Condition monitoring (CM) of electrical equipment is an important field in electrical engineering and a considerable amount of research is dedicated to this field. Power cables are one of the most important parts of any electrical network and the variety of techniques available for CM of electrical cables is therefore no surprise. Electrical cables are exposed to operational and environmental stressors which will cause degradation of the insulation material. The degradation will continue to the point where the cable fails. Blackouts caused by failing cables will have an effect on the safety, efficiency and production of an electrical network. It is therefore important to constantly monitor the condition of electrical cables, in order to prevent the premature failure of cables. The research presented in this dissertation sets out to investigate CM techniques for power cables and to design and implement a basic cable CM technique based on the principles of partial discharge (PD) measurements. A comprehensive literature study introduces the fundamental concepts regarding the CM of power cables. The basic construction of electrical cables, as well as the variety of different types is researched in order to lay a foundation for the research that follow. CM techniques for electrical equipment are investigated, with the emphasis on techniques used on cables. Conducted research led to the decision to focus on CM by means of PD measurements. PD as a phenomenon is investigated to be able to better understand the origins and effects of discharge activity. From there the focus shifts to the available techniques for monitoring the condition of electrical cables by means of PD measurements. The research conducted in the literature study chapter forms the basis from which the rest of the study is conducted. Simulation models were used to study PD characteristics. The models are derived from engineering and mathematical principles and are based on the well-known three-capacitor model of PD. The simulations were performed in order to study the effects of discharge activity. The designed simulation models allows for a variety of PD characteristics to be studied. The simulations were performed in the MATLAB® Simulink® environment. The research conducted in the dissertation was used to design an elementary CM technique which can be used to detect the presence of PD within electrical cables. The designed CM technique was used for the practical measurement of PD data. MATLAB® programs were designed in order to analyse the PD data in both the time- and frequency-domain. The analysis of the measured data revealed PD characteristics of the test specimen used for the measurements. The designed CM is used for the detection of PD activity within electrical cables and in combination with other techniques, may be used for complete CM of electrical cables. The experimental setup which was used to take practical PD measurements adds another dimension to the work presented in this dissertation. / MIng (Electrical and Electronic Engineering), North-West University, Potchefstroom Campus, 2015

Condition monitoring (CM) of electrical equipment is an important field in electrical engineering and a considerable amount of research is dedicated to this field. Power cables are one of the most important parts of any electrical network and the variety of techniques available for CM of electrical cables is therefore no surprise. Electrical cables are exposed to operational and environmental stressors which will cause degradation of the insulation material. The degradation will continue to the point where the cable fails. Blackouts caused by failing cables will have an effect on the safety, efficiency and production of an electrical network. It is therefore important to constantly monitor the condition of electrical cables, in order to prevent the premature failure of cables. The research presented in this dissertation sets out to investigate CM techniques for power cables and to design and implement a basic cable CM technique based on the principles of partial discharge (PD) measurements. A comprehensive literature study introduces the fundamental concepts regarding the CM of power cables. The basic construction of electrical cables, as well as the variety of different types is researched in order to lay a foundation for the research that follow. CM techniques for electrical equipment are investigated, with the emphasis on techniques used on cables. Conducted research led to the decision to focus on CM by means of PD measurements. PD as a phenomenon is investigated to be able to better understand the origins and effects of discharge activity. From there the focus shifts to the available techniques for monitoring the condition of electrical cables by means of PD measurements. The research conducted in the literature study chapter forms the basis from which the rest of the study is conducted. Simulation models were used to study PD characteristics. The models are derived from engineering and mathematical principles and are based on the well-known three-capacitor model of PD. The simulations were performed in order to study the effects of discharge activity. The designed simulation models allows for a variety of PD characteristics to be studied. The simulations were performed in the MATLAB® Simulink® environment. The research conducted in the dissertation was used to design an elementary CM technique which can be used to detect the presence of PD within electrical cables. The designed CM technique was used for the practical measurement of PD data. MATLAB® programs were designed in order to analyse the PD data in both the time- and frequency-domain. The analysis of the measured data revealed PD characteristics of the test specimen used for the measurements. The designed CM is used for the detection of PD activity within electrical cables and in combination with other techniques, may be used for complete CM of electrical cables. The experimental setup which was used to take practical PD measurements adds another dimension to the work presented in this dissertation. / MIng (Electrical and Electronic Engineering), North-West University, Potchefstroom Campus, 2015

No description available.

