D
Denis Rinas
Researcher at Technical University of Dortmund
Publications - 9
Citations - 101
Denis Rinas is an academic researcher from Technical University of Dortmund. The author has contributed to research in topics: Anechoic chamber & Time domain. The author has an hindex of 4, co-authored 9 publications receiving 77 citations.
Papers
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Journal ArticleDOI
Predicting the Radiated Emissions of Automotive Systems According to CISPR 25 Using Current Scan Methods
Jin Jia,Denis Rinas,Stephan Frei +2 more
TL;DR: In this article, the authors present a field prediction method, which combines a measured CM current distribution with numerical computations for the radiated fields in the frequency range of 30-1000 MHz.
Proceedings ArticleDOI
Prediction of radiated fields from cable bundles based on current distribution measurements
Jin Jia,Denis Rinas,Stephan Frei +2 more
TL;DR: In this paper, the amplitude of common mode current from phaseless measurements using a RF current probe is used to predict radiated emissions from setups according to ALSE method, without using a large anechoic chamber.
Proceedings Article
Optimization methods for equivalent source identification and electromagnetic model creation based on near-field measurements
TL;DR: In this paper, an approach to optimize the characterization method of printed circuit boards by near-field measurements is proposed, where the radiation of a PCB is modeled with a set of elementary sources, resulting in the same field like the electronic system itself.
Proceedings Article
An alternative method for measurement of radiated emissions according to CISPR 25
Jin Jia,Denis Rinas,Stephan Frei +2 more
TL;DR: In this paper, the authors proposed two alternative enhancements of the common-mode current scan methods in time domain for cable bundles, which can provide the amplitude and phase information of currents simultaneously through Fast Fourier Transform (FFT).
Journal ArticleDOI
PCB current identification based on near-field measurements using preconditioning and regularization
TL;DR: In this paper, an improved radiation model creation approach based on complex near-field data is presented, which is based on regularization methods and extended by current estimations from near field data.