Generator Insulation-Aging On-Line Monitoring Technique Based on Fiber Optic Detecting Technology

The relationship between insulation aging and generator lifespan using fiber optic sensors (FOSs) is explored to ultimately improve asset lifespan through smart choices in running conditions and maintenance. Insulation aging is a major factor that causes generator failure. FOS provides the rare opportunity of being installed up close to the insulation, monitoring degradations that are otherwise difficult to detect. FOSs, unlike purely electrical transducers, are immune to high voltage (HV) and strong electromagnetic (EM) fields. They are small and have a proven long life by their deployment in the Telecom industry. The proposed FOS is a Fabry-Perot cavity made up of two identical fiber Bragg gratings (FBGs) using light wave interference as the working principle. Such architecture delivers simultaneous vibration (10 Hz–1 kHz) and temperature (0.1°C resolution) monitoring, both helping to spot irregular vibration patterns (signatures) and hot-spots inside the generator stator slots. The signal processing unit equipped with a gateway device can help to connect the large volume of sensor data, allowing correlation with the supervisory control and data acquisition (SCADA) system data of the plant. This chapter also elaborates on the field test jointly conducted with Calpine Corporation and Oz Optics, Ltd. (Ottawa, Ontario, Canada)

Index to 1984 NASA Tech Briefs, volume 9, numbers 1-4

Short announcements of new technology derived from the R&D activities of NASA are presented. These briefs emphasize information considered likely to be transferrable across industrial, regional, or disciplinary lines and are issued to encourage commercial application. This index for 1984 Tech B Briefs contains abstracts and four indexes: subject, personal author, originating center, and Tech Brief Number. The following areas are covered: electronic components and circuits, electronic systems, physical sciences, materials, life sciences, mechanics, machinery, fabrication technology, and mathematics and information sciences

Faults Detection for Power Systems

Non

Bridges Structural Health Monitoring and Deterioration Detection Synthesis of Knowledge and Technology

INE/AUTC 10.0

Online Monitoring Technical Basis and Analysis Framework for Large Power Transformers; Interim Report for FY 2012

The Light Water Reactor Sustainability program at Idaho National Laboratory (INL) is actively conducting research to develop and demonstrate online monitoring (OLM) capabilities for active components in existing Nuclear Power Plants. A pilot project is currently underway to apply OLM to Generator Step-Up Transformers (GSUs) and Emergency Diesel Generators (EDGs). INL and the Electric Power Research Institute (EPRI) are working jointly to implement the pilot project. The EPRI Fleet-Wide Prognostic and Health Management (FW-PHM) Software Suite will be used to implement monitoring in conjunction with utility partners: the Shearon Harris Nuclear Generating Station (owned by Duke Energy for GSUs, and Braidwood Generating Station (owned by Exelon Corporation) for EDGs. This report presents monitoring techniques, fault signatures, and diagnostic and prognostic models for GSUs. GSUs are main transformers that are directly connected to generators, stepping up the voltage from the generator output voltage to the highest transmission voltages for supplying electricity to the transmission grid. Technical experts from Shearon Harris are assisting INL and EPRI in identifying critical faults and defining fault signatures associated with each fault. The resulting diagnostic models will be implemented in the FW-PHM Software Suite and tested using data from Shearon-Harris. Parallel research on EDGs is being conducted, and will be reported in an interim report during the first quarter of fiscal year 2013

Index to 1985 NASA Tech Briefs, volume 10, numbers 1-4

Short announcements of new technology derived from the R&D activities of NASA are presented. These briefs emphasize information considered likely to be transferrable across industrial, regional, or disciplinary lines and are issued to encourage commercial application. This index for 1985 Tech Briefs contains abstracts and four indexes: subject, personal author, originating center, and Tech Brief Number. The following areas are covered: electronic components and circuits, electronic systems, physical sciences, materials, life sciences, mechanics, machinery, fabrication technology, and mathematics and information sciences

Diagnosis of broken bar fault in three-phase induction motors using fibre bragg grating strain sensors assisted by an algorithm

