Data Processor for Magnetic Recording Control Accuracy
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Solution Overview
Problem
Current magnetic recording/reproducing devices face challenges in achieving high-density recording and reproduction due to limitations in control accuracy, with existing methods either requiring long-time measurements for high-resolution data or relying on low-resolution data that results in insufficient accuracy.
Innovation Solution
A data processor is implemented with an interface section and processor that acquires partial data on control conditions, processing it using multiple models to derive high-resolution data, selecting the appropriate model based on characteristics to enhance control accuracy and reduce differences with true high-resolution data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If long-time measurement is performed to obtain high-resolution control data, then measurement precision is improved, but productivity deteriorates due to extended measurement time
Solution Approach 1:
The system performs preliminary classification of recording positions into multiple regions based on track density before conducting measurements. This preliminary action allows subsequent measurements to be focused only on necessary regions with appropriate resolution, avoiding full high-resolution measurement across all positions and thus reducing measurement time while maintaining necessary precision.
Solution Approach 2:
The system applies partial measurement strategy by measuring only specific regions at high resolution rather than uniformly measuring all recording positions. The classification-based approach enables selective high-resolution measurement in critical regions while using lower resolution or no measurement in less critical regions, achieving acceptable overall control accuracy with reduced measurement time.
2Productivity
If low-resolution data is used for control, then productivity is improved by reducing measurement time, but measurement precision deteriorates resulting in insufficient control accuracy
Solution Approach 1:
The system applies different measurement resolutions to different recording position regions based on their classification. Critical regions requiring high control accuracy receive high-resolution measurements, while less critical regions use lower resolution or no measurement. This local differentiation optimizes the balance between measurement precision and productivity by allocating measurement resources according to actual needs.
3Device complexity
If single model processing is used for simplicity, then device complexity is reduced, but measurement precision deteriorates due to inability to handle diverse data characteristics
Solution Approach 1:
The system segments the data processing task by dividing recording positions into multiple classified regions and applying different processing models to each region based on its characteristics. This segmentation allows each model to be optimized for specific data types while keeping individual models relatively simple, achieving high overall precision without requiring one excessively complex universal model.
Data Source
AI summary
According to one embodiment, a data processor includes an interface section and a processor. The interface section is configured to acquire partial data relating to a control condition of a magnetic recording/reproducing device. The processor is configured to process the partial data. The processor is configured to derive a first data by processing the partial data with a first model based on characteristics of the partial data, a first resolution of the first data being higher than a partial resolution of the partial data. The processor is configured to derive a second data by processing the partial data with a second model based on the characteristic. The second model is different from the first model. A second resolution of the second data being higher than the partial resolution.