Usage of antenna for detection of tree falls on overhead lines with covered conductors

The direct contact of a tree or a branch of tree with Covered Conductors (CC) overhead lines causes Partial Discharges (PD) inside the insulation. The presence of PD degrades the insulation systems and eventually destroys insulation, which may lead to power delivery interruption. The detection and diagnosis of PD is an important tool to address the problem of tree caused faults in forested terrains. The PD occurs in the impulse component of the signal, which is usually measured by Rogowski coil (current signal) or single layer inductors (voltage signal). In this paper, we introduce a possibility to detect the tree caused faults with the usage of whip antenna. The advantage of the antenna is a very low price and the possibility to install antenna under voltage. The disadvantages are sensitivity to ferromagnetic materials and impossibility to distinguish affected phase. The measurements were carried out in the real environment in forested terrain in Jeseniky Mountains. The real environment is different from a laboratory conditions due to heavy noise (e.g. corona, radio emissions). This paper provides an examination of the background noise from the antenna signal. The experimental results indicate that the antenna may be successfully used instead of the current approach

Antennas parameterization for the detection of partial discharges

Partial discharge (PD) detection is a widely extended technique for electrical insulation diagnosis. Ultrahigh-frequency detection techniques appear as a feasible alternative to traditional methods owing to their inherent advantages such as the capability to detect PDs online and to locate the piece of equipment with insulation problems in substations and cables. In this paper, four antennas are thoroughly studied by means of their theoretical and experimental behavior when measuring electromagnetic pulses radiated by PD activity. The theoretic study of the band of frequencies in which the pulse emits and the measurement of the parameters S11 are complemented with the frequency response and wavelet transform of a set of 500 time signals acquired by the antennas, and the results are analyzed in detail.This work was supported by the Spanish Science and Technology Ministry under Contracts DPI 2009-14628-C03-02 and TEC 2011- 29006-C03-03.Publicad

Antenna deployment for the localization of partial discharges in open-air substations

Partial discharges are ionization processes inside or on the surface of dielectrics that can unveil insulation problems in electrical equipment. The charge accumulated is released under certain environmental and voltage conditions attacking the insulation both physically and chemically. The final consequence of a continuous occurrence of these events is the breakdown of the dielectric. The electron avalanche provokes a derivative of the electric field with respect to time, creating an electromagnetic impulse that can be detected with antennas. The localization of the source helps in the identification of the piece of equipment that has to be decommissioned. This can be done by deploying antennas and calculating the time difference of arrival (TDOA) of the electromagnetic pulses. However, small errors in this parameter can lead to great displacements of the calculated position of the source. Usually, four antennas are used to find the source but the array geometry has to be correctly deployed to have minimal errors in the localization. This paper demonstrates, by an analysis based on simulation and also experimentally, that the most common layouts are not always the best options and proposes a simple antenna layout to reduce the systematic error in the TDOA calculation due to the positions of the antennas in the array.Tests were done in the High-Voltage Research and Test Laboratory (LINEALT) at Universidad Carlos III de Madrid. This work has been partly funded by the Spanish Government through projects SI-DP (DPI2015-66478-C2-1), MIMOTEX (TEC2014-61776-EXP) and ELISA (TEC2014-59255-C3-3R)

Radio-Frequency Localization of Multiple Partial Discharges Sources with Two Receivers

Spatial localization of emitting sources is especially interesting in different fields of application. The focus of an earthquake, the determination of cracks in solid structures, or the position of bones inside a body are some examples of the use of multilateration techniques applied to acoustic and vibratory signals. Radar, GPS and wireless sensors networks location are based on radiofrequency emissions and the techniques are the same as in the case of acoustic emissions. This paper is focused on the determination of the position of sources of partial discharges in electrical insulation for maintenance based on the condition of the electrical equipment. The use of this phenomenon is a mere example of the capabilities of the proposed method but it is very representative because the emission can be electromagnetic in the VHF and UHF ranges or acoustic. This paper presents a method to locate more than one source in space with only two receivers, one of them in a fixed position and the other describing a circumference around the first one. The signals arriving from the different sources to the antennas are first separated using a classification technique based on their spectral components. Then, the individualized time differences of arrival (TDOA) from the sources collected at different angles describe a function, angle versus TDOA, that has all the geometric information needed to locate the source. The paper will show how to derive these functions for any source analytically with the position of the source as unknown parameters. Then, it will be demonstrated that it is possible to fit the curve with experimental measurements of the TDOA to obtain the parameters of the position of each source. Finally, the technique is extended to the localization of the emitter in three dimensions.The work done in this paper has been funded by the Spanish Government (MINECO) and the European Regional Development Fund (ERDF) under contract DPI2015-66478-C2-1-R (MINECO/FEDER, UE)

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

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.Tests were done in the High-Voltage Research and Test Laboratory (LINEALT) at Universidad Carlos III de Madrid

Classification of EMI discharge sources using time–frequency features and multi-class support vector machine

