Rolling virtual wheel spindle calibration

• US 10,365,095 B2
• Filed: 04/24/2018
• Issued: 07/30/2019
• Est. Priority Date: 01/07/2015
• Status: Active Grant

• Current Assignee: Snap-On Incorporated
• Original Assignee: Snap-On Incorporated
• Inventors: D'Agostino, Robert J., Fuhrman, Michael G.
• Primary Examiner(s): Guadalupe-McCall, Yaritza
• Application Number:
  US15/961,068
• Publication Number:
  US 20180238682A1
• Time in Patent Office: 462 Days
• Field of Search: 33228
• CPC Class Codes: G01B 11/2755 using photoelectric detection means
• CPC Class Codes: G01B 2210/14 One or more cameras or other optical devices capable of acquiring a two-dimensional image
• CPC Class Codes: G01B 2210/16 Active or passive device attached to the chassis of a vehicle
• CPC Class Codes: G01B 2210/20 Vehicle in a state of translatory motion
• CPC Class Codes: G01B 2210/26 Algorithms, instructions, databases, computerized methods and graphical user interfaces employed by a user in conjunction with the wheel aligner
• CPC Class Codes: G01B 2210/30 Reference markings, reflector, scale or other passive device

Abstract

A vehicle wheel alignment system and method is provided for performing a rolling wheel axis of rotation and wheel spindle point calculation every time an alignment is performed. Embodiments include an aligner having a target fixedly attachable to a wheel of the vehicle; a camera for viewing the target and capturing image data of the target; and a data processor. The data processor receives the image data from the camera, and determines a vector pointing from the target origin to a wheel spindle point based on the captured target image data, when the vehicle is rolled while the wheel is on a substantially flat surface such that the wheel and target rotate a number of degrees. The data processor is further adapted to calculate an alignment parameter for the vehicle based at least in part on the wheel axis of rotation and the coordinates of the wheel spindle point.

Claims

1. A method for detecting an occurrence of a movement deviation during a rolling movement of a wheel assembly across a supporting surface associated with a rolling compensation procedure of a vehicle service system, the method comprising:

rolling the wheel assembly across the supporting surface to generate the rolling movement;

acquiring data associated with the wheel assembly at a plurality of positions across said supporting surface during the rolling movement;

processing said acquired data to obtain a set of values representative of a parameter associated with the wheel assembly in each of said plurality of positions across said supporting surface;

evaluating said set of parameter values to identify each value in said set of parameter values which deviated, during said rolling movement, from an expected value by more than an acceptable tolerance in response to a movement deviation by the wheel assembly; and

selecting, within a vehicle service procedure, an action in response to said evaluation identifying at least one deviated value.

2. The method of claim 1 wherein said parameter is invariant during an ideal rolling movement, and wherein said acceptable tolerance is representative of an acceptable variation between sequential values representative of said parameter associated with the wheel assembly.

3. The method of claim 2, wherein said step of acquiring data includes securing an optical target to said wheel assembly;

acquiring, with a machine vision sensor, a sequence of images of said optical target at discrete rotational positions of the wheel assembly during said rolling movement across said supporting surface; and

processing said acquired sequence of images to identify a set of pose parameters for said optical target at each of said discrete rotational positions;

wherein the invariant parameter during an ideal rolling movement is a path traced out by said optical target, and a deviation of a value in said set of target pose parameters greater than the acceptable tolerance indicates the movement deviation by the wheel assembly.

4. The method of claim 3, wherein the path is a curtate cycloid path.

5. The method of claim 2, wherein said step of acquiring data includes securing an optical target to said wheel assembly;

acquiring, with a machine vision sensor, a sequence of images of said optical target at discrete rotational positions of the wheel assembly during said rolling movement across said supporting surface; and

processing said acquired sequence of images to identify a set of geometrical measurements for said optical target at each of said discrete rotational positions;

wherein the invariant parameter during an ideal rolling movement is a path traced out by said optical target, and a deviation of a value in said set of target geometrical measurements greater than the acceptable tolerance indicates the movement deviation by the wheel assembly.

6. The method of claim 1 wherein said movement deviation is a change in a vertical elevation of said wheel assembly during said rolling movement across said supporting surface.

7. The method of claim 1 wherein said movement deviation is a change in a steering angle parameter of said wheel assembly during said rolling movement across said supporting surface.

8. The method of claim 1 wherein said step of acquiring data includes securing an optical target to said wheel assembly;

acquiring, with a machine vision sensor, a sequence of images of said optical target at discrete rotational positions of the wheel assembly during said rolling movement across said supporting surface; and

processing said acquired sequence of images to identify a set of pose parameters for said optical target at each of said discrete rotational positions.

9. The method of claim 1, comprising securing an optical target to the wheel assembly;

wherein said parameter associated with the wheel assembly in each of said plurality of positions is a virtual wheel spindle point; and

wherein said movement deviation is a spatial change in said virtual wheel spindle point during said rolling movement across said supporting surface.

10. The method of claim 1 wherein said action includes generating a warning to an operator.

11. The method of claim 1 wherein said action includes determining a correction factor to offset at least a portion of a measurement effect introduced by said movement deviation.

12. The method of claim 11 wherein said measurement effect is a change in a compensation value established by said rolling compensation procedure.

13. The method of claim 1, wherein the rolling compensation procedure includes at least one of a rolling wheel spindle calibration procedure and a rolling runout compensation procedure.

14. The method of claim 1, wherein said step of selecting an action in response to identification of at least one deviated parameter value comprises:

removing one of the deviated parameter values from said set of parameter values;

repeating the evaluating step; and

iterating the removing and evaluating steps until an aggregate error falls below a threshold and there are sufficient remaining data points.

