Evaluating the performance of an X-ray tube by: recording arcing events that occurred during the use of the X-ray tube; classifying the arcing events by severity; generating, on the basis of the classified arcing events, a first growth pattern for occurrences of arcing events; and determining a level of bubbles in the X-ray tube by finding, on the basis of the first growth pattern, a matching second growth pattern associated with a known level of bubbles in the X-ray tube. An X-ray tube may be checked and replaced in a timely manner, without the need for an on-site inspection, by remotely predicting trends or patterns for growth of levels of bubbles in the X-ray tube.

The present invention relates to a method and system for predicting X-ray degradation, the system comprising; a generator (10) configured to generate a deployment fingerprint data set for recording cumulative radiation exposure of a currently deployed X-ray tube; a database (20) configured to provide a training data set comprising multiple tube fingerprint data sets for recording cumulative radiation exposure of previously deployed X-ray tubes correlated with failures of the previously deployed X-ray tubes; and a neural network (30) configured to be trained using the training data set and configured to predict at least one parameter of the currently deployed X-ray tube based on the training.

The present approach relates to generating one or both of a failure prediction indication for an X-ray tube or a remaining useful life estimate for the X-ray tube. In one implementation, a trained static tube model is used in estimating health (e.g., thickness) of the electron emitter of the X-ray tube, which in turn may be used in predicting remaining useful life of an electron emitter of the X-ray tube.

The present approach relates to generating one or both of a failure prediction indication for an X-ray tube or a remaining useful life estimate for the X-ray tube. In one implementation, a trained static tube model is used in estimating health (e.g., thickness) of the electron emitter of the X-ray tube, which in turn may be used in predicting remaining useful life of an electron emitter of the X-ray tube.

Evaluating the performance of an X-ray tube by: recording arcing events that occurred during the use of the X-ray tube; classifying the arcing events by severity; generating, on the basis of the classified arcing events, a first growth pattern for occurrences of arcing events; and determining a level of bubbles in the X-ray tube by finding, on the basis of the first growth pattern, a matching second growth pattern associated with a known level of bubbles in the X-ray tube. An X-ray tube may be checked and replaced in a timely manner, without the need for an on-site inspection, by remotely predicting trends or patterns for growth of levels of bubbles in the X-ray tube.

The present disclosure provides a testing station, testing module and testing method for testing a plurality of image intensifier tubes. In an embodiment, a testing station includes a first testing module and a second testing module. The first testing module has a first input connector, a first output connector and a plurality of first testing sections each configured to test an image intensifier tube. The second testing module has a second input connector, a second output connector and a plurality of second testing sections each configured to test an image intensifier tube. The first testing module and the second testing module are configured to be removably attached to each other in a first orientation and a second orientation. The first input connector is connected to the second output connector in the first orientation, and the second input connector is connected to the first output connector in the second orientation.