Snap-on Inc.

Snap-on Technologies, Inc.

Fmc Corporation

George Michael Gill

Steven W Rogers

David A Jackson

Michael L Baird

Brian K Gray

Bryan C Minor

Alan David Casby

Jean De Bellefeuille

Robert J D'Agostino

Rodney Harrell

Patrick O'Mahony

Michael J Kling

David R Coburn, Ii

John C Brennan

Steve L Glickman

Jean De Belleuille

James L Dale, Jr

Ronald D Swayne

Eric R Sellers

Eric F Bryan

Robert O Moran

Michael J Robb

Darwin Y Chen

Michael J Kling, Iii

Manjula Gururaj

Richard J Poe

Joel A Kunert

Patrick Brendan O'Mahony

Ju Zheng

Gary L Sandusky

Mike Kling

Matthew T Foreman

Sean P Lecrone

Larry D Klotz

Jonathan A Sperry

Stephen L Glickman

Carl W Pruitt

Donald L Walchuk

James Rodney Harrell

Matthew Todd Foreman

Stephen K Rigsby

Brian McAuliffe

Joe Gibbs

Brian O'Sullivan

Jean deBelleuille

Patrick O'Mahoney

Steve W Rogers

Anthony Carroll

Patrick Brendan O'MAHONY

Michael J Iii Kling

Methods and systems measure a vehicle body parameter; e.g., a wheel alignment parameter such as ride height. Embodiments include a system having a target attachable to a vehicle body, and an image sensor for viewing the target and capturing image data thereof. A processor processes the image data, determines an initial spatial position of the target based on the processed image data, compares the initial spatial position of the target with a reference position, and prompts a user to align the target to an adjusted spatial position when the initial spatial position differs from the reference position more than a threshold amount. The vehicle body parameter value is determined based on the target's adjusted spatial position. In certain embodiments, the adjusted spatial position differs from the reference position by a position error value, and the processor mathematically corrects the vehicle body parameter value based on the position error value.

Live ride height measurement

A wheel alignment system includes a side-to-side reference including an active reference pod and a passive reference pod disposed on opposite sides of the vehicle. The active reference pod includes a reference image sensor fixedly attached to a reference target, for mounting on a first side of the vehicle such that the reference image sensor produces image data including a perspective representation of the passive reference pod disposed on a second/opposite side of the vehicle. In operation, alignment cameras on the opposite sides of the vehicle capture perspective representations of targets mounted to vehicle wheels and of targets of the active and passive reference pods. A computer processes the image data to compute an alignment measurement of the vehicle based on a spatial relationship between the active reference pod and the passive reference pod determined according to the image data produced by the reference image sensor.

Vehicle wheel alignment methods and systems

A method and system for conducting a vehicle service comprises the steps of receiving signals representative of vehicle parameters, accessing data and/or software necessary for performing the vehicle service from at least one remote computer over a data transmission network, and performing signal processing related to the vehicle service based on the signals representative of the vehicle parameters and the accessed data and/or software. Since the data and/or software necessary for conducting the vehicle diagnostic analysis is distributed in different systems that are connected via a data communication network, an automotive service system can minimize the size of software stored locally and can access most of the information and/or algorithm required for conducting the vehicle diagnostic analysis from a remote system.

Distributed vehicle service method and system

An improved method and system are provided for performing rolling runout compensation for vehicle wheel alignment. A plurality of sets of camber and toe measurements are acquired for a pair of vehicle wheels, each at a different, relatively small rollback angle between measurements; e.g., rolling the vehicle more than 0&#xb0; and less than 180&#xb0; from the last wheel position. Best fit sine waves are computed for each of the camber and toe measurements using the acquired data, and the best fit parameters are applied to compute runout at the current wheel angle. The computed runouts are subtracted from the measured camber and toe values to get true camber and toe values of the pair of wheels.

Short rolling runout compensation for vehicle wheel alignment

A method and apparatus are provided for forming a wireless communications network using a standard communications link between a master controller and at least one slave device. In one example, a list of available slave devices for the network is generated, valid slave devices are determined from the list of available slave devices based on an identification protocol of the standard communications link, and the at least one slave device is selected from the valid slave devices. A network identification is established between the master controller and the at least one slave device, and the network identification is used to establish a network comprising only the master controller and the at least one slave device.

Wireless network and methodology for automotive service systems

A vehicle wheel alignment system may include wheel alignment sensors configured to measure toe angles of steerable wheels on the vehicle, a user interface configured to communicate information to a user, and a processing system. The processing system may be configured to cause the user interface to communicate instructions to rotate a steering wheel on the vehicle and to communicate centering information that is pertinent to whether the steering wheel is substantially centered with respect to the steerable wheels based at least in part on the toe angles.

Steering wheel level verification with alignment sensors attached

A method is provided for positioning a free-standing fixture relative to a vehicle, using a visual aligner system for imaging vehicle-mounted targets with reference image sensors and processing the resultant images. Embodiments include calculating locations of the vehicle-mounted targets, calculating a location of a reference point on the vehicle, and determining a longitudinal line along a longitudinal axis of the vehicle. A location of a center of the fixture and an axis of the fixture is then calculated based on an image of one of the targets obtained by a remote image sensor attached to the fixture. The fixture is positioned by adjusting the fixture relative to the vehicle to achieve a desired position or orientation of the fixture based on the performed comparison steps and angle calculations.

Method for use with an optical aligner system for positioning a fixture relative to a vehicle

In a vehicle alignment system an optical sensing mechanism is structurally coupled to a vehicle supporting lift for movement in unison with the lift so that the field of view of the sensing mechanism encompasses a wheel of a vehicle positioned on the lift during lift movement. Sensing modules may be selectively placed so that they are in correspondence with the vehicle wheel base. Modules may be deployed to extend outwardly from the lift, for viewing the wheel during an alignment procedure, or retract to a adjacent the lift for stowing. A protective cover extends above the sensing modules in the retracted position.

Wheel aligner measurement module attachment system

In a machine vision system utilizing computer processing of image data, an imaging module incorporates the image sensor as well as pre-processing circuitry, for example, for performing a background subtraction and/or a gradient calculation. The pre-processing circuitry may also compress the image information. The host computer receives the pre-processed image data and performs all other calculations necessary to complete the machine vision application, for example, to determine one or more wheel alignment parameters of a subject vehicle. In a disclosed example useful for wheel alignment, the module also includes illumination elements, and the module circuitry provides associated camera control. The background subtraction, gradient calculation and associated compression require simpler, less expensive circuitry than for typical image pre-processing boards. Yet, the pre-processing at the imaging module substantially reduces the processing burden on the host computer when compared to machine vision implementations using direct streaming of image data to the host computer.

Gradient calculating camera board

A common platform is used in conjunction with a host computer to control various equipment sensors that perform different functions. In one aspect, the common platform is a micro-controller board, the host computer is a personal computer (PC), and the equipment sensors comprise an add-on card and a sensor for use in automotive services. A universal serial bus (USB) or an RS232 interface used for the common platform communicates with the host computer and with the equipment sensors. The common platform is a plug and play board that, once attached to the host computer, operates with little or no human intervention. The common platform is capable of accommodating various equipment sensors that are run by various appropriate application software. Further, the common platform can run under different operation power sources. In one aspect, these power sources include a power source embedded in the common platform, an RS232 power source, and a power source external to the common platform, such as a battery.

Common platform for use in automotive services

Growing community of inventors

Vilonia, AR, United States of America

George Michael Gill