Dynamic Sensor Data Grouping for Industrial Monitoring GUIs
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Solution Overview
Problem
Industrial condition monitoring systems face challenges in effectively presenting and analyzing data from various sensors due to a lack of technically inclined personnel, necessitating improved graphical user interface (GUI) systems that can dynamically group and visualize data in a comprehensible manner.
Innovation Solution
A condition monitoring system with a dynamic GUI that allows users to select grouping modes for sensor data, displaying measurements in columns based on machine trains, machines, or sensors, enabling real-time data organization and visualization of industrial processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional static GUI displays are used for condition monitoring data, then the system structure is simple, but the ease of operation deteriorates due to inability to dynamically adapt to different analysis needs
Solution Approach 1:
The GUI display system is transformed from a static layout to a dynamic one that automatically reconfigures based on user selections and data characteristics. The display dynamically groups measurements by machine train, machine, or sensor based on user input, allowing the interface to adapt its structure and organization in real-time without requiring manual reconfiguration.
Solution Approach 2:
The GUI is designed to perform multiple grouping functions within a single interface framework. It can organize data by machine train, by individual machine, or by sensor type, all within the same display system. This multi-functionality allows the interface to serve diverse analysis needs without requiring separate specialized displays for each scenario.
2Loss of information
If data is displayed in detailed individual measurements, then the measurement precision is high, but the loss of information increases due to overwhelming quantity of data points
Solution Approach 1:
The system merges multiple individual measurement points into grouped displays organized by machine train, machine, or sensor categories. This consolidation reduces the visual clutter of numerous discrete data points while preserving the ability to access and analyze individual measurements when needed, thereby reducing information loss without sacrificing measurement precision.
Solution Approach 2:
The data display is segmented into hierarchical groups (machine trains containing machines containing sensors containing measurements). This segmentation allows users to navigate from high-level groupings to detailed individual measurements, preventing information overload while maintaining access to precise measurement data through the structured organization.
3Adaptability or versatility
If the GUI displays all available sensor data simultaneously, then the adaptability is high, but the device complexity increases due to managing large data volumes
Solution Approach 1:
The GUI implements dynamic data filtering and grouping that adapts to user selections. When a user selects a specific machine train or machine, the system dynamically filters and reorganizes the displayed data to show only relevant measurements in that context, reducing the complexity of managing all data simultaneously while maintaining high adaptability to different analysis scenarios.
Data Source
AI summary
Systems and methods are provided for dynamically grouping data analysis content derived from a plurality of sensors. In one embodiment, a plurality of sensors can be disposed on a plurality of machine trains or one or more machines within the plurality of machine trains configured in an industrial environment. A communication circuit can be operatively coupled to the plurality of sensors and configured to communicate data measured by the plurality of sensors, and a dynamic graphical user interface (GUI) can be provided on a touchscreen display and can be configured to dynamically generate one or more visualizations of the measured data. A processor can be configured to receive the measured data via the communication circuit, to generate a plurality of measurements based on the measured data, and to operatively control the dynamic GUI in response to a grouping mode selection.