Aircraft Fuselage Profile Analysis via Medial Axis Skeleton
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Solution Overview
Problem
The challenge lies in accurately controlling the dimensional accuracy of aircraft fuselage structures, which are prone to complex and dynamic deformation due to external loads, and existing methods struggle with efficient data processing of large-sized point-cloud data for deformation detection, particularly in generating smooth curve surfaces that meet requirements.
Innovation Solution
A method utilizing a medial-axis curve skeleton-driven approach, involving weighted locally optimal projection (WLOP) operators and L1 median curve-skeleton concepts, to extract and analyze the deformation of aircraft components, reducing calculation costs by fitting local cross-section contours instead of overall curved surfaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If global fitting of all point-cloud data is performed to extract cross-section, then comprehensive deformation analysis is achieved, but a large amount of time is required for calculation which significantly lowers data processing efficiency
Solution Approach 1:
The patent segments the point-cloud data by establishing a medial axis and projecting points onto it, dividing the global fitting problem into multiple local cross-sectional fitting problems. This segmentation reduces computational complexity while maintaining comprehensive deformation analysis capability across the entire fuselage structure.
Solution Approach 2:
The patent extracts only the necessary cross-sectional information by projecting point-cloud data onto the medial axis and selecting points at specific distances from the axis. This extraction approach obtains sufficient deformation data without processing the entire point-cloud dataset, thereby improving processing efficiency.
2Reliability
If curve surface fitting is performed on initial point cloud data to generate a single curve surface, then deformation detection is achieved, but it is troublesome to generate a surface satisfying requirements and the fitted surface fails to meet smoothness and control point number requirements
Solution Approach 1:
Instead of generating a single complex curve surface, the patent segments the problem into multiple local cross-sectional curves along the medial axis. Each cross-section is fitted independently, simplifying the overall process while ensuring smoothness and control point requirements are met at each local level.
Solution Approach 2:
The patent extracts only the essential cross-sectional contour information from the point-cloud data by projecting points onto the medial axis and selecting points at predetermined distances. This extraction eliminates the need for complex global surface fitting while retaining sufficient information for reliable deformation detection.
3Measurement precision
If large-sized and massive aircraft point-cloud data is acquired for comprehensive deformation analysis, then accurate deformation detection is achieved, but the large amount of data requires extensive calculation time
Solution Approach 1:
The patent extracts only the necessary data points by projecting the massive point-cloud onto the medial axis and selecting points at specific distances from the axis. This extraction reduces the data volume significantly while preserving the essential deformation information needed for accurate detection.
Solution Approach 2:
The patent segments the large dataset into manageable cross-sectional slices along the medial axis. Each slice is processed independently through local fitting, reducing the overall computational burden while maintaining comprehensive deformation analysis coverage across the entire structure.
Data Source
AI summary
A method for analyzing fuselage profile based on measurement data of an aircraft, including: acquiring point-cloud data of an aircraft via a laser scanner; selecting point-cloud data of a fuselage component from the point-cloud data of the aircraft; based on a weighted locally optimal projection (WLOP) operator and Ll median curve-skeleton concept of point cloud, extracting a medial axis from the point-cloud data of the fuselage component; uniformly sampling the medial axis into a plurality of skeleton points; extracting a discrete point set of a cross-section contour of the fuselage component; performing circle fitting on the discrete point set to obtain a fitted circle and parameters thereof; calculating a deformation displacement measurement indicator μ of the cross-section of the fuselage component to evaluate cross-section contour of the fuselage.