Vehicle Wheel Geometry Measurement Using Structured Light
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Solution Overview
Problem
Conventional wheel alignment methods require laborious installation of attachments on vehicles, restrict measurement to local wheel rotation, and offer low precision for rim run-out determination when the vehicle is in motion.
Innovation Solution
A method using structured and unstructured light to create a three-dimensional surface, texture, and motion model of a wheel area during rotation, allowing for the determination of axle geometry and axis of rotation while the vehicle is moving, and precise measurement of toe, camber, and translational vectors when stationary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If vehicle-mounted features or attachments are used for measurement, then measurement precision can be improved, but installation becomes laborious and time-consuming
Solution Approach 1:
The invention extracts the measurement features from the vehicle body and places them directly on the wheel components (tire, rim, hub). By using the wheel's own rotational movement as the measurement basis, the system eliminates the need for separate vehicle-mounted attachments while maintaining measurement precision through direct observation of wheel geometry changes during rotation.
Solution Approach 2:
The measurement system achieves multiple functions using a single approach: it measures wheel alignment, runout, and geometric parameters simultaneously by tracking features on the rotating wheel itself, eliminating the need for separate measurement devices attached to the vehicle body.
2Measurement precision
If the wheel rotates locally in rollers for measurement, then structured light evaluation becomes possible, but the measurement is restricted to local rotation only
Solution Approach 1:
The invention transitions from static local rotation measurement to dynamic full-rotation measurement. By tracking wheel features throughout the entire rotation cycle and using temporal analysis of the captured images, the system can evaluate wheel geometry under various dynamic conditions including different rotation speeds and positions, greatly enhancing measurement flexibility.
Solution Approach 2:
The system adds the temporal dimension to the measurement process by capturing images at multiple time points during wheel rotation. This allows the evaluation of not only spatial geometry but also temporal changes in wheel position and orientation, enabling comprehensive analysis of wheel dynamics beyond static measurements.
3Adaptability or versatility
If the vehicle moves for measurement, then comprehensive wheel geometry can be captured, but precision for rim run-out determination decreases
Solution Approach 1:
The system performs preliminary calibration by capturing images during a reference rotation to establish the relationship between camera coordinates and wheel coordinates. This preliminary action creates a transformation model that can then be applied to subsequent measurements, allowing precise runout determination even when the vehicle is in motion by compensating for vehicle movement effects.
Solution Approach 2:
The measurement system uses feedback from the captured image sequence to iteratively refine the wheel geometry parameters. By analyzing the temporal variation of wheel feature positions and comparing them against the expected rotational pattern, the system can distinguish between actual wheel runout and apparent displacement caused by vehicle motion, maintaining precision during dynamic measurement.
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
Enables robust and comprehensive three-dimensional modeling of wheels and vehicle parts, providing accurate axle geometry measurements without the need for vehicle-mounted features or local wheel rotation, enhancing precision and efficiency.
Implementation Method 1
a wheel area is illuminated with structured and with unstructured light during a wheel rotation of at least one wheel
Implementation Method 2
Multiple images of the wheel area are generated during illumination to create a three-dimensional surface model with surface parameters
Data Source
Figure 1
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Figure 3A~3D
AI summary
The invention relates to a method for determining the wheel or axle geometry of a vehicle (2), comprising the following steps: illumination of a wheel region with structured and unstructured light during the movement (B) of at least one wheel (3) and/or the vehicle (2); capturing of several images of the wheel region during illumination to generate a three-dimensional surface model comprising surface parameters, a texture model with texture parameters and a movement model with movement parameters of the captured wheel region; calculation of values for the surface parameters, texture parameters and the movement parameters by a variation calculation in conjunction with the captured images for minimising a deviation of the three-dimensional surface, texture and movement model from the image data of the captured images; and determination of a rotational axis and/or a rotational centre of the wheel (3) depending on the calculated values of the movement parameters.