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Partial discharges and noise separation in high frequency signals using inductive sensorsJ.M. Martínez-Tarifa1, M. Rojas,G. RoblesDepartment of ElectricalEngineering Universidad Carlos III de Madrid Leganés (Madrid), Spainjmmtarif@ing.uc3m.es1. B. MacPherson, P. Moore.Elimpus Ltd,Bellshill, United KingdomI. Portugués.Electric Power Research Institute,United States of AmericaAbstract—Partial discharges in high voltage equipment are a cause and consequence of premature ageing. Thus, its accurate measurement is an important diagnosis tool trying to avoid premature failures. Classical phase resolved patterns are now completed with pulse waveform analysis in order to discriminate between PD sources and PD from noise. For this purpose, high frequency inductive sensors are being used in recent years. In this paper, a fixed post-processing technique for PD pulse waveforms will be used to discriminate between discharges from electrical noise for two inductive sensors: a commercial High Frequency Current Transformer and a newly developed inductive loop sensor. Results will prove that this novel inductive loop sensor is able to discriminate PD from electrical noise for several test objects.Keywords-component; partial discharges, electrical insulation, inductive sensor, pulse shape analysis, noise rejection.I.I NTRODUCTIONElectrical equipment is usually exposed to several stresses through its whole lifetime. These devices (e.g. electrical machines and power cables) do not withstand voltages above their defined limits (dielectric strength) but, in addition to this, some of them show unexpected failures within their insulation systems at their rated voltages. A known source of insulation degradation are Partial Discharges (PD), that are a result of impurities or inhomogeneous areas inside insulation systems subjected to rated high voltages [1]. This phenomenon is a microscopic ionization localized at these sites, so they do not immediately lead to insulation breakdown; on the contrary, they are responsible for accelerated ageing through ion and electronic bombardment and resulting chemical attack [2].Partial discharges are not only a cause, but a symptom of insulation degradation, so their measurement is an important technique for power equipment status assessment [3]. Conventional PD measuring systems detect the discharge pulse amplitude and represent it in a phase resolved pattern which is used for PD source identification. These systems are typically bandwidth limited to 400 kHz.In order to help in PD interpretation it must be taken into account that not all kinds of PD are harmful for a long term operation of the equipment. In addition to this, PD measurements are commonly made on-line, so high levels of noise are always present in PD measurements [4]. Thus, conventional Phase Resolved Partial Discharge (PRPD) patterns sometimes cannot help in insulation diagnosis; furthermore, rejecting noise by means of increasing the trigger level is not reliable for PD detection in industrial environments because this means withdrawing low-magnitude PD pulses, that are more probable [1].For these reasons, modern techniques have been developed to process PD pulse waveform information from high frequency sensors [5], [6], [7], [8]. These devices provide complementary information to conventional PRPD patterns for PD detection and classification. The most commonly used sensor is the High Frequency Current Transformer (HFCT), but other recently developed inductive loop sensors have been proposed as well [9]. Despite these loop sensors show less sensitivity, they are a cheaper approach for high frequency pulse detection than HFCTs, and do not suffer from saturation when applied to power cables feeding electrical equipment diagnosed on-line.In this paper, PD pulse waveforms will be processed in order to distinguish them from noise pulses. This will be done using a previous technique proposed for pulse classification [5]. These pulses will be measured by means of an HFCT and an Inductive Loop Sensor (ILS). In this paper, the ILS pulse separation capability will be compared to that from HFCT for different test objects.II.E XPERIMENTAL SETUPPartial discharges have been measured in a classical indirect detection circuit, where high frequency pulses from ionization flow through the capacitive mesh formed by test object, and capacitive divider. A commercial PD detection circuit has been used in order to check PD activity in the test object. The inductive loop and the HFCT are placed at the low voltage terminal connecting the measurement impedance and ground (see Fig. 1).This research has been supported by the Spanish Science and Technology Ministry under Contract No. DPI 2009-14628-C03-02. Tests have been carried out in the High Voltage Research and Tests Laboratory at Universidad Carlos III de Madrid (LINEALT). The research stage of Technician Brian MacPherson was financed by Elimpus Ltd.978-1-4577-1772-7/12/$26.00 ©2012 IEEEFigure 1.- Experimental setup for PD measurements.The flow of charge due to PD produces currents in the parallel main ground conductor; this leads to a transient magnetic field that links the areas of both sensors.In the case of the ILS, the output signal corresponds to an inductive electromotive force that is proportional to the time rate of change of PD current, (1). M is the mutual inductance between the ILS and the conductor where the current flows.