Sensor Data Distribution Plotting via Gradient Shading
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Solution Overview
Problem
Existing data plotting methods fail to visually represent how measurement data from sensors distributed over time, making it difficult to monitor machine status effectively in environments with multiple machines and sensors.
Innovation Solution
A method and system that store and display measurement data with a first and second dimension, where each subunit includes minimum, maximum, distribution, mode, and mean values, represented by gradients parallel to the second axis, allowing for a clear graphical representation of data distribution over time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If data is plotted over time using conventional methods, then temporal trends are visible, but the distribution of data across repetitions is not graphically shown
Solution Approach 1:
The patent transforms the conventional single-dimension time-based plot into a two-dimensional representation by adding a distribution dimension. Each vertical bar represents a time point, while the shading within the bar represents the distribution of data points across repetitions, enabling simultaneous visualization of temporal trends and data distribution without increasing overall plot complexity
Solution Approach 2:
The patent segments the data visualization into discrete time points represented as vertical bars, with each bar further segmented into shaded regions that represent different distribution characteristics. This segmentation allows complex distribution information to be broken down into visually distinct segments that are easy to interpret at a glance
2Measurement precision
If detailed distribution statistics are calculated for each subunit, then data distribution is accurately represented, but processing time and computational resources increase
Solution Approach 1:
The patent calculates and displays only the essential distribution statistics (minimum, maximum, mean, mode) rather than all possible statistical measures. This partial action approach provides sufficient accuracy for effective data distribution representation while significantly reducing processing time and computational requirements compared to calculating every possible statistic
3Loss of information
If multiple statistics (min, max, mean, mode, distribution) are displayed for each subunit, then comprehensive data insights are provided, but the plot becomes more complex and harder to interpret
Solution Approach 1:
The patent merges multiple distribution statistics into a unified visual representation using shaded bars. The minimum, maximum, mean, and mode values are combined into a single bar structure where the shading pattern simultaneously encodes all these statistics, making the plot easier to interpret while preserving comprehensive data insights
Solution Approach 2:
The patent uses shading intensity and color variations within the bars to represent different statistical values. By encoding multiple statistics through visual variations in shading rather than separate textual labels or lines, the plot maintains high information density while improving interpretability through intuitive visual cues
Data Source
AI summary
In one aspect, a method for displaying measurement information from at least one sensor of a machine is provided. In another aspect, a computing device for displaying measurement information from at least one sensor of a machine is provided. In another aspect, a system for displaying measurement information from at least one sensor of a machine is provided.