Limits...
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.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.

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

TDOA frequency distribution histograms for all pairs of antennas in the case of surface discharges. (a) Antennas 1 and 2; (b) Antennas 1 and 3; (c) Antennas 1 and 4; (d) Antennas 2 and 3; (e) Antennas 2 and 4; (f) Antennas 3 and 4.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4481908&req=5

f9-sensors-15-09882: TDOA frequency distribution histograms for all pairs of antennas in the case of surface discharges. (a) Antennas 1 and 2; (b) Antennas 1 and 3; (c) Antennas 1 and 4; (d) Antennas 2 and 3; (e) Antennas 2 and 4; (f) Antennas 3 and 4.

Mentions: The next step to find what type of pulse has been selected is to calculate the six TDOA of all four antennas using the method explained in Section 3.2.3. The signals are artificially oversampled by interpolating points using cubic splines between two real samples so the sampling time is reduced tenfold to 20 picoseconds. This decision helps in the accuracy of the TDOA calculations giving errors that are below the actual sampling time. However, even in the case that all selected points correspond to the same type of event there can be errors in the calculation of the TDOA. Therefore, the frequency distributions of the TDOA are used to select only the points that give a solution in the interval of the mode or plus-minus ten samples after oversampling, see Figure 9. In these plots, the abscissa axis represents the time-difference between two antennas in tens of samples considering that . This is done to stress that there is a constraint in the time resolution limited by the sampling frequency. The ordinate axis is the number of events that give a certain TDOA. Assuming an error of ±10 samples is correct though it would induce an uncertainty in the possible geometric solutions.


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

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

TDOA frequency distribution histograms for all pairs of antennas in the case of surface discharges. (a) Antennas 1 and 2; (b) Antennas 1 and 3; (c) Antennas 1 and 4; (d) Antennas 2 and 3; (e) Antennas 2 and 4; (f) Antennas 3 and 4.
© Copyright Policy
Related In: Results  -  Collection

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

f9-sensors-15-09882: TDOA frequency distribution histograms for all pairs of antennas in the case of surface discharges. (a) Antennas 1 and 2; (b) Antennas 1 and 3; (c) Antennas 1 and 4; (d) Antennas 2 and 3; (e) Antennas 2 and 4; (f) Antennas 3 and 4.
Mentions: The next step to find what type of pulse has been selected is to calculate the six TDOA of all four antennas using the method explained in Section 3.2.3. The signals are artificially oversampled by interpolating points using cubic splines between two real samples so the sampling time is reduced tenfold to 20 picoseconds. This decision helps in the accuracy of the TDOA calculations giving errors that are below the actual sampling time. However, even in the case that all selected points correspond to the same type of event there can be errors in the calculation of the TDOA. Therefore, the frequency distributions of the TDOA are used to select only the points that give a solution in the interval of the mode or plus-minus ten samples after oversampling, see Figure 9. In these plots, the abscissa axis represents the time-difference between two antennas in tens of samples considering that . This is done to stress that there is a constraint in the time resolution limited by the sampling frequency. The ordinate axis is the number of events that give a certain TDOA. Assuming an error of ±10 samples is correct though it would induce an uncertainty in the possible geometric solutions.

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.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.

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