·(1)This ILS is connected to a 50 Ω oscilloscope channel that modifies the sensor output limiting its derivative response. According to the equivalent circuit of the Fig 2, the quotient of output voltage to the input PD current is determined by (2) in the Laplace domain.2where R o is the channel resistance and L the loop inductance.Figure 2.- Electric equivalent circuit.Initially, ILS response is derivative until a corner frequency, f c, (3). Afterwards, the effect of the reactive impedance is higher than that of the resistive one, so the output signal begins to be proportional to the current. Fig. 3 shows the frequency response of the ILS used in this paper. It has a derivative output up to 35 MHz, which is most of the PD inductive spectrum. More details about the sensor parameters and dimensions are presented in [9].23Figure 3.- Frequency response of the inductive sensor. The experimental data (dotted plot) and the theoretical data (solid data). [9].Regarding the HFCT, its output signal is always proportional to the current due to its large inductance. The HFCT used in this experimental work is a Techimp Systems S.r.l. clamp HFCT 39 with a bandwidth up to 40 MHz. Thus, for almost the same frequency interval, the ILS response provides an output signal that is the derivative of the HFCT signal.Since PD pulses will be measured by means of both sensors, the response of the commercial HFCT and this new ILS to the same discharge phenomenon will be compared.III.TEST SPECIMENSPartial discharge and noise waveforms depend on the test object, since its equivalent electrical network may change the response to ionization current from discharge sites. Thus, instrumentation techniques devoted to PD measurements must be proven on different test objects. In this paper tests were done on three insulation systems representing some of the main PD phenomena found in electrical insulation systems [10]:a)Corona PD. Typically produced near the tip in point-gas-plane setups or in highly divergent field zones. They are the result of local ionizations in the gas volume.b)Surface PD. Associated with gas ionization along a path on a solid dielectric-gas interface. They appear in bushings, outdoor insulators and in electrical machines windings.c)Internal PD. Produced in gaseous voids surrounded by solid insulation, normally in non-homogeneous insulating materials or due to unavoidable air impurities inside epoxy resins or polyethylene.Partial discharges are a stochastic phenomenon, whose behaviour changes for the same applied voltage and test objects. Temperature, humidity and dielectric material degradation change the PD response. In addition to this, noise sources are not unique and different noise pulse waveforms may be recorded as well. Thus, several measurements for the same test object and applied voltage are needed to get statistically reliable data. In this paper, 10 measurements ofpartial discharges, 10 from electrical noise and 10 lowmagnitude PD (superimposed on noise) have been recorded, in order to get a first approximation to the capability of the sensor to separate PD.A.Corona discharge setupIn this experimental setup, a 0.5 mm thick needle was placed above of a wide metallic ground plane. The air gap was adjusted with a screw to 4mm.B.Surface discharge setupThese discharges were generated using a wide (1m x 1m) polyethylene (PE) sheet 2 mm thick placed on a wider metallic ground plane. A 2 cm diameter electrode connected to a high voltage source is placed on this sheet. This provides a high electric field and an easy path to ground through the surface of the polyethylene layer. Surface discharges will appear in these paths due to the roughness of the layer, dust and other impurities.C.Internal discharge setupThe setup to generate internal discharges consists of three glued insulating papers 0.4 mm thick, typically used in high voltage generators as slot insulation systems. The papers are placed between two heavy metallic electrodes so they are pressed together. The central paper was pierced with a needle, creating a hole measuring 1 mm in diameter with a circular shape. Thus, the test object will have a disk-shaped void created inside the solid insulation system and will guarantee the generation of internal PD at moderate voltage levels.IV.PULSE WAVEFORM MEASUREMENTS In these experiments, Partial Discharge Inception Voltage (PDIV) was measured for all test objects using classical PRPD patterns from the commercial measuring system. Pulses detected below PDIV were electrical noise, whereas pulses above this voltage level were PD, noise or the superposition of both. Higher trigger levels for voltages well above PDIV lead to clear discharge waveforms, but pulses detected for lower trigger levels may be noise, or low magnitude PD superimposed on noise. For voltages below PDIV, the highest amplitude noise pulses were recorded, in order to get the worst case for PD-noise separation. These noise pulses are high magnitude and sporadic bursts that are present in the High Voltage Laboratory, so the noise level superimposed to low magnitude PD is different from the noise level presented in the worst case.Pulse waveforms for all test objects were recorded. The response to PD from HFCT and ILS will be compared in the following traces. For clarity, only a selection of characteristic pulses for one test object will be shown.A.Corona discharges and noise pulses measurementsFor voltages below PDIV (2400 V), different kinds of waveforms were acquired with an oscilloscope. Typical noise signals are shown in Fig. 4.When the voltage was raised above PDIV, clear PD were observed. These waveforms are very repetitive, as can be seen in Fig. 5. In addition to this, low-magnitude discharges superimposed to noise were observed as well, Fig. 6.As can be seen from Figs. 4-6, detected noise pulses can have higher magnitudes than clear corona discharge pulses. Thus, low magnitude PD are difficult to detect just controlling the trigger level and PD pulse processing techniques will be especially useful.Figure 4.