Alarm Graph Visualization for Faster Root-Cause Analysis
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Solution Overview
Problem
Operators in industrial plants face challenges in quickly obtaining an overview of the status and topology of processing systems, particularly during critical phases or alarm situations, due to the complexity of data spread across multiple screens and sources, leading to time-consuming and error-prone alarm analysis.
Innovation Solution
A method is provided to represent the processing system as a directed graph, allowing selection of a starting node, construction of a subgraph based on forward-connected nodes, and outputting relevant attributes, which can be visualized interactively to facilitate fast access to process data and improve alarm handling through machine learning-based anomaly detection and cross-correlation analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If operators manually analyze data from multiple screens and sources, then comprehensive alarm analysis can be achieved, but the process becomes time-consuming and error-prone
Solution Approach 1:
The patent combines multiple data sources and screens into a unified graph visualization that displays the processing system topology and alarm relationships in a single integrated view. This merging eliminates the need for operators to manually switch between multiple screens while maintaining comprehensive analysis capability.
Solution Approach 2:
The patent introduces an automated graph generation and analysis system that acts as an intermediary between raw alarm data and operator decision-making. This intermediary automatically constructs the subgraph, identifies forward-connected nodes, and highlights critical paths, thereby reducing manual analysis time while preserving accuracy.
2Loss of information
If detailed data from all system elements is displayed, then complete system status can be obtained, but data complexity and difficulty of interpretation increase
Solution Approach 1:
The patent extracts only the relevant subset of system elements by constructing a subgraph that includes only forward-connected nodes from the alarm source. This extraction removes unnecessary data while preserving critical information about affected process elements, thereby reducing visualization complexity without losing essential system status.
Solution Approach 2:
The patent applies local quality by differentiating the visualization based on the alarm context - forward-connected nodes are highlighted to show causal relationships, while other nodes are displayed with reduced detail. This selective emphasis makes the visualization easier to interpret while maintaining complete information availability.
3Reliability
If comprehensive alarm data is analyzed, then root cause can be identified, but the analysis process becomes complex and difficult to navigate
Solution Approach 1:
The patent segments the complex alarm analysis process into distinct visual components: the subgraph showing forward-connected elements, directed edges representing causal relationships, and highlighted critical paths. This segmentation organizes comprehensive data into manageable visual segments that are easier to navigate while maintaining complete analytical capability.
Solution Approach 2:
The patent transforms traditional flat alarm data into a multi-dimensional graph visualization that adds spatial and relational dimensions. By representing system elements as nodes and relationships as directed edges in a graphical layout, the system makes complex causal relationships more intuitive and easier to navigate while preserving complete alarm analysis capability.
Data Source
AI summary
A method for providing an attribute of an element in a processing system having a plurality of elements, the processing system being represented as a directed graph having a plurality of nodes and directed edges, each node representing an element, each node having an attribute, and each directed edge representing a relation between two elements of the plurality of elements, the method including: selecting one node of the plurality of nodes as a starting node; constructing a subgraph, the subgraph including all the nodes that are forward-connected by at least one directed edge from the starting node; and outputting all nodes and the attribute of the nodes of the subgraph.