Adaptive classification algorithm for EMC-compliance testing of electronic devices

A novel technique that facilitates near-field (NF) scanning for electromagnetic compatibility-compliance testing is described. It performs measurements in a sequential way with the aim of discovering multiple, possibly disjoint regions where the amplitudes of an NF component belong to certain output ranges. The measured data samples are used to train a classification model where each NF range is represented by a given class (e.g. low/medium/high NF amplitudes). The outcome of the algorithm is a visual map that clearly characterises and pinpoints the exact location and boundaries of each class. Such maps are useful, for example, to detect hotspots or regions that are prone to electromagnetic compatibility issues. The technique has been validated on a measured microstrip bend discontinuity

Sequential sampling algorithm for simultaneous near-field scanning of amplitude and phase

This paper describes an automated sequential sampling algorithm for EMI near-field scanning of electronic systems which allows to measure both magnitude and phase of the electromagnetic near-fields simultaneously. The main goal of the sequential sampling algorithm is to drastically reduce the total measurement time to obtain a complete model of the electronic system's near-field distribution. Measuring both magnitude and phase is important for predicting the far-field emission from the near-field or for building equivalent radiation models of the device under test. Previous work described such a sequential sampling algorithm for amplitude-only measurements. The extension towards both amplitude and phase poses two challenges. First, the underlying sampling and modelling techniques have to be adapted such that they can handle building up two separate models at the same time using a common set of optimal sampling points and without significant increase of the measurement time. Second, a good choice has to be made with respect to which components will be sampled and modelled. It is shown that the most advantageous choice is to sample and model the real and imaginary components of the near-fields instead of the amplitude and phase directly