- Noise pulses for corona discharge test measured with ILS (blue plot) and HFCT (brown plot). The vertical scales are 20 mV/div and 100 mV/div for ILS and HFCT, respectively; 80ns/div in horizontal scale.Figure 5- PD pulses for corona discharge test measured with ILS (blue plot) and HFCT (brown plot). The vertical scales are 5 mV/div and 20 mV/div for ILS and HFCT, respectively; 80ns/div in horizontal scale.Figure 6- Low-magnitude PD pulses for corona discharge test measured with ILS (blue plot) and HFCT (brown plot). The vertical scales are 5 mV/div and20 mV/div for ILS and HFCT, respectively; 80ns/div in horizontal scale.B.Surface discharges and noise pulses measurementsThe experimental procedure from point-plane geometry was repeated for the polyethylene sheet stressed by means of one low-diameter steel electrode. Noise waveforms detected for voltages below PDIV and partial discharges measured for 1200 V of applied voltage are not shown now for sake ofbriefness.C. Internal discharges and noise pulses measurementsNoise, low magnitude and high magnitude PD pulses were also measured for the three glued papers acquiring ten measurements from each case.V.NOISE REJECTION CAPABILITY . C LUSTERINGTECHINQUES .Pulse waveform analysis provides helpful information regarding PD source separation and PD-noise rejection. A successful example of the application of these techniques is the clustering analysis developed by [5], where two parameters related to pulse waveforms are used to classify signals in a two dimensional map.In this approach, each detected signal u(t) and its Fast Fourier Transform U(f) is sampled K times (sampling frequency 1.25GHz). The statistical time position of the signal t 0 is calculated as follows:∑4 This is used for the calculation of the equivalent time length T and the equivalent bandwidth BW of the signal:∑ · 5 ∑ ·| | ∑|| 6 In this paper, the T-BW maps have been slightly modified in order to represent both magnitudes in units of seconds. For this purpose, the inverse of the equivalent bandwidth T’=1/BW has been used as the second pulse indicator.The results of applying this processing technique to pulses measured with HFCT and ILS are presented in the Fig. 7-9. It is clearly seen that both sensors provide different clusters for noise (+) and high magnitude PD pulses (*), so noise rejection is possible with these devices; this holds even for corona discharges, where many noise pulses amplitudes were higher than most detected discharges (see Fig. 4 and 5). For ILS measurements, low magnitude PD (green Δ) are clearly overlapped to the high magnitude PD cluster for corona discharges or define a completely different cluster for internal and surface discharges. This means that the inductive loop sensor is capable of distinguishing low magnitude PD from noise in each scenario. On the other hand, the same low magnitude pulses create a cluster that is clearly overlapped to noise pulses clusters when they are measured using the HFCT for the three test objects. Thus, ILS allows the detection of low magnitude PD without confusing them as noise and performs better than HFCT. The derivative response to PD current pulses from the ILS gives better frequency components for PD-noise separation using the currently commercial techniques proposed by [5].Figure 7.- T-T’ maps for corona discharge setup. Results for HFCT (up) andILS (down) measurements. PD (blue *), noise (red +) and low magnitude PD(green Δ).Figure 8.- T-T’ maps for surface discharge setup. Results for HFCT (up) and ILS (down) measurements. PD (blue *), noise (red +) and low magnitude PD(greenΔ).Figure 9.- T-T’ maps for internal discharge setup. Results for HFCT (up) and ILS (down) measurements. PD (blue *), noise (red +) and low magnitude PD(green Δ).VI.CONCLUSIONS AND FUTURE WORK.In this paper, partial discharge pulse waveform analysis has been used to aid in PD recognition. The novel inductive loop sensor has shown a proper response to discriminate between high magnitude noise pulses and high magnitude discharges. Moreover, the difficult task of noise rejection when detecting low magnitude PD can be accomplished using this inductive loop sensor in a reliable way. The authors have shown that the pulse processing techniques commercially available in some detection equipments to deal with PD recognition are compatible and appropriate for this new and inexpensive inductive sensor. This study shall be extended to PD source classification when several discharge sites (for example, corona and internal PD) are simultaneously active. For this objective, PD digital acquisition systems able to detect and process hundreds of pulses per second must be used.R EFERENCES[1]Bartnikas, McMahon; “Engineering Dielectrics: Volume I, CoronaMeasurement and Interpretation”; 1979; ASTM; Philadelphia; pp 23-66. [2]Morshuis P.; “Degradation of Solid Dielectrics due to internal partialdischarge: Some thoughts on progress made and where to go now”;IEEE Transactions On Dielectrics and Electrical Insulation; 2005; Vol 12; pp 905-913.[3]IEC 60270; “High Voltage Test Techniques. 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