1,720,999 research outputs found
Classification of Electric Signals Based on Time–Frequency Signal Decomposition
A classification procedure based on timefrequency
decomposition of the signal is presented.
Parametric spectral ESPRIT method is used for
estimation of relevant parameters of signal components
and specific areas of the time-frequency plane are
chosen, where the signal is expected to show most
characteristic patterns. Classification is based on timedomain
correlation of reconstructed signals. It is applied
to event classification of non-stationary electric signals
obtained from a simulated power converter
Intelligent wireless street lighting system
We propose an innovative wireless street lighting system with optimized management and efficiency. Wireless communication uses ZigBee-based wireless devices which allow more efficient street lamp system management, thanks to an advanced interface and control architecture. It uses many sensors to control and guarantee the optimal system parameters; the information is transferred point-by-point using ZigBee transmitters and receivers and is sent to a control terminal used to check the state of the street lamps and to take appropriate measures in case of failure. The system allows substantial energy savings with increased performance and maintainability
Assessment of the Impact of Active Compensation Devices of DC Arc Furnaces Using Advanced Spectrum Estimation Methods
Comparison between DFT, Adpative Window DFT and EDFT for Power Quality Frequency Spectrum Analysis
Spectral leakage and picket-fence effects associated with the system fundamental frequency variation and improperly selected sampling time window prevents a direct application of the DFT algorithm with a constant sampling rate. In particular it’s very difficult to detect low level interharmoincs and subharmonics. In this paper we compare two methods, proposed in literature, evaluating the detection capability and accuracy in frequency spectrum estimation. Several tests in different condition has been effected for the comparison
Detection of Voltage Dips and Micro Interruptions Using the Hilbert Transform
In electrical energy power networks,
disturbances can cause problems in electronic devices so
their monitoring is fundamental in Power Quality. In this
paper we address the problem of disturbances estimation by
using the Hilbert Transform (HT). It is employed as an
effective technique for tracking the voltage waveforms in
electrical distribution systems. The mathematical simplicity
of the proposed technique, compared with the commonly
used algorithms from the literature, renders them
competitive candidate for the on-line tracking of
disturbances. The accurate tracking of the HT facilitates its
implementation for the control of disturbances mitigation
devices. Simulation results are provided to verify the
tracking capabilities of the algorithm and this has been
tested under different conditions: voltage dip with phase
jump, noise and frequency changes shows that the Hilbert
Transform can be used as a valid methodology for this type
of phenomena
Methods for detection of sub-harmonics in power systems
With a wide range of power electronics-related applications
in power systems, harmonic currents are increasing at
an alarming rate which has greatly deteriorated the power
quality in electrical power networks. Moreover, some of
electronic controlled equipments used in power systems,
such as cycloconverters, produce sub-harmonics, a type of
waveform distortion, which can severely degrade the power
system performance. Therefore, they must be closely monitored.
Moreover, Fast Fourier Transform cannot accurately
analyze waveforms containing sub-harmonics because the
synchronization of the sampling procedure to subharmonics
is practically infeasible. The detection of subharmonics
requires a different approach from that used for
harmonics analysis. In most analysis methods the voltage
waveform is expected to be a pure sinusoid with a given
frequency and amplitude. Standard tools of harmonic
analysis based on the Fourier transform assume that only
harmonics are present in the investigated signal and the
periodicity intervals are fixed, while periodicity intervals in
the presence of interharmonics and sub-harmonics can be
variable and very long. Two novel approaches to analyze
non-stationary signals are shown in this paper. The first is
the “Root-Music” harmonic retrieval method that is an
example of high-resolution eigenstructure-based method,
the second is a numerical method based on moving average
Electrical Energy Measurements for Rome LV Customers by Distributed Web-Server Instruments
Power Quality (PQ) measurements for low voltage
(LV) customers, domestic and business, have been carried out in
order to detect the behaviour of the electric net over time and the
quality of the electric energy being bought. In order to measure
PQ parameters, we realized an instrument based on web server
personal computers, which are common in office or in domestic
environment. This allows us to conjugate the high PC calculus
capability with the possibility to send data via internet to a central
server; moreover, the use of the existing hardware infrastructure
makes the instruments extremely cheap
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