3D Structured Light Vehicle Gap Measurement Without Laser Alignment
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Solution Overview
Problem
Existing manual measurement methods for vehicle body gaps and surface differences are inaccurate and labor-intensive, and existing 3D structured light systems require precise laser alignment, leading to inefficiencies and measurement errors.
Innovation Solution
A 3D structured light camera system that computes the mean distance vector between contours on either side of the gap, allowing for automatic gap measurement without requiring laser perpendicularity, and includes a microprocessor-based system for data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual measurement mode is used, then device complexity is low, but measurement precision and productivity are poor
Solution Approach 1:
The patent replaces manual mechanical measurement tools (gap gauges, surface difference meters) with an automated 3D structured light vision system. The system uses structured light projection, camera imaging, and computational algorithms to automatically measure gap and surface difference, eliminating manual operations and significantly improving measurement speed and consistency.
Solution Approach 2:
The patent creates a digital 3D model (point cloud) of the vehicle body surface by projecting structured light and capturing images with a camera. This digital copy allows for automated extraction of gap and surface difference features without physical contact or manual measurement, enabling high-speed automated measurement.
2Extent of automation
If multi-view vision based measurement system is used, then automation degree is improved, but measurement precision deteriorates due to low precision and large measurement deviation
Solution Approach 1:
The patent changes the measurement approach from 2D multi-view images to 3D structured light scanning. By using 3D line structured light to capture spatial information directly, the system achieves micron-level precision while maintaining automation, overcoming the precision limitations of traditional 2D vision-based methods.
Solution Approach 2:
The patent transitions from 2D image-based measurement to 3D point cloud-based measurement. By adding the third dimension (depth/spatial information) through structured light scanning, the system achieves more accurate gap and surface difference measurement while maintaining automated operation.
3Measurement precision
If 3D line structured light based visual system is used, then measurement precision is improved to micron level, but adaptability deteriorates due to high positioning requirement and difficulty to be compatible with workpiece positioning deviation
Solution Approach 1:
The patent incorporates feedback mechanisms through automated feature recognition and calculation. The system automatically identifies gap features and surface difference features on the 3D point cloud, computes measurements, and provides results without requiring manual intervention or precise pre-positioning, thereby improving adaptability while maintaining precision.
Solution Approach 2:
The system performs self-alignment and automatic feature extraction on the 3D scanned data. By automatically identifying and calculating gap and surface difference features from the point cloud, the system eliminates the need for manual positioning adjustment and adapts to various workpiece positions and orientations.
4Manufacturing precision
If contour scanning method is used, then computation accuracy is improved, but device complexity increases due to high positioning requirement
Solution Approach 1:
The patent replaces complex mechanical positioning systems with a 3D structured light scanning system that captures spatial information automatically. The 3D point cloud data enables automated feature extraction and gap calculation without requiring precise mechanical positioning, reducing device complexity while maintaining computation accuracy.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Improves measurement accuracy and reduces mounting time by automatically computing gap and surface differences with high precision, adapting to various vehicle body configurations.
Implementation Method 1
a 3D structured light camera based method for measuring a gap of a vehicle body
Implementation Method 2
obtaining point cloud data obtained by a 3D structured light camera scanning the gap of the measured vehicle body
Data Source
AI summary
A three-dimensional (3D) structured light camera based method and system for measuring a gap of a vehicle body is provided. The method includes: obtaining point cloud data obtained by a 3D structured light camera scanning the gap of the measured vehicle body; with a group of point cloud data of the gap of the measured vehicle body in a transverse direction as a contour, extracting contour gap points of each contour, so as to obtain a left side contour gap point set N0 and a right side contour gap point set N1; computing a mean distance vector {right arrow over (τ)} between contours on two sides of the gap of the measured vehicle body according to the left side contour gap point set N0 and the right side contour gap point set N1; and computing the gap d of the measured vehicle body according to the mean distance vector {right arrow over (τ)}.