1. Ph.D Theses
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Item Localisation of Partial Discharge Source in Oil Insulation Using Acoustic Emission Technique: Non-Iterative Method, Newton’s Method and Genetic Algorithm(National Institute of Technology Karnataka, Surathkal, 2019) Antony, Deepthi; Punekar, G. S.The power transformers are a vital component of power systems. The condition assessment of transformers is of utmost importance to ensure the reliable operation of the power system. The partial discharges (PD) originating from defects in operating transformers should be detected as early as possible. In large power apparatus like transformers, locating the source of PD is as important as identifying it. The PD source localisation helps in risk assessment and in planning of maintenance activities. The acoustic emission (AE) technique is one of the on-line non-destructive testing (NDT) techniques for PD source localisation in power transformers. The PD source is located by solving a system of non-linear sphere equations obtained by modeling the acoustic emission partial discharge (AEPD) location system mathematically. The algorithms that have been developed to solve the mathematical model of AEPD location system need to be improved due to the various limitations. Hence, the current research proposal aims to address this existing research gap by suggesting new algorithms/modifications in the existing algorithms. Further, the factors which affect the accuracy of PD source localisation will be studied and analysed. According to IEEE standard C.57.127-2007, there are two AEPD location systems: (i) allacoustic system; and (ii) combined acoustic-electrical system. When AE technique is used for PD source localisation in power transformers, the error in PD localisation can occur mainly due to two reasons: (i) the inefficacy of the algorithm used for solving the mathematical model; and (ii) the error in measurement of acoustic signal arrival time from the PD source to various sensors. For an all-acoustic system, a hybrid method combining the advantages of both the iterative and random search algorithms is developed to solve the mathematical model of AEPD location system. The existing non-iterative algorithm is modified/extended so that it works for cases with zero time-differences. The PD localisation experiments in an all-acoustic system are conducted in the diagnostic laboratory of Central Power Research Institute (CPRI), Bangalore. The proposed algorithms are verified using data from laboratory experiments. For the combined acoustic-electrical PD-locator-system, a non-iterative algorithm is devised for the first time. The effect of the sensor positioning on the performance of the method is studied, and some guidelines for the sensor placement on the transformer’s tank wall are suggested. The efficacy of the proposed algorithm is verified by applying to data from published literature. The error in estimating the acoustic signal arrival time from the PD source to the multiple AE sensors results in false localisation of the PD source, irrespective of the algorithm used for the AEPD source localisation in transformers. Two mathematical methods for the identification of such erroneous time measurements are proposed: (i) using discriminant; and (ii) using Jacobian determinant. The verification of the proposed methods are carried out by applying to published data in literature.Item Acoustic Emission Signal Based Investigations Involving Laboratory and Field Studies Related To Partial Discharges & Hot-Spots in Power Transformers(National Institute of Technology Karnataka, Surathkal, 2017) Shanker, Tangella Bhavani; Punekar, G. S.; Nagamani, H. N.Power transformers are important and vital components of ac power systems. It is essential to monitor the condition of these transformers periodically in order to ascertain the performance for continuous operation for its expected average life of 25-30 years. The defects in power transformers lead to the deterioration of insulation and eventual premature failure. The deterioration of insulation of power transformers can be assessed by carrying out the condition monitoring tests periodically. The condition monitoring test techniques can be off-line or on-line. The off-line test techniques are being followed as given in IEEE Std. 62(1995). These tests require outage of the transformer, thereby causing interruption of power supply. Whereas, on-line test techniques do not require any outage. Hence, on-line diagnostic techniques have gained importance. Literature review shows application of Acoustic Emission (AE) detection technique as a promising on-line tool for condition monitoring/diagnosis of the power transformers. The general guidelines for the application of AE technique for this purpose are outlined in IEEE Std. C57.127 (2007). Few typical case studies of AE signal measurements are discussed involving (i) two identical transformers, (ii) same transformer on different occasions (years) in power stations in India are reported. Some case studies with AE signals, involving On-Load Tap Changer (OLTC) and cooling system pump are also reported. These case studies also help in comprehending the efficacy of integrating the Dissolved Gas Analysis (DGA) data with the AE test results. Laboratory experimental work is carried out by simulating the most probable defects like Partial Discharge (PD) and hot-spots (leading to heat-waves) in order to capture AE signals in the range of 0-500 kHz. The classification and characterization of the defects based on the energy distribution of AE signals over the different frequency ranges is carried out using Discrete Wavelet Transform (DWT) utilizing the MATLAB toolbox. The eight-level decomposition revealed that the dominant frequency ranges for the energy distribution of the AE signals due to PD and heat-wave are 125 kHz-250 kHz and 62.5 kHz–125 kHz, respectively. The AE signal data from the transformers (field test) involving PD and hotspots are also analyzed using DWT. The laboratory based characterization of PD and heatwave got validated through the analysis of field data. The proposed method of identifying defects by AE signal analysis using DWT would complement the DGA of the transformeroil. Thus this would be a better substitute for DGA based analysis as AE based technique can be adopted in real time. The Acoustic Emission Partial Discharge (AEPD) signal parameters such as discharge magnitude and peak frequencies are studied using Fast Fourier Transform (FFT) to understand the behavior of AE signals at temperatures ranging from 30°C to 75°C. The results reported are intended to give an understanding of behavior of AEPD signals over the entire working temperature range of a transformer. At temperatures above 65°C a reduction in AEPD magnitude and peak frequencies are observed. Such behavior is noticed and probably being reported for the first time. An attempt is also made to explain the same.