Mestrado de dupla diplomação com a UTFPR - Universidade Tecnológica Federal do ParanáIn this study, we developed an algorithm for identifying failures caused by broken bars in the rotors of three-phase induction motors through the analysis of their dynamic deformation using fibre optic Bragg gratings (FBGs) as sensing elements. The analysis of dynamic deformation enables the detection and diagnosis of various mechanical faults, such as misalignment, imbalance, bearing failures, and mechanical looseness. Furthermore, it allows for the identification of electrical faults, such as fractures or cracks in the rotor rings or bars To measure the dynamic deformation, we employed FBG-based sensors known for their key features, including high multiplexing capability, electromagnetic radiation immunity, and long-distance operation. Experimental tests were conducted on a small-scale induction motor (3 HP) to validate the method and explore its applicability to medium and large-scale machines. The motor was powered by two different supply sources: the utility power grid and a controled power sources, under load conditions of 75% and 100% of the rated load. During the tests, we used a rotor without any bar defects and subsequently a rotor with a broken bar. The presence of a broken bar was successfully identified under both load conditions and across all two power supply sources. The fault caused by the broken bar in the rotor was detected in two frequency regions obtained from the three sets of experiments. The first region was centred around the mechanical rotational frequency of the rotor, while the second region was approximately twice the electrical frequency of the power supply. The system demonstrated high sensitivity with a good signal-to-noise ratio and showcased advantages over conventional methods and sensors commonly used for identifying broken bar faults in induction motors.Neste estudo, desenvolvemos um algoritmo para identificar falhas em barras quebradas no rotor de motores de indução trifásicos por meio da análise da deformação dinâmica do estator usando grades de Bragg em fibras ópticas (FBGs) com assitência de um algoritmo. Essa análise possibilita a detecção e o diagnóstico de várias falhas mecânicas, como desalinhamento, desbalanceamento e folga mecânica. Além disso, permite a identificação de falhas elétricas, como fraturas ou rachaduras nos anéis ou barras do rotor. Para medir a deformação dinâmica, empregamos sensores baseados em FBG conhecidos por suas principais características, incluindo alta capacidade de multiplexação, imunidade à radiação eletromagnética e operação a longa distância. Testes experimentais foram conduzidos em um motor de indução em pequena escala (3 HP) para validar o método e explorar sua aplicabilidade em máquinas de médio e grande porte. O motor foi alimentado por duas fontes de alimentação diferentes: a rede elétrica de utilidade pública e por uma fonte controlada, sob condições de carga de 75% e 100% da carga nominal. Durante os testes, utilizamos um rotor sem defeitos no rotor e, posteriormente, um rotor com uma barra quebrada. A presença da barra quebrada foi identificada com sucesso em ambas as condições de carga e em todas as duas fontes de alimentação. A barra quebrada no rotor foi detectada em duas regiões de frequência obtidas a partir dos três conjuntos de experimentos. A primeira região estava centrada em torno da frequência rotacional mecânica do rotor, enquanto a segunda região era aproximadamente o dobro da frequência elétrica da fonte de alimentação. O sistema demonstrou alta sensibilidade com uma boa relação sinal-ruído e apresentou vantagens sobre os métodos convencionais e sensores comumente usados para identificar falhas em barras quebradas em motores de indução

Silica rod based optical fibre sensor for high refractive index sensing application in ageing power transformer oil

Power transformer is one of the most essential components in power transmission and distribution systems. A thorough inspection of the condition of a power transformer is critical to avert malfunctions. An essential part of this inspection includes degradation control of the transformer oil. In fact, studies have incorporated optical fibre sensors (OFSs) for transformer oil degradation detection owing to the distinct advantages of OFS over conventional methods. Despite the diversity of techniques which have been employed for the developed OFSs, they pose problems of complicated fabrication and cross-sensitivity to temperature. As such, this study reports the original research work on the development of high refractive index (RI) fibre sensors based on silica rod (SR) structure to address the aforementioned problems. This study details the conceptual sensor design, the fabrication, the experimentation, and the application to transformer oil degradation detection. Related mathematical models of the sensor architectures, such as principles of leaky mode interference (LMI) and multimode interference (MMI), were explored to comprehend sensor behaviour. The sensors were numerically analysed using BeamPROP software to determine their functions from field distribution and sensor spectra. Systematic procedures for fabrication and experimentation of the sensor were developed to ensure high repeatability. Notably, four sensor designs are proposed in this study. Design 1 signifies RI sensing based on wavelength shift and spectrum power level change. The use of SR as a sensing element induced the spectrum power level change due to the LMI at the SR section. Meanwhile, spectrum wavelength shift was induced because the input of MMI in MMF was substantially influenced by its surrounding high RI. The sensor responded to the surrounding RI by the changes of dip wavelength and output power level with maximum sensitivity of 38.65 nm/RIU and 63.15 dBm/RIU, respectively. Design 2 is proposed to simultaneously measure high RI and temperature by monitoring the respective output power level and wavelength shift of the single dip transmission spectrum of the sensor. The experimental results revealed that the sensor had RI sensitivity of 108.07 dBm/RIU and temperature sensitivity of 9.31 pm/oC. Design 3 deployed a SR with larger diameter exceeding the MMF core diameter to increase the leakage loss of high-order leaky modes to the surrounding. By monitoring the output power of the interference dip, this sensor achieved 5-fold greater sensitivity than Design 1, which was up to -293.53 dBm/RIU. Design 4 refers to a full intensity-based RI sensor that completely depends on the LMI at the SR section. The measurement of high RI was executed by monitoring the spectrum power level change caused by LMI. The sensitivity of this sensor was 93.82 dBm/RIU. Design 4 sensor was selected and applied in power transformer applications to detect transformer oil degradation due to its compact structure, easy interrogation scheme, and resistance to temperature variations. The findings revealed that the sensor was capable of sensing the variations of oil that belonged to the good and fair regions in accordance to ASTM D1500 colour scale. This scenario highlights the great potential of the sensor for remote in-situ detection of transformer oil degradation