Multi-Pass Data Sector Recovery via Block-Level Quality Selection
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Solution Overview
Problem
As hard disk drives increase areal density, they experience increased chances of read errors due to misregistration, where the read/write head is not centered over the track, leading to weak signal detection and interference from adjacent tracks, causing multiple retry attempts to fail in recovering data sectors.
Innovation Solution
A data recovery method that involves reading a data sector with multiple passes of a read head at different cross-track offsets, dividing each sector into blocks, calculating the deviation of each block, and selecting the highest quality data from each pass to combine and form recovered data, using a retry buffer to store and process data from multiple attempts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple retry attempts are made to read data sectors, then data recovery chances increase, but read errors due to misregistration and adjacent track interference persist causing retries to fail
Solution Approach 1:
The patent divides a data sector into multiple blocks and performs separate read operations on each block. By segmenting the sector, the system can identify and select only the high-quality portions from multiple retry attempts, rather than requiring complete sector recovery. This segmentation allows selective data recovery even when some blocks remain corrupted despite multiple retries.
Solution Approach 2:
The patent evaluates the quality of individual blocks separately and selects only the high-quality blocks from multiple retry attempts. Instead of treating the entire sector uniformly, the system applies local quality assessment to each block, allowing recovery of usable data portions while discarding corrupted segments. This local quality approach maximizes data recovery by accepting partial sector recovery.
2Quantity of substance
If areal density of recording media is increased to meet storage demands, then storage capacity increases, but misregistration errors and adjacent track interference increase causing more read failures
Solution Approach 1:
By dividing sectors into blocks and processing them independently, the system can tolerate higher error rates associated with increased areal density. The segmentation allows the system to recover data from blocks that were readable despite misregistration issues, maintaining effective storage capacity even as density increases and errors become more frequent.
Solution Approach 2:
The patent changes the approach from requiring complete sector integrity to accepting partial block-level recovery. By modifying the recovery threshold and acceptance criteria at the block level rather than sector level, the system can effectively utilize storage capacity at higher areal densities where error rates are inherently higher.
Data Source
AI summary
A data sector is read using two or more passes of a read head over a recording medium. Each of the passes corresponds to a different cross-track offset, each of the data sectors being divided into two or more blocks. For each of the blocks, data is selected from one of the passes that read the block with a higher quality than other passes that read the block. The selected data from each of the blocks to is combined to form recovered data of the data sector.