Asset Intelligence Interface for Corrosion Prediction Visualization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Industrial facilities, such as oil and gas production plants, face challenges in monitoring and predicting the status of assets like pipes due to the large volume of data from sensors and the complexity of corrosion processes, making it difficult to identify potential failures and take corrective action before equipment fails.
Innovation Solution
An interface that provides improved visualization of data by allowing users to simultaneously view sensor data and predictive model data, enabling seamless toggling between plots and recalibration to occupy a predetermined region, facilitating quick assessment of asset status and corrosion profiles without needing to review detailed sensor data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If detailed sensor data is reviewed to assess asset status, then measurement precision is improved, but time consumption increases
Solution Approach 1:
The patent creates visual representations (plots and graphs) that copy and represent the essential information from detailed sensor data in a simplified format. These visualizations serve as copies that convey the same critical asset status information without requiring users to examine the raw detailed data, thus reducing time while maintaining assessment accuracy.
Solution Approach 2:
The patent introduces visual representations as an intermediary between the raw sensor data and the user's understanding. These visual plots act as mediators that translate complex sensor data into intuitive graphical formats, allowing users to quickly grasp asset status without directly analyzing the detailed underlying data.
2Loss of information
If multiple data plots are displayed simultaneously to provide comprehensive asset information, then information completeness is improved, but device complexity increases
Solution Approach 1:
The patent divides comprehensive asset information into multiple separate plots, each focusing on specific aspects such as corrosion profiles, temperature trends, or pressure data. This segmentation allows the interface to display detailed information without overwhelming the user with a single complex visualization, maintaining information completeness while managing interface complexity through organized separation.
Solution Approach 2:
The patent transforms complex multidimensional sensor data into visual representations that add spatial and temporal dimensions to the display. By plotting data across multiple dimensions (time, location, parameter type), the system presents comprehensive information in an organized visual format that is easier to comprehend than raw tabular data.
3Reliability
If predictive model data is integrated with sensor data to forecast future asset status, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent merges predictive model data with actual sensor data into a unified visualization interface. Both historical sensor measurements and future predictions are displayed together in coordinated plots, allowing users to see the connection between current asset state and projected future conditions. This integration improves reliability by combining empirical data with predictive analytics while presenting them through a single coherent interface.
Solution Approach 2:
The patent implements predictive modeling that performs preliminary analysis of future asset conditions before actual failures occur. By forecasting future status based on current trends and environmental factors, the system enables proactive maintenance planning. The predictive data is calculated and prepared in advance, allowing users to take preliminary actions to prevent failures before they happen.
Data Source
AI summary
A method can include receiving data characterizing a first property of an asset over a first time period. The method can also include receiving data characterizing user interaction with an interactive graphical object. The method can further include determining, by a predictive model, data characterizing the first property of the asset over a second time period. The determining can be based in part on the received data characterizing the user interaction. The method can also include rendering, in a graphical display space, one or more of a first plot of the received data characterizing the first property over the first time period and a second plot of the determined data characterizing the first property over the second time period.