Wheel aligner with advanced diagnostics and no-stop positioning

Patent metadata

Field	Value
Publication number	US-10072926-B2
Application number	US-201615287528-A
Country	US
Kind code	B2
Filing date	Oct 6, 2016
Priority date	Oct 6, 2015
Publication date	Sep 11, 2018
Grant date	Sep 11, 2018

Abstract

A vehicle wheel alignment system has a plurality of cameras, each camera for viewing a respective target disposed at a respective wheel of the vehicle and capturing image data of the target as the wheel and target are continuously rotated a number of degrees of rotation without a pause. The image data is used to calculate a minimum number of poses of the target of at least one pose for every five degrees of rotation as the wheel and target are continuously rotated the number of degrees of rotation without a pause. At least one of the cameras comprises a data processor for performing the steps of preprocessing the image data, and calculating an alignment parameter for the vehicle based on the preprocessed image data.

First claim

What is claimed is:

1. A vehicle wheel alignment system comprising:
a plurality of cameras, each camera for viewing a respective target disposed at a respective wheel of the vehicle and capturing image data of the target as the wheel and target are continuously rotated a number of degrees of rotation without a pause,
wherein the image data is used to calculate a minimum number of poses of the target; wherein the minimum number of poses of the target comprises at least one pose for every five degrees of rotation captured by each camera as the wheel and target are continuously rotated the number of degrees of rotation without a pause; and
wherein at least one of the cameras comprises a data processor for performing the steps of: preprocessing the image data; and calculating an alignment parameter for the vehicle based on the preprocessed image data.

2. The system of claim 1 , wherein the data processor of one of the cameras is for serving a user interface.

3. The system of claim 1 , wherein the data processor is for calculating a change in an alignment parameter for each vehicle wheel based on the preprocessed image data, and for analyzing the change in the alignment parameter to detect an error.

4. The system of claim 3 , where the detected error includes at least one of (a) vehicle wheel axis precession; (b) surface flatness errors of a surface of an alignment rack on which the vehicle wheels and targets rotate; (c) plate slipping errors of a plate which comprises part of the surface of the alignment rack; and (d) stress in a suspension of the vehicle beyond predetermined rest conditions.

5. The system of claim 4 , wherein the data processor is for attempting to correct or compensate for detected problems (a)-(d).

6. The system of claim 5 , wherein the data processor is for alerting a user of the system if the processor cannot correct the detected problems.

7. The system of claim 1 , wherein the data processor is for:
detecting, at least in part based on the image data, at least one of (e) instability of one or more of the cameras; and (f) excessive vehicle thrust angle changes.

8. The system of claim 7 , wherein the data processor is for attempting to correct or compensate for detected problems (e)-(f).

9. The system of claim 8 , wherein the data processor is for alerting a user of the system if the processor cannot correct the detected problems.

10. The system of claim 1 , wherein calculating the poses comprises (g) acquiring, as a first wheel is rotating, a first pose of the target at the first wheel, (h) storing the first pose when the first pose is different from previously stored target poses of the first wheel to a predetermined degree, (i) repeating steps (g) and (h) when the first wheel has been rotated less than the minimum number of degrees of rotation; and (j) performing steps (g) through (i) for all the wheels of the vehicle having a target.

11. The system of claim 5 , wherein detecting surface flatness errors of the surface of the alignment rack comprises calculating the center point of at least one of the vehicle wheels for each of the captured target poses of that wheel, computing a best fit line through all the computed wheel center points, and determining whether a deviation from the best fit line is below a predetermined error threshold.

12. The system of claim 11 , wherein when the deviation from the best fit line is above the error threshold, the step of attempting to correct or compensate for the surface flatness error comprises (k) removing the wheel center point with the largest deviation from the best fit line, (l) recomputing the deviation, (m) determining whether the deviation is below the error threshold, (n) repeating steps (k) through (m) until the deviation from the best fit line is below the error threshold or until less than a predetermined minimum number of data points remain.

13. The system of claim 12 , wherein the data processor is for alerting the user the processor cannot correct the surface flatness error if less than the minimum number of data points remain.

14. The system of claim 5 , wherein detecting plate slipping errors comprises detecting translation of the center of one of the vehicle wheels without a predetermined amount of angular rotation of that wheel.

15. The system of claim 14 , wherein detecting plate slipping errors comprises calculating the center point of the one of the vehicle wheels for each of the captured target poses of that wheel, determining an elapsed linear travel distance of the center point and a corresponding elapsed angle of wheel rotation, computing a best fit line of elapsed linear travel distance versus elapsed angle of wheel rotation, and determining whether a deviation from the best fit line is below a predetermined error threshold.

16. The system of claim 15 , wherein when the deviation from the best fit line is above the error threshold, the step of attempting to correct or compensate for the plate slipping error comprises (o) removing the wheel center point with the largest deviation from the best fit line, (p) recomputing the deviation, (q) determining whether the deviation is below the error threshold, (r) repeating steps (o) through (q) until the deviation from the best fit line is below the error threshold or until less than a predetermined minimum number of data points remain.

17. The system of claim 16 , wherein the data processor is for alerting the user the processor cannot correct the plate slipping error if less than the minimum number of data points remain.

18. The system of claim 5 , wherein detecting wheel axis precession comprises calculating the wheel axis of rotation vectors of one of the vehicle wheels for each of the captured target poses of that wheel, calculating an axis of precession based on the calculated wheel axes of rotation, calculating a wheel wobble angle between the axis of precession and each of the calculated wheel axes of rotation, calculating a standard deviation of the calculated wobble angles, and determining whether the standard deviation of the wobble angles is below a predetermined error threshold.

19. The system of claim 18 , wherein when the standard deviation of the wobble angles is below the error threshold, the step of attempting to correct or compensate for wheel axis precession comprises assigning the axis of precession to be the true wheel axis for a following alignment step.

20. The system of claim 19 , wherein when the standard deviation of the wobble angles is above the error threshold, alerting the user the processor cannot correct for wheel axis precession.

21. The system of claim 18 , wherein computing the axis of precession comprises computing a best fit plane through the tips of the calculated wheel axis vectors, and determining whether a deviation from the best fit plane is below a predetermined root mean square (RMS) error threshold;
wherein when the deviation from the best fit plane is above the RMS error threshold, the step of attempting to correct or compensate for wheel axis precession comprises (s) removing the wheel axis of rotation vector with the largest deviation from the best fit plane, (t) recomputing the best fit plane, (u) determining whether the deviation is below the RMS error threshold, (v) repeating steps (s) through (u) until the RMS deviation from the best fit plane is below the error threshold or until less than a predetermined minimum number of data points remain.

22. The system of claim 21 , wherein the processor is for alerting the u

Assignees

• Snap On Tools Corp
• Snap On Tools Corp

Inventors

• Rogers Steven W
• Jackson David A
• Lewis Bradley
• Brown Adam C
• D'Agostino Robert J
• Sellers Eric R

Classifications

• G01B11/275 Primary

  for testing wheel alignment · CPC title

• G01B11/2755 Primary

  using photoelectric detection means · CPC title

• H04N23/90

  Arrangement of cameras or camera modules, e.g. multiple cameras in TV studios or sports stadiums · CPC title

• G06V20/00

  Scenes; Scene-specific elements (control of digital cameras H04N23/60) · CPC title

• G01B2210/12

  Method or fixture for calibrating the wheel aligner · CPC title