General Electric Company

Ge Medical Technology Services, Inc.

Ge Medical Systems

John Breunissen

Mark Gilbert Benz

Gregory Alan Steinlage

Paul A Siemers

Thomas Robert Raber

Constantinos Minas

Charles Gitahi Mukira

Douglas J Snyder

Gregory Reznikov

Diane Marie Miesbauer

Liang Tang

Eric Biehr

James Michael Gent

Richard W Lindberg

William Allen Berezowitz

Kallahalli R Shubha

Christopher C Hardiman

Ping Huang

A diagnostic tool for an x-ray imaging system includes a first test device configured to simulate a first load condition of an x-ray tube, and a first connector electrically coupled to the first test device and configured to couple the first test device to a high-voltage generator in the x-ray imaging system.

Apparatus and method of use of a high-voltage diagnostic tool for x-ray systems

A technique for scheduling planned maintenance of equipment, such as medical imaging systems, permits selection of time-based or usage-based scheduling. If usage-based scheduling is selected, operational data collected from the systems serves as the basis for computing a maintenance schedule along with reference usage values for parameters indicative of use. Reference may be made to norms for similar equipment, and the schedule may be adapted accordingly. Trends in usage, increasing or decreasing, may be accommodated by comparison of the usage determinations over time, and schedules may be adjusted accordingly.

Medical equipment predictive maintenance method and apparatus

A brazed X-ray target includes a metallic cap and a graphite back including a nonlinear record groove attached thereto along a stepped surface. An upper corner joint of the stepped surface is distanced from a cap outer edge and a focal track where the maximum heat is generated during use of the target. The graphite back is extended outward toward the cap outer edge to increase a thermal storage of the graphite, and a recess is formed into the cap to maintain a selected moment of inertia of the target and thereby maintain the rotordynamics of a given X-ray tube.

High performance x-ray target

Possible failure of x-ray tubes is predicted by monitoring and analysis of operating parameters considered leading indicators of failure. Historical data for a tube population is analyzed by discriminant analysis to develop a failure prediction algorithm. The algorithm is used to correlate operating parameters, or values derived from the operating parameters with a potential for tube failure. The operating parameters may include anode overcurrent events and spits, or spit rate exceeded errors for a diagnostic system in which the x-ray tube is installed.

X-ray tube life prediction method and apparatus

Growing community of inventors

Wauwatosa, WI, United States of America

John Breunissen