Scan Coordinate Mapping for Precise Large-Object Data Correlation
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Solution Overview
Problem
Existing methods struggle to accurately map and correlate operation data points from an operation coordinate system to a global coordinate system for large objects, such as aircraft, making it difficult to locate specific positions and correlate data with downstream manufacturing or in-service performance.
Innovation Solution
The method involves obtaining a local operation dataset with a plurality of operation data points and their corresponding locations within an operation coordinate system, and then mapping these data points to a global coordinate system using a computing device, thereby generating a global operation dataset with corresponding global locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If operation data is collected within a local operation coordinate system, then data collection is simplified and operations can be performed efficiently, but the ability to locate specific positions on the object and correlate data with downstream operations is lost
Solution Approach 1:
The system performs preliminary actions by establishing a transformation relationship between the operation coordinate system and the object coordinate system before data collection. This allows the robot to collect data in the convenient operation coordinate system while pre-computing the mapping to object coordinates, thus preserving spatial correlation information without complicating the data collection process.
Solution Approach 2:
The patent introduces a coordinate transformation mechanism as an intermediary between the operation coordinate system and the object coordinate system. This intermediary computes the mapping relationship, allowing data to be collected in the local operation system while the transformation mediator converts these coordinates to global object coordinates, thus preserving spatial correlation without affecting ease of data collection.
2Productivity
If a robot performs raster scanning within a two-dimensional grid, then nondestructive testing data can be collected systematically, but it becomes difficult to locate specific positions after the scan is complete
Solution Approach 1:
The patent adds a third dimension to the coordinate system by introducing the Z-axis (vertical dimension) to the existing two-dimensional operation grid. This creates a three-dimensional operation coordinate system that can map to the three-dimensional object coordinate system, enabling precise location of specific positions after scanning while maintaining the systematic raster scanning approach for efficient data collection.
Solution Approach 2:
A coordinate transformation mechanism serves as an intermediary that converts coordinates from the two-dimensional operation grid to the three-dimensional object coordinate system. This intermediary preserves the efficiency of raster scanning in 2D while enabling precise position location in 3D by computing the mapping relationship between the two coordinate systems.
3Ease of manufacture
If operations are performed without reference to specific locations on the object, then manufacturing operations can be completed, but correlation with downstream manufacturing operations and in-service performance becomes difficult
Solution Approach 1:
The system performs preliminary coordinate transformation setup before manufacturing operations. By pre-establishing the transformation relationship between operation coordinates and object coordinates, the system allows operations to be performed easily in the operation coordinate system while pre-computing the mapping to preserve location correlation information for downstream manufacturing and in-service performance analysis.
Solution Approach 2:
The coordinate transformation mechanism acts as an intermediary that bridges the operation coordinate system and the object coordinate system. This intermediary preserves location correlation information by computing and storing the mapping relationship, allowing operations to be performed without direct reference to specific object locations while maintaining the ability to correlate data with downstream manufacturing and in-service performance.
Data Source
AI summary
Methods and scan systems for analyzing an object. The methods include obtaining a local operation dataset that includes a plurality of operation data points obtained from an object and a corresponding location, within the operation coordinate system, for each operation data point of the plurality of operation data points. The methods also include mapping the plurality of operation data points from the operation coordinate system to a global coordinate system for the object. The mapping includes mapping to generate a global operation dataset that includes the plurality of operation data points and a corresponding global location, within the global coordinate system, for each operation data point. The scan systems include a robot that performs a plurality of operations on an object within an operation coordinate system and a computing device that maps the plurality of operation data points from the operation coordinate system to a global coordinate system.