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TITANN: Rethink X-Ray Sample Manipulation

Sep
04

TITANN: Rethink X-Ray Sample Manipulation

The determination of where the sample is located inside the x-ray chamber is critical to automated applications where several sample locations are inspected continuously and without operator intervention. The ability to go to the same location in the stage reliably and accurately is highly desirable. The state of the art in sample manipulation for x-ray inspections relies on the use of step motors connected to actuators that move a stage inside the x-ray chamber. The main problem with the use of step motors is that a number of steps is sent to motor so it can move, but there is no certainty the motor shaft turned the correct amount of times. Thus it is impossible to determine by how much the sample moved. Modern manipulation systems utilize encoders connected to the shaft of the step motor to count the number of turns of the motor. This feedback method improves the repeatability of the system and reduces the overall error. However, it is still prone to deviations between the number of turns of the motor and the actual movement of the sample. Another major shortcoming of this tracking method is that the error is cumulative. As the system is used the motion error compounds. As a result, these systems need to be regularly calibrated.

The TruView Infrared Tracking with Artificial Neural Networks (TITANN) is a patent pending technology that utilizes an optical target to locate the stage inside the x-ray chamber. These targets are infrared LEDs used to minimize noise in the image caused by visible light. By tracking the location of the infrared LED, the TruView software can determine the location of the stage/sample within 500um without the need for calibration. Better resolutions have been achieved for applications that require better sample control, including computed tomography (CT), laminography, and tomosynthesis.

We’ve also designed a custom infrared camera to track the location of the infrared LED on the stage. This megapixel camera is specially suited to operate inside the x-ray chamber.

TITANN-IR-Camera-sm

Artificial neural networks are ideal for repetitive applications – thus a perfect fit for an x-ray sample tracking control. The artificial neural networks utilized in TITANN greatly reduce system errors and optimize travel of the stage. The custom artificial neural network algorithms in TITANN keep track of the location errors at each stage movement and automatically adjust the control system to the motors to minimize the distance between desired and achieved location.

TITANN-Neural-Network-sm

The TITANN technology is currently available on a selected number of TruView inspection systems. Contact us today for more information.

About the Author:

Dr. Bill Cardoso is the President of Creative Electron. He holds a MS and PhD degrees from the Illinois Institute of Technology (IIT) and an MBA from The University of Chicago. An industry thought leader, Bill has been recognized as IIT's 2011 Outstanding Young Alumnus Awardee for his contributions to science and technology. He is also a Senior member of the Institute of Electrical and Electronics Engineers (IEEE), Surface Mount Technology Association (SMTA), American Physics Society (APS), and the International Society for Optics and Photonics (SPIE). Bill is a holder of several patents in the areas of radiation detection, radiography, and quality inspection.

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