Historian Interface System for Dynamic Industrial Data Visualization
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Solution Overview
Problem
Industrial processes generate overwhelming volumes of data from sensors and control elements, which existing data management systems struggle to efficiently process and visualize, particularly in complex industrial environments, leading to difficulties in identifying and addressing potential issues within these systems.
Innovation Solution
A historian interface system that includes a local historian coupled with a remote display device over a communication network, allowing for contextualization and dynamic visualization of time-series data through a graphical user interface, enabling users to select and analyze tags based on metadata attributes, and dynamically determine an optimal visualization scheme for efficient data analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional data management systems are used to store and retrieve industrial process data, then data storage capability is maintained, but data retrieval efficiency and visualization quality deteriorate due to overwhelming data volumes and strict query syntax requirements
Solution Approach 1:
The patent introduces an intermediary layer between the historian system and the user interface that automatically translates natural language or simplified queries into the required strict query syntax. This intermediary handles the complexity of SQL syntax and data retrieval logic, allowing users to interact with the system using simple, intuitive language while maintaining efficient data access to the underlying historian database.
Solution Approach 2:
The system creates visual copies and representations of the underlying process data through graphical icons, panels, and hierarchical displays. Instead of requiring users to work directly with raw data or complex queries, the system generates visual copies that represent process variables, trends, and relationships in an easily interpretable format, significantly improving data retrieval efficiency and user understanding.
2Ease of operation
If detailed tabular formats are used to display retrieved data, then data completeness is maintained, but ease of understanding and problem identification deteriorates due to inefficient visual presentation
Solution Approach 1:
The patent segments the display of process data into hierarchical levels: overview panels showing summary information, detailed panels showing specific variable trends, and contextual panels showing related process information. This segmentation allows users to understand data at appropriate levels of detail without being overwhelmed by complete tabular data, while still maintaining access to all necessary information through organized, contextually-relevant groupings.
Solution Approach 2:
The system transforms one-dimensional tabular data into multi-dimensional visual presentations using graphical icons, color-coded indicators, hierarchical panel structures, and spatial relationships. This dimensional transformation preserves all contextual information while making it visually accessible and easier to understand, allowing users to quickly identify problems through visual patterns rather than scanning tables.
3Measurement precision
If thousands of sensors and control elements monitor industrial processes, then measurement precision and process control accuracy are improved, but data volume and processing complexity increases to overwhelming levels
Solution Approach 1:
The patent merges data from thousands of individual sensors and control elements into organized groups and panels based on process hierarchy and functional relationships. Related variables are combined into cohesive display units that show collective behavior patterns, reducing the perceived data volume while maintaining all measurement precision. The system consolidates redundant information and presents aggregated views that preserve critical details.
Solution Approach 2:
The system extracts and highlights only the most critical and relevant information from the overwhelming data volume, separating essential process variables from less important data. Through intelligent filtering and prioritization based on process context and user needs, the system extracts key trends and anomalies for immediate attention while maintaining access to the complete data set for detailed analysis when needed.
Data Source
AI summary
A historian interface system provides a graphical representation of tags that represent attributes of a continuous process. A historian system stores the tags and metadata values describing the tags. A display device coupled to the historian system via a communication network displays graphical representations of the tags via display panels and receives selections of the tags. The historian system contextualizes selected tags based on the metadata values describing the selected tag and determines an optimal visualization scheme for the selected tags. The display device displays graphical representations of values of the tags and dynamically determines optimal grouping of the tags based on properties of the display device.