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Agilent Technologies Introduces CAN Eye-Diagram Mask Testing on InfiniiVision X-Series Oscilloscopes


May 25, 2012

Agilent Technologies Inc. has introduced the oscilloscope industry’s first eye-diagram mask testing capability for the differential Controller Area Network serial bus. The CAN serial bus is used extensively for control and sensor monitoring in automotive applications as well as a broad range of industrial and medical equipment applications.

For years, oscilloscopes have been the primary measurement tools used to verify the signal integrity of the CAN bus physical layer. With the new CAN eye-diagram mask test capability in Agilent’s 3000 X-Series oscilloscopes, engineers now have the ability to perform a composite signal-integrity measurement of their CAN buses in one easy measurement.

Eye-diagram mask testing is one of the most important ways designers can measure the overall signal quality of their serial bus networks. The CAN eye-diagram test randomly captures and overlays every differential bit of every CAN frame based on a unique clock-recovery algorithm that emulates worst-case CAN receiver hard synchronization, resynchronization and sampling. The result is a single measurement that provides insight into the overall signal integrity of the CAN’s physical layer to show worst-case timing and worst-case vertical amplitude variations. Overlaid bits are then continually compared against a six-point polygon-shaped pass/fail mask limit, which is based on CAN physical-layer specifications.

Controller Area Networks are based on an asynchronous event-driven architecture, so physical delays are the dominant contributor of timing uncertainty. The longer the Controller Area Network, the longer the delays. Agilent’s new CAN eye-diagram mask testing capability clearly detects and shows these worst-case network delays.

Information about the DSOX3AUTO option is available at www.agilent.com/find/scopes-auto. Product photographs and screen images of a CAN eye-diagram mask test are available at www.agilent.com/find/caneye_images.






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