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Separation of radio-frequency sources and localization of partial discharges in noisy environments.

Robles G, Fresno JM, Martínez-Tarifa JM - Sensors (Basel) (2015)

Bottom Line: The radio-frequency emission of these events can be measured with antennas even when the equipment is in service which reduces dramatically the maintenance costs and favours the implementation of condition-based monitoring systems.This paper proposes a robust method to separate the events captured with the antennas, identify which of them are partial discharges and localize the piece of equipment that is having problems.Several classical methods to calculate the time differences of arrival (TDOA) of the emission to the antennas have been tested, and the localization is done using particle swarm optimization (PSO) to minimize a distance function.

View Article: PubMed Central - PubMed

Affiliation: Department of Electrical Engineering, University Carlos III of Madrid, Avda. Universidad, 30, Leganés 28911, Spain. grobles@ing.uc3m.es.

ABSTRACT
The detection of partial discharges (PD) can help in early-warning detection systems to protect critical assets in power systems. The radio-frequency emission of these events can be measured with antennas even when the equipment is in service which reduces dramatically the maintenance costs and favours the implementation of condition-based monitoring systems. The drawback of these type of measurements is the difficulty of having a reference signal to study the events in a classical phase-resolved partial discharge pattern (PRPD). Therefore, in open-air substations and overhead lines where interferences from radio and TV broadcasting and mobile communications are important sources of noise and other pulsed interferences from rectifiers or inverters can be present, it is difficult to identify whether there is partial discharges activity or not. This paper proposes a robust method to separate the events captured with the antennas, identify which of them are partial discharges and localize the piece of equipment that is having problems. The separation is done with power ratio (PR) maps based on the spectral characteristics of the signal and the identification of the type of event is done localizing the source with an array of four antennas. Several classical methods to calculate the time differences of arrival (TDOA) of the emission to the antennas have been tested, and the localization is done using particle swarm optimization (PSO) to minimize a distance function.

No MeSH data available.


Related in: MedlinePlus

Onset determination with the AIC method using the same signals.
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f6-sensors-15-09882: Onset determination with the AIC method using the same signals.

Mentions: Figure 6 shows the performance of the Akaike information criterion for the same pair of signals. The TDOA is again 11 samples though the picking is found one sample earlier. Notice that the time of arrival has to be located in a window that encompasses closely the onset of the signal, otherwise, the minimum value of the AIC would be far from the correct solution. For this reason, the method applied in this paper has been the cumulative energy with negative slope.


Separation of radio-frequency sources and localization of partial discharges in noisy environments.

Robles G, Fresno JM, Martínez-Tarifa JM - Sensors (Basel) (2015)

Onset determination with the AIC method using the same signals.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4481908&req=5

f6-sensors-15-09882: Onset determination with the AIC method using the same signals.
Mentions: Figure 6 shows the performance of the Akaike information criterion for the same pair of signals. The TDOA is again 11 samples though the picking is found one sample earlier. Notice that the time of arrival has to be located in a window that encompasses closely the onset of the signal, otherwise, the minimum value of the AIC would be far from the correct solution. For this reason, the method applied in this paper has been the cumulative energy with negative slope.

Bottom Line: The radio-frequency emission of these events can be measured with antennas even when the equipment is in service which reduces dramatically the maintenance costs and favours the implementation of condition-based monitoring systems.This paper proposes a robust method to separate the events captured with the antennas, identify which of them are partial discharges and localize the piece of equipment that is having problems.Several classical methods to calculate the time differences of arrival (TDOA) of the emission to the antennas have been tested, and the localization is done using particle swarm optimization (PSO) to minimize a distance function.

View Article: PubMed Central - PubMed

Affiliation: Department of Electrical Engineering, University Carlos III of Madrid, Avda. Universidad, 30, Leganés 28911, Spain. grobles@ing.uc3m.es.

ABSTRACT
The detection of partial discharges (PD) can help in early-warning detection systems to protect critical assets in power systems. The radio-frequency emission of these events can be measured with antennas even when the equipment is in service which reduces dramatically the maintenance costs and favours the implementation of condition-based monitoring systems. The drawback of these type of measurements is the difficulty of having a reference signal to study the events in a classical phase-resolved partial discharge pattern (PRPD). Therefore, in open-air substations and overhead lines where interferences from radio and TV broadcasting and mobile communications are important sources of noise and other pulsed interferences from rectifiers or inverters can be present, it is difficult to identify whether there is partial discharges activity or not. This paper proposes a robust method to separate the events captured with the antennas, identify which of them are partial discharges and localize the piece of equipment that is having problems. The separation is done with power ratio (PR) maps based on the spectral characteristics of the signal and the identification of the type of event is done localizing the source with an array of four antennas. Several classical methods to calculate the time differences of arrival (TDOA) of the emission to the antennas have been tested, and the localization is done using particle swarm optimization (PSO) to minimize a distance function.

No MeSH data available.


Related in: MedlinePlus