15. The method of claim 1, wherein said evaluating step includes comparing said set of acquired parameter values to calculated reference values to detect errors;

and

wherein said step of selecting an action in response to identification of at least one deviated parameter value comprises compensating for the detected errors by varying one or more predetermined parameter values using a mathematical fitting process to improve agreement between the predetermined parameter values and the calculated reference values.

16. The method of claim 15, wherein the mathematical fitting process comprises an iterative nonlinear least squares analysis.

17. The method of claim 1 wherein said step of acquiring data includes securing an optical target to said wheel assembly;

acquiring, with a machine vision sensor, a sequence of images of said optical target at discrete rotational positions of the wheel assembly during said rolling movement across said supporting surface; and

processing said acquired sequence of images to identify a set of geometrical measurements for said optical target at each of said discrete rotational positions.

18. A method for detecting variations in a surface supporting a rolling wheel assembly, comprising:

rolling the wheel assembly across the surface to generate a rolling movement;

acquiring spatial data associated with the rolling wheel assembly at a plurality of positions during the rolling movement;

evaluating said spatial data to detect a change in a position or an orientation of the rolling wheel assembly exceeding an acceptable tolerance; and

associating said detected change in said position or orientation with said surface supporting said rolling wheel assembly.

19. The method of claim 18 wherein said step of associating includes conveying a warning of a detected surface variation to an operator.

20. The method of claim 18 wherein said evaluation of said spatial data determines at least one point on an axis of rotation for the rolling wheel assembly at each of said positions of the wheel assembly.

21. The method of claim 20 wherein said at least one point on said axis of rotation is a virtual wheel spindle point of intersection between said axis of rotation and a plane defined by an optical target secured to said rolling wheel assembly.

22. The method of claim 18 wherein said step of associating includes generating, for use in at least one wheel alignment measurement procedure, a calibration correction factor based on said detected changes in said position or orientation of said rolling wheel assembly which exceed said acceptable tolerance for subsequent use when said wheel assembly is disposed at a location on said supporting surface associated with said detected changes in said position or orientation.

23. The method of claim 18 wherein said change in position or orientation of the rolling wheel assembly exceeding said acceptable tolerance is a positional change for the rolling wheel assembly in a vertical direction.

24. A vehicle service system, comprising:

at least one sensor configured to acquire data associated with a wheel assembly on a vehicle at a plurality of rotational positions during a rolling movement across a supporting surface;

a processing system configured to receive said acquired data from said at least one sensor, said processing system further configured with a set of software instructions to process said acquired data to obtain a sequence of values representative of at least one parameter associated with the wheel assembly in each of said plurality of rotational positions;

said processing system further configured with software instructions to evaluate said sequence of values to identify at least one value which deviates during said rolling movement, from an expected value by more than a tolerance; and

wherein said processing system is further configured with software instructions to respond to an identification of at least one deviating value.

25. The vehicle service system of claim 24 wherein said processing system is configured with software instructions to respond by generating a warning to an operator indicating the occurrence of said movement deviation by said wheel assembly during said rolling movement across said supporting surface.

26. The vehicle service system of claim 24 wherein said processing system is configured with software instructions to respond by establishing a correction factor to offset at least a portion of a measurement effect introduced by said movement deviation of said wheel assembly.

27. The vehicle service system of claim 24, wherein said at least one parameter is invariant during an ideal rolling movement, and wherein said tolerance is representative of an acceptable variation between said sequential values representative of said at least one parameter;

wherein the vehicle service system further includes an optical target attachable to said wheel assembly;

wherein said at least one sensor is a machine vision sensor for acquiring a sequence of images of said optical target at discrete rotational positions of the wheel assembly during said rolling movement as said acquired data;

wherein the processing system is configured with software instructions for processing the acquired sequence of images to identify a set of pose parameters for said optical target at each of said rotational positions; and

wherein the invariant parameter during an ideal rolling movement is a path traced out by said optical target, and a deviation of a value in said set of target pose parameters greater than said tolerance indicates said deviating value.

28. The vehicle service system of claim 24, wherein said software instructions to respond to the identification of the at least one deviating value are for performing the steps of:

removing one of said deviated values from said sequence of values;

repeating the evaluation of said sequence of values; and

iterating the removing and evaluation steps until an aggregate error falls below a threshold and there are sufficient remaining data points.

29. The vehicle service system of claim 24, wherein said software instructions to evaluate said sequence of values are for comparing said sequence of values to calculated reference values to detect errors;

and

wherein said software instructions to respond to the identification of the at least one deviating value are for compensating for the detected errors by varying one or more predetermined parameter values using a mathematical fitting process to improve agreement between the predetermined parameter values and the calculated reference values.

30. The vehicle service system of claim 29, wherein the mathematical fitting process comprises an iterative nonlinear least squares analysis.

31. The vehicle service system of claim 24, wherein said at least one parameter is invariant during an ideal rolling movement, and wherein said tolerance is representative of an acceptable variation between said sequential values representative of said at least one parameter;

wherein the vehicle service system further includes an optical target attachable to said wheel assembly;

wherein said at least one sensor is a machine vision sensor for acquiring a sequence of images of said optical target at discrete rotational positions of the wheel assembly during said rolling movement as said acquired data;

wherein the processing system is configured with software instructions for processing the acquired sequence of images to identify a set of geometrical measurements for said optical target at each of said rotational positions; and

wherein the invariant parameter during an ideal rolling movement is a path traced out by said optical target, and a deviation of a value in said set of target geometrical measurements greater than said tolerance indicates said deviating value.