Time-Series Data Filtering for Industrial Process Visualization
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Solution Overview
Problem
Current industrial process control systems face challenges in efficiently managing and displaying large volumes of time-series data, as traditional methods consume significant computer resources and fail to adequately address instances where the sample rate exceeds the rate at which data can be effectively displayed on graphical interfaces.
Innovation Solution
A client application invokes filtering operations on received time-series data, applying techniques such as best fit, swinging door, and value/time filtering to reduce the number of data points plotted, thereby optimizing data display and reducing computational burden.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all time-series data points are plotted on graphical displays, then complete data representation is achieved, but computer resources are excessively consumed and display efficiency deteriorates
Solution Approach 1:
The patent extracts only the essential data points from the complete time-series dataset for graphical display. By applying filtering operations that identify and retain only significant data points (those representing actual process changes) while discarding redundant points (those within deadband ranges), the system achieves effective data representation with reduced computational burden.
Solution Approach 2:
The patent applies partial action by plotting only a subset of data points rather than all available points. The filtering mechanism selectively processes data points based on predetermined criteria (deadband filtering, time-based filtering), performing the plotting action only on necessary points while skipping unnecessary ones, thereby reducing resource consumption without sacrificing essential information.
2Measurement precision
If high sample rates are used for data acquisition, then measurement precision is improved, but the rate at which data can be effectively displayed becomes the limiting factor
Solution Approach 1:
The patent introduces filtering operations as an intermediary between data acquisition and data display. This intermediary layer processes the high-sample-rate data stream, applying deadband filtering and time-based filtering to reduce the data points to a manageable subset that can be effectively displayed, thereby bridging the gap between high measurement precision and display rate limitations.
Solution Approach 2:
The patent changes the parameter of data point density by applying filtering operations that selectively reduce the number of plotted points. By transforming the raw high-sample-rate data into a filtered dataset with reduced point density (while preserving essential information), the system resolves the contradiction between measurement precision and display rate.
3Productivity
If filtering operations are applied to reduce data points, then computational efficiency is improved, but data processing complexity increases
Solution Approach 1:
The patent segments the data processing task into distinct filtering operations (deadband filtering, time-based filtering) that can be applied sequentially. This segmentation allows each filtering operation to be independently optimized and managed, reducing overall processing complexity while maintaining efficiency gains from data reduction.
Data Source
AI summary
A process control and manufacturing information database client application is disclosed for rendering and displaying a filtered set of received time-series data. A client application, such as a trending client that graphically displays a series of data point values for a particular observed parameter of a manufacturing process receives, via a data acquisition interface, a set of timestamped time-series data values for an observed parameter from a process control and manufacturing information database. Thereafter, the client application invokes a time-series data filter that includes/supports at least one filtering operation that is applied to the set of timestamped time-series data values to render a filtered data set for plotting/drawing on the graphical display interface. The filtered data set is thereafter rendered by a display function as a series of plotted points on a time-line graph.