This paper introduces the first application of feature extraction and machine learning to Electromagnetic Interference (EMI) signals for discharge sources classification in high voltage power generating plants. This work presents an investigation on signals that represent different discharge sources, which are measured using EMI techniques from operating electrical machines within power plant. The analysis involves Time-Frequency image calculation of EMI signals using General Linear Chirplet Analysis (GLCT) which reveals both time and frequency varying characteristics. Histograms of uniform Local Binary Patterns (LBP) are implemented as a feature reduction and extraction technique for the classification of discharge sources using Multi-Class Support Vector Machine (MCSVM). The novelty that this paper introduces is the combination of GLCT and LBP applications to develop a new feature extraction algorithm applied to EMI signals classification. The proposed algorithm is demonstrated to be successful with excellent classification accuracy being achieved. For the first time, this work transfers expert's knowledge on EMI faults to an intelligent system which could potentially be exploited to develop an automatic condition monitoring system

Gated pipelined folding ADC based low power sensor for large-scale radiometric partial discharge monitoring

Partial discharge is a well-established metric for condition assessment of high-voltage plant equipment. Traditional techniques for partial discharge detection involve physical connection of sensors to the device under observation, limiting sensors to monitoring of individual apparatus, and therefore, limiting coverage. Wireless measurement provides an attractive low-cost alternative. The measurement of the radiometric signal propagated from a partial discharge source allows for multiple plant items to be observed by a single sensor, without any physical connection to the plant. Moreover, the implementation of a large-scale wireless sensor network for radiometric monitoring facilitates a simple approach to high voltage fault diagnostics. However, accurate measurement typically requires fast data conversion rates to ensure accurate measurement of faults. The use of high-speed conversion requires continuous high-power dissipation, degrading sensor efficiency and increasing cost and complexity. Thus, we propose a radiometric sensor which utilizes a gated, pipelined, sample-and-hold based folding analogue-todigital converter structure that only samples when a signal is received, reducing the power consumption and increasing the efficiency of the sensor. A proof of concept circuit has been developed using discrete components to evaluate the performance and power consumption of the system

Partial Discharge Spectral Characterization in HF, VHF and UHF Bands Using Particle Swarm Optimization

The measurement of partial discharge (PD) signals in the radio frequency (RF) range has gained popularity among utilities and specialized monitoring companies in recent years. Unfortunately, in most of the occasions the data are hidden by noise and coupled interferences that hinder their interpretation and renders them useless especially in acquisition systems in the ultra high frequency (UHF) band where the signals of interest are weak. This paper is focused on a method that uses a selective spectral signal characterization to feature each signal, type of partial discharge or interferences/noise, with the power contained in the most representative frequency bands. The technique can be considered as a dimensionality reduction problem where all the energy information contained in the frequency components is condensed in a reduced number of UHF or high frequency (HF) and very high frequency (VHF) bands. In general, dimensionality reduction methods make the interpretation of results a difficult task because the inherent physical nature of the signal is lost in the process. The proposed selective spectral characterization is a preprocessing tool that facilitates further main processing. The starting point is a clustering of signals that could form the core of a PD monitoring system. Therefore, the dimensionality reduction technique should discover the best frequency bands to enhance the affinity between signals in the same cluster and the differences between signals in different clusters. This is done maximizing the minimum Mahalanobis distance between clusters using particle swarm optimization (PSO). The tool is tested with three sets of experimental signals to demonstrate its capabilities in separating noise and PDs with low signal-to-noise ratio and separating different types of partial discharges measured in the UHF and HF/VHF bands.The work done in this paper has been funded by the Spanish Government (MINECO) and the European Regional Development Fund (ERDF) under contract DPI2015-66478-C2-1-R (MINECO/FEDER, UE)

Instrumentation system for location of partial discharges using acoustic detection with piezoelectric transducers and optical fiber sensors

In this paper, a multichannel instrumentation system for the location of partial discharges (PDs) in power transformers is presented. It is based on the detection of the acoustic emissions from PDs in oil with several piezoelectric (PZT) and fiber optic sensors. An acoustic detection and location approach is proposed based on a time reference given by one fiber optic sensor installed inside the tank and the times of arrival to several PZT sensors installed outside the tank (two in front of each phase windings of a three phase transformer for a typical application). The signal processing includes digital denoising techniques and time-difference lookup table-based 3-D location algorithms; these algorithms have been implemented with virtual instrumentation. The system is tested in an acoustic experimental setup and the location accuracy is evaluated. Finally, the error propagation from the times of arrival and the influence of the number of sensors and their sites in the 3-D location algorithm were analyzed.This work was supported in part by the Spanish National Ministry of Science and Innovation under the Project DPI 2009-14628-C03-01 and in part by the scholarship FPI under Grant BES-2010-04208

Application of Non-destructive Testing for Measurement of Partial Discharges in Oil Insulation Systems

The subject area regards to metrology and measurement methods applied for non-destructive investigation of electrical discharges occurring in oil insulation systems of high-voltage devices. The main aim of performed research studies is a detailed and multivariate analysis of physical phenomena associated with generation of electrical partial discharges (PD), which occur in oil insulation of electrical equipment. An important cognitive component was the verification whether the form of PD has an effect on the energy contribution of the physical phenomena associated with their generation. For investigating the physical processes associated with generation of PD, a system for modelling, the study and analysis of physical phenomena associated with their generation in insulating oil were designed and implemented. In particular, the PD were simulated in three setups: (1) a surface system, (2) needle-needle system in insulating oil and (3) needle-needle system in insulating oil with gas bubbles. In these experimental setups, optical signals (IR, UV and visible), ultra–high frequency electromagnetic and high-energy X-ray radiation, acoustic emission and thermal images were registered. Recorded signals were subjected for multi-variant investigation and analyses in the time and frequency domains. The contribution of particular physical phenomena was determined