Structural Health Monitoring Data Grouping for Visual Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current Structural Health Monitoring (SHM) systems face challenges in efficiently collecting, analyzing, and visualizing data to detect structural weaknesses in vehicles, leading to potential delays in maintenance and safety issues, as they often require manual analysis of large amounts of data without effective organizational structures.
Innovation Solution
A method and system that utilize SHM sensors to collect data from various zones of a vehicle, transmit it to a computer system with a display and user interface, automatically group the data into structural regions and areas, and provide a visual representation of structural health, allowing for early detection of damage and streamlined maintenance planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If manual analysis of large amounts of SHM data is performed, then data collection completeness is improved, but analysis time and productivity deteriorate
Solution Approach 1:
The patent replaces manual mechanical analysis with automated computer-based processing. The system automatically processes SHM data, generates visual representations, and identifies structural issues without human intervention in the analysis phase, thereby maintaining complete data collection while dramatically improving analysis efficiency
Solution Approach 2:
The system performs self-service by automatically analyzing SHM data, generating visual representations of structural health, and identifying potential issues without requiring manual analysis. The computer system serves itself by processing the data it collects and presenting results in an actionable format
2Measurement precision
If manual analysis of SHM data is performed, then data accuracy is maintained, but time consumption and operational complexity increase
Solution Approach 1:
The system performs preliminary automated analysis of SHM data continuously, preparing visual representations and damage assessments in advance before maintenance personnel need them. This allows accurate damage detection to be ready immediately when needed, eliminating delays associated with manual analysis while maintaining detection accuracy
Solution Approach 2:
The patent replaces time-consuming manual analysis with automated computer processing that maintains measurement precision. The system accurately detects structural damage through automated algorithms while reducing analysis time from hours or days to minutes or seconds
3Adaptability or versatility
If SHM data is collected from multiple zones and structures, then monitoring coverage is improved, but data organization complexity and device complexity increase
Solution Approach 1:
The patent applies segmentation by dividing the vehicle structure into multiple zones and monitoring them independently with dedicated sensors. Each zone's data is processed separately and then integrated into a comprehensive visual representation, making the complex data set manageable while maintaining wide monitoring coverage
Solution Approach 2:
The system uses a universal computer-based processing platform that handles data from all zones and structures through a single integrated system. The same hardware and software infrastructure processes data from multiple sources, reducing overall device complexity compared to having separate systems for each zone
4Productivity
If automated grouping of zones into structural regions is implemented, then analysis efficiency is improved, but system complexity increases
Solution Approach 1:
The system automatically segments zones into structural regions based on their spatial and functional relationships. This automated segmentation improves processing efficiency by organizing data into meaningful groups while the computer system handles the complexity of determining region boundaries and relationships
Solution Approach 2:
The patent replaces manual data organization with automated computer-based grouping algorithms. The system automatically processes zone data, determines structural region memberships, and organizes information efficiently without human intervention, improving productivity while the computer system manages the inherent complexity
Data Source
AI summary
A system and method includes a structural body, a plurality of structural health monitoring (SHM) sensors, and first and second computer systems. The structural body includes a plurality of structures. The SHM sensors are configured to sense structural health data for a plurality of zones of the structures. The first computer system is configured to collect the structural health data from the SHM sensors. The second computer system includes a display and is configured to receive the structural health data from the first computer system and groups the zones into a plurality of structural regions, and groups the plurality of structural regions into at least one structural area. The display is configured to provide a visual representation of a structural region health of a first one of the plurality of structural regions based on the structural data for respective ones of the zones within the first one of the plurality of structural regions.