This document describes a low-power wireless detector for monitoring partial discharge (PD) in electrical equipment. The detector uses three frequency bands to capture PD signals from sensors. It was tested in a laboratory setup with different defect types in SF6 gas. The results showed the detector could distinguish between defect types based on variations in the frequency spectra. Multiple defects were also differentiated. The conclusions were that the novel frequency-based approach is capable of PD detection and basic defect classification with low power consumption for wireless applications.

1. A Frequency-based RF Partial
Discharge Detector for Low-power
Wireless Sensing

2. index
 INTRODUCTION
 Rf pd monitoring
 PD frequency characteristics
 Wireless sensor network
 Detector requirement
 DETECTOR OVERVIEW
 OUTPUT DATA
 Laboratory case study
 CONCLUSION
 Reference

3. INTRODUCTION
PARTIAL DISCHARGE
“Partial discharge is a localized dielectric break down
of a solid or fluid electrical insulation system under
high voltage stress”
 Degradation in dielectric insulation during
operational life time or manufacturing time
 Leads to internal arcing
NEED FOR DETECTION
• To avoid equipment failure
• Ensure equipment uptime
• Mitigate business risk

4. Rf pd monitoring
Analyzing unit
•Wide band UHF signal capture unit
•Conditioning unit
•Coupled PC
Visualizing unit
•User interface

5. Advantages
• Effective & accurate tool.
•GIS & oil filled transformer.
Disadvantages
•It requires a large processing capability
to capture UHF signals
•Not viable to install in all high voltage plants

6. PD frequency characteristics
•Defect-specific information used for classification
based on frequency spectrum.
•The relationship between PD source and sensor in
terms of geometry and distance due to complex
propagation effects

7. Wireless sensor network
 wide-range of monitoring applications.
 Ad-hoc network with redundant links.
 Sensory data is passed back through data
aggregation nodes to a wired network
 Data is presented to monitoring engineers.
 Integrated computing platform;
 Encapsulating sensing, processing, data storage,
communications & power components in a single
compact Package.

8. Advantages
 Low cost
 Absence of potentially hazardous cabling
 Reduced bandwidth requirements
 High capacity communication links b/w
substations &corporate networks.
Disadvantages
 Degrading effect of Impulsive noise emitted by
PDs on wireless data channels.

9. Detector requirement
Functional requirements
 Sensing & recording
intensity of PD signals & relative spectral magnitudes
 Differentiation of PD from RF noise
 Relatively small
 Interface with RF sensors ( plant enclosures)
A Low-power 3channel detector-

10. DETECTOR OVERVIEW
DETECTOR FREQUENCY BANDS
Band Range
Lower 0 – 450 MHz
Middle 400 – 750 MHz
Upper 700 – 3200 MHz

11. 3 identical
channels
Schottky diode
detector
5MHz
LPF
Amplifier
PHYSICAL DEVICE OVERVIEW
Sampling
by an ADC
output
WB RF
signals
 Output is three pulse envelopes ( the relative
energy within the three frequency bands)

12. OUTPUT DATA
• Peak value of the PD envelope for three
discrete frequency bands.
•Values are then normalized into a proportional
form,
•It represents the relative spectral energies
within the PD signal.
•The total magnitude of the captured sample is
also included as a feature, as the sum of the
three channels.

13. Laboratory case study
Test tank with three monopole RF sensors.
Addition panel with RF PD sensor types.
Three test cells.
A 50kV foster transformer, energized up to 15kV to
generate PDs within each of the cells.
Cells filled with SF6, pressurized at 2 bar .

14. Two of the test cells. On the left
is the floating electrode in SF6
test cell, and on the right is
the
rolling particle in SF6 test
cell..
Internal view of RF test tank,
Defect positions within the test tank

15. •Two positions are available within the test tank-in
front of the sensor hatch and in the center of the test
tank.
• limiting factors -position of the transformer and
the length of the high-voltage cables .
•Safer operation directly beneath the sensor hatch,
.
•The floating electrode test cell was oriented in three
planes to simulate the RF emission of an individual
defect propagating in different directions.

16. 1
EXPERIMENTAL RESULTS
Protrusion in sf6:

17. • The spectra varies in intensity between
the lower and middle bands, but have less than a
10% proportion of high-frequency content.
•The results fall into two distinct clusters,
corresponding to two positions.
•That multiple protrusion defects in SF6 & can be
distinguished based upon frequency spectra.

18. 2

19. •PDs generated by this test cell were found to form a
Tight cluster.
•The defect orientation have little effect
on the recorded RF spectrum.
• higher proportion of spectral energy in
the >700 MHz band, differentiating them from the
floating particle and protrusion.

20. 3 Rolling particle in sf6

21. •The results from both positions fall within the
same region of the chart, with half the spectral
energy falling within the middle 400MHz-750MHz
band.
• The remaining spectral energy varies
between the upper and lower bands based upon
position.
•Results from each position are uniform with
minor variance, falling in tight clusters.
defect test cell is uniform, and the measured
spectrum varies only with location.

22. CONCLUSION:
Novel approach to RF PD monitoring using a low-powered
detector employing frequency-based
technique.
 Capable of determining the presence of multiple
defects, & rudimentary defect classification.
Ternary plots have been used for the presentation
and analysis of the PD data, allowing linear
separation of defects

23. Reference
•IEEE Transactions on Dielectrics and Electrical Insulation Vol. 17,
No. 1; February 2010 ”A Frequency-based RF Partial Discharge
Detector for Low-power Wireless Sensing” P. C. Baker, M. D. Judd
and S. D. J. McArthur
•P. C. Baker, S. D. J. McArthur, and M. D. Judd, “Data Management of
On-Line Partial Discharge Monitoring Using Wireless Sensor Nodes
Integrated with a Multi-Agent System”, Intern. Conf. Intelligent
Systems Applications to Power Systems (ISAP), pp. 1–6, 2007.
•Z. Tang, C. Li, X. Cheng, W. Wang, J. Li, and J. Li, “Partial
discharge
location in power transformers using wideband RF detection”,

24. Thank you