In this work, we first analyze the behavior of the acoustic wave from the theoretical point of view using a simplified 1-dimensional model. The model was developed based on the conservation of mass, the conservation of momentum, and the state equation; in addition, the fluid medium obeys Stokes assumption and it is homogeneous, adiabatic and isentropic. Experiment and simulation results show consistency to theoretical calculation. The second part of this thesis focuses on the PD signal analysis from an on-site PD measurement of the in-house design fiber optic sensors (by Virginia Tech, Center for Photonics Technology). Several commercial piezoelectric transducers (PZTs) were also used to compare the measurement results. The signal analysis employs the application of wavelet-based denoising technique to remove the noises, which mainly came from vibration, EMI, and light sources, embedded in the PD signal. The denoising technique includes the discrete wavelet transform (DWT) decomposition, thresh-holding of wavelet coefficients, and signal recovery by inverse discrete wavelet transform. Several approaches were compared to determine the optimal mother wavelet. The threshold limits are selected to remove the maximum Gaussian noises for each level of wavelet coefficients. The results indicate that this method could extract the PD spike from the noisy measurement effectively. The frequency of the PD pulse is also analyzed; it is shown that the frequencies lie in the range of 70 kHz to 250 kHz. In addition, with the assumed acoustic wave propagation delay between PD source and sensors, it was found that all PD activities occur in the first and third quadrant in reference to the applied sinusoidal transformer voltage. / Master of Science

No description available.

No description available.

Power transformers are one of the most important components in the electrical energy network. Extending transformer life is very economically valuable due to power outage. Therefore the development of instruments to monitor the transformer condition is of great interest. Detection of partial discharges (PDs) in power transformers is an effective diagnostic because it may reveal and quantify an important aging factor and provide information on the condition of the transformer. However, partial discharge diagnostics are still not effectively used for online monitoring of transformers because of the complexity of PD measurements and difficulties of discriminating of PDs and other noise sources. This thesis presents a further study of detection and location of partial discharges in power transformers based on previous work conducted at the Center for Photonics Technology (CPT) at Virginia Tech. The detection and positioning system consists of multiple extrinsic Fabry-Parot interferometric (EFPI) fiber acoustic sensors which can survive the harsh environment of oil-filled transformers. This thesis work is focused on optimal arrangement of multiple sensors to monitor and locate PD activities in a power transformer. This includes the following aspects. First, the sensor design requirements are discussed in order to successfully detect and accurately position the PD sources. In the following sections, Finite Element Method (FEM) is used to model the EFPI sensor fabricated at CPT. Experiments were conducted to measure the angular dependence of the frequency response of the sensor. It is shown that within the range of ±45º incident angles, the sensitivity varies by 3-5dB. Finally, the thesis demonstrates a PD positioning experiment in a 500 gallon water tank (R à H = 74" à 30" cylinder) using a hyperbolic positioning algorithm and time difference of arrival (TDOA). Finally we demonstrated that 100% of the positioning data is bounded by a 22.7à 4.1à 5.3 mm₃ cube, with a sensing range of 810 mm using the leading edge method with FIR filtering. / Master of Science

A partial discharge (PD) is the dissipation of energy caused by the buildup of localized electric field intensity. In high voltage devices such as transformers, this buildup of charge and its release can be symptomatic of problems associated with aging, such as floating components and insulation breakdown. This is why PD detection is used in power systems to monitor the state of health of high voltage transformers. If such problems are not detected and repaired, the strength and frequency of PDs increases and eventually leads to the catastrophic failure of the transformer, which can cause external equipment damage, fires and loss of revenue due to an unscheduled outage. Reliable online PD detection is a critical need for power companies to improve personnel safety and decrease the potential for loss of service. The PD phenomenon is manifested in a variety of physically observable signals including electric and acoustic pulses and is currently detected using a host of exterior measurement techniques. These techniques include electrical lead tapping and piezoelectric transducer (PZT) based acoustic detection. Many modern systems use a combination of these techniques because electrical detection is an older and proven technology and acoustic detection allows for the source to be located when several sensors are mounted to the exterior of the tank. However, if an acoustic sensor could be placed inside the tank, not only would acoustic detection be easier due to the increased signal amplitude and elimination of multipath interference, but positioning could also be performed with more accuracy in a shorter time. This thesis presents a fiber optic acoustic sensing system design that can be used to detect and locate PD sources within a high voltage transformer. The system is based on an optical acoustic (OA) sensor that is capable of surviving the harsh environment of the transformer interior while not compromising the transformer's functionality, which allows for online detection and positioning. This thesis presents the theoretical functionality and experimental validation of a band-limited OA sensor with a usable range of 100-300 kHz, which is consistent with the frequency content of an acoustic pulse caused by a PD event. It also presents a positioning system using the time difference of arrival (TDOA) of the acoustic pulse with respect to four sensors that is capable of reporting the three-dimensional position of a PD to within ±5cm on any axis. / Master of Science

No description available.

