to obtain accurate RRO data, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent applies preliminary action by performing initial sampling to acquire RRO data, then using interpolation processing to generate additional data points before final correction. This preliminary data generation reduces the need for extensive direct sampling, thereby shortening acquisition time while maintaining accuracy through subsequent correction using the learned difference values.
Solution Approach 2:
The patent implements feedback by calculating the difference between measured RRO data and interpolated RRO data, then using this difference information to correct future interpolation results. This feedback mechanism allows the system to learn from measurement errors and improve accuracy, enabling reduced sampling while maintaining high measurement precision.
2Loss of time
If fewer samples are used for data acquisition, then loss of time is reduced, but measurement precision deteriorates
Solution Approach 1:
The patent introduces an intermediary processing step between sampling and final data generation. Instead of directly using interpolated data or raw sampled data, the system computes the difference between them and applies this as a correction term. This intermediary correction mechanism enables accurate RRO data generation from fewer samples by compensating for interpolation errors.
Solution Approach 2:
The patent changes the parameter representation by transforming the problem from directly generating accurate RRO data to generating the difference between measured and interpolated data. This parameter transformation allows the system to work with fewer samples while maintaining accuracy, as the difference values capture the essential error patterns that need correction.
3Productivity
If interpolation processing is applied to generate RRO data, then productivity is improved, but manufacturing precision deteriorates
Solution Approach 1:
The patent replaces the mechanical approach of extensive direct sampling with a computational system combining interpolation and correction. Instead of relying solely on numerous physical measurements, the system uses mathematical interpolation to generate data points and applies learned correction differences to maintain accuracy. This substitution improves productivity while preserving precision through the correction mechanism.
Solution Approach 2:
The patent performs preliminary interpolation to generate RRO data points before applying correction. This preliminary action allows the system to quickly generate data through computation rather than waiting for extensive sampling, improving productivity. The subsequent correction step then refines these interpolated values to maintain manufacturing precision.
Data Source
AI summary
According to one embodiment, a data processing device includes an acquisitor and a processor. The acquisitor is configured to acquire a plurality of second data corresponding to at least a part of waveform data including a first data. the processor is configured to perform a first operation and a second operation. The processor is configured to correct a first processing so that a difference between the first data and fourth data obtained by interpolating a plurality of third data obtained by processing the plurality of second data by the first processing decreases in the first operation. The processor is configured to process a plurality of fifth data by the first processing after the correcting to derive a plurality of sixth data in the second operation.