Communications: electrical – Condition responsive indicating system – Specific condition
Reexamination Certificate
1999-12-21
2001-11-27
Tong, Nina (Department: 2632)
Communications: electrical
Condition responsive indicating system
Specific condition
C356S155000, C382S152000, C382S172000, C382S176000
Reexamination Certificate
active
06323776
ABSTRACT:
FIELD OF THE INVENTION
The present invention generally relates to machine vision measuring systems, for example, three-dimensional computerized wheel alignment systems. The invention relates more specifically to a method and apparatus of automatically identifying faults in the operation of a machine vision measuring system caused by electronic noise, environmental contamination, or other problems.
BACKGROUND OF THE INVENTION
Machine vision measuring systems that have cameras are used in many applications. For example, wheels of motor vehicles may be aligned on an alignment rack using a computer-aided, three-dimensional (3D) machine vision alignment apparatus and a related alignment method. Targets are attached to the wheels of the vehicle to be aligned. Cameras of the alignment apparatus view the targets and form images of the targets. A computer in the apparatus analyzes the images of the targets to determine wheel position, and guides an operator in properly adjusting the wheels to accomplish precise alignment.
Examples of methods and apparatus useful in 3D alignment of motor vehicles are described in U.S. Pat. No. 5,943,783, Method and apparatus for determining the alignment of motor vehicle wheels, U.S. Pat. No. 5,809,658, Method and apparatus for calibrating cameras used in the alignment of motor vehicle wheels, U.S. Pat. No. 5,724,743, Method and apparatus for determining the alignment of motor vehicle wheels, and U.S. Pat. No. 5,535,522, Method and apparatus for determining the alignment of motor vehicle wheels. The apparatus described in these references is sometimes called a “3D aligner” or “aligner.”
An example of a commercial embodiment of an aligner is the Visualiner 3D, commercially available from John Bean Company, Conway, Ark., a unit of Snap-on Tools Company.
To determine the alignment of the motor vehicle wheels, such 3D aligners use cameras that view targets affixed to the wheels. Each target comprises numerous marks that are used for the purpose of determining target position (“fiducials”). Proper operation of the aligner requires the aligner to create an image and recognize most of the fiducials on a target at any given time.
However, such aligners are normally installed in an automotive shop or other environment that is an inherently dirty environment. Normal handling of the targets by technicians can result in the targets becoming dirty. Grease, dirt or other contaminants may be deposited on the targets, obscuring one or more fiducials of the targets. Further, with some kinds of aligners that have “floating” booms and cameras, movement of the booms or cameras can cause placement of the cameras in a position at which the cameras can see only part of a target and therefore form only an incomplete image of a target.
In one current approach, if the aligner cannot recognize enough fiducials of a target, as a result of dirt, other contamination or obscuration of fiducials, or obstruction of the target, it cannot determine the location of that target, and stops operating. Although this approach ensures that the aligner operates based on an accurate view of the targets, a drawback is that the operator is not always certain why the aligner stops operating. In particular, the operator may have insufficient information film the aligner to determine why operation has stopped. The aligner simply ceases operating and the operator may therefore assume that the aligner is malfunctioning when, in fact, a dirty target is the source of the fault. When the fault involves obstruction of the target or mis-alignment of a floating boom or cameras, the operator may visually inspect the targets and yet may be unable to determine why the aligner will not operate, or may incorrectly assume that the aligner hardware or software is faulty.
Based on the foregoing, there is a clear need in this field for an apparatus and method that provides for automatic identification of faults in a machine vision measuring system.
There is a particular need for an aligner that can identify faults such as electronic noise, environmental contamination of targets, etc., and report information about the fault to an operator so that remedial action can be taken. There is also a need for an aligner that can suggest remedial action to be taken by an operator in response to detecting a fault.
SUMMARY OF THE INVENTION
The foregoing needs and objects, and other needs that will become apparent from the following description, are fulfilled by the present invention, which comprises, in one aspect, an apparatus and method for automatically identifying faults in the operation of a machine vision measuring systems. Embodiments provide an improved self-diagnostic capability for machine vision based metrology and tracking systems. The method and apparatus validate performance of tracking operations, and detect deterioration that may be caused by electronic noise, environmental contamination, etc.
A mathematical model of the target visualized by the system is created and stored. A target is imaged in the field and fiducials of the target arc identified. Centroid positions of detected fiducials of the imaged target are compared to the centroid positions of fiducials in the mathematical model. When a fiducial is obscured or dirty, its geometric characteristics (such as centroid, brightness, edge smoothness, area, or shape) differ from the true or idealized values of the characteristics. Values representing detected fiducials are discarded when the offset exceeds predetermined criteria, or when its properties vary from ideal. If the remaining number of detected fiducials is below a pre-determined threshold, a warning message is displayed or an error is generated. Thus, when a fault is detected that degrades performance beyond a preset tolerance, the fault is flagged for attention and a suggested corrective action is displayed.
In one embodiment, a method of detecting a fault of a machine vision measuring system that includes a target having a plurality of fiducials and stored image of the target and the fiducials is provided. The method involves the steps of creating and storing a list of values representing detected fiducials of the target based on the image; comparing the detected fiducials to a plurality of values representing true fiducials of the target in a stored model of the target; selectively removing one or more of the detected fiducials from the list that fail to satisfy pre-determined criteria; and generating a warning message using the machine vision measuring system when fewer than a first pre-determined number of detected fiducials remain in the list. Specific features of this aspect, and other aspects and their features, will become apparent from the following description and claims.
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Christian Donald J.
Glickman Stephen
Jackson David A.
Shroff Hoshang
McDermott & Will & Emery
Snap-on Technologies, Inc.
Tong Nina
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