Long Data Record Analysis Using Reference Waveform Deviation
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Solution Overview
Problem
Analyzing long data records in digital oscilloscopes is time-consuming due to the need to scroll through and scan large amounts of data to identify trends and problem areas, especially when the data is repetitive or not segmented, requiring additional effort for statistical analysis.
Innovation Solution
A data analysis technique that uses a reference frame, either user-provided or calculated, to compare with the long data record, identifying significant deviations and outliers, which are then displayed as iconic images, allowing for quick identification of problem areas by varying tolerance values and highlighting deviations in waveform shapes or time intervals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the user scrolls through frames one at a time to analyze long data records, then the user can visually compare each frame with a reference waveform, but the analysis process becomes very time consuming
Solution Approach 1:
The patent segments the long data record into multiple frames and further divides each frame into segments. It then creates a summary frame that consolidates key information from all frames, allowing users to analyze the entire long data record by examining a single summary frame rather than scrolling through thousands of individual frames. This segmentation approach maintains measurement precision while dramatically reducing analysis time.
Solution Approach 2:
The patent creates a summary frame that is a condensed representation or copy of the essential information from all frames in the long data record. This summary frame contains aggregated data and highlighted outliers, serving as a simplified copy that preserves the critical information needed for analysis without requiring users to examine every original frame individually.
2Measurement precision
If the user scans timestamp tables to locate records with significant deviations, then problem areas can be identified, but the scanning of large columns of numbers is very time consuming
Solution Approach 1:
The patent extracts only the most significant information from the timestamp tables and frames, specifically identifying and highlighting outlier records that deviate significantly from the reference. Instead of requiring users to scan all timestamp entries, the system extracts and presents only the problematic records that need attention, dramatically reducing scanning time while maintaining detection accuracy.
Solution Approach 2:
The patent uses visual highlighting and color changes to indicate records with significant deviations in the summary frame. Problematic records are visually distinguished from normal records through color coding and highlighting, allowing users to quickly locate issue areas without manually scanning numerical data, thereby reducing scanning time while preserving deviation detection capability.
3Measurement precision
If the entire long data record is analyzed without segmentation, then comprehensive analysis is possible, but the user has to scroll through the long data record looking for problem signatures
Solution Approach 1:
The patent segments the long data record into multiple frames and creates a summary frame that represents the entire dataset. This segmentation allows comprehensive analysis coverage by ensuring all frames are processed and represented in the summary, while simultaneously improving ease of operation by presenting the consolidated information in a single viewable frame rather than requiring navigation through the entire long record.
Solution Approach 2:
The patent transitions from analyzing data in the time dimension (scrolling through sequential frames) to analyzing data in a condensed dimensional representation (summary frame). The summary frame aggregates information from all time points into a single comprehensive view, maintaining complete coverage while changing the dimension of analysis from temporal sequence to consolidated representation, thereby improving ease of operation.
Data Source
AI summary
A data analysis technique for a long data record in a memory uses a reference, either user-provided or calculated from the data in the long data record, as a representative event. Each event in the long data record is compared with the reference to determine whether there are significant deviations from the reference. Those events having significant deviations are identified as events of particular interest for a user. The reference may be either a waveform shape or a mean time interval between events. A tolerance value may be added to the waveform reference and varied for dynamic limit testing. Events that are outside the waveform reference as modified by the tolerance value are identified as outliers and may be reduced to iconic images for display simultaneously with the long data record and a selected one of the outliers.