IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY, VOL. 58, NO. 2, APRIL 2016 385
Decomposition of Electromagnetic Interferences
in the Time-Domain
Marco A. Azp ´ urua, Member, IEEE, Marc Pous, and Ferran Silva, Member, IEEE
Abstract—Electromagnetic interferences are potentially very
complex signals formed by the superposition of transient (broad-
band) and continuous wave (narrowband) components with signif-
icant randomness in both amplitude and phase. Decomposing the
electromagnetic interference measured in the time domain into a
set of intrinsic mode functions is useful to gain insights of the pro-
cess that generates the interference. Evaluating the intrinsic mode
functions contributes to improving the measurement capabilities
of the time-domain electromagnetic emissions measurement sys-
tems based on the general-purpose oscilloscopes. In this paper, a
combination of techniques that includes empirical mode decom-
position and transient mode decomposition is used to separate the
main components of complex electromagnetic disturbances. This
approach requires no prior information on the spectral content
of the measured EMI and it does not perform a domain transfor-
mation. Examples of electromagnetic interference decomposition
verify the effectiveness and the accuracy of the proposed approach.
Finally, a discussion on the advantages, practical applications, lim-
itations, and drawbacks of the described techniques is addressed.
Index Terms—Digital signal processing, electromagnetic com-
patibility, electromagnetic interference, electromagnetic measure-
ments, time-domain analysis.
I. INTRODUCTION
E
LECTROMAGNETIC interferences are complex signals
composed of the superposition of continuous-wave, tran-
sient, and random disturbances. In consequence, measuring
properly and defining specific features of an electromagnetic
interference (EMI) are challenging tasks.
In this regard, the conventional approach for the evaluation
of the electromagnetic emissions consists in measuring the am-
plitude spectrum of the disturbance using a frequency sweep
receiver and the CISPR standard detectors [1]. Therefore, the
current standard measurement procedures for assessing an EMI
neglect important time-domain characteristics of the electro-
magnetic disturbances, such as the repetition rate, the different
emission profiles of an EUT as it changes its operation mode, and
the impact of transient events [2]. This is particularly relevant
for evaluating and predicting the degradation suffered by digital
Manuscript received June 16, 2015; revised November 20, 2015; accepted
January 4, 2016. Date of publication January 25, 2016; date of current ver-
sion March 8, 2016. This work was supported in part by the EURAMET
IND60EMC research project (the EMRP is jointly funded by the EMRP par-
ticipating countries within EURAMET and the European Union) and by the
Spanish “Ministerio de Econom´ ıa y Competitividad,” under project TEC2013-
48414-C3-3-R.
The authors are with Group of Electromagnetic Compatibility, Department of
Electronic Engineering, Polytechnic University of Catalonia, Barcelona 08034,
Spain (e-mail: marco.azpurua@upc.edu; marc.pous@upc.edu; ferran.silva@
upc.edu).
Color versions of one or more of the figures in this paper are available online
at http://ieeexplore.ieee.org.
Digital Object Identifier 10.1109/TEMC.2016.2518302
communication systems due to the influence of a transient EMI
[2]. Consequently, in some cases, the standardized methods of
EMI measurement and evaluation are not completely suitable,
insufficient or might require an enormous amount of time to
provide reliable measurement results [3], [4].
Currently, the fast Fourier transform-based EMI test re-
ceivers and real-time spectrum analyzers have time-scan mea-
surement capabilities that overcome many of the limitations
of the stepped frequency scan in the EMI receivers. However,
the bandwidth of their intermediate frequency filter and the
tradeoff between the time domain and the frequency-domain
resolutions [5] are their main constraints for measuring simulta-
neously broadband and narrowband interferences on the whole
frequency range. Recently, advances in an EMI postprocessing
and the enhanced capabilities of digital oscilloscopes allowed
to implement entirely time-domain EMI (TDEMI) measure-
ment systems. Those TDEMI systems provide accurate, full
spectrum, multichannel, time saving, and cost-effective EMI
measurements [6].
Nonetheless, estimating the spectral content of an EMI is
only one side of a multifaceted problem. For example, tran-
sient, intermittent, or event triggered (i.e., by changing opera-
tion modes) disturbances could be unnoticed by conventional
frequency sweep EMI measurements because the unsynchro-
nized occurrence of the EMI and its short duration. Previous
research has addressed some of those problems using time-
domain EMI analysis. In particular, Alban et al. [7] used an ad
hoc oscilloscope-based TDEMI measurement system for devel-
oping a statistical model for the broadband noise in comput-
ing platforms. In the field of power electronics, time-domain
EMI measurements have also been used for providing time-
frequency-energy distributions by means of the wavelet analysis
used for emissions mitigation in chaotic converters [8]. More re-
cently, statistical approaches to the evaluation of EMI measured
in the time-domain have been used to predict the degradation
caused by transient disturbances on digital communication sys-
tems [2], [9] and to model the distribution of peak measurements
using extreme value theory [10].
In that sense, exploring new processing approaches and tech-
niques is fundamental to enhance the performance of such
TDEMI systems. In particular, this paper presents an entirely
time-domain method that comprises techniques and algorithms
for signal decomposition that offer further possibilities to EMI
analysis. This method is based on the empirical mode decompo-
sition (EMD) [11] and includes a preliminary stage of transient
EMI separation that improves EMD performance.
The decomposition of an EMI in the time-domain seeks
to decompose the main components of the measured signal
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