Cette thèse s’inscrit dans le contexte de la surveillance des postes sous enveloppe métallique (PSEM) en courant continu (DC). La disponibilité de ces équipements étant primordiale pour leurs utilisateurs, il est nécessaire de disposer d’un outil de surveillance (monitoring) permettant de prévenir toute défaillance. Cet outil doit être capable de détecter et d’identifier les défauts présents, afin d’apporter une réponse adaptée. Depuis de nombreuses années, le monitoring des PSEM en AC est réalisé grâce à la mesure des décharges partielles (DP). Malheureusement, les connaissances des DP dans les PSEM en DC sont encore lacunaires, et les techniques d’identification des défauts sont intrinsèquement liées à l’environnement AC. De nouvelles techniques sont donc nécessaires en DC.Ce travail de thèse avait pour but de caractériser les décharges partielles dans les postes sous enveloppe métallique en tension continue, et de mettre en place une solution de reconnaissance automatique des défauts. Pour cela, un banc de mesure des décharges partielles a d’abord été mis en place. Afin de garantir la pertinence des résultats pour des systèmes industriels, les travaux ont été réalisés dans une section de PSEM sous tension continue. Le comportement des DP a été étudié pour deux types de défauts : des pointes sur le conducteur haute-tension et des particules libres métalliques. La caractérisation a porté sur l’influence de plusieurs paramètres : la nature et la pression du gaz, le niveau et la polarité de la tension. La mesure des DP a d’abord été réalisée en conformité avec la norme IEC 60270, permettant ainsi d’évaluer la pertinence de cette méthode pour les applications DC. La caractérisation a été complétée grâce à d’autres chaînes de mesure : une mesure de courant stationnaire, une mesure de courant haute-fréquence, une mesure de lumière, et une mesure des ondes ultra-haute fréquence (UHF). Le travail sur l’identification des défauts a d’abord consisté à construire une signature pertinente à partir des mesures de DP, puis à constituer une base de données, et enfin à implémenter un algorithme de reconnaissance automatique.Ces travaux ont montré que la méthode conventionnelle de mesure des DP présente certaines limites pour la détection des décharges partielles en DC, notamment pour les décharges couronne. Elle a tout de même permis de faire une bonne partie du travail de caractérisation. Les résultats obtenus avec les autres chaînes de mesure utilisées ont permis d’expliquer les lacunes de la méthode conventionnelle. Ils ont également permis un véritable apport pour la caractérisation des DP engendrées par des défauts de type pointe et particule. Enfin, une classification automatique efficace des défauts a été mise en place. Elle s’appuie sur le diagramme q(Δt) issu des données de la mesure conventionnelle des décharges partielles et sur un algorithme de réseau de neurones. / The framework of this thesis is the monitoring of High-Voltage, Direct Current (HVDC) Gas-Insulated Substations (GIS). The availability of these equipment is crucial for electrical networks operators. That is why they need a preventive diagnosis tool. The solution must be able to detect and identify the insulation defects, so that an appropriate maintenance can be planned. The last 40 years have seen Partial Discharges (PD) measurement become a classic monitoring tool for AC GIS. Unfortunately, there is a lack of scientific information about PD in HVDC GIS, and the known defect identification techniques are very specific to the AC environment. New techniques are thus needed in DC.This thesis aimed to characterize partial discharges in DC gas-insulated substations, and to develop an automatic defect identification tool. The first step of this work was the development of a partial discharge measuring bench. The complete study has been performed in a GIS section, so that the results can be directly applied to industrial equipment. Two kinds of defect have been investigated: protrusions on the high-voltage conductor, and free metallic particles. The influence of parameters such as gas nature and pressure, voltage level and polarity has been evaluated. First, PD have been measured in conformity with the IEC 60270 standard, and the relevance of this method in a DC environment has been evaluated. Then, other measuring chains have been used to improve the characterization of partial discharges: a steady-state current measurement, a high-frequency current measurement, a light measurement and a measurement of Ultra-High Frequency (UHF) waves. Finally, a relevant signature for defect identification has been designed and extracted from DP recordings. A database has been constituted, and an automated recognition algorithm has been implemented.The results show that the conventional PD measurement technique is not fully adapted to partial discharges detection in DC, corona discharges being the most problematic situation. Nevertheless, this method has brought enough information to start the characterization of PD. The limitations of the conventional method have been explained thanks to the results of the other measurements. These other experimental results have led to an actual improvement of the characterization of protrusion and particle-generated partial discharges. An effective automated defect classification solution has been implemented. The signature is derived from the q(Δt) diagram that has been extracted from the data obtained with the partial discharge conventional measurement. The identification algorithm has a neural network structure.