Bad Column Screening in Data Storage Media
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Solution Overview
Problem
Conventional methods for screening bad columns in data storage media are limited by the number of available labels, leading to valid data storage space being wasted as normal columns are incorrectly labeled as bad, reducing the overall capacity of the medium.
Innovation Solution
A method involving writing predetermined data into sample blocks, calculating error bits, defining an inspection window, and determining the start and terminal points of bad column intervals to accurately label only defective columns, thereby maximizing valid storage capacity by reserving mistakenly labeled columns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional bad column screening methods are used, then all bad columns can be identified, but normal columns are mistakenly labeled as bad, reducing valid storage capacity
Solution Approach 1:
The patent applies local quality by introducing an inspection window that examines only a portion of columns at a time rather than treating all columns uniformly. By locally analyzing error bit distributions within the inspection window and comparing against a threshold, the method selectively identifies bad columns without mistakenly labeling normal columns, thus preserving valid storage capacity while maintaining identification reliability.
2Quantity of substance
If the number of available labels for bad columns is limited, then labeling capacity is constrained, but using all labels results in normal columns being labeled as bad
Solution Approach 1:
The patent applies parameter changes by introducing a threshold parameter for error bit counting within the inspection window. By adjusting this threshold, the method optimizes the balance between identifying bad columns and avoiding false positives. This parameter-based approach enables accurate column classification even with limited label availability, preventing normal columns from being mislabeled while effectively utilizing the limited label resource.
Data Source
AI summary
A method for screening bad columns in a data storage medium includes steps of: writing predetermined data into at least one sample block; comparing the written data with the predetermined data to calculate numbers of error bits in the plurality of columns; defining an inspection window covering a portion of the columns; summing the numbers of error bits in the portion of columns in the inspection window to obtain a total number of error bits and determining whether the total number of error bits is greater than a number of correctable bits; if yes, determining a start point and a terminal point of a bad column interval in the inspection window, wherein the numbers of error bits in the columns between the start point and the terminal point are greater than a threshold of error bits; and labeling the columns in the bad column interval as bad columns.