Industrial Monitoring Plot Overlay for Automated Trend Alignment
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Solution Overview
Problem
Industrial condition monitoring systems face challenges in effectively operating graphical user interfaces due to a decreasing availability of technically inclined personnel, necessitating improved methods for automating data visualization and trend analysis across multiple equipment and time periods.
Innovation Solution
The system automates the overlay of data from multiple graphical plots within a condition monitoring system's graphical user interface, allowing for automatic alignment and comparison of trends across different equipment and time periods, enabling quick identification of similar trends and potential issues without manual operator input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual data comparison and analysis methods are used in condition monitoring systems, then operators can perform detailed equipment diagnostics, but the complexity of operation increases and requires highly skilled personnel
Solution Approach 1:
The system performs preliminary actions by automatically detecting features of interest in historical data and pre-aligning multiple plots based on these features before the operator needs to analyze current equipment data. This pre-processing reduces the operational complexity while maintaining diagnostic accuracy.
Solution Approach 2:
The system creates visual copies of historical equipment data plots and overlays them with current equipment data plots. This copying approach allows operators to compare current conditions with historical patterns without manually processing raw data, simplifying the interface while preserving analytical depth.
2Loss of information
If multiple data plots are displayed simultaneously for comprehensive equipment monitoring, then more information becomes available for diagnosis, but the device complexity and interface difficulty increase
Solution Approach 1:
The system merges multiple data plots representing different equipment or time periods by aligning them based on detected features of interest. This combining approach displays comprehensive information in an integrated view rather than requiring operators to manually switch between multiple separate plots.
Solution Approach 2:
The system adds a temporal dimension to data visualization by overlaying historical plots with current plots, allowing operators to view multiple time periods simultaneously. This dimensional approach consolidates information that would otherwise require separate displays.
3Productivity
If automated feature detection and plot alignment is implemented, then data comparison speed increases, but the extent of automation requires sophisticated algorithms
Solution Approach 1:
The system performs self-service by automatically detecting features of interest in the data and autonomously aligning multiple plots based on these detected features. This self-automation eliminates the need for manual plot alignment while maintaining diagnostic accuracy, though it does require sophisticated detection algorithms.
Data Source
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AI summary
Systems and methods include receiving an indication of a selection of a first piece of equipment in an industrial monitoring system. The systems and methods also include determining a first feature of interest (150,151) in a plot corresponding to a first sensor. Additionally, the systems and methods include matching the first feature of interest (150,151) with corresponding second features of interest (154,155) in a second plot. Furthermore, the systems and methods include overlaying the first plot with the second plot based at least in part on the first feature of interest (150,151) and the corresponding second feature of interest (154,155).