Es wird untersucht, ob das High-Variability-Training (HVT) die Perzeptions- und Produktionsleistungen des Gespanntheitskontrastes deutscher Vokale bei russischspra-chigen Deutschlernenden positiv beeinflusst. Dafür wurde in Anlehnung an bekannte HVT-Studien ein Aussprachetraining speziell für die Vokaldauer konzipiert. Basis ist die Gegenüberstellung zweier phonetischer Lautkontraste als Minimalpaare der fünf deutschen Vokale (A, E, I, O, U). An dem HVT nahmen dreißig fortgeschrittene russischsprachige Lernende des Deut-schen mit muttersprachlich bedingten Fehlern der L2-Vokalproduktion teil, gemäß dem Lernalter (während bzw. nach der kritischen Phase) in zwei Untersuchungsgruppen (RM1, RM2) getrennt. Die Untersuchung verlief in drei Phasen (Pretest, Training und Posttest). Das Training bestand aus acht Sitzungen von jeweils ca. zwanzig Minuten Dauer. Davor und danach wurden die Produktions- und Perzeptionsfähigkeiten ermittelt. Die Testdaten ergeben, dass 73,3 % der RM1- und 80 % der RM2-Probanden die Perzeptionsleistung der deutschen Vokalphoneme signifikant steigerten. In beiden Gruppen stiegen ebenfalls tendenziell die Produktionsfähigkeiten, 66,7 % der RM1- und 60 % der RM2-Probanden erhöhten sie signifikant. Dennoch konnte kein Teil-nehmer eine Vokalproduktion auf muttersprachlichem Niveau erreichen. Gezieltes HVT-Aussprachetraining wirkt sich demnach positiv auf die Perzeption und Produktion des Gespanntheitskontrastes bei russischsprachigen Deutschlernenden aus und ist eine effektive Erweiterung für den Vokalerwerb auch für fortgeschrittene L2-Lernende. Diese Erkenntnis unterstützt die Ergebnisse der Studien von Logan et al. (1991), Wang et al. (1999), Cenoz & Garciá-Lecumberri (1999), Lambacher et al. (2005), Nishi & Kewley-Port (2007), Iverson & Evans (2009), Liatambur & Lai (2011), Iverson, Pinet & Evans (2012), Wong (2012), Rato (2014), Jügler et al. (2015). / This study investigates whether high variability training (HVT) positively influences perception and production of the tension contrast of German vowels in Russian-speaking learners of German. For this task a pronunciation training course was developed especially for vowel length, drawing on established HVT studies. The basis for this is the comparison of two phonetic contrasts as minimal pairs, taken from the five German vowels (A, E, I, O, U). 30 advanced Russian-speaking learners of German with mother tongue interference in L2 vowel production took part in the HVT, separated according to learning age (during or after the critical phase) into two study groups (RM1, RM2). The study took place in three phases (pre-test, training and post-test). The training consisted of eight sessions, each of approx. 20 minutes in length. Production and perception abilities were tested before and after this. The test results show that 73.3% of the RM1 and 80% of the RM2 test subjects significantly increased their ability to perceive the German vowel phonemes. In both groups the production abilities also tended to rise, with 66.7% of the RM1 and 60% of the RM2 test subjects improving them significantly. However, no participant was able to achieve vowel production at native speaker level. This shows that targeted HVT pronunciation training has a positive effect on the perception and production of tension contrast in Russian-speaking learners of German and is an effective extension for vowel development, also for advanced L2 learners. These findings support the results of studies by Logan et al. (1991), Wang et al. (1999), Cenoz & Garciá-Lecumberri (1999), Lambacher et al. (2005), Nishi & Kewley-Port (2007), Iverson & Evans (2009), Liatambur & Lai (2011), Iverson, Pinet & Evans (2012), Wong (2012), Rato (2014), Jügler et al. (2015).

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