Localisation of partial discharge sources using radio fingerprinting technique

Partial discharge (PD) is a well-known indicator of the failure of insulators in electrical plant. Operators are pushing toward lower operating cost and higher reliability and this stimulates a demand for a diagnostic system capable of accurately locating PD sources especially in ageing electricity substations. Existing techniques used for PD source localisation can be prohibitively expensive. In this paper, a cost-effective radio fingerprinting technique is proposed. This technique uses the Received Signal Strength (RSS) extracted from PD measurements gathered using RF sensors. The proposed technique models the complex spatial characteristics of the radio environment, and uses this model for accurate PD localisation. Two models were developed and compared: k-nearest neighbour and a feed-forward neural network which uses regression as a form of function approximation. The results demonstrate that the neural network produced superior performance as a result of its robustness against noise

Diagnostic Potential of Free-Space Radiometric Partial Discharge Measurements

The work reported in this paper addresses the calibration of four types of partial discharge (PD) emulator required for the development of a PD Wireless Sensor Network (WSN). Three partial discharge (PD) emulators have been constructed: a floating-electrode emulator, and two internal PD emulators. Both DC and AC HV power supplies are used to initiate PD which is measured using concurrent free-space radiometry (FSR) and a galvanic contact method based on the IEC 60270 standard. A new method of estimating absolute PD activity level from a radiometric measurement is proposed

Wireless Sensor Network for Radiometric Detection and Assessment of Partial Discharge in HV Equipment

Monitoring of partial discharge (PD) activity within high voltage electrical environments is frequently used for the assessment of insulation condition. Traditional measurement techniques employ technologies that require either offline installation or high power consumption and cost. A wireless sensor network is proposed that utilizes only received signal strength to locate partial discharge within a high-voltage electricity Substation. The network comprises low-power and lowcost radiometric sensor nodes which receive the radiation propagated from a source of partial discharge. Results are reported from a test performed within a large indoor environment with a network of nine sensor nodes. An emulated PD source was placed at multiple locations within the network. Signal strength measured by the nodes is reported via WirelessHART to a data collection hub where it is processed using a location algorithm. The results obtained place the measured location within 2 m of the actual source location

Localisation of partial discharge sources using radio fingerprinting technique

Partial discharge (PD) is a well-known indicator of the failure of insulators in electrical plant. Operators are pushing toward lower operating cost and higher reliability and this stimulates a demand for a diagnostic system capable of accurately locating PD sources especially in ageing electricity substations. Existing techniques used for PD source localisation can be prohibitively expensive. In this paper, a cost-effective radio fingerprinting technique is proposed. This technique uses the Received Signal Strength (RSS) extracted from PD measurements gathered using RF sensors. The proposed technique models the complex spatial characteristics of the radio environment, and uses this model for accurate PD localisation. Two models were developed and compared: nearest neighbour and a feed-forward neural network which uses regression as a form of function approximation. The results demonstrate that the neural network produced superior performance as a result of its robustness against noise