Spurious electromagnetic emission arising during operation of power converters can create a significant problem of electromagnetic compatibility for components of complex electronic systems. Therefore, when designing electronic systems, it is necessary to estimate the possible parameters of such emission in advance and, if necessary, take protective measures in advance. Existing approaches to predicting electromagnetic emission often do not allow to fully take into account explicit and implicit electromagnetic processes in power converters and in the operating environment. The article implements a practical technique for predicting the intensity of spurious electromagnetic emission from power converters using an artificial neural network. To demonstrate the possibility of using this tool, an experimental stand for preparing training and test data was created. An example of training an artificial neural network based on experimental data for 100 epochs is given. For the test sample, the average absolute percentage error is no more than 11 %. Examples of predicting the intensity of spurious electromagnetic emission from an electric power converter using a trained neural network are given. Prospects for using this tool are seen in the tasks of predicting electromagnetic interference along power lines, etc.
Гизатуллин et al. (Fri,) studied this question.