Plant Data Display Mapping for State Transition Guidance
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Solution Overview
Problem
Existing methods struggle to effectively visualize relationships among multiple operation and condition parameters in plant data, and fail to provide clear guidance on transitioning plant states to improve evaluation indices.
Innovation Solution
A plant data display processing device that classifies multidimensional operation data into categories using techniques like Adaptive Resonance Theory, calculates evaluation indexes, and maps category identification information to two- or three-dimensional spaces to display relationships between categories and evaluation indices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a data clustering technique is used to classify multidimensional operation data into categories, then the plant state can be managed by category numbers, but it becomes difficult to determine how to change the plant state when state change is needed
Solution Approach 1:
The patent maps category identification information to two-dimensional space based on similarity of representative values, creating a spatial arrangement that preserves relationships between categories. This dimensional transformation allows operators to visually understand state transitions by observing proximity and spatial relationships, rather than dealing with abstract category numbers alone.
Solution Approach 2:
The patent introduces representative values as intermediaries between raw operation data and category classifications. These representative values serve as mediators that capture the essential characteristics of each category, enabling both accurate classification and meaningful visualization of state relationships.
2Quantity of substance
If the number of equipment or machines in the plant increases, then more measurement data becomes available for analysis, but the number of measurement points increases making data visualization more difficult
Solution Approach 1:
The patent extracts the essential characteristics of multidimensional operation data by calculating representative values for each category. This extraction process separates the core information from the vast amount of raw measurement data, reducing complexity while preserving the meaningful relationships between different plant states.
Solution Approach 2:
The patent transforms high-dimensional measurement data into lower-dimensional representations by mapping category identification information to two-dimensional space based on similarity metrics. This parameter transformation reduces the complexity of data visualization while maintaining the essential relationships between categories.
Data Source
AI summary
Provided is a plant data display processing device including: a data classification unit that classifies operation data into categories according to similarity; an evaluation index calculation unit that calculates an evaluation index of a category from a value of the operation data; and a classification result display processing unit that calculates a representative value of the operation data for each of the categories from the operation data contained in each of the categories, maps identification information of each of the categories to two-dimensional space in accordance with similarity of a representative value of the operation data, and generates three-dimensional image data in which the identification information of each of the categories is shown on a plane formed of a first axis and a second axis, and the evaluation index of the category is shown on a third axis.